BioMed Research International

Identification of m7G Methylation‐Related miRNA Signature Associated with Survival and Immune Microenvironment Regulation in Uterine Corpus Endometrial Carcinoma

Background. N7‐methylguanosine (m7G) has been implicated in the development of cancer. The role of m7G‐related miRNAs in the survival prediction of UCEC patients has not been investigated. Current research was the first to construct an m7G‐related miRNA model to accurately predict the survival of patients with uterine corpus endometrial carcinoma (UCEC) and to explore immune cell infiltration and immune activity in the tumor microenvironment. Methods. RNA‐seq data and clinical information of UCEC patients were derived from The Cancer Genome Atlas (TCGA) database. Using the TargetScan online database, we predicted miRNAs linked to the m7G‐related genes and identified miRNAs which were significantly associated with the survival in UCEC patients and constructed a risk scoring model. The TCGA‐UCEC cases were scored according to the risk model, and the high‐ and low‐risk groups were divided by the median risk value. Gene enrichment analysis and immune cell infiltration and immune function analysis were performed using “clusterProfiler” and “GSVA” packages in R. Results. The survival prediction model consisted of 9 miRNAs, namely, hsa‐miR‐1301, hsa‐miR‐940, hsa‐miR‐592, hsa‐miR‐3170, hsa‐miR‐876, hsa‐miR‐215, hsa‐miR‐934, hsa‐miR‐3920, and hsa‐miR‐216b. Survival of UCEC patients in the high‐risk group was worse than that in the low‐risk group (p < 0.001). The receiver operating characteristic (ROC) curve showed that the model had good predictive performance, and the area under the curve was 0.800, 0.690, and 0.705 for 1‐, 3‐, and 5‐year survival predictions, respectively. There were differences in the degree of immune cell infiltration and immune activity between the low‐risk and high‐risk groups. The expression levels of the identified differentially expressed genes correlated with the susceptibility to multiple anticancer drugs. Conclusions. The survival prediction model constructed based on 9 m7G‐related miRNAs had good predictive performance.

The Association Between Anti‐Neoplastic Effects of Curcumin and Urogenital Cancers: A Systematic Review

Background: Curcumin is a polyphenol compound with anticancer effects. We aimed to review the anti‐neoplastic effects of curcumin on urogenital cancers, by regulating different microRNA expressions.Methods: A systematic search was conducted in Medline (PubMed), Embase, Scopus, and Web of Science up to the end of August 2024. All English, in vitro, and observational studies that evaluated the effect of curcumin on preventing or treating urogenital cancers through its impact on microRNA expression were included. In vivo or silico studies were excluded.Result: A total of 2549 records were found. Finally, 25 studies were included. Twelve studies assessed the effect of curcumin on prostate cancer, six studies on ovarian cancer, three studies on cervical cancer, three studies on bladder cancer, and one study on renal cancer. MicroRNAs are small noncoding RNAs that regulate the post‐transcriptional pathways. They possess pivotal roles in different fundamental mechanisms in cells such as differentiation, migration, apoptosis, and proliferation. Curcumin exerts its anticancer effects on urogenital neoplasms by upregulating tumor suppressor microRNAs (miR‐143, miR‐145, miR‐Let‐7, miR‐101, miR‐3127, miR‐3178, miR‐1275, miR‐3198, miR‐1908, miR‐770, miR‐1247, miR‐411, miR‐34a, miR‐383, miR‐708, miR‐483, miR‐199a, miR‐335, miR‐503, miR‐10b, miR‐551a, miR‐9, miR‐203, miR‐7110, miR‐29b, and miR‐126) and downregulating oncogenic microRNAs (miR‐21, miR‐210, miR‐382, miR‐654, miR‐494, miR‐193b, miR‐671, miR‐222, miR‐23b, miR‐664, miR‐183, miR‐214, miR‐320a, miR‐23a, miR‐30a, miR‐320d, miR‐1285, miR‐32, miR‐181a, miR‐205, miR‐216a, miR‐1246, and miR‐106b).Conclusion: Cell proliferation is inhibited, and cell apoptosis is induced by curcumin in different urogenital cancers through suppressing oncogenic microRNAs or provoking tumor suppressor microRNAs.

Integrative Analysis Reveals a Nine TP53 Pathway‐Related lncRNA Prognostic Signature in Endometrial Cancer

Background. TP53 mutation is a common mutation gene in uterine corpus endometrial carcinoma (UCEC), and the TP53 signaling pathway plays an essential role in the tumorigenesis, progression, and immune infiltration in UCEC. We aimed to discover TP53 pathway‐related lncRNAs in UCEC. Materials and methods. 528 UCEC patients with 587 transcriptional profiles were enrolled in this study. We first investigated the differential status of TP53 signaling pathway between tumor and normal tissues by GSEA analysis, then identified TP53 pathway‐related lncRNAs, accordingly establishing a nine TP53 pathway related to the lncRNA signature in the training set and verified this signature in the test set. Besides, the interaction network was constructed; the immune infiltration, drug response to cisplatin and paclitaxel, and mutation atlas were investigated. Finally, we performed a subgroup analysis to check the universality of this signature. Results. A nine TP53 pathway‐related lncRNA prognostic signature was constructed and verified superior accuracy in predicting the overall survival of UCEC patients. Besides, high‐risk patients showed a poor prognosis, but they were more sensitive to the cisplatin and paclitaxel. Notably, M2 macrophages were higher infiltrated in high‐risk patients, and TP53 showed a significantly higher mutation in high‐risk patients than low‐risk patients. Conclusions. We constructed and verified a nine TP53 pathway‐related lncRNA prognostic signature in UCEC, which also contributes to the decision‐making of the chemotherapy.

Fertility‐Sparing Approach in Patients with Endometrioid Endometrial Cancer Grade 2 Stage IA (FIGO): A Qualitative Systematic Review

Background. Endometrial cancer (EC) is one of the most common gynecologic malignancy, mostly in postmenopausal women. The gold standard treatment for EC is surgery, but in the early stages, it is possible to opt for conservative treatment. In the last decade, different clinical and pathological markers have been studied to identify women who respond to conservative treatment. A lot of immunohistochemical markers have been evaluated to predict response to progestin treatment, even if their usefulness is still unclear; the prognosis of this neoplasm depends on tumor stage, and a specific therapeutic protocol is set according to the stage of the disease. Objective. (1) To provide an overview of the conservative management of Stage 1A Grade (G) 2 endometrioid EC (FIGO) and the oncological and reproductive outcomes related; (2) to describe the molecular alterations before and after progestin therapy in patients undergoing conservative treatment. Materials and Methods. A systematic computerized search of the literature was performed in the main electronic databases (MEDLINE, Embase, Web of Science, PubMed, and Cochrane Library), from 2010 to September 2021, in order to evaluate the oncological and reproductive outcomes in patients with G2 stage IA EC who ask for fertility‐sparing treatment. The expression of several immunohistochemical markers was evaluated in pretreatment phase and during the follow‐up in relation to response to hormonal therapy. Only scientific publications in English were included. The risk of bias assessment was performed. Review authors’ judgments were categorized as “low risk,” “high risk,” or “unclear risk” of bias. Results. Twelve articles were included in the study: 7 observational studies and 5 case series/reports. Eighty‐four patients who took progestins (megestrol acetate, medroxyprogesterone acetate, and/or levonorgestrel‐releasing intrauterine devices) were analyzed. The publication bias analysis turned out to be “low.” 54/84 patients had a complete response, 23/84 patients underwent radical surgery, and 20/84 had a relapse after conservative treatment. Twenty‐two patients had a pregnancy. The length of follow‐up was variable, from 6 to 142 months according to the different studies analyzed. Several clinical and pathological markers have been studied to identify women who do not respond to conservative treatment: PR and ER were the most studied predictive markers, in particular PR appeared as the most promising; MMR, SPAG9, Ki67, and Nrf2‐survivin pathway provided good results with a significant association with a good response to progestin therapy. However, no reliable predictive markers are currently available to be used in clinical practice. Conclusions. The conservative treatment may be an option for patients with stage IA G2 EEC who desire to preserve their fertility. The immunohistochemical markers evaluation looks promising in predicting response to conservative treatment. Further large series and randomized clinical trials are needed to confirm these results.

[Retracted] A Rehabilitation Model Conducive to Postoperative Recovery of Endometrial Cancer Patients after Laparoscopy

Although collaborative care is increasingly being implemented in the treatment of various diseases, there are currently no related studies on its effects in endometrial cancer patients after laparoscopic treatment. Thus, this study is aimed at investigating the significance of an integrated medical and nursing care model for women with gynecologic malignant tumors who underwent laparoscopic treatment. The patients were randomly divided into a medical‐nursing integrated nursing group (study group) and a general nursing group (control group). Their serum carbohydrate antigen 19‐9 (CA19‐9), human epididymal protein 4 (HE4), CA15‐3, and CA125 levels were measured at admission, 7 and 15 days after admission, and 30 days after discharge. Their first postoperative flatulence time, eating time, and hospitalization duration were recorded, and the self‐rating anxiety scale (SAS) and self‐rating depression scale (SDS) were used to evaluate the psychological state of the patients. A questionnaire survey was also used to evaluate their satisfaction with nursing. Adverse events within 2 years of follow‐up were recorded. The results showed that the clinical performance of the study group was significantly better than that of the control group. Further, the study group demonstrated significantly lower serum tumor marker levels, SAS score, SDS score, and incidence of adverse events at 7 and 15 days after admission and 30 days after discharge and higher nursing satisfaction than the control group. Thus, the collaborative nursing mode might be more conducive to the recovery of women who have underwent laparoscopic treatment for gynecologic malignant tumors than normal routine nursing.

TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer

Objective. Endometrial cancer (EC) is one of the most common malignant gynaecological tumours worldwide. This study was aimed at identifying EC prognostic genes and investigating the molecular mechanisms of these genes in EC. Methods. Two mRNA datasets of EC were downloaded from the Gene Expression Omnibus (GEO). The GEO2R tool and Draw Venn Diagram were used to identify differentially expressed genes (DEGs) between normal endometrial tissues and EC tissues. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Next, the protein‐protein interactions (PPIs) of these DEGs were determined by the Search Tool for the Retrieval of Interacting Genes (STRING) tool and Cytoscape with Molecular Complex Detection (MCODE). Furthermore, Kaplan‐Meier survival analysis was performed by UALCAN to verify genes associated with significantly poor prognosis. Next, Gene Expression Profiling Interactive Analysis (GEPIA) was used to verify the expression levels of these selected genes. Additionally, a reanalysis of the KEGG pathways was performed to understand the potential biological functions of selected genes. Finally, the associations between these genes and clinical features were analysed based on TCGA cancer genomic datasets for EC. Results. In EC tissues, compared with normal endometrial tissues, 147 of 249 DEGs were upregulated and 102 were downregulated. A total of 64 upregulated genes were assembled into a PPI network. Next, 14 genes were found to be both associated with significantly poor prognosis and highly expressed in EC tissues. Reanalysis of the KEGG pathways found that three of these genes were enriched in the cell cycle pathway. TTK, CDC25A, and ESPL1 showed higher expression in cancers with late stage and higher tumour grade. Conclusion. In summary, through integrated bioinformatics approaches, we found three significant prognostic genes of EC, which might be potential therapeutic targets for EC patients.

[Retracted] Ferroptosis‐Related lncRNA for the Establishment of Novel Prognostic Signature and Therapeutic Response Prediction to Endometrial Carcinoma

Background. Ferroptosis is a recently described form of intentional cellular damage that is iron‐dependent and separate from apoptosis, cellular necrosis, and autophagy. It has been demonstrated to be adequately regulated by long noncoding RNAs (lncRNAs) in various cancers. However, the predictive profile of ferroptosis‐related lncRNAs (FRLs) in endometrial carcinoma (EC) is unknown. Herein, FRLs associated with uterine corpus endometrial carcinoma (UCEC) prognosis were screened to predict treatment response in EC. Methods. Samples of EC and adjacent normal tissues were obtained from The Cancer Genome Atlas (TCGA) dataset repository. Limma and survival packages in R software were used to screen FRLs associated with the prognosis of EC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) chord and circle plots of FRLs were also plotted. Next, FRLs screened by the least absolute shrinkage and selection operator (LASSO) method were applied to construct and validate a multivariate Cox proportional risk regression model. Nomogram plots were created to forecast the outcome of UCEC patients, and gene set enrichment analysis (GSEA), principal component analysis (PCA), and immunoassays were performed on the prognostic models. Finally, limma, ggpubr, pRRophetic, and ggplot2 programs were used for drug sensitivity analysis of the prognostic models. Results. A signature based on nine FRLs (CFAP58‐DT, LINC00443, EMSLR, HYI‐AS1, ADIRF‐AS1, LINC02474, CDKN2B‐AS1, LINC01629, and LINC00942) was constructed. The developed FRL prognostic model effectively discriminated UCEC patients into low‐risk and high‐risk groups. Immunological checkpoints CD80 and CD40 were strongly expressed in the high‐risk group. In addition, the nine FRLs were all more expressed in the high‐risk group compared to the low‐risk group. Conclusion. These findings significantly contribute to the understanding of the function of FRLs in UCEC and provide promising therapeutic strategies for UCEC.

Integrated Bioinformatic Analysis of DNA Methylation and Immune Infiltration in Endometrial Cancer

Background. Endometrial cancer greatly threatens the health of female. Emerging evidences have demonstrated that DNA methylation and immune infiltration are involved in the occurrence and development of endometrial cancer. However, the mechanism and prognostic biomarkers of endometrial cancer are still unclear. In this study, we assess DNA methylation and immune infiltration via bioinformatic analysis. Methods. The latest RNA‐Seq, DNA methylation data, and clinical data related to endometrial cancer were downloaded from the UCSC Xena dataset. The methylation‐driven genes were selected, and then the risk score was obtained using “MethylMix” and “corrplot” R packages. The connection between methylated genes and the expression of screened driven genes were explored using “survminer” and “beeswarm” packages, respectively. Finally, the role of VTCN1in immune infiltration was analyzed using “CIBERSORT” package. Results. In this study, 179 upregulated genes, and 311 downregulated genes were identified and found to be related to extracellular matrix organization, cell–cell junctions, and cell adhesion molecular binding. The methylation‐driven gene VTCN1 was selected, and patients classified to the hypomethylation and high expression group displayed poor prognosis. The VTCN1 gene exhibited highest correlation coefficient between methylation and expression. More importantly, the hypomethylation of promoter of VTCN1 led to its high expression, thereby induce tumor development by inhibiting CD8+ T cell infiltration. Conclusions. Overall, our study was the first to reveal the mechanism of endometrial cancer by assessing DNA methylation and immune infiltration via integrated bioinformatic analysis. In addition, we found a pivotal prognostic biomarker for the disease. Our study provides potential targets for the diagnosis and prognosis of endometrial cancer in the future.

Expression of Selected Epithelial‐Mesenchymal Transition Transcription Factors in Endometrial Cancer

Endometrial cancer (EC) is the most common gynecologic malignancy in developed countries. The aim of this study was to analyze the expression of SNAIL, SLUG, TWIST1, TWIST2, ZEB1, and ZEB 2 in primary tumor and the correlation with morphological and clinical characteristics of EC. The study included 158 patients with EC after surgical treatments: total hysterectomy and lymphadenectomy. The percentages of EC specimens testing positively for the EMT transcription factors were 84.5% for SNAIL, 92.2% for SLUG, 10.9% for TWIST1, 100% for TWIST2, 89% for ZEB1, and 98% for ZEB2. The expression of SLUG in patients with FIGO stage III or IV, type II EC, myometrial invasion ≥ 50% of the uterine wall thickness, and adnexal involvement and in patients with distant metastases was significantly higher. SLUG and ZEB2 expressions were identified as significant predictors of higher FIGO stages (III or IV) on univariate analysis. The overexpression of SLUG was a significant predictor of more aggressive type II EC, myometrial invasion ≥ 50% of the uterine wall thickness, and distant metastases on both univariate and multivariate analysis. Moreover, the overexpression of SLUG and ZEB2 was shown to be significant predictors of adnexal involvement on univariate analysis. ZEB 2 overexpression was identified in multivariate analysis as another independent predictor associated with a lesser likelihood of type II EC. Both univariate and multivariate analyses demonstrated that SLUG expression was the only predictor of 5‐year survival in the study group. The overexpression of SLUG was associated with a significant increase in mortality hazard on univariate analysis and was shown to be a highly significant predictor of death on multivariate analysis. Conclusions. Selected proteins of the EMT pathway play a role in endometrial carcinogenesis; SLUG and ZEB2 expressions in the primary tumor might predict clinical outcomes in EC and drive therapeutic decisions regarding adjuvant treatment in patients with this malignancy.

RON Mediates Tumor‐Promoting Effects in Endometrial Adenocarcinoma

Endometrial adenocarcinoma is one of the most prevalent female reproductive tract cancers in the world, and the development of effective treatment is still the main goal of its current research. Epithelial‐mesenchymal transition (EMT) plays a significant part in the occurrence and development of epithelial carcinoma, including endometrial adenocarcinoma. Recepteur d’origine nantais (RON) induces EMT and promotes proliferation, migration, and invasion in various epithelial‐derived cancers, but its role in endometrial adenocarcinoma is still poorly studied. The purpose of this study is to verify the overexpression of RON in endometrial adenocarcinoma and to explore its specific roles. RON expression in tumor lesions was verified by immunohistochemical staining, HEC‐1B cells were used to construct stable cell lines with RON overexpression or knockdown to investigate the effects of RON on the function of endometrial adenocarcinoma cells, and xenotransplantation experiment was carried out in nude mice to explore the effect of RON on the growth of endometrial adenocarcinoma in vivo. This study revealed that RON could promote the proliferation, migration, and invasion of HEC‐1B cells and induce EMT, and these effects were regulated through the Smad pathway. RON overexpression could promote growth of endometrial adenocarcinoma cells in nude mice, while its inhibitor BMS777607 could restrict this role. RON played an important role in endometrial adenocarcinoma and had a potential to become a new therapeutic target for endometrial adenocarcinoma.

An Integrated Autophagy‐Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer: A Bioinformatics‐Based Approach

Endometrial cancer is one of the most common malignant tumors, lowering the quality of life among women worldwide. Autophagy plays dual roles in these malignancies. To search for prognostic markers for endometrial cancer, we mined The Cancer Genome Atlas and the Human Autophagy Database for information on endometrial cancer and autophagy‐related genes and identified five autophagy‐related long noncoding RNAs (lncRNAs) (LINC01871, SCARNA9, SOS1‐IT1, AL161618.1, and FIRRE). Based on these autophagy‐related lncRNAs, samples were divided into high‐risk and low‐risk groups. Survival analysis showed that the survival rate of the high‐risk group was significantly lower than that of the low‐risk group. Univariate and multivariate independent prognostic analyses showed that patients’ age, pathological grade, and FIGO stage were all risk factors for poor prognosis. A clinical correlation analysis of the relationship between the five autophagy‐related lncRNAs and patients’ age, pathological grade, and FIGO stage was also per https://orcid.org/0000‐0001‐7090‐1750 formed. Histopathological assessment of the tumor microenvironment showed that the ESTIMATE, immune, and stromal scores in the high‐risk group were lower than those in the low‐risk group. Principal component analysis and functional annotation were performed to confirm the correlations. To further evaluate the effect of the model constructed on prognosis, samples were divided into training (60%) and validation (40%) groups, regarding the risk status as an independent prognostic risk factor. A prognostic nomogram was constructed using patients’ age, pathological grade, FIGO stage, and risk status to estimate the patients’ survival rate. C‐index and multi‐index ROC curves were generated to verify the stability and accuracy of the nomogram. From this analysis, we concluded that the five lncRNAs identified in this study could affect the incidence and development of endometrial cancer by regulating the autophagy process. Therefore, these molecules may have the potential to serve as novel therapeutic targets and biomarkers.

PD‐1 Coexpression Gene Analysis and the Regulatory Network in Endometrial Cancer Based on Bioinformatics Analysis

Gynecological malignancies are tumors of the female reproductive system, mainly cervical cancer, endometrial cancer, and ovarian cancer. Endometrial cancer (EC) is the most common gynecological malignant tumor in developed countries. The aim of this study was to construct a network of programmed cell death protein 1 (PD‐1) coexpressed genes through bioinformatics analysis and screen the potential biomarkers of PD‐1 in endometrial cancer. In addition, genes and pathways involved in PD‐1 and modulating tumor immune status were identified. We select the EC transcriptomic dataset in TCGA to retrieve gene sets on the cBioPortal platform, and the PD‐1 coexpressed genes were obtained on the platform. GO and KEGG enrichment analysis of coexpressed genes was performed using the DAVID database. The target protein‐protein interaction (PPI) network was constructed using Cytoscape 3.7.1 software, and the hub genes were then screened. A total of 976 coexpression genes were obtained. The enrichment analysis showed that PD‐1 coexpressed genes were significantly enriched in overall components of the cell structure, the interaction of cytokines with cytokine receptors, chemokine signaling pathways, and cell adhesion molecules (CAMs). Ten hub genes were obtained by node degree analysis. CD3E gene is involved in the prognosis and immune process of EC, and the expression level is related to PD‐1 (Pearson correlation coefficient is 0.82, P < 0.01). Patients with low CD3E gene expression in EC have a poor prognosis. The coexpression hub genes of PD‐1 are related to immunity, in which CD3E is a prognostic marker that is involved in the PD‐1/PD‐L1‐induced tumor immune escape. This study provides a new area to study the mechanism of PD‐1/PD‐L1 in EC and the precise treatment with targeted drugs.

Tailored Therapy Based on Molecular Characteristics in Endometrial Cancer

Management of endometrial cancer, an adenocarcinoma of the endometrium which occupies most uterine corpus neoplasms, including uterine sarcomas, has been more relevant due to its increasing incidence. Extensive research on tumorigenesis molecular mechanisms and molecular characterization across cancers has brought paradigm shifts in the treatment of various malignant tumors. Endometrial cancer treatment has been traditionally guided according to the disease extent or histology types, while recent studies on molecular features have led to the introduction of targeted agents into clinical use, along with conventional chemotherapeutic agents in patients with recurrent or metastatic disease. Considering the proven efficacy and relatively tolerable toxicities of targeted therapies across malignant tumors, improvement of treatment outcomes is also expected in endometrial cancer by adopting an individualized therapy depending on the specific molecular features. Efficacy assessment of new biological agents is still ongoing based on previous preclinical data on endometrial cancer molecular features. Here, endometrial cancer molecular characterization will be reviewed, and then, we will introduce preclinical data, directing the adoption of new biological agents.

[Retracted] The Promotional Effect of Hollow MnO2 with Brucea Javanica Oil Emulsion (BJOE) on Endometrial Cancer Apoptosis

Endometrial cancer (EC) is a common gynecological malignancy worldwide whose therapy mainly depends on chemotherapy. In past years, an increasing number of studies indicate that hollow MnO2 could serve as a nanoplatform in the drug delivery system. The Brucea javanica oil emulsion (BJOE) has been illustrated to play a vital role in cancers. However, knowledge about the combined effect of H‐MnO2‐PEG/BJOE in endometrial cancer remains ambiguous up to now. In the present work, we prepared a drug‐delivery vector H‐MnO2‐PEG by chemical synthesis and found that H‐MnO2‐PEG significantly inhibited cell proliferation in endometrial cancer cells. Moreover, the combination of H‐MnO2‐PEG/BJOE could repress cell proliferation more efficiently and promote cell apoptosis. Mechanistically, we found that BJOE exerted its role as a promoter of endometrial apoptosis by regulating relative protein expressions. In general, the present study demonstrates that H‐MnO2‐PEG functions as a critical vector in the tumor microenvironment of endometrial cancer and the significant effect of H‐MnO2‐PEG/BJOE on cancer cells, suggesting a new paradigm for the treatment of endometrial cancer.

Proteomic Analysis of Human Endometrial Tissues Reveals the Roles of PI3K/AKT/mTOR Pathway and Tumor Angiogenesis Molecules in the Pathogenesis of Endometrial Cancer

As one major gynecological malignancy, endometrial cancer (EC) has been widely studied recently. However, its pathogenesis is still unclear to date. In this study, we identified differentially expressed proteins between 30 endometrial cancer tissues and 30 matched normal controls using 2D LC‐MS/MS quantitative proteomics. As a result, we identified 619 differentially expressed proteins among all 2521 proteins being quantified. Further analyses suggested that the changes of fat, amino acid metabolism, peroxisome, extracellular signal, cytoskeleton, and other signaling or metabolic pathways may be closely related to the development of this cancer. Particularly, the PI3K/AKT/mTOR pathway‐related molecules including PI3K and mTOR, ERK (the molecule of the ERK pathway), SPP1, and ANGPT2 (angiogenesis‐related molecules) are highly associated with the pathogenesis of EC, which were reconfirmed by western blot and immunohistochemistry (IHC) analysis. In summary, our study revealed that the PI3K/AKT/mTOR pathway and tumor angiogenesis molecules contribute to the pathogenesis of endometrial cancer.

Machine Learning Supports Long Noncoding RNAs as Expression Markers for Endometrial Carcinoma

Uterine corpus endometrial carcinoma (UCEC) is the second most common type of gynecological tumor. Several research studies have recently shown the potential of different ncRNAs as biomarkers for prognostics and diagnosis in different types of cancers, including UCEC. Thus, we hypothesized that long noncoding RNAs (lncRNAs) could serve as efficient factors to discriminate solid primary (TP) and normal adjacent (NT) tissues in UCEC with high accuracy. We performed an in silico differential expression analysis comparing TP and NT from a set of samples downloaded from the Cancer Genome Atlas (TCGA) database, targeting highly differentially expressed lncRNAs that could potentially serve as gene expression markers. All analyses were performed in R software. The receiver operator characteristics (ROC) analyses and both supervised and unsupervised machine learning indicated a set of 14 lncRNAs that may serve as biomarkers for UCEC. Functions and putative pathways were assessed through a coexpression network and target enrichment analysis.

Acceptance of HPV Vaccination: A Systematic Review of Knowledge, Attitudes and Barriers Among Healthcare Practitioners in Low‐ and Middle‐Income Countries

Background Cervical cancer is one of the diseases that reflects global inequities. Vaccination against the human papillomavirus (HPV) is one of the main pillars of the World Health Organization (WHO) 2030 cervical cancer 90:70:90 elimination strategy. The role of healthcare practitioners in HPV vaccination acceptance cannot be overemphasized. This review investigated healthcare practitioners′ knowledge, attitudes and barriers to promoting HPV vaccination in low‐ and middle‐income countries (LMICs). Methods A comprehensive search for relevant literature from 2006 to 2024 was conducted in the following databases: Web of Science, Scopus, MEDLINE, EMBASE, PsycINFO (via Ovid), Cochrane Library and CINAHL PLUS (via EBSCOhost). The included studies were published in the English language. Screening of eligible studies, data extraction and quality assessment were conducted in duplicate. The data was synthesise using narrative synthesis. Results A total of 671 papers were identified from the database search, with seven studies meeting the criteria for inclusion. This review demonstrates varied levels of awareness, knowledge and attitudes of 136 healthcare practitioners in LMICs towards HPV vaccination. Although some studies demonstrated a positive attitude, others reported resistance towards the vaccine. The perceived barriers to HPV vaccination by healthcare practitioners identified were interpersonal, community‐level and systemic in nature. Additionally, acceptance of HPV vaccination varied across the studies. Conclusions This review highlights the need for capacity building programmes for healthcare practitioners in the area of HPV vaccination to enhance their knowledge and attitudes and develop contextually relevant interventions to eliminate the many barriers they encounter.

Comprehensive Analysis of DGATs and PLINs in Ovarian Cancer: Implications for Diagnosis and Prognosis

Background Lipid droplet (LD) dynamics drive cancer cell proliferation, resistance, and aggressiveness. Diacylglycerol O‐acyltransferases (DGATs) and perilipins (PLINs) are key LD‐associated genes implicated in cancer pathophysiology. Objective This study aimed to comprehensively analyze the expression and clinical significance of DGATs and PLINs in ovarian cancer (OC), focusing on their correlation with LDs and triglyceride (TG) levels, and to explore their diagnostic and prognostic implications. Methods LD and TG levels in ovarian cell lines and clinical samples were assessed using BODIPY staining, fluorometric, colorimetric assays, and thin‐layer chromatography (TLC). Gene expression profiling of DGATs and PLINs in cell lines and tissue was conducted via RT‐qPCR, ELISA, and bioinformatics analysis. Correlation analyses between gene expression, Ki67, and survival data were performed. ROC curve analysis evaluated diagnostic potential. Results LD accumulation was significantly higher in OC cell lines and tissues compared with normal controls. Diacylglycerol O‐acyltransferase 1 (DGAT1) and diacylglycerol O‐acyltransferase 2 (DGAT2) were overexpressed in OC cell lines and tissues, particularly in advanced stages (III and IV). Elevated TG levels were observed in OC cell lines and clinical samples, correlating with LD abundance and the expression of DGAT1 and DGAT2. PLIN2 and PLIN3 were significantly upregulated in OC tissues. Bioinformatics analysis identified dysregulation of DGATs and PLINs in OC. Survival analysis indicated DGAT2 is a predictor of poor prognosis. Diagnostic assessments revealed DGAT2 as a potential biomarker for OC detection. Conclusion DGATs and PLINs are pivotal in LD metabolism and tumor progression in OC, with DGAT2 being a good candidate as prognostic and diagnostic marker. They present promising avenues for therapeutic targeting and diagnostic biomarkers, holding the potential to improve patient outcomes. Further exploration of their mechanistic roles and clinical implications is essential for advancing personalized cancer care.

Cervical Cancer in Women With HIV: A Call to Action for Equitable Prevention in Low‐ and Middle‐Income Countries

Cervical cancer is preventable; however, it remains the leading cause of death in low‐ and middle‐income countries (LMICs). Women with HIV (WWHs) have a sixfold higher risk of developing and dying from cervical cancer than women without HIV. Cervical cancer can be prevented by vaccination against high‐risk human papillomaviruses (hrHPVs) and by screening for and treating precancer cervical lesions. While these preventive measures are routinely available to WWHs in developed countries, they are lacking in most LMICs, where the burden of HIV and cervical cancer is the highest. To prevent cervical cancer deaths among WWHs in LMICs, it is imperative to determine the dual burden of HIV and cervical cancer in LMICs. This narrative review synthesized scientific papers and policy documents on the intersection of HIV and cervical cancer in LMICs published between August 2006 and July 2025. We searched PubMed, Scopus, Web of Science, and Google Scholar for articles and official reports from the World Health Organization (WHO) and the US Centers for Disease Control and Prevention (CDC) on cervical cancer burden, prevention strategies, barriers, and outcomes among WWHs. Despite its proven effectiveness, HPV vaccination coverage in LMICs is under 30%, and screening uptake is below 20%. Weak health systems, workforce shortages, stigma, reliance on donor funding, and late‐stage case presentation are major challenges in curbing cervical cancer in LMICs. Urgent political commitment is required to integrate precancer screening and HPV testing into routine HIV care and scale‐up HPV vaccination to achieve the WHO′s triple‐intervention targets to eliminate cervical cancer among WWHs in LMICs.

Applications and Prospects of Single‐Cell RNA Sequencing and Spatial Transcriptomics in Cervical Cancer

Cervical cancer (CC) is the fourth commonest malignant tumor among women worldwide and is characterized by high heterogeneity and a complex ecosystem. A comprehensive understanding of the heterogeneity of tumors and the tumor microenvironment (TME) is crucial for effective CC management. Single‐cell RNA sequencing (scRNA‐seq) is a powerful tool that can be employed to unveil the heterogeneity of tumors and the TME, as well as to elucidate the evolutionary trajectories of tumors. Spatial transcriptomics (ST) technology, on the other hand, can address the complexity and diversity of the spatial microenvironment of tumors, thereby compensating for the limitations of scRNA‐seq. As emerging technologies, both scRNA‐seq and ST are increasingly being utilized in CC research. In this review, we summarized the latest advancements in scRNA‐seq and ST for CC, with a focus on investigating tumor heterogeneity, the TME, tumor evolutionary trajectories, treatment resistance mechanisms, and potential therapeutic targets. These insights collectively contribute to the development of more effective treatment and prevention strategies for CC.

Knowledge, Practices, and Perceptions of the Healthcare Providers on Cervical Cancer Screening Among HIV‐Positive Women at Lira Regional Referral Hospital, Lira City

Background: Cervical cancer remains a global burden and is by far one of the major causes of premature death among women of reproductive age. We explored the knowledge, practices, and perceptions of healthcare providers on cervical cancer screening (CCS) among HIV‐positive women aged 18–49 years in Lira City. Methods: In June 2023, a qualitative cross‐sectional study was conducted among healthcare providers at Lira Regional Referral Hospital (LRRH), Lira City, Northern Uganda. Key informant interviews (KIIs) were used to collect data among purposively selected healthcare providers. Interviews were audio‐recorded, transcribed verbatim, and coded using the NVivo (QSR International) software. Thematic content analysis was used in data analysis. Results: The study found that participants had good knowledge about cervical cancer and screening. They provided health education and vaccination for eligible girls and screened HIV‐positive women for cervical cancer. Long waiting hours, long distances to healthcare facilities, and negative attitudes of some health providers were reported as barriers to CCS utilization. However, increased awareness, the presence of signs/symptoms, and the desire to maintain optimal health facilitated CCS utilization among HIV‐positive women. Conclusion: Whereas the participants’ knowledge and perceptions about CCS were good, their practices towards CCS among HIV‐positive women were suboptimal. Continuous education of healthcare providers, decentralization of CCS, and routine and ongoing health education initiatives are pivotal in improving CCS practices among HIV‐positive women.

Systematic Construction and Validation of an Immune‐Related Gene‐Based Model to Predict Prognosis for Ovarian Cancer

Ovarian cancer (OC) is a malignancy with poor prognosis, stubborn resistance, and frequent recurrence. Recently, it has been widely recognized that immune‐related genes (IRGs) have demonstrated their indispensable importance in the occurrence and progression of OC. Given this, this study aimed to identify IRGs with predictive value and build a prognostic model for a more accurate assessment. First, we obtained transcriptome and clinical information of ovarian samples from both TCGA and GTEx databases. After integration, we figured out 10 genes as immune‐related prognostic genes (IRPGs) by performing the univariate Cox regression analysis. Subsequently, we established a TF‐associated network to investigate its internal mechanism. The prognosis model consisting of 5 IRPGs was constructed later by lasso regression analysis. The comparison of the score with the clinical factors validated its independence and superiority in OC’s prognosis. Moreover, the association between the signature and immune cell infiltration demonstrated its ability to image the immune situation of the tumor microenvironment. Finally, the reliability of the risk model was confirmed by the GEO cohort. Together, our study has constructed an independent prognostic model for OC, which may deepen the understanding of the immune microenvironment and help present novel biomarkers or ideas for targeted therapy.

Identification of Circulating MicroRNAs as a Promising Diagnostic Biomarker for Cervical Intraepithelial Neoplasia and Early Cancer: A Meta‐Analysis

Background. Cervical cancer (CC) is one of the most common female malignant tumors. And cervical intraepithelial neoplasia (CIN) is the precancerous lesion of CC, which can progress to invasive CC. MicroRNAs (miRNAs) have been found to be potential diagnostic biomarkers for CIN or CC. However, recently, the lack of sufficient studies about the diagnostic value of miRNAs for CIN made it challenging to separately investigate the diagnostic efficacy of miRNAs for CIN. Likewise, the conclusions among those studies were discordant. Therefore, we conducted this meta‐analysis, aimed at evaluating the diagnostic efficacy of miRNAs for CIN and CC patients. Methods. Literature search was performed in PubMed, Embase, and Web of Science databases. Pooled sensitivity, specificity, and other diagnostic parameters were calculated through Stata 14.0 software. Furthermore, subgroup analyses and metaregression analysis were conducted to explore the main sources of heterogeneity. Results. Ten articles covering 50 studies were eligible, which included 5,908 patients and 4,819 healthy individuals. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were 0.81 (95% CI, 0.77‐0.85), 0.86 (95% CI, 0.83‐0.89), 5.9 (95% CI, 4.5‐7.7), 0.22 (95% CI, 0.17‐0.28), 27 (95% CI, 17‐44), and 0.91 (95% CI, 0.88‐0.93), respectively. Additionally, the ethnicity and internal reference were the main sources of heterogeneity. Conclusions. Circulating miRNAs can be a promising noninvasive diagnostic biomarker for CIN and early CC, especially miR‐9 and miR‐205, which need to be verified by large‐scale studies.

Construction of Immune‐Associated Nomogram for Predicting the Recurrence Survival Risk of Stage I Cervical Cancer

Background. Various studies reported that the prognosis of patients with cervical cancer (CC) was significantly associated with immunity, whereas limited studies have explored whether immune‐associated genes could be classifiers for recurrence‐free survival (RFS) of stage I CC. Thus, an improved immune‐related gene signature for stage I CC patients’ prognosis is urgently required. Materials and Methods. We retrospectively analyzed the gene expression profiles of stage I CC patients in the GSE44001 set from the Gene Expression Omnibus (GEO) database. The stage I CC patients were randomly divided into the training group and the internal validation group. The training patients were adopted to develop a prognostic immune gene‐based signature; meanwhile, the internal validation patients were used to validate the power of the selected immune gene‐related signature using univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis. The accuracy and reliability of the immune gene‐related signature were evaluated based on Kaplan‐Meier analysis and time‐dependent receiver operating characteristic (ROC) curves. Results. High power of the 8‐immune gene signature was found on the basis of ROC analysis (AUC at 1, 3, and 5 years were exhibited in the internal validation group (0.702, 0.715, and 0.728, respectively), external validation group (0.702, 0.825, and 0.842, respectively), and entire GEO dataset (0.840, 0.894, and 0.852, respectively)). Besides, C‐index, ROC, calibration plots, and decision curve analysis (DCA) also acted well in our nomogram, suggestive of a high ability of the nomogram to elevate the prognostic prediction of stage I CC patients. Conclusions. In this study, we successfully constructed an integrated 8‐immune gene‐based signature which could accurately identify patients with low prognostic risk from those with high prognostic risk. In addition, we developed an immune‐related nomogram which can elevate the prognostic prediction of stage I CC patients.

A Comprehensive Analysis of Interferon Regulatory Factor Expression: Correlation with Immune Cell Infiltration and Patient Prognosis in Endometrial Carcinoma

As a family of transcription factors, the correlations between expression pattern of nine interferon regulatory factor (IRF) family members, the immune invasion pattern, and the associated patient survival rate in endometrial carcinoma (EC) remain to be elucidated. Based on The Cancer Genome Atlas (TCGA), the expression profiles of the high and low IRF mRNA expression groups were analyzed using R (3.6.3) statistical software. Gene annotation and pathway analyses were performed using Metascape. GSEA was performed using the R package clusterProfiler (3.6.3). The single‐sample gene set enrichment analysis (ssGSEA) was used to quantify the relative tumor infiltration levels of immune cell types. Immunohistochemistry data provided by HPA database was used to study the expression of the IRF proteins. Using the GEPIA dataset, the correlation between the expression of IRFs and the tumor stage of EC was analyzed. The correlations between the different IRFs were analyzed using cBioPortal. The expression of IRF2, IRF3, IRF5, IRF6, IRF7, IRF8, and IRF9 was different when comparing EC and normal endometrial samples. IRF2, IRF6, IRF7, and IRF8 were indicated to be potential diagnostic markers for EC. In combination with receiver operating characteristic analysis results, IRF2, IRF6, IRF7, and IRF8 were indicated to be potential diagnostic markers for EC. Levels of individual IRFs were associated with alternate outcomes, with the expression of IRF3 being correlated with the stage of EC and high expression of IRF4 being positively correlated with overall survival (OS); conversely, high expression of IRF5 was negatively correlated with OS. Additionally, high expression levels of both IRF2 and IRF4 were positively correlated with the disease‐specific survival rate, and high expression of IRF4 was positively correlated with the progression‐free interval. These data suggest a role for IRF2, IRF4, and IRF5 in the prognosis of EC. The expression of IRFs is associated with immune infiltration.

Integrative Analysis of Differently Expressed Genes Reveals a 17‐Gene Prognosis Signature for Endometrial Carcinoma

Endometrial carcinoma (EC) is the fifth widely occurring malignant neoplasm among women all over the world. However, there is still lacking efficacy indicators for EC’s prognosis. Here, we analyzed two databases including an RNA‐sequencing‐based TCGA dataset and a microarray‐based GSE106191. After normalizing the raw data, we identified 114 common genes with upregulation and 308 common genes with downregulation in both the TCGA and GSE106191 databases. Bioinformatics analysis showed that the differently expressed genes in EC were related to the IL17 signaling pathway, PI3K‐Akt signaling pathway, and cGMP‐PKG signaling pathway. Furthermore, we performed the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and generated a signature featuring 17 prognosis‐related genes (MAL2, ANKRD22, METTL7B, IL32, ERFE, OAS1, TRPC1, SRPX, RAPGEF4, PSD3, SIMC1, TRPC6, WFS1, PGR, PAMR1, KCNK6, and FAM189A2) and found that it could predict OS in EC patients. The further analysis showed that OAS1, MAL2, ANKRD22, METTL7B, and IL32 were significantly upregulated in EC samples after comparison with normal samples. However, TRPC1, SRPX, RAPGEF4, PSD3, SIMC1, TRPC6, WFS1, PGR, PAMR1, KCNK6, and FAM189A2 were significantly downregulated in EC samples in comparison with normal samples. And correlation analysis showed that our results showed that the expressions of 17 prognosis‐related hub genes were significantly correlated based on Pearson correlation. We here offer a newly genetic biomarker for the prediction of EC patients’ prognosis.

lncRNA SNHG15 Promotes Ovarian Cancer Progression through Regulated CDK6 via Sponging miR‐370‐3p

Ovarian cancer is a kind of cancer from the female genital tract; the molecular mechanism still needs to be explored. lncRNA plays a vital role in tumorigenesis and development. Our aim was to identify oncogenic lncRNAs in ovarian cancer and explore the potential molecular mechanism. SNHG15 was initially identified by using GEO datasets (GSE135886 and GSE119054) and validated by tumor tissues and the cell line, identifying that SNHG15 was upregulated in ovarian cancer. Besides, high SNHG15 indicated poor prognosis in ovarian cancer. Furthermore, knockdown SNHG15 suppresses ovarian cancer proliferation and promotes apoptosis. Mechanistically, SNHG15 promotes proliferation through upregulated CDK6 via sponging miR‐370‐3p. Taken together, our findings emphasize the important role of SNHG15 in ovarian cancer, suggesting that SNHG15 may be a promising target for ovarian cancer.

Screening and Identification of an Immune‐Associated lncRNA Prognostic Signature in Ovarian Carcinoma: Evidence from Bioinformatic Analysis

Backgrounds. The dysregulated long noncoding RNAs (lncRNAs) have been described to be crucial regulators in the progression of ovarian carcinoma. The infiltration status of immune cells is also related to the clinical outcomes in ovarian carcinoma. The present research is aimed at constructing an immune‐associated lncRNA signature with potential prognostic value for ovarian carcinoma patients. Methods. We obtained 379 ovarian carcinoma cases with available clinical data and transcriptome data from The Cancer Genome Atlas database to evaluate the infiltration status of immune cells, thereby generating high and low immune cell infiltration groups. According to the expression of the immune‐associated lncRNA signature, the risk score of each case was calculated. The high‐ and low‐risk groups were classified using the median risk score as threshold. Results. A total of 169 immune‐associated lncRNAs that differentially expressed in ovarian carcinoma were included. According to the Lasso regression analysis and Cox univariate and multivariate analyses, 5 immune‐associated lncRNAs, including AC134312.1, AL133467.1, CHRM3‐AS2, LINC01722, and LINC02207, were identified as a predictive signature with significant prognostic value in ovarian carcinoma. The following Kaplan‐Meier analysis, ROC analysis, and Cox univariate and multivariate analyses further suggested that the predicted signature may be an independent prognosticator for patients with ovarian carcinoma. The following gene set enrichment analysis showed that this 5 immune‐associated lncRNAs signature was significantly related to the hedgehog pathway, basal cell carcinoma, Wnt signaling pathway, cytokine receptor interaction, antigen processing and presentation, and T cell receptor pathway. Conclusion: This study suggested a predictive model with 5 immune‐associated lncRNAs that has an independent prognostic value for ovarian carcinoma patients.

Analysis of Characteristics of Endometrial Carcinoma in Peri- and Postmenopausal Women with Abnormal Uterine Bleeding

Objective. To analyze the menstrual characteristics of endometrial carcinoma and investigate whether abnormal uterine bleeding in the perimenopausal period differs from postmenopausal bleeding. Methods. We conducted a retrospective analysis of 928 cases of endometrial carcinoma in patients admitted from January 2016 to December 2022. We gathered fundamental clinical data and analyzed distinct clinical risk factors between the perimenopausal and postmenopausal groups. Furthermore, we computed the statistical variances in menarche, regular menstrual cycles, and the duration of abnormal uterine bleeding. Results. Perimenopausal patients with endometrial carcinoma exhibit similar factors to postmenopausal patients, especially if they have a history of menstrual cycles lasting more than 30 years, hypertension, abnormal uterine bleeding for over 1 year, and a high risk of endometrial carcinoma. Early intervention for abnormal uterine bleeding during the perimenopausal stage can prevent up to 80% of women from developing endometrial carcinoma. Conclusion. Perimenopause women experiencing abnormal uterine bleeding should be mindful of the risk of endometrial carcinoma, as this awareness can substantially decrease the occurrence of the disease.

Development and Validation of an Immune‐Related Prognostic Signature for Ovarian Cancer Based on Weighted Gene Coexpression Network Analysis

Background. Ovarian cancer is one of the most lethal diseases of women. The prognosis of ovarian cancer patients was closely correlated with immune cell expression and immune responses. Therefore, it is important to identify a robust prognostic signature, which correlates not only with prognoses but also with immune responses in ovarian cancer, thus, providing immune‐related patient therapies. Methods. The weighted gene coexpression network analysis (WGCNA) was used to identify candidate genes correlated with ovarian cancer prognoses. Univariate and multivariate Cox regression analyses were used to construct the prognostic signature. The Kaplan‐Meier method was used to predict survival, and the immune‐related bioinformatics analysis was performed using the R software. The relationship between the signature and clinical parameters was analyzed with the GraphPad Prism 7 and SPSS software. Results. Gene expression from The Cancer Genome Atlas dataset was used to perform the WGCNA analysis, and candidate prognostic‐related genes in patients with ovarian cancer were identified. According to the Cox regression analysis, the prognostic signature was constructed, which divided patients into two groups. The high‐risk group showed the least favorable prognosis. Three independent cohorts from the Gene Expression Omnibus (GEO) database were used for the validation studies. According to the immune analyses, the GEO database signatures were significantly correlated with the immune statuses of ovarian cancer patients. By analyzing the combination of the prognostic signature and total mutational burden (TMB), ovarian cancer patients were divided into four groups. In these groups, memory B cell, resting memory CD4 T cell, M2 macrophage, resting mast cell, and neutrophil were found with significant distinctions among these groups. Conclusions. This novel signature predicted the prognosis of ovarian cancer patients precisely and independently and showed significant correlations with immune responses. Therefore, this prognostic signature could indicate targeted immunotherapies for ovarian cancer patients.

The Prognostic Values of the Insulin‐Like Growth Factor Binding Protein Family in Ovarian Cancer

Purpose. To assess the expression of insulin‐like growth factor binding protein (IGFBP) family and its prognostic impact in ovarian cancer (OC) patients. Materials and Methods. The mRNA expression and protein expression of individual IGFBPs in healthy ovarian samples and OC tissues were explored through Oncomine, Gene Expression Profiling Interactive Analysis, and Human Protein Atlas database. Additionally, the prognostic values of the six IGFBP members in patients with OC were evaluated by Kaplan‐Meier plotter. Results. IGFBP2 and IGFBP4 mRNA expression were remarkably upregulated in patients with OC. To be specific, the mRNA expression of IGFBP2 was upregulated in patients with serous ovarian cancer (SOC), while IGFBP1/3/4/5/6 mRNA levels were downregulated. In addition, the IGFBP4 protein expression was upregulated in SOC, and the IGFBP6 protein expression was upregulated in both of SOC and endometrioid ovarian cancer (EOC) tissues. High IGFBP1 mRNA levels showed favorable overall survival (OS) and progression‐free survival (PFS) in all OC. Meanwhile, increased IGFBP5/6 mRNA levels revealed worsen OS and PFS in all OC patients. IGFBP4/6 mRNA levels predicted unfavorable OS and PFS only in SOC patients. Moreover, the aberrant mRNA expression of IGFBP1/2/4/5/6 was correlated with significantly prognosis in patients receiving different chemotherapeutic regimens. Conclusion. This study indicates that the IGFBP family reveals distinct prognosis in patients with OC. IGFBP1/2/4/5/6 are useful prognostic predictors for chemotherapeutic effect in OC patients, and IGFBP2/4 are potential tumor markers for the diagnosis of OC.

The Overexpression of Keratin 23 Promotes Migration of Ovarian Cancer via Epithelial‐Mesenchymal Transition

Background. Keratin 23 (KRT23) is a new member of the KRT gene family and known to be involved in the development and migration of various types of tumors. However, the role of KRT23 in ovarian cancer (OC) remains unclear. This study is aimed at investigating the function of KRT23 in OC. Methods. The expression of KRT23 in normal ovarian and OC tissues was determined using the Oncomine database and immunohistochemical staining. Reverse transcription quantitative polymerase chain reaction assay was used to analyze the expression of KRT23 in normal ovarian epithelial cell lines and OC cell lines. Small interfering RNA (siRNA), wound healing assay, and transwell assay were conducted to detect the effects of KRT23 on OC cell migration and invasion. Further mechanistic studies were verified by the Gene Expression Profiling Interactive Analysis platform, Western blotting, and immunofluorescence staining. Results. KRT23 was highly expressed in OC tissues and cell lines. High KRT23 expression could regulate OC cell migration and invasion, and the reduction of KRT23 by siRNA inhibited the migration and invasion of OC cells in vitro. Furthermore, KRT23 mediated epithelial‐mesenchymal transition (EMT) by regulating p‐Smad2/3 levels in the TGF‐β/Smad signaling pathway. Conclusions. These results demonstrate that KRT23 plays an important role in OC migration via EMT by regulating the TGF‐β/Smad signaling pathway.

Gene‐Gene Interaction Analysis for the Survival Phenotype Based on the Kaplan‐Meier Median Estimate

In this study, we propose a simple and computationally efficient method based on the multifactor dimensional reduction algorithm to identify gene‐gene interactions associated with the survival phenotype. The proposed method, referred to as KM‐MDR, uses the Kaplan‐Meier median survival time as a classifier. The KM‐MDR method classifies multilocus genotypes into a binary attribute for high‐ or low‐risk groups using median survival time and replaces balanced accuracy with log‐rank test statistics as a score to determine the best model. Through intensive simulation studies, we compared the power of KM‐MDR with that of Surv‐MDR, Cox‐MDR, and AFT‐MDR. It was found that KM‐MDR has a similar power to that of Surv‐MDR, with less computing time, and has comparable power to that of Cox‐MDR and AFT‐MDR, even when there is a covariate effect. Furthermore, we apply KM‐MDR to a real dataset of ovarian cancer patients from The Cancer Genome Atlas (TCGA).

Prognostic Values of Transforming Growth Factor‐Beta Subtypes in Ovarian Cancer

Purpose. To explore the potential role of the transforming growth factor‐beta (TGF‐β) subtypes in the prognosis of ovarian cancer patients. Materials and Methods. The prognostic roles of individual TGF‐β subtypes in women with ovarian cancer were retrieved from the Kaplan‐Meier plotter (KM plotter) database. In addition, the Oncomine database and immunohistochemistry were used to observe the mRNA and protein expression of TGF‐β subtypes between human ovarian carcinoma and normal ovarian samples, respectively. Results. TGF‐β1 and TGF‐β4 were totally uncorrelated with survival outcomes in women with ovarian cancer. Increased TGF‐β2 and TGF‐β3 mRNA expression was markedly related to unfavorable prognosis, especially in women with serous, poorly differentiated, and late‐stage ovarian carcinoma. High expression levels of TGF‐β2 were related to worse progression‐free survival (PFS) while TGF‐β3 was linked to unfavorable overall survival (OS) and PFS in women with TP53‐mutated ovarian cancer. TGF‐β2 was associated with poor OS and PFS from treatment with chemotherapy with platins, Taxol, or a platin+Taxol. However, overexpression of TGF‐β3 was associated with poor OS from the use of platins and poor PFS of Taxol or a platin+Taxol in women with ovarian carcinoma. Furthermore, the expression of TGF‐β2 mRNA and protein was higher but only TGF‐β3 mRNA expression was higher in cancerous tissues than in normal ovarian samples. Conclusion. Higher expression of TGF‐β2 functioned as a significant predictor of poor prognosis in women with ovarian cancer, especially those with TP53 mutations or who were undergoing chemotherapy with platins, Taxol, or a platin+Taxol.

Overexpression of BMPER in Ovarian Cancer and the Mechanism by which It Promotes Malignant Biological Behavior in Tumor Cells

Background. BMPER has been reported to be associated with the biological behavior of a few malignant tumors, but the mechanism is still unclear. We aimed to detect BMPER expression in ovarian epithelial tumor tissues and its effects on their biological behaviors, as well as to elucidate the possible mechanism. Methods. BMPER expression in ovarian epithelial tumor tissues was detected by immunohistochemistry. BMPER expression in ovarian cancer cell lines was inhibited via RNA interference. Changes in the malignant behaviors of ovarian cancer cells were detected by MTT, wound healing, Transwell, and flow cytometry assays. Changes in proteins in the MAPK and autophagy‐related signaling pathways were detected by Western blot analysis. Results. The expression of BMPER was significantly upregulated in ovarian epithelial malignant tumors and was related to increased lymph node metastasis and lower survival rate. High BMPER expression is an independent risk factor for poor prognosis in patients. Inhibition of BMPER inhibited the proliferation, invasion, and migration of ovarian cancer cells and promoted apoptosis. In addition, BMPER downregulation decreased the expression of PCNA, Bcl‐2, MMP2, and MMP9 and increased the expression of Bax. Moreover, the levels of p‐ERK, p‐MEK, and the autophagy‐related protein p‐mTOR were decreased, and Beclin 1 levels and the LC3II/I ratio were increased. Conclusions. Our findings indicated that BMPER is closely related to poor prognosis in ovarian cancer. BMPER plays a role in promoting the malignant biological behavior of tumor cells through the MAPK and autophagy‐related signaling pathways.

Recurrence‐Associated Multi‐RNA Signature to Predict Disease‐Free Survival for Ovarian Cancer Patients

Ovarian cancer (OvCa) is an intractable gynecological malignancy due to the high recurrence rate. Several molecular biomarkers have been previously screened for early identifying patients with a high recurrence risk and poor prognosis. However, all the known studies focused on a single type of RNAs, not integrating various types. This study was to construct a new multi‐RNA‐based model to predict the recurrence and prognosis for OvCa patients by using the messenger RNA (mRNA, including long noncoding RNA (lncRNA)) and microRNA (miRNA) sequencing data of The Cancer Genome Atlas database. After univariate Cox regression and least absolute shrinkage and selection operator analyses, a multi‐RNA‐based signature (2 miRNAs: hsa‐miR‐508, hsa‐miR‐506; 1 lncRNA: TM4SF1‐AS1; 11 mRNAs: MAGI3, SLAMF7, GLI2, PDK1, ARID3A, PLEKHG4B, TNFAIP8L3, C1QTNF3, NDUFAF1, CH25H, TMEM129) was generated and used to establish a risk score model. The high‐ and low‐risk patients classified by the median risk score exhibited significantly different recurrence risks (89% versus 61%, p < 0.001) and survival time (the area under the receiver operating characteristic curve (AUC) = 0.901 for 5‐year disease‐free survival (DFS)). This risk model was independent of other clinical features and superior to pathologic staging for DFS prediction (AUC, 0.906 versus 0.524; C‐index, 0.633 versus 0.510). Furthermore, some new interaction axes were revealed to explain the possible functions of these RNAs (competing endogenous RNA: TM4SF1‐AS1‐miR‐186‐STEAP2, LINC00536‐miR‐508‐STEAP2, LINC00475‐miR‐506‐TMEM129; coexpression: LINC00598‐PLEKHG4B). In conclusion, this multi‐RNA‐based risk model may be clinically useful to stratify OvCa patients with different recurrence risks and survival outcomes and included RNAs may be potential therapeutic targets.

Different Genotype Distribution of Human Papillomavirus between Cervical and Esophageal Cancers: A Study in Both High‐Incidence Areas, Xinjiang, China

The aim of this study is to reveal the certain human papillomavirus (HPV) genotype distribution between cervical cancer and esophageal cancer in the both high‐incidence geographic regions. For this study, we collected and detected the infection of HPV in 120 paraffin‐embedded esophageal tissues and 152 paraffin‐embedded cervical tissues, respectively. The esophageal tissues include 40 normal epithelium (ENOR), 26 dysplasia (DYS), and 54 invasive squamous cell carcinoma (ESCC). The cervical tissues consisted of 40 normal epithelium (CNOR), 53 intraepithelial neoplasia (CIN), and 59 invasive squamous cell carcinoma (CSCC). Both esophageal and cervical tissues collected in this study came from the same area, in which both the ESCC and CSCC were in high incidence, Xinjiang province, China. HPV GenoArray test kits were served to analyze the HPV infection. The result shows that among the 59 CSCC tissues, the total infection rate of HPV was 98.3% (58/59). The positive rate of HPV‐16 infection was 63.8% (37/58). It indicated that HPV‐16 is the most common infection among all of the high‐risk HPV. The multiple infection rate was 19.0% (11/58). Among the 54 ESCC, a total of 7 genotypes were detected. The total infection rate of HPV was 61.1% (33/54). The positive rate of HPV‐16 infection was 63.6% (21/33). The multiple infection rate was 6.1% (2/33). Our result shows that high‐risk‐type HPV‐16 was associated with both cervical cancer and esophageal cancer, which play a role in the high‐incidence area in Xinjiang. We hope that our results could point out the direction for the treatment strategy of HPV‐associated cancer, cervical cancer, and esophageal cancer and for the application of HPV vaccines in the future.

Identifying Sequence Variants of 18 Hereditary Ovarian Cancer‐Associated Genes in Chinese Epithelial Ovarian Cancer Patients

Objectives. The causes of ovarian cancer (OC) have been confirmed to be closely related to genetic factors. Identifying sequence variants of hereditary ovarian cancer (HOC) susceptibility genes can increase clinical surveillance, facilitate early detection, and provide personalized treatment for patients. This study is aimed at investigating the variation frequency of HOC susceptibility genes in the Chinese population and providing information for the etiology and genetics of OC. Methods. 118 epithelial OC patients were recruited in this clinical study. Variants of 18‐gene panel were detected in blood samples by next‐generation sequencing (NGS) technology. Results. Overall, 36.44% (43/118) of patients carried at least one pathogenic variant. Among these, BRCA1 pathogenic variants were detected in 31 (26.27%) patients, and 5 (4.24%) patients carried pathogenic variants of BRCA2. Moreover, 27.12% (32/118) of patients carried variants of unknown significance (VUSs). Importantly, we detected eight variants that were not reported previously. Conclusions. Our study enlarged the spectrum of HOC‐associated gene sequence variants in the Chinese population and also proved the necessity of multigene testing in epithelial OC patients. The identification of patients with HOC will allow family members to undergo cascade testing where identification of unaffected carriers can facilitate early detection, risk reduction, or prevention of OC and ultimately improve long‐term outcomes.

Integrated miRNA‐mRNA Expression Profiles Revealing Key Molecules in Ovarian Cancer Based on Bioinformatics Analysis

Ovarian cancer is one of the leading causes of gynecological malignancy‐related deaths. The underlying molecular development mechanism has however not been elucidated. In this study, we used bioinformatics to reveal critical molecular and biological processes associated with ovarian cancer. The microarray datasets of miRNA and mRNA expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. Besides, we performed target prediction of the identified differentially expressed miRNAs. The overlapped differentially expressed genes (DEGs) were obtained combined with miRNA targets predicted and the DEGs identified from the mRNA dataset. The Cytoscape software was used to design a regulatory network of miRNA‐gene. Moreover, the overlapped DEGs in the network were subjected to enrichment analysis to explore the associated biological processes. The molecular protein‐protein interaction (PPI) network was used to identify the key genes among the DEGs of prognostic value for ovarian cancer, and the genes were evaluated via Kaplan‐Meier curve analysis. A total of 186 overlapped DEGs were identified. Through miRNA‐gene network analysis, we found that miR‐195‐5p, miR‐424‐5p, and miR‐497‐5p highly exhibited targeted association with overlapped DEGs. The three miRNAs are critical in the regulatory network and act as tumor suppressors. The overlapped DEGs were mainly associated with protein metabolism, histogenesis, and development of the reproductive system and ocular tissues. The PPI network identified 10 vital genes that promote tumor progression. Survival analysis found that CEP55 and CCNE1 may be associated with the prognosis of ovarian cancer. These findings provide insights to understand the pathogenesis of ovarian cancer and suggest new candidate biomarkers for early screening of ovarian cancer.

Identification of Specific Cell Subpopulations and Marker Genes in Ovarian Cancer Using Single‐Cell RNA Sequencing

Objective. Ovarian cancer is the deadliest gynaecological cancer globally. In our study, we aimed to analyze specific cell subpopulations and marker genes among ovarian cancer cells by single‐cell RNA sequencing (RNA‐seq). Methods. Single‐cell RNA‐seq data of 66 high‐grade serous ovarian cancer cells were employed from the Gene Expression Omnibus (GEO). Using the Seurat package, we performed quality control to remove cells with low quality. After normalization, we detected highly variable genes across the single cells. Then, principal component analysis (PCA) and cell clustering were performed. The marker genes in different cell clusters were detected. A total of 568 ovarian cancer samples and 8 normal ovarian samples were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes were identified according to ∣log2fold change (FC) | >1 and adjusted p value <0.05. To explore potential biological processes and pathways, functional enrichment analyses were performed. Furthermore, survival analyses of differentially expressed marker genes were performed. Results. After normalization, 6000 highly variable genes were identified across the single cells. The cells were divided into 3 cell populations, including G1, G2M, and S cell cycles. A total of 1,124 differentially expressed genes were identified in ovarian cancer samples. These differentially expressed genes were enriched in several pathways associated with cancer, such as metabolic pathways, pathways in cancer, and PI3K‐Akt signaling pathway. Furthermore, marker genes, STAT1, ANP32E, GPRC5A, and EGFL6, were highly expressed in ovarian cancer, while PMP22, FBXO21, and CYB5R3 were lowly expressed in ovarian cancer. These marker genes were positively associated with prognosis of ovarian cancer. Conclusion. Our findings revealed specific cell subpopulations and marker genes in ovarian cancer using single‐cell RNA‐seq, which provided a novel insight into the heterogeneity of ovarian cancer.

Cytoreductive Surgery plus Hyperthermic Intraperitoneal Chemotherapy Improves Survival with Acceptable Safety for Advanced Ovarian Cancer: A Clinical Study of 100 Patients

Background . The mainstay of treatment for advanced ovarian cancer is debulking surgery followed by chemotherapy that includes carboplatin and paclitaxel, but the prognosis is poor. This study is aimed at evaluating the efficacy and safety of cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy (CRS+HIPEC) as first‐line surgical treatment in patients with advanced ovarian cancer (AOC). Methods . FIGO stage III/IV AOC patients underwent CRS+HIPEC as first‐line surgical treatment at our center from December 2007 to January 2020. The primary endpoint was survival, and the secondary endpoint was safety. Results . Among 100 patients, the median Karnofsky performance status (KPS) score was 80 (50‐100), median peritoneal cancer index (PCI) was 19 (1‐39), median completeness of cytoreduction (CC) score was 1 (0‐3), number of organ regions removed was 4 (3‐9), number of peritoneal regions removed was 4 (1‐9), and number of anastomoses was 1 (0‐4). The median follow‐up was 36.8 months; 75 (75.0%) patients were still alive, and 25 (25.0%) had died. The median overall survival (mOS) was 87.6 (95% CI: 72.1‐103.0) months, and the 1‐, 2‐, 3‐, 4‐, and 5‐year survival rates were 94.1%, 77.2%, 68.2%, 64.2%, and 64.2%, respectively. Univariate analysis showed that better mOS correlated with an age ≤, KPS ≥ 80, ascites ≤ 1000 ml, PCI < 19, and CC score 0‐1. Multivariate Cox analysis showed that CC was an independent factor for OS; patients who underwent CRS with a CC score 0‐1 had a mPFS of 67.8 (95% CI: 48.3‐87.4) months. The perioperative serious adverse event and morbidity rates were 4.0% and 2.0%, respectively. Conclusions . CRS+HIPEC improves survival for AOC patients with acceptable safety at experienced high‐volume centers. Stringent patient selection and complete CRS are key factors for better survival.

Overexpression of RIPK4 Predicts Poor Prognosis and Promotes Metastasis in Ovarian Cancer

This study was conducted to evaluate the prognostic value of receptor‐interacting protein kinase 4 (RIPK4) in ovarian cancer (OC) and its role in tumorigenesis. RNA expression and the corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and Genotype‐Tissue Expression (GTEx) databases. The relationship between clinical‐pathological characteristics and RIPK4 expression was analyzed using the Wilcoxon signed‐rank test and logistic regression. The Cox regression and the Kaplan‐Meier method were used to evaluate the relationship between clinicopathological features and overall survival (OS). Gene set enrichment analysis (GSEA) was performed using Molecular Signatures Database. Scratch assay, transwell assay, and cell transfection were used to verify the function of RIPK4. Overexpression of RIPK4 was associated with the stage of OC and distant metastasis. Survival analysis revealed that patients with OC and higher expression of RIPK4 had a poorer prognosis. Univariate and multivariate analyses indicated that high expression of RIPK4 was associated with poor OS, as well as age and stage of OC. The areas under the curve (AUC) at 1, 4, and 8 years were 0.737, 0.634, and 0.669, respectively, according to the established OS prediction model. GSEA revealed that adherens junction, cadherin binding, and Wnt signaling pathway were enriched in the high RIPK4 expression group. Cell transfection confirmed RIPK4 was involved in the Wnt signaling pathway. RIPK4 can act as a potential prognostic molecular marker for poor survival in OC. Moreover, RIPK4 is associated with tumor metastasis and implicated in the regulation of the Wnt signaling pathway.

Predicting Ovarian/Breast Cancer Pathogenic Risks of Human BRCA1 Gene Variants of Unknown Significance

High‐throughput sequencing is gaining popularity in clinical diagnoses, but more and more novel gene variants with unknown clinical significance are being found, giving difficulties to interpretations of people’s genetic data, precise disease diagnoses, and the making of therapeutic strategies and decisions. In order to solve these issues, it is of critical importance to figure out ways to analyze and interpret such variants. In this work, BRCA1 gene variants with unknown clinical significance were identified from clinical sequencing data, and then, we developed machine learning models so as to predict the pathogenicity for variants with unknown clinical significance. Through performance benchmarking, we found that the optimized random forest model scored 0.85 in area under receiver operating characteristic curve, which outperformed other models. Finally, we applied the best random forest model to predict the pathogenicity of 6321 BRCA1 variants from both sequencing data and ClinVar database. As a result, we obtained the predictive pathogenic risks of BRCA1 variants of unknown significance.

Increased Expression of LYNX1 in Ovarian Serous Cystadenocarcinoma Predicts Poor Prognosis

Few studies have reported the function of LYNX1 in ovarian cancer. We retrieved LYNX1 gene expression data and clinical information of 376 patients with ovarian cancer from The Cancer Genome Atlas (TCGA) project website. Wilcoxon signed‐rank test and logistic regression were used to analyze the relationship between clinical pathologic features and LYNX1 expression. The Kaplan–Meier method was used to draw survival curves of patients, and Cox regression was used to calculate the relationship between LYNX1 expression and survival rate or the clinicopathological characteristics of the patients. Gene set enrichment analysis (GSEA) was performed, and the correlation between LYNX1 expression and cancer immune infiltrates was investigated via single sample gene set enrichment analysis (ssGSEA). High LYNX1 expression in ovarian serous cystadenocarcinoma (OVs) was associated with tumor residual disease (RD). In Kaplan–Meier survival analysis, patients with OVs who also displayed high LYNX1 expression had decreased overall survival (OS) and disease‐specific survival (DSS) than those with low LYNX1 expression. Univariate analysis also supported that patients with high LYNX1 expression had lower OS than those with low LYNX1 expression. LYNX1 expression has the potential to be a prognostic molecular marker of poor survival in OVs.

Determination of Potential Therapeutic Targets and Prognostic Markers of Ovarian Cancer by Bioinformatics Analysis

This study is to study the expression of CXCRs in ovarian cancer tissues and their value in prognosis. The expressions of CXCR1‐CXCR7 mRNA between ovarian tumor tissues and normal tissues and in different pathological types of ovarian tumor tissues were compared by ONCOMINE online tool. The relationship between the expression of CXCRs and clinical pathological staging was studied by GEPIA. Kaplan‐Meier plotter online tool was used to analyze prognosis. Finally, GO and KEGG analyses and protein interaction network analysis were performed for CXCRs by the DAVID software to predict their function, and cBioPortal was used to identify the key functional genes. The expression of CXCR3/4/7 mRNA in ovarian cancer tissues was higher than that in normal ovarian tissues, and the expression of CXCR4 was the highest (fold change = 306.413, P < 0.05). The expression of CXCR1/2/3/4/7 mRNA in different pathological types of ovarian tumors was significantly different (P < 0.05). Only CXCR5 expression level was associated with tumor staging. Survival analysis showed that high CXCR7 mRNA expression and low CXCR5/6 expression were associated with the shortening of overall survival. High CXCR4/7 expression and low CXCR5/6 expression were associated with the shortening of progression‐free survival. High CXCR2/4 expression and low CXCR5/6 expression were closely related to the shortening of postprogressing survival. Protein interaction network analysis showed that GNB1, PTK2, MAPK1, PIK3CA, GNB4, GNA11, KNG1, and ARNT proteins were closely related to the CXC receptor family. CXCR3/4/7 are potential therapeutic targets, and CXCR2/4/5/6/7 are new markers for the prognosis of ovarian cancer.

Serum Levels of S100A11 and MMP‐9 in Patients with Epithelial Ovarian Cancer and Their Clinical Significance

Objective. To investigate the serum levels of calgizzarin (S100A11) and matrix metalloproteinase‐9 (MMP9) in patients with epithelial ovarian cancer (EOC) and determine their clinical significance. Methods. Serum levels of S100A11 and MMP9 were detected in patients with EOC, patients with benign ovarian tumor, and healthy women. The correlation between the two markers and clinicopathological characteristics of ovarian cancer was analysed. Results. The serum levels of S100A11 and MMP‐9 in patients with EOC were higher than those in patients with benign ovarian tumor and in healthy women, and the expression levels of S100A11 and MMP‐9 were positively correlated. S100A11 and MMP‐9 were correlated with tumor staging, postoperative residual foci, ascites volume, serum CA125 level, chemotherapy response, and lymph node metastasis, while S100A11 and MMP‐9 were not associated with the bilevel classification, histological type, age, and degree of differentiation. Conclusion. S100A11 and MMP‐9 were both highly expressed in the serum of patients with EOC and were associated with cancer development, invasion, and metastasis. Therefore, they can be used as an important reference maker in the diagnosis and treatment of ovarian cancer.

Application of O‐RADS Ultrasound Lexicon‐Based Logistic Regression Analysis Model in the Diagnosis of Solid Component‐Containing Ovarian Malignancies

Objective. To use the logistic regression model to evaluate the value of ultrasound characteristics in the Ovarian‐Adnexal Reporting and Data System ultrasound lexicon in determining ovarian solid component‐containing mass benignancy/malignancy. Methods. We retrospectively analyzed the data of 172 patients with adnexal masses discovered by ultrasound, and diagnosis was confirmed by postoperative pathological tests from January 2019 to December 2021. Thirteen ovarian tumor‐related parameters in the benign and malignant ovarian tumor groups were selected for univariate analyses. Statistically significant parameters were included in multivariate logistic regression analyses to construct a logistic regression diagnosis model, and the diagnostic performance of the model in predicting ovarian malignancies was calculated. Results. Of the 172 adnexal tumors, 104 were benign, and 68 were malignant. There were differences in cancer antigen 125, maximum mass diameter, maximum solid component diameter, multilocular cyst with solid component, external contour, whether acoustic shadows were present in the solid component, number of papillae, vascularity, presence/absence of ascites, and presence/absence of peritoneal thickening or nodules between the benign ovarian tumor and malignancy groups (p < 0.05). Logistic regression analyses showed that maximum solid component diameter, whether acoustic shadows were present in the solid component, number of papillae, and presence/absence of ascites were included in the logistic regression model, and the area under the receiver operating characteristic curve for this regression model in predicting ovarian malignancy was 0.962 (95% confidence interval: 0.933~0.990; p < 0.001). Logit (p) ≥ −0.02 was used as the cutoff value, and the prediction accuracy, sensitivity, specificity, positive predictive value, and negative predictive values were 93.6%, 86.8%, 98.1%, 96.7%, and 91.9%, respectively. Conclusion. The logistic regression model containing the maximum solid component diameter, whether acoustic shadows were present in the solid component, number of papillae, and presence/absence of ascites can help in determining the benignancy/malignancy of solid component‐containing masses.

GJA1 Expression and Its Prognostic Value in Cervical Cancer

Gap Junction Protein Alpha 1 (GJA1) belongs to the gap junction family and has been widely studied in cancers. We evaluated the role of GJA1 in cervical cancer (CC) using public data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. The difference of GJA1 expression level between CC and normal tissues was analyzed by the Gene Expression Profiling Interactive Analysis (GEPIA), six GEO datasets, and the Human Protein Atlas (HPA). The relationship between clinicopathological features and GJA1 expression was analyzed by the chi‐squared test and the logistic regression. Kaplan–Meier survival analysis and Cox proportional hazard regression analysis were used to assessing the effect of GJA1 expression on survival. Gene set enrichment analysis (GSEA) was used to screen the signaling pathways regulated by GJA1. Immune Cell Abundance Identifier (ImmuCellAI) was chosen to analyze the immune cells affected by GJA1. The expression of GJA1 in CC was significantly lower than that in normal tissues based on the GEPIA, GEO datasets, and HPA. Both the chi‐squared test and the logistic regression showed that high‐GJA1 expression was significantly correlated with keratinization, hormone use, tumor size, and FIGO stage. The Kaplan–Meier curves suggested that high‐GJA1 expression could indicate poor prognosis (p = 0.0058). Multivariate analysis showed that high‐GJA1 expression was an independent predictor of poor overall survival (HR, 4.084; 95% CI, 1.354‐12.320; p = 0.013). GSEA showed many cancer‐related pathways, such as the p53 signaling pathway and the Wnt signaling pathway, were enriched in the high‐GJA1‐expression group. Immune cell abundance analysis revealed that the abundance of CD8 naive, DC, and neutrophil was significantly increased in the high‐GJA1‐expression group. In conclusion, GJA1 can be regarded as a potential prognostic marker of poor survival and therapeutic target in CC. Moreover, many cancer‐related pathways may be the critical pathways regulated by GJA1. Furthermore, GJA1 can affect the abundance of immune cells.

Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer

Purpose. We want to develop a model for predicting lymph node status based on positron emission computed tomography (PET) images of untreated ovarian cancer patients. We use the feature map formed by wavelet transform and the parameters obtained by image segmentation to build the model. The model is expected to help clinicians and provide additional information about what to do with first‐visit patients. Materials and Methods. Our study included 224 patients with ovarian cancer. We have chosen two main methods to extract information from images. On the one hand, we segmented the image to extract the parameters to evaluate the clustering effect. On the other hand, we used wavelet transform to extract the image’s texture information to form the image’s feature map. Based on the above two kinds of information, we used residual neural network and support vector machine for modeling. Results. We established a model to predict lymph node metastasis in patients with primary ovarian cancer using PET images. On the training set, our accuracy was 0.8854, AUC: 0.9472, CI: 0.9098‐0.9752, sensitivity was 0.9865, and specificity was 0.7952. On the test set, our accuracy was 0.9104, AUC: 0.9259, CI: 0.8417‐0.9889, sensitivity was 0.8125, and specificity was 1.0000. Conclusions. We used wavelet transform to process the preoperative medical images of ovarian cancer patients, and the residual neural network can effectively predict the lymph node metastasis of ovarian cancer patients, which is undoubted of great significance for patients’ staging and treatment options.

[Retracted] SPOCK2 Promotes the Malignant Behavior of Ovarian Cancer via Regulation of the Wnt/β‐Catenin Signaling Pathway

Background . Ovarian cancer (OC) is a common clinical gynecological disease, which seriously threatens women’s health and life. We investigated the roles of SPOCK2 in OC and its associated molecular mechanism in the current study. Methods . The expressions and prognostic value of SPOCK2 in OC were identified using the clinical data and data from the GEPIA database. Then, SPOCK2 silence was implemented to search functions of SPOCK2 in OC cells. CCK‐8 was used to examine cell proliferation. Cell apoptosis was detected by flow cytometry. The OC cell invasion and migration were evaluated by transwell assays. Results . Overexpressed SPOCK2 was identified in OC, which was correlated with poor prognosis and a shorter survival rate. SPOCK2 downregulation significantly suppressed OC cell proliferation, migration, and invasion, and cell apoptosis was markedly promoted by SPOCK2 silence. Meanwhile, SPOCK2 knockdown could effectively suppress Wnt/ β ‐catenin. Conclusion . SPOCK2 exerted crucial functions in OC progression and could serve as a promising candidate for OC targeted therapy.

Immune‐Related Four‐lncRNA Signature for Patients with Cervical Cancer

Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune‐related lncRNAs (IRLs) of CC has never been reported. This study is aimed at establishing an IRL signature for patients with CC. A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty‐eight IRLs were collected according to the Pearson correlation analysis between the immune score and lncRNA expression (p < 0.01). Four IRLs (BZRAP1‐AS1, EMX2OS, ZNF667‐AS1, and CTC‐429P9.1) with the most significant prognostic values (p < 0.05) were identified which demonstrated an ability to stratify patients into the low‐risk and high‐risk groups by developing a risk score model. It was observed that patients in the low‐risk group showed longer overall survival (OS) than those in the high‐risk group in the training set, valid set, and total set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four‐IRL signature in predicting the one‐, two‐, and three‐year survival rates was larger than 0.65. In addition, the low‐risk and high‐risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four IRLs in the development of CC were ascertained preliminarily.

An Immune‐Related lncRNA Pairing Model for Predicting the Prognosis and Immune‐Infiltrating Cell Condition in Human Ovarian Cancer

Ovarian cancer is the second common cancer among the gynecological tumors. It is difficult to be found and diagnosed in the early stage and easy to relapse due to chemoresistance and deficiency in choices of treatment. Therefore, future exploring the biomarkers for diagnosis, treatment, and prognosis prediction of ovarian cancer is significant to women in the world. We downloaded data from TCGA and GTEx and used R “limma” package for analyzing the differentially expressed immune‐related lncRNA in ovarian cancer and finally got 7 downregulated and 171 upregulated lncRNA. Then, we paired the differentially expressed immune‐related lncRNA and constructed a novel lncRNA pairing model containing 7 lncRNA pairs. Based on the cut‐off point with the highest AUC value, 102 patients were selected in high‐risk group and 272 in low‐risk group. The KM analysis suggested that the patients in the low‐risk group had a longer overall survival. Future analysis showed the correlations between risk scores and clinicopathological parameters and infiltrating immune cells. In conclusion, we identified an immune‐related lncRNA pairing model for predicting the prognosis and immune‐infiltrating cell condition in human ovarian cancer, which thus further can instruct immunotherapy.

Association between XRCC3 rs861539 Polymorphism and the Risk of Ovarian Cancer: Meta‐Analysis and Trial Sequential Analysis

Background. Current studies on the relationship between XRCC3 rs861539 polymorphism and ovarian cancer risk have been inconsistent. Therefore, we performed a meta‐analysis to explore their association. Methods. Six electronic databases (PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, and China Wanfang Database) were searched for relevant studies published before December 2021. Meta‐analysis, subgroup analysis, sensitivity analysis, and publication bias analysis were performed using Stata software 16.0. Trial sequential analysis (TSA) was performed using TSA 0.9.5.10 Beta software. Results. A total of 12 studies were included in 9 literatures, comprising 4,634 cases of ovarian cancer and 7,381 controls. After Bonferroni correction, the meta‐analysis showed an association between XRCC3 rs861539 polymorphism and ovarian cancer risk in the heterozygote model and the dominant model (GA vs. GG: OR = 0.88, 95%CI = 0.81‐0.96, P = 0.003; GG vs. GA+AA: OR = 0.89, 95%CI = 0.82‐0.96, P = 0.004). In an ethnically stratified subgroup analysis, XRCC3 rs861539 was shown to reduce the risk of ovarian cancer in Caucasian in the heterozygote model and the dominant model (GA vs. GG: OR = 0.88, 95%CI = 0.81‐0.96, P = 0.004; GG vs. GA+AA: OR = 0.88, 95%CI = 0.81‐0.96, P = 0.004). In the control source and detection method stratified subgroup analysis, hospital‐based studies and PCR‐RFLP‐based studies were found to increase ovarian cancer risk (GG vs. AA: OR = 1.30, 95%CI = 1.05‐1.62, P = 0.016; GG vs. AA: OR = 1.31, 95%CI = 1.06‐1.62, P = 0.013). Conclusion. This meta‐analysis showed a significant association between XRCC3 rs861539 polymorphism and ovarian cancer risk, especially in Caucasians. Large‐scale multicenter case‐control studies in more different regions will be needed in the future.

Effects of Autophagy‐Related Genes on the Prognosis and Immune Microenvironment of Ovarian Cancer

Ovarian cancer (OC) is among the most malignant tumors of the female reproductive system. The role of autophagy in cancer is complex, and the functional relationship between autophagy‐related genes and OC remains unclear. Here, the prognostic value of autophagy‐related genes in OC and relationships between autophagy and immune function were evaluated. OC data from The Cancer Genome Atlas and the Human Autophagy Database were obtained to identify autophagy‐related genes. Univariate and multivariate Cox analyses were used to construct a prognostic model based on autophagy‐related genes. Relationships between risk scores and clinical traits were evaluated. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Cytoscape were used to analyze gene functions and their effects on the immune microenvironment. Relationships between autophagy genes and long noncoding RNAs (lncRNAs) were evaluated by Pearson’s correlation coefficients, and lncRNAs corresponding to the autophagy‐related genes associated with OC prognosis were used to construct a model. Relationships between risk scores and survival and prognosis were evaluated. Finally, a gene set enrichment analysis was performed. Seven autophagy‐related genes (CAPN1, CDKN1B, DNAJB1, GNAI3, MTMR14, RHEB, and SIRT2) were identified as independent predictors of prognosis. Three lncRNAs corresponding to autophagy genes independently influenced prognosis. Autophagy genes are closely related to immunity. Fifteen immune cell types showed different levels of infiltration between the high‐ and low‐risk groups. Moreover, immune cell infiltration differed between the high‐ and low‐risk groups based on the model. Our analysis of genes and lncRNAs related to prognosis clarifies the role of autophagy in OC and provides a theoretical basis for further research.

Performance Analysis of Ovarian Cancer Detection and Classification for Microarray Gene Data

The most common gynecologic cancer, behind cervical and uterine, is ovarian cancer. Ovarian cancer is a severe concern for women. Abnormal cells form and spread throughout the body. Ovarian cancer microarray data can diagnose and prognosis. Typically, ovarian cancer microarray data contains tens of thousands of genes. In order to reduce computational complexity, selecting the most critical genes or attributes in the entire dataset is necessary. Because microarray datasets have limited samples and many characteristics, classifier detection lags. So, dimensionality reduction measures are essential to protect disease classification genes. In this research, initially the ANOVA method is used for gene selection and then two clustering‐based and three transform‐based feature extraction methods, namely, Fuzzy C Means, Softmax Discriminant Algorithm (SDA), Hilbert Transform, Fast Fourier Transform (FFT), and Discrete Cosine Transform (DCT), respectively, are used to select relevant genes further. Six classifiers further classify the features as normal and abnormal. The NLR classifier gives the highest accuracy for SDA features at 92%, and KNN gives the lowest accuracy of 55% for SDA, Hilbert, and DCT features. With correlation distance feature selection, the NLR classifier attains the lowest accuracy of 53%, and the highest accuracy of 88% is obtained by the GMM classifier.

Association between Rheumatoid Arthritis Disease Activity and Risk of Ovarian Malignancy in Middle‐Aged and Elderly Women

Objective. To investigate the risk of ovarian malignancy in middle‐aged and elderly women with rheumatoid arthritis (RA) and its correlation with disease activity. Methods. 219 middle‐aged and elderly (age ≥ 40) female RA patients who were treated at the Department of Rheumatology and Immunology of the Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine from August 2019 to September 2020 were selected. Their general information such as age and medical history was collected. RA disease activity‐related indicators include rheumatoid factor (RF), anticyclic citrullinated peptide antibody (ACPA), ESR, CRP, and ovarian malignancy risk‐related indicators including alpha fetoprotein (AFP), carcinoembryonic antigen (CEA), CA125, CA199, and human epididymis protein 4 (HE4) were detected. According to Risk of Ovarian Malignancy Algorithm (ROMA), they were divided into a low‐risk group (ROMA‐low, premenopausal: ROMA ≤ 11.4%, postmenopausal: ROMA ≤ 29.9%) and a high‐risk group (ROMA‐high, premenopausal: ROMA > 11.4%, postmenopausal: ROMA > 29.9%) for ovarian malignancy. Meanwhile, according to the DAS28‐ESR, they were divided into the general disease activity group (DAS28‐ESR ≤ 5.1) and the high disease activity group (DAS28‐ESR > 5.1). SPSS 25.0 software was used to compare the differences among groups and to analyze the correlation between ovarian malignancy risk and RA disease activity. Results. Compared with the ROMA‐low group, the levels of RF, ACCP, CDAI, SDAI, DAS28‐ESR, and DAS28‐CRP in the ROMA‐high group were significantly increased (P < 0.05). HE4 and ROMA in the high disease activity group were significantly higher than general disease activity group (P < 0.05). Spearman correlation analysis showed that age (r = 0.472), RF (r = 0.221), ACPA (r = 0.156), CDAI (r = 0.226), SDAI (r = 0.221), DAS28‐ESR (r = 0.254), DAS28‐CRP (r = 0.208), medications (r = 0.189), and CA199 (r = 0.250) were correlated with ROMA (P < 0.05). Multivariate regression analysis showed that ESR (OR = 1.11), SDAI (OR = 1.02), DAS28‐ESR (OR = 1.33), DAS28‐CRP (OR = 1.26), and CA199 (OR = 1.03) were independent risk factors for high risk of ovarian malignancy (P < 0.05). Subgroup analysis showed that CA199 is an effect modification factor for DAS28‐ESR (P < 0.05). Conclusion. The risk of ovarian malignancy is significantly increased in middle‐aged and elderly women with high disease activity with rheumatoid arthritis. In clinical, full attention should be paid to the risk of ovarian malignancy in this population. Screening in time, especially in patients with increased DAS28‐ESR and CA199 at the same time, is needed.

[Retracted] Time Intervals between Double Primary Breast and Ovarian Cancers and Survival Outcomes of Patients with Both Cancers: A SEER Database Analysis

Background. The time interval rules and survival outcomes of individuals with synchronous and metachronous breast cancer (BC) and ovarian cancer (OC) were examined in this retrospective population‐based investigation. Methods . The National Cancer Institute’s Surveillance, Epidemiology, and End Results database was used to create a cohort of people diagnosed with BC and OC between 1973 and 2015. Patients were separated into three groups: those with main BC followed by primary OC (group 1), those with synchronous primary breast and ovarian cancer (group 2), and those with OC prior to BC (group 3). The Kaplan‐Meier technique was used to assess overall survival (OS) and cancer‐specific survival (CSS). Results . A total of 4,975 patients were identified: 2,929 patients in group 1, 680 patients in group 2, and 1,366 patients in group 3. The average duration between these tumors was 60 months (range 0–499). Approximately 50% of second primary cancer cases occurred during the first 60 months of the first primary cancer diagnosis, and more than 70% occurred within the first 120 months. The median survival time for 4,975 individuals was 140 months. Group 2 had the smallest median OS (35 months), whereas group 3 had the longest (45 months) (239 months). Conclusions . The majority of second primary cancer cases occurred during the first 120 months following the diagnosis of the first original malignancy. Individuals who had primary OC prior to BC had better prognoses, whereas patients who had synchronous BC and OC had worse prognoses.

An Innovative Immune Score‐Based Prognostic Nomogram for Patients with Cervical Cancer

Background. In the past few years, the immune system and tumor immune microenvironment are becoming increasingly popular as more work has been accomplished in this field. However, nomograms based on immune‐related characteristics for prognosis prediction of cervical cancer have not been fully explored to our knowledge. We constructed a novel immune score‐based nomogram to predict patients with high risk and poor prognosis. Materials and Methods. 198 patients with cervical cancer from The Cancer Genome Atlas (TCGA) database were included in our study. Immune scores were generated with Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm, and clinic‐pathological characteristics were also included for subsequent analysis. Cox proportional hazards regression models were performed for univariate and multivariate analyses to screen the significant factors, and a prognostic nomogram was built. Bootstrap resampling analysis was used for internal validation. The calibration curve and concordance index (C‐index) were used to assess the predictive performance of the nomogram. Results. Patients were split into three subgroups based on immune scores. We found that patients with high immune scores conferred significantly better overall survival (OS) compared with those with medium and low immune scores (hazard ratio (HR), 0.305; 95% confidence interval (CI), 0.108‐0.869). A nomogram with a C‐index of 0.720 had a favorable performance for predicting survival rate for clinical use by combining immune scores with other clinical features. The calibration curves at 3 and 5 years suggested a good consistency between the predicted OS and the actual OS probability. Conclusions. Our work highlights the potential clinical application significance of immune score‐based nomogram in predicting the OS of cervical cancer patients.

Understanding the Correlation between Metabolic Regulator SIRT1 and Exosomes with CA‐125 in Ovarian Cancer: A Clinicopathological Study

Background. Ovarian cancer (OvCa), the deadliest gynaecological malignancy, is associated with poor prognosis and high mortality rate. Ovarian cancer has been related with CA‐125 and metabolic reprogramming by SIRT1 leading to metastasis with the involvement of exosomes. Methods. Clinicopathological data of OvCa patients were collected to perform the analysis. Patients’ samples were collected during surgery for immunohistochemistry and flow cytometric analysis of SIRT1, HIF‐1α, exosomal markers (CD81 and CD63), ki‐67, and PAS staining for glycogen deposition. Adjacent normal and tumor tissues were collected as per the CA‐125 levels. Results. CA‐125, a vital diagnostic marker, has shown significant correlation with body mass index (BMI) (P = 0.0153), tumor type (P = 0.0029), ascites level, ascites malignancy, degree of dissemination, tumor differentiation, FIGO stage, TNM stage, laterality, and tumor size at P < 0.0001. Since significant correlation was associated with BMI and degree of dissemination, as disclosed by IHC analysis, metabolic marker SIRT1 (P = 0.0003), HIF‐1α (P < 0.0001), exosomal marker CD81 (P < 0.0001), ki‐67 status (P = 0.0034), and glycogen deposition (P <0.0001) were expressed more in tumor tissues as compared to the normal ones. ROC analysis of CA‐125 had shown 327.7 U/ml has the best cutoff point with 82.4% sensitivity and specificity of 52.3%. In addition, Kaplan‐Meier plots of CA‐125 (P < 0.0001), BMI (P = 0.001), degree of dissemination (P < 0.0001), and ascites level (P <0.0001) reflected significant correlation with overall survival (OS). Upon multivariate Cox‐regression analysis for overall survival (OS), BMI (P = 0.008, HR 1.759, 95% CI 1.156‐2.677), ascites malignancy (P = 0.032, HR 0.336, 95% CI 0.124‐0.911), and degree of dissemination (P = 0.004, HR 1.994, 95% CI 1.251‐3.178) were significant proving to be independent indicators of the disease. Conclusion. Clinicopathological parameters like BMI, degree of dissemination, and ascites level along with CA‐125 can be prognostic factors for the disease. Levels of CA‐125 can depict the metabolic and metastatic factors. Thus, by targeting SIRT1 and assessing exosomal concentrations to overcome metastasis and glycogen deposition, individualized treatment strategy could be designed. In‐depth studies are still required.

Fuzheng Jiedu Decoction Induces Apoptosis and Enhances Cisplatin Efficacy in Ovarian Cancer Cells In Vitro and In Vivo through Inhibiting the PI3K/AKT/mTOR/NF‐κB Signaling Pathway

Objectives. This study is aimed at investigating the anticancer activity of Fuzheng Jiedu decoction (FJD) alone or in combination with cisplatin in ovarian cancer (OC) models, as well as its underlying mechanisms of action. Methods. The anticancer activities of FJD, cisplatin, and the combination of the PI3K inhibitor (LY294002, LY) or activator (IGF‐1) were evaluated in OC cell lines in vitro and in a SKOV3 xenograft mouse model in vivo. The cell proliferation and invasion ability were measured using MTT, EdU, and transwell assays, respectively. The cell apoptosis was examined by flow cytometry and JC‐1 assays. The expression levels of the Bcl‐2 family and the PI3K/AKT/mTOR/NF‐κB pathway‐related proteins were analyzed by Western blot. Results. The in vivo and in vitro studies showed that FJD administration could significantly inhibit cell proliferation and promote cell apoptosis in two OC cell lines SKOV3 and 3AO and partially decreased the tumor volumes and weights. In addition, FJD could significantly downregulate the protein levels of p‐PI3K/PI3K, p‐AKT/AKT, p‐mTOR/mTOR, NF‐κB, p38, and Bcl‐2 and upregulate the Bax, Cyt‐C, and cleaved caspase‐3 in OC tumor tissues and cells. FJD cotreatment increased the efficacy of cisplatin, including inhibiting OC cell proliferation and invasion, promoting cell apoptosis, and inhibiting the PI3K/AKT/mTOR signaling pathway, while this enhancement was suppressed by IGF‐1. Similarly, LY also enhanced the anticancer efficacy of cisplatin. Conclusions. This study indicated that FJD could improve the efficacy of cisplatin by inhibiting the PI3K/AKT/mTOR/NF‐κB signaling pathway. It is suggested that FJD may be a valuable adjuvant drug for the treatment of OC.

Molecular Mechanism of Gleditsiae Spina for the Treatment of High‐Grade Serous Ovarian Cancer Based on Network Pharmacology and Pharmacological Experiments

Background. Gleditsiae Spina, widely used in traditional Chinese medicine, has a good curative effect on malignant tumors such as ovarian cancer, but the mechanism is not clear. So, we aimed to analyze the pharmacological mechanism of Gleditsiae Spina in the treatment of high‐grade serous ovarian cancer (HGSC) based on network pharmacology and biological experiments. Methods. The main active ingredients of Gleditsiae Spina were identified by high performance liquid chromatography (HPLC) and mass spectrometry (MS), and the active ingredients were performed by ADME screening. The component targets of Gleditsiae Spina were screened using the PharmMapper platform, and differentially expressed genes in normal and HGSC tissues were identified through the GEO database. Thereafter, the network of “active ingredient‐targets” was constructed by cytoscape 3.7.2 software. The protein‐protein interaction network was established by the BioGenet database to mine the potential protein function. Biological processes and pathways were analyzed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. The binding ability of the core components of the Gleditsiae Spina and the core target of HGSC was verified by molecular docking and molecular dynamics simulation, and the therapeutic effect of Gleditsiae Spina was proved in vitro through cytotoxicity experiments. The effect of Gleditsiae Spina on the core pathway is obtained by western blotting. Results. Gleditsiae Spina had cytotoxicity on HGSC based on network pharmacology and biological experiments. Luteolin, genistein, D‐(+)‐tryptophan, ursolic acid, and berberine are the identified core active ingredients of Gleditsiae Spina for regulating HGSC, with HPSE, PI3KCA, AKT1, and CTNNB1as the ideal targets. The prediction results were verified by molecular docking, molecular dynamic simulation, cell viability, and western blot analysis. Conclusion. Gleditsiae Spina mainly downregulates the expression of heparanase and β‐catenin to affect the composition of tumor cytoplasmic matrix and can regulate the PI3K‐AKT pathway, integrating multiple targets and multiple pathways to play a therapeutic role. It also provides a theoretical basis for the prevention of ovarian cancer and its treatment using traditional Chinese medicine in the future.

Application Values of 2D and 3D Radiomics Models Based on CT Plain Scan in Differentiating Benign from Malignant Ovarian Tumors

Background. Accurate identification of ovarian tumors as benign or malignant is highly crucial. Radiomics is a new branch of imaging that has emerged in recent years to replace the traditional naked eye qualitative diagnosis. Objective. This study is aimed at exploring the difference in the application potential of two‐ (2D) and three‐dimensional (3D) radiomics models based on CT plain scan in differentiating benign from malignant ovarian tumors. Method. A retrospective analysis was performed on 140 patients with ovarian tumors confirmed by surgery and pathology in our hospital from July 2017 to August 2020. These 140 patients were divided into benign group and malignant group according to the pathological results. The ITK‐SNAP software was used to outline the regions‐of‐interest (ROI) of 2D or 3D tumors on the CT plain scan image of each patient; the texture features were extracted through analysis kit (AK), and the cases were randomly divided into training groups (n = 99) and validation group (n = 41) in a ratio of 7 : 3. The least absolute shrinkage and selection operator (LASSO) algorithm was used to perform dimensionality reduction, followed by the construction of the radiomics nomogram model using the logistic regression method. The receiver operating characteristic (ROC) curve was drawn, and the calibration curve and decision curve analysis (DCA) were used to evaluate and verify the results of the radiomics nomogram and compare the differences between 2D and 3D diagnostic performance. Results. There were 396 quantitative radiomics feature parameters extracted from 2D group and the 3D group, respectively. The area under the curve (AUC) of the radiomics nomogram of the 2D training group and the validation group were 0.96 and 0.97, respectively. The accuracy, specificity, and sensitivity of the training set were 92.9%, 88.9%, and 96.3%, respectively, and those of the validation set were 90.2%, 82.6%, and 100.0%, respectively. The AUCs of the radiomics nomogram of the 3D training group and validation group were 0.96% and 0.99%, respectively. The accuracy, sensitivity, and specificity of the training set were 92.9%, 96.3%, and 88.9%, respectively, and those of the validation set were 97.6%, 95.7%, and 100.0%, respectively. DeLong’s test indicated that there was no statistical significance between the two sets (P > 0.05). Conclusions. For the differential diagnosis of benign and malignant ovarian tumors, the 2D and 3D radiomics nomogram models exhibited comparable diagnostic performance. Considering that the 2D model was cost‐effective and time‐efficient, it was more recommended to use 2D features in future research.

Prognostic Value and Immune Infiltration Analysis of Nuclear Factor Erythroid‐2 Family Members in Ovarian Cancer

Ovarian cancer (OC) often presents at an advanced stage and is still one of the most frequent causes of gynecological cancer‐related mortality worldwide. The nuclear factor erythroid‐2 (NFE2) transcription factors include nuclear factor, erythroid 2 like 1 (NFE2L1), NFE2L2, and NFE2L3. NFE2 members bind to the antioxidant‐response element (ARE) region and activate the expression of targeted genes. The distinct functions of NFE2 members in OC remain poorly elucidated. Several online bioinformatics databases were applied to determine gene expression, prognosis, mutations, and immune infiltration correlation in OC patients. NFE2L1 and NFE2L2 were decreased in OC, whereas NFE2L3 was increased. NFE2L2 and NFE2L3 were significantly correlated with the clinical stages of OC. High NFE2L1 level was significantly associated with short progression‐free survival (PFS) in patients with OC (HR = 1.18, P = 0.021), while high NFE2L2 expression strongly correlated with long PFS (HR = 0.77, P = 0.00067). High NFE2L3 expression was associated with better overall survival and postprogression survival in OC. Functional analysis showed that NFE2 members mainly focused on transcription coactivator activities. Genetic alterations of NFE2 members were found in 13% of OC patients, and amplification ranked the top. The expression of NFE2 members was significantly correlated with immune infiltration of CD4+ T cells, CD8+ T cells, B cells, macrophages, and neutrophils in OC. Our study provides novel insights into the roles and prognostic potential of NFE2 family members in OC.

Phenolic Compounds from Polygonum chinense Induce Growth Inhibition and Apoptosis of Cervical Cancer SiHa Cells

Cervical cancer is considered to be one of the most serious malignant tumors in women. Natural compounds have been considered as important sources in the search for new anticancer agents. Polygonum chinense (PC) has been used as herbal medicine and Chinese cool tea. By activity‐guided of the extracts from PC, PCwater shows good growth inhibition on SiHa cell, then by chromatographic analysis (HPLC and HPLC‐MS/MS), we found twelve components, seven were phenolic compounds (PHE), two PHE named ellagic acid and corilagin were found to show strong growth inhibition effects in SiHa cell dose‐dependently, while the seven phenolic compounds showed low inhibition on the common human HcerEpic cell. Further research found ellagic acid and corilagin induced G2 phase cell cycle arrest by upregulating levels of P53, Bcl‐2, caspase 3, and caspase 9, while the Bax was reduced. These results suggested that PHE from PC might have potential anticancer effects against SiHa cells by acting through the apoptosis pathway, PHE from PC might have the potential to be used as a nutraceutical for the prevention and treatment of ovarian cancer.

Safety and Prognostic Impacts of Ovarian Preservation during Radical Hysterectomy for Early‐Stage Adenocarcinoma and Adenosquamous Cervical Cancer

Objective. To identify the incidence of ovarian metastasis and the impact of ovarian preservation on oncological outcomes for early‐stage adenocarcinoma and adenosquamous cervical cancer. Methods. 281 patients with stages IA2‐IB1 adenocarcinoma and adenosquamous cervical cancer who underwent radical hysterectomy with pelvic lymphadenectomy (RHND) were included in the study. The incidence of ovarian metastasis was evaluated from 173 patients who underwent oophorectomy during RHND. Subgroup analysis was performed for patients less than 50 years (196 of 281 patients) who were classified into two groups, ovarian preservation and nonovarian preservation groups. 5‐year recurrence‐free survival (5‐yr RFS) and 5‐year overall survival (5‐yr OS) were evaluated and compared between these groups. Results. There was no evidence of ovarian metastasis, synchronous ovarian cancer, or ovarian recurrence during follow‐up. In patients less than 50 years of age, there were no statistically significant differences in the 5‐yr RFS (P = 0.363), or 5‐yr OS (P = 0.974) between the ovarian preservation and nonovarian preservation groups. In Kaplan–Meier analysis, the ovarian preservation group seemed to have a slightly better OS in long‐term follow‐up (after 15 years); however, the difference was not statistically significant. Conclusions. Ovarian preservation was safe in adenocarcinoma and adenosquamous cervical cancer stages IA2‐B1. However, the impact of ovarian preservation on oncological outcomes needs to be further investigated.

SOX1 and PAX1 Are Hypermethylated in Cervical Adenocarcinoma and Associated with Better Prognosis

Background. The increased risk and poor survival outcome of cervical adenocarcinoma (CAC) demand for effective early diagnostic biomarkers that can predict the disease progression and outcome. The purpose of this study was to investigate the value of methylation status of SOX1 and PAX1 in the detection and prognosis of CAC. Methods. We performed a quantitative methylation‐specific polymerase chain reaction in 205 cervical paraffin‐embedded specimens (175 CACs, 30 noncancer cervical tissues). Overall and progression‐free survival (OS and PFS, respectively) rates were calculated and compared using the Kaplan‐Meier method. The prognostic value of SOX1m and PAX1m on CAC patients was assessed by the Cox regression model. A mathematical formula combining SOX1m, PAX1m, and age was constructed for survival prediction. Results. The methylation status of SOX1 and PAX1 was higher in CAC tissues than in noncancer cervical tissues. In addition, SOX1m‐positive CAC patients showed a higher 5‐year OS rate than SOX1m‐negative patients. In CAC patients with smaller tumor size (<4 cm), the PAX1m‐positive group showed a higher 5‐year PFS rate than the PAX1m‐negative group. In the algorithm combining SOX1m, PAX1m, and age, the low‐risk group showed a better 5‐year OS and PFS rate than the high‐risk group. Conclusion. SOX1 and PAX1 methylation levels are higher in CAC than in normal cervical tissues and are potential biomarkers for monitoring CAC prognosis.

miR‐9, miR‐21, miR‐27b, and miR‐34a Expression in HPV16/58/52‐Infected Cervical Cancer

The aim of this study was to observe the expression of miR‐9, miR‐21, miR‐27b, and miR‐34a related with E6/E7 in HPV16‐, HPV52‐, and HPV58‐infected cervical cancer patients and explore their possible role in cervical cancer with HPV infection. The expression levels of 4 miRNAs were detected in cervical exfoliated cells using qRT‐PCR. In the current study, miR‐34a expression was significantly upregulated in HPV‐positive cervical cancer compared with the HPV‐negative healthy population and HPV‐positive CIN, but just the expression of miR‐34a in HPV16 cervical cancer was statistically significant, and the expression of HPV52 and HPV58 was not statistically significant. The expression of miR‐21 increased in HPV‐positive cervical cancer compared with HPV‐positive CIN, but only HPV16‐infected cervical cancer had statistical significance compared with HPV16‐infected CIN. By observing the change trend of each subtype group, we can show that the expression of miR‐9 in HPV16 CIN was opposite to the other subtypes, and it was upregulated, compared with HPV58 CIN, and significantly increased. The level change of miR‐27b in HPV58 cervical cancer and HPV58 CIN was opposite to the other subtypes; unlike the expression of miR‐27b which was upregulated in HPV16 and HPV52 infected, it was downregulated compared with Normal. We also found that the expression of miR‐34a and miR‐9 was contrary to other studies. These findings indicate that the upregulated miR‐21 expression may be a biomarker to distinguish between CC and CIN. miR‐34a in HPV infection, especially in HPV16 infection, might be related to the occurrence and development of cervical cancer. The infection of different subtypes may play different roles in disease by activating different mechanisms; miRNAs play a very complex role in tumorigenesis and development, and there may be multiple targets in which multiple mechanisms play a role.

Identification of Recurrent Variants in BRCA1 and BRCA2 across Multiple Cancers in the Chinese Population

BRCA1 and BRCA2 as important DNA repair genes have been thoroughly investigated in abundant studies. The potential relationships of BRCA1/2 pathogenic variants between multicancers have been verified in Caucasians but few in Chinese. In this study, we performed a two‐stage study to screen BRCA1/2 pathogenic variants or variants of uncertain significance (VUS) with 7580 cancer cases and 4874 cancer‐free controls, consisting of a discovery stage with 70 familial breast cancer cases and a subsequent validation stage with 7510 cases (3217 breast cancer, 1133 cervical cancer, 2044 hepatocellular carcinoma, and 1116 colorectal cancer). 48 variants were obtained from 70 familial breast cancer cases after BRCA1/2 exon detection, and finally, 20 pathogenic variants or VUS were selected for subsequent validation. Four recurrent variants in sporadic cases (BRCA1 c.4801A>T, BRCA1 c.3257del, BRCA1 c.440del, and BRCA2 c.7409dup) were identified and three of them were labeled Class 5 by ENIGMA. Two variants (BRCA1 c.3257del and c.440del) were specific in breast cancer cases, while BRCA2 c.7409dup and c.4307T>C were detected in two hepatocellular carcinoma patients and the BRCA1 c.4801A>T variant in one cervical cancer patient, respectively. Moreover, BRCA1 c.3257del was the most frequent variant observed in Chinese sporadic breast cancer and showed increased proliferation of BRCA1c.3257del‐overexpressing triple‐negative breast cancer cell lines (MDA‐MB‐231) in vitro. In addition to the known founder deleterious mutations, our findings highlight that the recurrently pathogenic variants in breast cancer cases could be taken as candidate genetic screening loci for a more efficient genetic screening of the Chinese population.

Uncovering PD‐L1 and CD8+ TILS Expression and Clinical Implication in Cervical Squamous Cell Carcinoma

Objective. To investigate the association between programmed death‐ligand 1 (PD‐L1) coupled with CD8+ tumor‐infiltrating lymphocytes (TILS) and the clinicopathological features, along with prognosis of cervical squamous cell carcinoma (CSCC). Methods. 95 patients of CSCC received tumor resection at the Department of Pathology of the First Affiliated Hospital of University of Science and Technology of China (USTC) from 2015 to 2020. Full‐automatic immunohistochemistry was applied to measure PD‐L1 expression and CD8+ TILS density. Our literature deeply assessed the links between PD‐L1 expression, clinicopathological features, and the influences of combination of PD‐L1 and CD8+ TILS (PD‐L1+/CD8+ TILS) on the prognosis of CSCC. Results. 64.21% of CSCC patients (61/95) expressed PD‐L1, and PD‐L1 expression was related to the Federation of Gynecology and Obstetrics (FIGO) stage, tumor size, invasion depth, differentiation degree, metastasis of lymph node, and vascular invasion (P < 0.05). Dramatic correlation between PD‐L1 expression and CD8+ TILS density was illustrated in CSCC patients (r = −0.461, P < 0.001). Obvious differences in differentiation degree, FIGO stage, infiltration depth, and lymph node metastasis were shown between patients with PD‐L1 coupled with high‐density of CD8+ TILS and those with PD‐L1 coupled with low‐density of CD8+ TILS (P < 0.05). Patients with PD‐L1 negative expression exhibited better prognosis compared with those with PD‐L1 positive expression (P < 0.05). Patients with PD‐L1 coupled with high‐density of CD8+ TILS showed better prognostic status, while those with PD‐L1 coupled with low‐density of CD8+ TILS had worse prognostic condition (P < 0.05). Differentiation, metastasis of lymph node, and FIGO stage were substantive impact elements of a CSCC patient’s overall survival (OS) by Cox multivariate analysis. Conclusions. CD8+ TILS density is related to PD‐L1 expression in carcinoma. PD‐L1/CD8+ TILS density can be regarded as evaluation for the prognosis of patients with CSCC, providing a new therapeutic target in clinical application.

The Abnormal Expression of miR‐205‐5p, miR‐195‐5p, and VEGF‐A in Human Cervical Cancer Is Related to the Treatment of Venous Thromboembolism

Background. Low molecular heparin (LWMH) therapy can prevent the occurrence of VTE in tumor patients and may have a direct antitumor effect. However, the expression pattern of VEGF‐A and microRNAs was less reported in cervical cancer subjects who received concurrent chemoradiotherapy (CCRT) or received anticoagulant treatment with low molecular weight heparin (LWMH) after CCRT (CCRT+LWMH). Methods. In this study, 30 cervical cancer subjects treated with CCRT and 30 cervical cancer patients treated with CCRT+LWMH were enrolled. We screened five miRNAs (miR‐15a‐5p, miR‐16‐5p, miR‐29a‐3p, miR‐195‐5p, and miR‐205‐5p), which have multiple binding sites with VEGF‐A and are highly expressed in serum of patients with cervical cancer, by RT‐qPCR. The expression level of VEGF‐A was also detected by RT‐qPCR and ELISA. Statistical methods were used for difference and correlation analyses. Results. We observed the curative effect in the two treatment methods. In the CCRT group, the total effective rate was 60.00%, and in the CCRT+LWMT group, the total effective rate was 83.33% (P = 0.013, χ2 = 6.129). Additionally, the serum levels of VEGF‐A in the CCRT+LWMH group were downregulated, relative to the CCRT group (P < 0.05), and VEGF‐A in serum was significantly positively correlated with venous thromboembolism (VTE) (r = 2.134, P = 0.035). Only miR‐205‐5p and miR‐195‐5p were upregulated in CCRT+LWMH, relative to CCRT (P < 0.05). In serum of patients with cervical cancer after CCRT+LWMH treatment, there was no significant correlation between VEGF‐A and miR‐15a‐5p (r = −0.132, P = 0.209), miR‐16‐5p (r = −0.205, P = 0.311), or miR‐29a‐3p (r = −0.029, P = 0.662), but VEGF‐A was significantly negatively correlated with miR‐195‐5p (r = −0.396, P = 0.040) and miR‐205‐5p (r = −0.315, P = 0.032). Furthermore, VTE was also significantly negatively correlated with miR‐195‐5p (r = −0.412, P = 0.031) and miR‐205‐5p (r = −0.123, P = 0.044). Conclusion. These data revealed roles for VEGF‐A and these miRNAs as potential biomarkers in cervical cancer patients with VTE, which exhibited usage potential in the treatment of venous thromboembolism.

Effect of BRCA1 on the Concurrent Chemoradiotherapy Resistance of Cervical Squamous Cell Carcinoma Based on Transcriptome Sequencing Analysis

Background. Cervical squamous cell carcinoma (CSCC) is the main pathological type of cervical cancer, accounting for 80%–85% of cervical cancer. Owing to concurrent chemoradiotherapy (CCRT) resistance in a subset of CSCC patients, the treatment response is often unsatisfactory. Identifying predictors and therapeutic targets related to cisplatin‐based CCRT resistance in CSCC is critical. Methods. We reanalyzed GSE56363, an mRNA dataset from the GEO database with 21 patients with locally advanced CSCC, to identify differentially expressed genes (DEGs) related to CCRT resistance. The hub genes were screened from the protein‐protein interaction network of DEGs using cytoHubba plug‐in of Cytoscape software. Transcriptome sequencing technology was used to compare differential expression between SiHa cells overexpressing BRCA1 compared with control SiHa cells. Functional annotation for DEGs and gene set enrichment analysis (GSEA) was performed to identify DEG‐enriched relative signaling pathways to examine the molecular mechanisms of BRCA1 in CCRT resistance of CSCC. qPCR was used to verify the expression of key genes in SiHa/DDP cells. Results. A total of 609 DEGs including 223 upregulated DEGs and 386 downregulated DEGs were identified between the complete response to CCRT (CR) and noncomplete response to CCRT (NCR) CSCC patients based on the GSE56363 dataset. Ten hub genes with the highest degrees were identified via the plug‐in CytoHubba in Cytoscape: BRCA1, CDCA8, ASPM, CDC45, RAD51, HMMR, CENPF, EXO1, DTL, and ZWINT genes, and BRCA1 ranked first. Through transcriptome sequencing analysis based on GSE141558, 1344 DEGs were identified in BRCA1‐overexpressing SiHa cells, including 824 upregulated DEGs and 520 downregulated DEGs. GSEA results showed that CCRT‐resistance related signaling pathways, such as the JAK/STAT signaling pathway and the WNT signaling pathway, were differentially enriched in BRCA1‐expressing SiHa cells. STAT1, STAT2, and CCND1 were screened as the differentially expressed target genes of BRCA1 and may correlate with resistance of CSCC. qPCR results showed that only STAT1 was significantly increased in SiHa cells with GV230‐BRCA1 plasmid transfection. Conclusion. BRCA1 overexpression in SiHa cells may upregulate STAT1 to activate the JAK/STAT signaling pathway, suggesting a mechanism for enhanced CCRT resistance.

Changes of miRNA Expression Profiles from Cervical‐Vaginal Fluid‐Derived Exosomes in Response to HPV16 Infection

As an oncogenic virus, HPV16 can lead to the dysfunction of cervical epithelial cells and contribute to the progression of cervical cancer. Components from the cervical‐vaginal fluid (CVF) could be used as the basis for cervical cancer screening. Exosomes are widely present in various body fluids and participate in intercellular communication via its cargos of proteins, mRNAs, and miRNAs. This study was conducted to explore the changes of miRNAs in exosomes isolated form the cervical‐vaginal fluid during HPV16 infection and to predict the potential effects of exosomal miRNAs on the development of cervical cancer. CVF was collected from volunteers with or without HPV16 infection. The exosomes in CVF were identified by electron microscopy. Microarray analysis was subjected to find the differentially expressed miRNAs in CVF exosomes. To confirm the results, 16 miRNAs were randomly selected to go through real‐time quantitative polymerase chain reaction. In addition, GO and pathway analyses were conducted to reveal potential functions of differentially expressed miRNAs. A total of 2548 conserved miRNAs were identified in the cervical‐vaginal fluid‐derived exosomes. In response to HPV16 infection, 45 miRNAs are significantly upregulated and 55 miRNAs are significantly downregulated (P < 0.05). The GO and KEGG pathway analyses revealed that these differentially expressed miRNAs are tightly associated with cervical cancer tumorigenesis, through interaction with the Notch signaling pathway, TNF signaling pathway, and TGF‐β signaling pathway. These results suggest that exosomal miRNAs in CVF are differentially expressed in HPV16 infection patients and HPV16‐free volunteers. It provided a novel insight to understand the underlying mechanism of HPV16 infection in regulating cervical cancer progression.

Flavonoids in Ageratum conyzoides L. Exert Potent Antitumor Effects on Human Cervical Adenocarcinoma HeLa Cells In Vitro and In Vivo

The Ageratum conyzoides L. (A. conyzoides) is commonly used as a traditional medicine, and its antitumor effects have also been studied. However, the functional roles of flavonoids in A. conyzoides in antitumor activities have not been clarified. The present study is aimed at investigating the biological effects of flavonoids in A. conyzoides on human cervical adenocarcinoma. Firstly, we detected that flavonoids in A. conyzoides significantly inhibited the proliferation, invasion, migration, and clonality of human cervical adenocarcinoma HeLa cells in vitro. Furthermore, we found that flavonoids in A. conyzoides induced significant S phase arrest and apoptosis and obviously decreased the intracellular reactive oxygen species (ROS) level in HeLa cells. Finally, we found that flavonoids in A. conyzoides significantly inhibited the HeLa xenograft tumor growth and epithelial‐mesenchymal transition (EMT) in vivo. In conclusion, our results demonstrated the obvious antitumor effects of flavonoids in A. conyzoides on HeLa cells, suggesting that flavonoids in A. conyzoides could be provided as a novel therapeutic compound for human cervical adenocarcinoma.

The New Biomarker for Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) Based on Public Database Mining

To reconstruct the ceRNA biological network of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) and to select an appropriate mRNA as a biomarker that could be used for CESC early diagnosis and prognosis evaluation. We downloaded CESC data from the TCGA public database, and statistical analysis was conducted with the R software to find out differential expressed genes encoding for lncRNAs, miRNAs, and mRNAs. The differentially expressed mRNAs (DEmRNAs) screened in the ceRNA network were analyzed for survival to find the mRNAs with significantly linked to the survival prognosis. These mRNAs were searched in the Pathological Atlas to identify the final appropriate mRNAs. Differential expression analysis revealed 773 lncRNAs, 94 miRNAs, and 2466 mRNAs. Survival analysis of DEmRNAs in the ceRNA network indicated that ADGRF4, ANXA8L1, HCAR3, IRF6, and PDE2A (P < 0.05) were negatively correlated with survival time. Verification of these six DEmRNAs in the Pathology Atlas indicated that PDE2A was a possible biomarker for CESC patients. PDE2A might be a biomarker for early diagnosis and prognosis evaluation of CESC patients, but due to the lack of available data, further studies may be needed for confirmation.

Identification of Core Prognosis‐Related Candidate Genes in Cervical Cancer via Integrated Bioinformatical Analysis

Purposes. Cervical cancer (CC) is one of the highest frequently occurred malignant gynecological tumors with high rates of morbidity and mortality. Here, we aimed to identify significant genes associated with poor outcome. Materials and methods. Differentially expressed genes (DEGs) between CC tissues and normal cervical tissues were picked out by GEO2R tool and Venn diagram software. Database for Annotation, Visualization and Integrated Discovery (DAVID) was performed to analyze gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway. The protein‐protein interactions (PPIs) of these DEGs were visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). Afterwards, Kaplan‐Meier analysis was applied to analyze the overall survival among these genes. The Gene Expression Profiling Interactive Analysis (GEPIA) was applied for further validation of the expression level of these genes. Results. The mRNA expression profile datasets of GSE63514, GSE27678, and GSE6791 were downloaded from the Gene Expression Omnibus database (GEO). In total, 76 CC tissues and 35 normal tissues were collected in the three profile datasets. There were totally 73 consistently expressed genes in the three datasets, including 65 up‐regulated genes and 8 down‐regulated genes. Of PPI network analyzed by Molecular Complex Detection (MCODE) plug‐in, all 65 up‐regulated genes and 4 down‐regulated genes were selected. The results of the Kaplan‐Meier survival analysis showed that 3 of the 65 up‐regulated genes had a significantly worse prognosis, while 3 of the 4 down‐regulated genes had a significantly better outcome. For validation in GEPIA, 4 of 6 genes (PLOD2, ANLN, AURKA, and AR) were confirmed to be significantly deregulated in CC tissues compared to normal tissues. Conclusion. We have identified three up‐regulated (PLOD2, ANLN, and AURKA) and a down‐regulated DEGs (AR) with poor prognosis in CC on the basis of integrated bioinformatical methods, which could be regarded as potential therapeutic targets for CC patients.

Application of the Cobas 4800 System for the Detection of High‐Risk Human Papillomavirus in 5650 Asymptomatic Women

High‐risk papillomavirus (HR‐HPV) testing combined with cytology improves the detection of cervical lesions and increases length of screening intervals. For a population‐based HR‐HPV survey, testing automation is in great need. The Cobas 4800 HPV Test System is a fully automated assay that can simultaneously detect HPV16, HPV18, and other 12 pooled HR‐HPV genotypes. This system has been employed for HR‐HPV screening in a number of countries; however, such application in a large population in China has not been documented. In this study, we employed the Cobas 4800 HPV Test System to detect HR‐HPV in cervical cytology specimens collected from a total of 5650 asymptomatic women from a region of South China. We reported the following: (1) the prevalence of the 14 genotypes of HR‐HPV was 12.96%; (2) for those with HR‐HPV infection, 2.25% were positive for HPV16, 0.50% for HPV18, 9.15% for pooled 12 HPV types, and 1.06% for multiple HPV infection; and (3) there was no significant difference in the HR‐HPV prevalence among different age groups. HPV16 and HPV18 have been shown to be the predominant HPV types found in cervical cancer patients in some regions in China, indicating that a fully automated assay like the Cobas 4800 HPV Test System is especially valuable for population‐based HR‐HPV screening in these regions as this assay can concurrently detect HPV16 and HPV18.

The Effects of Preoperative Oral Carbohydrate on Frequency of T and NK Cells in Patients with Cervical Cancer Treated Using Neoadjuvant Chemotherapy and Surgery: A Prospective Cohort Study

Background. Immune dysfunction can occur after neoadjuvant chemotherapy (NAC) and surgery for cancer. We investigated whether preoperative oral carbohydrate affected the postoperative percentages of T cells (CD4+ and CD8+) and natural killer (NK) cells in patients with cervical cancer treated with NAC and surgery. Methods. This prospective cohort study enrolled consecutive patients with cervical cancer treated by radical hysterectomy with PLND at the Gynecologic Oncology Department of Fujian Provincial Cancer Hospital (China) between January 2018 and December 2018. Patients were divided into three groups according to the treatment method: NAC (two cycles, surgery 1 month later), NAC+CHO (chemotherapy and surgical methods same as with the NAC group but with 300 mL of oral carbohydrate administered 2 h before surgery), and non‐NAC (surgery alone). Percentages of NK, CD3+, CD4+, and CD8+ cells were evaluated by flow cytometry the day after the first admission, just before surgery, immediately after tracheal tube removal, and the day after surgery. This trial is registered with NCT03872635 at clinicaltrials.com. Results. The final analysis included 77 patients (non‐NAC group, n = 26; NAC group, n = 25; and NAC‐CHO group, n = 26). Baseline characteristics and preoperative NK, CD3+, CD4+, and CD8+ cell percentages were similar between groups. Postoperatively, all groups exhibited reductions in NK, CD3+, and CD4+ cell percentages and increases in CD8+ cell percentages (all P < 0.05). The changes in NK, CD3+, CD4+, and CD8+ cell percentages were attenuated in the NAC‐CHO group (P < 0.05 vs. both other groups). Conclusion. Preoperative oral carbohydrate can improve the postoperative populations of NK and T cells after the treatment of cervical cancer by NAC and surgery.

Research Progress on Tumor‐Associated Macrophages and Inflammation in Cervical Cancer

Cervical cancer is the most common gynecological tumor worldwide. Persistent infection of high‐risk HPV‐induced smouldering inflammation is considered to be an important risk factor for cervical cancer. The tumor microenvironment (TME) plays an important role in the progress of the tumor occurrence, development, and prognosis of cervical cancer. Macrophages are the main contributor to the TME, which is called tumor‐associated macrophages (TAMs). During the inflammatory response, the phenotype and function of TAMs are constantly changing, which are involved in different regulatory networks. The phenotype of TAMs is related to the metabolism and secretory factors release, which facilitate the angiogenesis and lymphatic duct formation during cervical cancer metastasis, thus affecting the prognosis of cervical cancer. This review intends to discuss the recent research progress on the relationship between TAMs and cervical cancer, which is helpful to elucidate the mechanism of TAMs in cervical cancer.

LncRNA CAR10 Upregulates PDPK1 to Promote Cervical Cancer Development by Sponging miR‐125b‐5p

Cervical cancer is one of the malignant tumors that seriously threaten women’s health. The mechanism of development needs to be deeply studied. In recent years, lncRNA has been identified as one of the important factors affecting the malignant progression of tumors. In this study, we illustrated the important mechanism of lncRNA CAR10 in the development of cervical cancer. We found that CAR10 is significantly increased in4 cervical cancer tissues and cells, which can promote the proliferation of cervical cancer cells in vitro and in vivo, indicating that CAR10 is involved in the progression of cervical cancer as an oncogene. Further studies showed that CAR10 is a target gene of miR‐125b‐5p, and miR‐125b‐5p can inhibit the effect of CAR10 on the proliferation of cervical cancer cells. In addition, we also found that 3‐phosphoinositide‐dependent protein kinase 1 (PDPK1) is also a target gene of miR‐125b‐5p, and CAR10 can upregulate the expression level of PDPK1. The results showed that CAR10 acts as a ceRNA to upregulate the expression of PDPK1 by sponging miR‐125b‐5p. Knockdown of PDPK1 can inhibit the effect of CAR10 on cervical cancer cells. Our study demonstrates that, based on ceRNA mechanism, CAR10/miR‐125b‐5p/PDPK1 network can regulate the proliferation of cervical cancer cells and play an important role in the development of cervical cancer. In addition, our study also suggests that intervention of CAR10/miR‐125b‐5p/PDPK1 network may be a new strategy for targeted therapy of cervical cancer.

Diagnosis of Cervical Cancer based on Ensemble Deep Learning Network using Colposcopy Images

Traditional screening of cervical cancer type classification majorly depends on the pathologist’s experience, which also has less accuracy. Colposcopy is a critical component of cervical cancer prevention. In conjunction with precancer screening and treatment, colposcopy has played an essential role in lowering the incidence and mortality from cervical cancer over the last 50 years. However, due to the increase in workload, vision screening causes misdiagnosis and low diagnostic efficiency. Medical image processing using the convolutional neural network (CNN) model shows its superiority for the classification of cervical cancer type in the field of deep learning. This paper proposes two deep learning CNN architectures to detect cervical cancer using the colposcopy images; one is the VGG19 (TL) model, and the other is CYENET. In the CNN architecture, VGG19 is adopted as a transfer learning for the studies. A new model is developed and termed as the Colposcopy Ensemble Network (CYENET) to classify cervical cancers from colposcopy images automatically. The accuracy, specificity, and sensitivity are estimated for the developed model. The classification accuracy for VGG19 was 73.3%. Relatively satisfied results are obtained for VGG19 (TL). From the kappa score of the VGG19 model, we can interpret that it comes under the category of moderate classification. The experimental results show that the proposed CYENET exhibited high sensitivity, specificity, and kappa scores of 92.4%, 96.2%, and 88%, respectively. The classification accuracy of the CYENET model is improved as 92.3%, which is 19% higher than the VGG19 (TL) model.

The Association between Five Genetic Variants in MicroRNAs (rs2910164, rs11614913, rs3746444, rs11134527, and rs531564) and Cervical Cancer Risk: A Meta‐Analysis

The objective of this study was to conduct a meta‐analysis to systematically summarize and investigate the association of miRNA‐124 rs531564, miRNA‐218 rs11134527, miRNA‐146a rs2910164, miRNA‐196a2 rs11614913, and miRNA‐499 rs3746444 polymorphisms with cervical cancer. A systematic review was performed to identify relevant studies using Embase and PubMed databases. A chi‐square‐based Q‐test combined with the inconsistency index (I2) was used to check the heterogeneity between studies. A total of six case‐control studies on rs2910164 and rs11614913, 4 studies on rs3746444 and rs11134527, and three studies on rs531564 were included. No evidence of association was found between miR‐146a rs2910164, miR‐196a2 rs11614913, miRNA‐499 rs3746444, and miR‐218 rs11134527 polymorphisms and cervical cancer risk in all the genetic models. The miR‐124 rs531564 polymorphism was associated with a statistically increased risk of cervical cancer in a homozygote model (CC vs. GG: OR = 2.87, 95% CI: 1.40‐5.91, PH = 0.887), dominant model (GC/CC vs. GG: OR = 1.38, 95% CI: 1.07‐1.80, PH = 0.409), and recessive model (CC vs. GC/GG: OR = 2.26, 95% CI: 1.58‐3.23, PH = 0.979). However, this finding should be interpreted with caution for limited samples and heterogeneity. Large‐scale and well‐designed studies are needed to validate our result.

Overexpression of Long Noncoding RNA H19 Downregulates miR‐140‐5p and Activates PI3K/AKT Signaling Pathway to Promote Invasion, Migration and Epithelial‐Mesenchymal Transition of Ovarian Cancer Cells

Objective. The abnormal expression of LncRNA H19 and miR‐140‐5p has been linked to ovarian cancer (OC). Whether H19 directly regulates miR‐140‐5p in ovarian cancer cells has been unclear. In this study, we deeply explored the relationship between H19 and miR‐140‐5p in ovarian cancer and the mechanism of action in regulating OC progression. Methods. A total of 66 patients with OC admitted to the hospital from June 2017 to June 2019 were selected as the research group (RG), and meanwhile, 60 cases of healthy subjects were selected as the control group (CG). In addition, OC cells and normal ovarian epithelial cells were used to detect H19 and miR‐140‐5p expression levels and to analyze the effect of H19 on OC cells. The activation of the PI3K/AKT pathway and downstream proteins were analyzed by western blot. Results. H19 was highly expressed while miR‐140‐5p was lowly expressed in OC patients and cell lines (P < 0.050). The proliferation, invasion, migration ability, and epithelial‐mesenchymal transition (EMT) of OC cells were reduced after inhibiting H19 expression, and the apoptosis rate was increased. Transfection of cells with miR‐140‐5p mimics brought opposite effects. Online prediction and dual‐luciferase reporter (DLR) confirmed that H19 directly binds miR‐140‐5p. Western blot assay indicated overexpression activated the PI3K/AKT signaling pathway in OC cells. Moreover, overexpression promoted tumor growth in nude mice and was suppressed by PI3K inhibitor. Conclusion. LncRNA H19 downregulation of miR‐140‐5p to activate the PI3K/AKT signaling pathway and promote the proliferation, invasion, migration and EMT of OC.

TCF7L1 Genetic Variants Are Associated with the Susceptibility to Cervical Cancer in a Chinese Population

Background. Cervical cancer (CC) is the second most common tumor in women worldwide. Studies have been accepted that genetic variations play an important role in the development of CC. The aim of this study was to evaluate the impact of TCF7L1 variants on CC risk. Methods. 508 patients of cervical cancer and 497 healthy subjects were recruited to determine the impact of TCF7L1 polymorphisms on CC susceptibility. The associations were investigated by computing odds ratios (ORs) and 95% confidence intervals. The effect of SNP‐SNP interactions on CC risk was explored by multifactor dimensionality reduction analysis. Results. Our study showed that rs11904127 (OR 0.79, p = 0.010) and rs62162674 (OR 0.82, p = 0.044) of TCF7L1 significantly decreased cervical cancer risk. Stratified analysis indicated that rs11904127 and rs62162674 present decreased susceptibility to CC in age > 51 years (OR 0.74, p = 0.019; OR 0.72, p = 0.014, respectively). Haplotype analyses revealed that Grs2366264Trs11689667Crs62162674 has a lower risk to cervical cancer (OR = 0.43, p = 0.018). Besides, there is strong interaction of rs11904127 and rs2366264. Conclusion. Rs11904127 and rs62162674 in TCF7L1 are related to cervical cancer. We suggest that these variants can be used as prognostic markers for judging the susceptibility to cervical cancer.

B7‐H4 Expression in Precancerous Lesions of the Uterine Cervix

Over 10% of patients diagnosed with cervical intraepithelial neoplasia (CIN) have no lesions detected in their cervical conization specimens. The purpose of this study was to determine the factors related to the absence of such lesions. We particularly sought to investigate whether the expression of B7‐H4 in precancerous lesions and cancer of the uterine cervix plays a role in the presence or absence of residual lesions in conization specimens and whether this protein is associated with T cells (i.e., Foxp3+ regulatory T cells, CD4+, and CD8+) and interferon‐γ production. Of the 807 patients with CIN treated by conization, 104 (12.9%) had no lesions in their conization specimens. Seventy‐five of these patients were deemed the study group and were matched with 75 patients who did have CIN detected in their conization specimens (the control group). Immunohistochemistry and immunofluorescence staining were used to detect B7‐H4, Foxp3, CD4, CD8, and interferon‐γ in the 75 pairs of specimens obtained via biopsy; 20 samples were found to have chronic cervicitis, and another 20 had squamous cell carcinoma of the cervix. Menopause, the absence of human papillomavirus, low‐grade histological findings, and a diagnosis of CIN1 and CIN2 on biopsy correlated with a low probability of lesions on conization specimens. B7‐H4 expression was detected in 11.1% of CIN2, 46.6% of CIN3, and 70% of cervical cancer samples, but not in tissues representing chronic cervicitis or CIN1. B7‐H4 expression was associated with the presence of lesions on conization specimens, increased regulatory T cells, decreased CD8+ T cells, and lower interferon‐γ production. These data suggest that close follow‐up and thorough reevaluation should be considered for patients diagnosed with CIN2 who are negative for B7‐H4 expression on biopsy before proceeding with cervical conization.

Upregulation of CDC7 Associated with Cervical Cancer Incidence and Development

Background. Cervical cancer is a common malignant tumor of women. Using integrated bioinformatics, this study identified key disease‐causing genes in cervical cancer that may provide effective biomarkers or therapeutic targets for early diagnosis and treatment. Results. We used high‐throughput sequencing data from the Gene Expression Omnibus (GEO) to identify new cervical cancer biomarkers. The GSE63678 dataset was downloaded. The data was analyzed via bioinformatics methods, and 61 differentially expressed genes were obtained. These differential genes were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments analyses. GO analysis demonstrated that the basic biological functions of differential genes were mostly regulating cell division, mitotic nuclear division, and immune response. Analysis of the KEGG pathway showed the primary involved in the cell cycle, p53 signaling pathway, and cytokine‐cytokine receptor interactions. Using TCGA database to query differential expression of differential genes in cervical cancer, the CDC7 gene was found to be highly expressed. In silico analysis of protein interactions using the STRING database revealed that CDC7 interacts with many proteins. These findings were then validated in vitro with immunohistochemistry and qRt‐PCR to confirm that CDC7 is highly expressed in cervical cancer tissues. Cell function tests demonstrated that inhibition of CDC7 expression could inhibit the proliferation and migration of cervical cancer HeLa and SiHa cells and promote apoptosis. Conclusion. With comprehensive bioinformatics combined with clinical and cellular function analysis, CDC7 is important to the development of cervical cancer. Targeting of this biomarker may improve the early diagnosis and treatment of cervical cancer.

PLOD2 Is a Potent Prognostic Marker and Associates with Immune Infiltration in Cervical Cancer

Background. PLOD2 is overexpressed in diverse tumors and plays a vital role in tumorigenesis. However, the prognostic value of PLOD2 in cervical cancer (CESC) remains unclear. Methods. PLOD2 expression and CESC patients’ survival data were collected from the Oncomine, GEPIA, UALCAN, and Kaplan‐Meier Plotter databases; immunohistochemistry (IHC) was used to validate the expression of PLOD2 in CESC; Gene Set Enrichment Analysis was performed using the STRING and DAVID databases; and the correlations between PLOD2 and cancer immune infiltrates were investigated using the TIMER and TISIDB databases. Results. We found that the expression level of PLOD2 was increased in various cancers, and meta‐analysis in the Oncomine database revealed that PLOD2 was significantly upregulated in CESC compared to that in normal tissues (P < 0.001). In addition, the high expression of PLOD2 was closely related to poor overall survival (OS) and disease‐free survival (DFS) in patients with CESC (OS HR = 1.73, P = 0.029; DFS HR = 2.60, P = 0.018). Functional annotations indicated that differentially expressed PLOD2 were primarily related to protein digestion and absorption pathways and to the collagen fibril organization process. Immune infiltration analysis showed that PLOD2 was highly correlated with B cells, CD4+ T cells, T helper type 2 (Th2) cells, and eosinophils in CESC. Conclusion. PLOD2 is positively associated with poor prognosis and might be considered a novel diagnostic and prognostic marker for CESC patients.

The Effects of Age, Period, and Cohort on the Mortality of Cervical Cancer in Three High‐Income Countries: Canada, Korea, and Italy

Background. As the second most common gynecologic cancer worldwide, cervical cancer has led to morbidity and mortality in thousands of women. Our study is aimed at comparing the long‐term trends of mortality rates for cervical cancer in three high‐income countries—Canada, Korea, and Italy—and analyzing the detached effects of chronological age, time period, and birth cohort by age‐period‐cohort (APC) analysis. Methods. Joinpoint regression was used in this study, and the age‐period‐cohort model combined with the intrinsic estimator method was also applied to estimate the detached effect of each age, time period, and birth cohort on cervical cancer mortality. Results. For the overall trends of ASMRs for cervical cancer, the rates for Canada and Italy generally decreased during the whole observation periods while the rate for Korea exhibited a significant increase from 1986 to 2003. The APC analysis suggested that the cancer mortality risks consistently increased with age in the age groups including women aged 20 to 50 years in all areas. The period effect exhibited a general upward trend for both Korea and Italy, while a decreased trend was observed for Canada during the whole observation period. The mortality risk generally decreased with birth cohort, except there was a slight increase for younger generations in the three countries. Conclusions. Our study shows that the overall decrease in the cohort effect may have contributed to the reduced mortality rate for Italy and Canada, and the increased period effects and cohort effect in younger generations may have led to the increase in cancer mortality rate for Korea.

Vitamin D Receptor Gene Polymorphisms and the Risk of CIN2+ in Shanxi Population

Cervical cancer is one of the most common malignancies in women with high morbidity and mortality. Human papillomavirus (HPV) infection is the primary cause of cervical cancer, of which HPV 16 is the predominant. Early detection and effective treatment of cervical precancerous lesions are the key to preventing cervical cancer. Vitamin D receptor (VDR) gene polymorphism is considered to be an important cause of cancer development. Here, we studied the association of VDR polymorphisms (FOKI, BsmI, ApaI, and TaqI) in HPV16‐positive cervical intraepithelial neoplasia (CIN)2+ patients. HPV16‐positive patients who visited the Colposcopy Clinic of Obstetrics and Gynecology, the Second Hospital of Shanxi Medical University for biopsy due to abnormal HPV and/or Thinprep cytologic test (TCT) from September 1, 2020 to October 1, 2021 were grouped by pathological results. The fasting blood samples were collected and VDR polymorphisms were detected using TaqMan fluorescent probes, and the three sites of BsmI‐ApaI‐TaqI were subjected to haplotype analysis. FOKI ff genotype (OR = 2.01; 95% CI = 1.12 − 3.59; p = 0.019) and f allele (OR = 1.48; 95% CI = 1.10 − 1.98; p = 0.009) were found to be associated with the risk of CIN2+. TaqI Tt genotype (OR = 2.03; 95% CI = 1.20 − 3.43; p = 0.008), tt genotype (OR = 2.09; 95% CI = 1.09 − 4.02; p = 0.028), and t allele (OR = 1.35; 95% CI = 1.01 − 1.80; p = 0.041) were associated with the risk of CIN2+. No haplotype was associated with CIN2+ risk. According to the results, FOKI and TaqI polymorphisms are associated with CIN2+ risk.

Plasma‐Based Metabolomics Profiling of High‐Risk Human Papillomavirus and their Emerging Roles in the Progression of Cervical Cancer

High‐risk human papillomavirus (HR‐HPV) is the main etiological factor for cervical cancer. Accumulating evidence has suggested the active role of metabolites in the initiation and progression of cancers. This study explored the plasma metabolic profiles of HPV‐16 positive (HPV16 (+)), HPV‐18 positive (HPV18 (+)), and HPV negative (CTL) individuals using a nontargeted metabolomics approach. C8 ceramide‐1‐Phosphate (d18 : 1/8 : 0) was found to inhibit cervical cancer cell proliferation and migration in vitro, evidenced by CCK8 experiments, a cell migration test, RT‐qPCR, and western blotting. The underlying mechanism demonstrated that C8 inhibited proliferation and migration in cervical cancer cells via the MAPK/JNK1 signaling pathway. These findings may contribute to the clinical treatment of HR‐HPV‐induced cervical cancer by intervening in its initiation and progression.

Resveratrol Induces Apoptosis, Suppresses Migration, and Invasion of Cervical Cancer Cells by Inhibiting the Hedgehog Signaling Pathway

To investigate the effect and mechanism of resveratrol on the biological behavior of cervical cancer cells (HeLa cells), the apoptosis, migration, and invasion of HeLa cells were detected by flow cytometry, wound healing, and transwell assays. The expression levels of Hedgehog signal pathway proteins (smoothened (SMO), zinc finger transcription factors (Gli1), and sonic hedgehog homolog (Shh)) were detected by quantitative real‐time PCR (qPCR) and western blotting. Compared with that control group, resveratrol (RES) significantly induced apoptosis, inhibited the migration and invasion of the HeLa cells. The expression of SMO, Gli1, and Shh were downregulated in the HeLa cells treated with RES. The Hedgehog agonist purmorphamine (PUR) reversed the RES‐induced increase of apoptosis and reduction of migration and invasion in the HeLa cells. In conclusion, RES induced the apoptosis and suppressed the migration and invasion of HeLa cells by inhibiting Hedgehog signal pathway.

Primary and Triage Cervical Screening Diagnostic Value of Methods for the Detection of Cervical Dysplasia

Background. Cervical cancer is a leading cause of mortality among women globally. Approaches to reduce cervical cancer incidence and mortality are “screen‐and‐treat,” where positive primary test only is used in the treatment and “screen, triage and treat,” where treatment is based on positive primary and triage tests with/without histological analysis. Objectives. To determine cervical screening outcomes among HIV‐infected and noninfected women using VIA, Pap smear, and HPV‐PCR cervical screening methods and to determine the sensitivity, specificity, PPV and NPV of VIA, Pap smear, and HPV‐PCR as primary test and sequential triage based on abnormal histopathology among HIV‐infected and noninfected women. Methodology. This was a comparative cross‐sectional study where women aged 18‐46 years women underwent cervical screening and colposcopy‐biopsy test as a positive‐confirmatory test in the Referral Hospitals of Eastern Kenya. Results. A total of 317 (HIV negative: 156/317 (49.2%) and HIV positive: 161/317 (50.8%)) women were enrolled. Of these 81/317 (25.6%), 84/317 (26.5%), 96/317 (30.2%), and 78/122 (63.9%) participants had VIA, HPV DNA‐PCR, Pap smear, and cervical histology positive results, respectively; average: 27.4% (HIV positive: 21.5%; HIV negative: 5.9%). Majority of women with LSIL [17/317 (5.4%)], HSIL [22/317 (6.9%)], invasive cancer [5/317 (1.6%)], cervicitis [45/317 (14.2%], and candidiasis 47/317 (14.8%) were HIV‐infected (p < 0.001). 78/317 (24.6%) participants had positive histology test [ASCUS: 34/317 (10.7%) CIN1:17/317 (5.3%), CIN2: 16/317 (5.0%), CIN3:6/317 (1.9%), and ICC: 5/317 (1.6%)] (p > 0.001). A higher primary diagnostic accuracy was established by HPV DNA‐PCR (sensitivity: 95.5%; specificity: 92.6%) than Pap smear and VIA test while in triage testing, high sensitivity was obtained by HPV DNA‐PCR parallel testing with VIA test (92.6%) and Pap smear test (92.7%) and VIA cotesting with Pap smear (99.9%). HIV‐infected women had increased specificity and reduced sensitivity and diagnostic accuracy by both primary and triage testing approaches. Discussion. Abnormal cervical screening outcome was high among HIV‐infected than noninfected women. HIV‐infected women had significantly high cases of cervical neoplastic changes. The diagnostic value of primary tests increased upon concurrent testing with other test methods hence reducing the number of women who would have been referred for biopsy. Conclusion. High sensitivity and specificity in detection of CIN+ were established among HIV‐infected than HIV noninfected women by HPV DNA‐PCR and Pap smear than VIA test. HPV DNA‐PCR test and Pap smear are more accurate in primary and sequential triage cervical screening based on abnormal histopathology outcomes among HIV‐infected than noninfected women.

[Retracted] LINC00707 Promotes Cell Proliferation in Cervical Cancer via the miR‐374c‐5p/SDC4 Axis

Cervical cancer (CC) is the second main reason of cancer‐related deaths in women around the world. Long intergenic nonprotein coding RNA 707, which is known as LINC00707, has been elucidated to facilitate the progression of multifarious tumors, but how it may exert functions in CC has not been elucidated yet. By using quantitative real‐time RT‐PCR (RT‐qPCR), we identified the expression pattern LINC00707 may possess in CC. Loss‐of‐function assays including Cell Counting Kit‐8 (CCK‐8), colony formation, and transferase‐mediated dUTP nick‐end labeling (TUNEL) assays were taken to verify the effects of LINC00707 inhibition on CC cell proliferation and apoptosis. The downstream RNAs were selected through bioinformatics prediction, and their interaction with LINC00707 was verified through mechanism assays including the luciferase reporter assay, RNA pull‐down assay, and RNA immunoprecipitation (RIP) assay. According to results, LINC00707 was upregulated in CC cells, and LINC00707 insufficiency inhibited cell proliferation while facilitating cell apoptosis. MicroRNA (miRNA) miR‐374c‐5p interacted with LINC00707, and syndecan‐4 (SDC4) was verified to be the downstream target gene. Data of rescue assays proved that LINC00707 could promote CC cell malignancy via the miR‐374c‐5p/SDC4 axis, which revealed a potential treatment option for CC.

The Leaf Extract of Mitrephora chulabhorniana Suppresses Migration and Invasion and Induces Human Cervical Cancer Cell Apoptosis through Caspase‐Dependent Pathway

Cervical cancer is rated to be the leading cause of cancer‐related death in women worldwide. Since screening test and conventional treatments are less accessible for people in developing countries, an alternative use of medicinal plants exhibiting strong anticancer activities may be an affordable means to treat cervical cancer. Mitrephora chulabhorniana (MC) is the newly identified species; however, its biological functions including anticancer activities have been largely unexplored. Hence, in this study, we were interested in investigating anticancer effects of this plant on the human cervical cell line (HeLa). MC extract was profiled for phytochemicals by TLC. This plant was tested to contain alkaloids, flavonoids, and terpenes. HeLa cells were treated with MC extract to investigate the anticancer activities. Cytotoxicity and viability of cells treated with MC were determined by MTT assay and Trypan blue exclusion assay. Cell migration was tested by wound healing assay, and cell invasion was determined by Transwell assay. The level of caspase 7, caspase 9, and PARP was determined by western blot analysis. We found that the leaf extract of MC strongly reduced cancer cell survival rate. This finding was consistent with the discovery that the extract dramatically induced apoptosis of cervical cancer cells through the activation of caspase 7 and caspase 9 which consequently degraded PARP protein. Furthermore, MC extract at lower concentrations which were not cytotoxic to the cancer cells showed potent inhibitory activities against HeLa cervical cancer cell migration and invasion. Mitrephora chulabhorniana possesses its pharmacological properties in inhibiting cervical cancer cell migration/invasion and inducing apoptotic signaling. This accumulated information suggests that Mitrephora chulabhorniana may be a beneficial source of potential agents for cervical cancer treatment.

Network Pharmacology‐Based and Clinically Relevant Prediction of the Potential Targets of Chinese Herbs in Ovarian Cancer Patients

Reports increasingly suggest that Chinese herbal medicine (CHM) has been used to treat ovarian cancer (OvCa) with a good curative effect; however, the molecular mechanisms underlying CHM are still unclear. In this retrospective study, we explored CHM’s molecular targets for the treatment of OvCa based on clinical data and network pharmacology. We used the Kaplan‐Meier method and Cox regression analysis to verify the survival rate of 202 patients with CHM‐treated OvCa. The association between CHM and survival time was analyzed by bivariate correlation. A target network of CHM active ingredients against OvCa was established via network pharmacology. Cox regression analysis showed that CHM is an independent favorable prognostic factor. The median survival time was 91 months in the CHM group and 65 months in the non‐CHM group. The survival time of FIGO stage III patients in the two groups was 91 months and 52 months, and the median survival period of FIOG stage IV patients was 60 months and 22 months, respectively (p < 0.001). Correlation analysis demonstrated that 12 herbs were closely associated with prognosis, especially in regard to the long‐term benefits. Bioinformatics analysis indicated that the anti‐OvCa activity of these 12 herbs occurs mainly through the regulation of apoptosis‐related protein expression, which promotes OvCa cell apoptosis and inhibits OvCa development. They also regulate the progress of OvCa treatment by promoting or inhibiting protein expression on the p53 signaling pathway and by inhibiting the NF‐κB signaling pathway by directly inhibiting NF‐κB.

Correlation between Vaginal Microecological Status and Prognosis of CIN Patients with High‐Risk HPV Infection

Many microorganisms live in the vagina of healthy women. They interact with and compete with the microenvironment in the female vagina to form a dynamic balance of the microenvironment in the female vagina. However, imbalanced vaginal microecology can lead to vaginal resistance to pathogenic microorganisms. Poor capacity can cause women to develop infections of the reproductive tract. This article analyzes the vaginal microecological status of women with high‐risk HPV infection for more than 6 months and healthy women and explores the risk factors that cause long‐term high‐risk HPV infection for timely detection and regulation of possible vaginal microecological imbalance in women with high‐risk HPV infection for more than 6 months to prevent further development of cervical lesions in such patients. This article covers women with a sexual life history who attended the gynecology department of a hospital from January 2020 to September 2021. There were 280 patients in the experimental group: positive high‐risk HPV; and there were 140 patients in the control group: negative high‐risk HPV test. The correlation between vaginal microecology of CIN patients and patient prognosis according to the subject’s vaginal microecology test results and prognosis of various levels of cervical lesions was analyzed. The experiment proved that the detection rate of normal vaginal microecology in the experimental group was 12.14% (34/280) compared with the detection rate of 29.29% (41/140) in the control group, and there was a trend of decrease, and the difference was statistically significant (χ2 = 17.23, P < 0.05). The detection rate of vaginal BV in the experimental group was 10.36% (29/280) compared with the detection rate of 5.0% (7/140) in the control group, and the difference was statistically significant (χ2 = 5.19, P < 0.05). This indicates that women with high‐risk HPV infections for 6 months or longer have a higher incidence of vaginal microecological imbalances than healthy individuals and aggressive vaginal microecological screening. It is necessary to carry out the program. Detect and treat possible abnormal conditions in time to prevent the further onset of the disease.

FOXM1 Promotes Drug Resistance in Cervical Cancer Cells by Regulating ABCC5 Gene Transcription

Objective. The aim of the present study was to investigate the effect of forkhead box M1 (FOXM1) to paclitaxel resistance in cervical cancer cells, to determine the underlying mechanism, and to identify novel targets for the treatment of paclitaxel‐resistant cervical cancer. Methods. Paclitaxel‐resistant Caski cells (Caski/Taxol cells) were established by intermittently exposing the Caski cells to gradually increasing concentrations of paclitaxel. The association between FOXM1, ATP‐binding cassette subfamily C member 5 (ABCC5), and cervical cancer cell drug resistance was assessed by overexpressing or knocking down the expression of FOXM1 in Caski or Caski/Taxol cells. The protein and mRNA expression levels, the ratio of cellular apoptosis, and cell migration as well as intracellular drug concentrations were measured in cells following the different treatments. Results. After the successful establishment of resistant Caski/Taxol cells, cell cycle distribution analysis showed that a significantly larger percentage of Caski/Taxol cells was in the G0/G1 stage compared with the Caski cells (P < 0.01), whereas a significantly larger percentage of Caski cells was in the S and G2/M stage compared with the Caski/Taxol cells following treatment with paclitaxel (P < 0.01). Both the protein and mRNA expression levels of FOXM1 and ABCC5 transporters were significantly higher in the paclitaxel‐resistant Caski/Taxol cells compared with Caski cells (P < 0.05). Knockdown of FOXM1 significantly lowered the protein expression levels of FOXM1 and ABCC5. Intracellular paclitaxel concentrations were significantly higher amongst the Caski/Taxol cells following the knockdown of FOXM1 by shRNA or Siomycin A (P < 0.05). Conclusion. FOXM1 promotes drug resistance in cervical cancer cells by regulating ABCC5 gene transcription. The knockdown of FOXM1 with shRNA or Siomycin A promotes paclitaxel‐induced cell death by regulating ABCC5 gene transcription.