The Journal of Gene Medicine

Metabolism‐related gene vaccines and immune infiltration in ovarian cancer: A novel risk score model of machine learning

AbstractBackgroundThe present study aims to develop a metabolic gene signature to evaluate the survival rate of ovarian cancer (OC) patients and analyze the potential mechanisms of metabolic genes in OC because the difficulty in early detection of OC often leads to poor treatment outcomes.MethodsA non‐negative matrix factorization algorithm was applied to determine molecular subtypes according to metabolism genes. To build a risk prognosis model, least absolute shrinkage and selection operator multivariate Cox analysis was carried out with weighted correlation network analysis (WCGNA). Glycolytic flux and mitochondrial function were evaluated by conducting seahorse analysis.ResultsOn the basis of metabolism‐related genes, the two subtypes of OC samples present in The Cancer Genome Atlas database were distinguished. An analysis of WGCNA identified 1056 genes. Lastly, a 10‐gene signature (CMAS, ADH1B, PLA2G2D, BHMT, CACNA1C, AADAC, ALOX12, CYP2R1, SCN1B and ME1) was constructed that demonstrated promising performance in predicting outcome in patients with OC. The RiskScore of the gene signature was linked to microenvironment cell infiltration and immune checkpoint. Higher RiskScores were associated with poorer results for OC patients. Seahorse analysis shows the influence of CMAS in cell energy metabolism.ConclusionsIn the present study, a novel marker for evaluating the survival of OC patients was developed through the creation of a gene signature incorporating metabolism‐related genes. Our knowledge of immunotherapy and microenvironment cell infiltration may be enriched by evaluating metabolism‐related gene modification patterns.

Decoding dysregulated genes, molecular pathways and microRNAs involved in cervical cancer

AbstractBackgroundThe present study aimed to identify dysregulated genes, molecular pathways, and regulatory mechanisms in human papillomavirus (HPV)‐associated cervical cancers. We have investigated the disease‐associated genes along with the Gene Ontology, survival prognosis, transcription factors and the microRNA (miRNA) that are involved in cervical carcinogenesis, enabling a deeper comprehension of cervical cancer linked to HPV.MethodsWe used 10 publicly accessible Gene Expression Omnibus (GEO) datasets to examine the patterns of gene expression in cervical cancer. Differentially expressed genes (DEGs), which showed a clear distinction between cervical cancer and healthy tissue samples, were analyzed using the GEO2R tool. Additional bioinformatic techniques were used to carry out pathway analysis and functional enrichment, as well as to analyze the connection between altered gene expression and HPV infection.ResultsIn total, 48 DEGs were identified to be differentially expressed in cervical cancer tissues in comparison to healthy tissues. Among DEGs, CCND1, CCNA2 and SPP1 were the key dysregulated genes involved in HPV‐associated cervical cancer. The five common miRNAs that were identified against these genes are miR‐7‐5p, miR‐16‐5p, miR‐124‐3p, miR‐10b‐5p and miR‐27a‐3p. The hub‐DEGs targeted by miRNA hsa‐miR‐27a‐3p are controlled by the common transcription factor SP1.ConclusionsThe present study has identified DEGs involved in HPV‐associated cervical cancer progression and the various molecular pathways and transcription factors regulating them. These findings have led to a better understanding of cervical cancer resulting in the development and identification of possible therapeutic and intervention targets, respectively.

Inhibition of lncRNA DCST1‐AS1 suppresses proliferation, migration and invasion of cervical cancer cells by increasing miR‐874‐3p expression

AbstractBackgroundCervical cancer seriously threatens both the health and life of women. We aimed to investigate whether RNA interference of long non‐coding RNA (lncRNA) DCST1‐AS1 could promote miR‐874‐3p expression to affect the proliferation, migration and invasion of cervical cancer cells.MethodsDCST1‐AS1 expression levels in cervical cancer cells and transfection effects were detected by quantitative reverse transcriptase‐polymerase chain reaction analysis. Proliferation, invasion and migration of cells were separately shown by cell‐counting kit‐8, wound healing and transwell assays, and relative protein expression was determined by western blot analysis. Dual‐luciferase reporter and RNA immunoprecipitation assays verified the interaction of DCST1‐AS1 and miR‐874‐3p.ResultsDCST1‐AS1 expression was increased in cervical cancer tissues and cells. The DCST1‐AS1 expression in Hela and SiHa cells was the highest, and so the cells were selected for the next experiment. Inhibition of DCST1‐AS1 suppressed the proliferation, invasion and migration of cervical cancer cells and decreased the expression of KI67, proliferating cell nuclear antigen, matrix metalloproteinase (MMP)‐2 and MMP‐9. miR‐874‐3p expression was increased when cells were transfected with miR‐874‐3p mimic or shRNA‐DCST1‐AS1‐1, and DCST1‐AS1 expression was down‐regulated when cells were transfected with miR‐874‐3p mimic. DCST1‐AS1 can directly target miR‐874‐3p. Furthermore, inhibition of miR‐874‐3p could effectively alleviate the effect of inhibition of DCST1‐AS1 with respect to the proliferation, invasion and migration of cervical cancer cells.ConclusionsInhibition of DCST1‐AS1 suppressed the proliferation, migration and invasion of cervical cancer cells by increasing miR‐874‐3p expression, which could be alleviated by the inhibition of miR‐874‐3p.

Hypoxia‐Inducible Factor HIF1α Regulates the Expression of SLC7A1 to Mediate Erastin‐Induced Ferroptosis in Cervical Cancer Cells

ABSTRACTObjectiveThis study aims to investigate the regulation of hypoxia‐inducible factor 1α (HIF1α) on cationic amino acid transporter 1 (SLC7A1) expression and its potential mechanism YTH N6‐methyladenosine RNA binding protein 1 (YTHDF1) in Erastin‐induced ferroptosis in human cervical cancer (CaCx) cells.MethodsHuman CaCx cell lines (HeLa and SiHa) were cultured in vitro under normoxic or hypoxic conditions and treated with Erastin (30 μM, a stimulator of ferroptosis) before cell transfection with small interfering RNAs against HIF1α, YTHDF1, or SLC7A1 (si‐HIF1α, si‐YTHDF1 or si‐SLC7A1). Cell viability and the levels of malondialdehyde (MDA), reactive oxygen species (ROS), glutathione (GSH), and Fe2+ were measured, followed by transmission electron microscopy for ferroptosis‐associated mitochondrial morphological changes in CaCx cells. The interaction of HIF1α in YTHDF1 was determined by JASPAR database and dual‐luciferase reporter assay. Chromatin immunoprecipitation (ChIP) was performed to determine the enrichment of HIF1α at YTHDF1 promoter. The N6‐methyladenosine (m6A) methylation level of SLC7A1 was detected using Methylated RNA Immunoprecipitation (MeRIP) assay. In vivo experiments were conducted on nude mice via injection of HeLa or SiHa cells.ResultsErastin repressed cell growth and induced ferroptosis in CaCx cells, while hypoxia pretreatment partly reversed the Erastin‐induced cytotoxicity and ferroptosis in CaCx cells. Erastin caused low HIF1α levels in CaCx cells, while hypoxia pretreatment partially counteracted this downregulation. Knockdown of HIF1α and YTHDF1 downregulated SLC7A1 expression and promoted Erastin‐induced ferroptosis in hypoxic CaCx cells. Additionally, HIF1α regulated YTHDF1 expression, leading to increased m6A methylation and activation of SLC7A1. The in vivo xenograft model further validated that Erastin inhibited tumor growth in CaCx, while the antitumor effect of Erastin was partially reversed by HIF1α overexpression.ConclusionsHIF1α regulates the expression of YTHDF1, thereby enhancing the m6A modification level of SLC7A1, promoting its expression, and ultimately inhibiting Erastin‐induced ferroptosis in CaCx cells.

Ovarian cancer classification and prognosis assessment model based on prognostic target genes in key microRNA‐target gene networks

AbstractBackgroundThe present study was designed to screen key microRNA (miRNA)‐target gene networks for ovarian cancer (OC) and to classify and construct a risk assessment system for OC based on the target genes.MethodsOC sample data of The Cancer Genome Atlas dataset and GSE26193, GSE30161, GSE63885 and GSE9891 datasets were retrospectively collected. Pearson correlation analysis and targeted analysis of miRNA and target gene were performed to screen key miRNA‐target gene networks. Target genes associated with the prognosis of OC were screened from key miRNA‐target gene networks for consensus clustering and least absolute shrinkage and selection operator‐based regression machine learning analysis of OC samples.ResultsTwenty target genes of 2651 key miRNA‐target gene pairs had significant prognostic correlation in each OC cohort, and OC was divided into three clusters. There were differences in prognostic outcome, biological pathways, immune cell abundance and susceptibility to immune checkpoint blockade (ICB) therapy and anti‐tumor drugs among the three molecular clusters. S2 exhibited the least advantage in prognosis and immunotherapy response rate in the three molecular clusters, and the pathways regulating immunity, hypoxia, metabolism and promoting malignant progression of cancer, as well as infiltrating immune and stromal cell population abundance, were the highest in this cluster. An eight‐target gene prognostic model was created, and the risk index obtained by using this model not only significantly distinguished the immune characteristics of the sample, but also predicted the response of the sample to ICB treatment, and helped to screen 36 potential anti‐OC drugs.ConclusionsThe present study provides a classification strategy for OC based on prognostic target genes in key miRNA‐target gene networks, and creates a risk assessment system for predicting prognosis and response to ICB therapy in OC patients, providing molecular basis for prognosis and precise treatment of OC.

Ovarian carcinoma immune‐related microRNA affects the heterogeneity of the endocrine microenvironment and anti‐tumor immune pattern

AbstractBackgroundThe eighth‐leading cause of cancer‐related mortality and the seventh‐most prevalent malignancy in women globally is ovarian cancer (OV). However, 5‐year survival expectancy after conventional treatment is not good. Therefore, there is an urgent need for novel signatures to guide the designation of therapeutic schemes for OV patients.MethodsWe used univariate Cox analysis to screen hormone secretion regulation axis‐related microRNAs (miRNAs), least absolute shrinkage and selection operator analysis to select candidate miRNAs and multivariate Cox analysis to build the risk model. To evaluate possible route and functional differences, enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed on the differentially expressed genes (DEGs) across various risk groups. We compared Tumor Immune Dysfunction and Exclusion (TIDE) scores across risk categories by analyzing immune cell infiltration, immune checkpoint gene expression, immunological function and TIDE scores. In the end, we determined the half maximal inhibitory concentration (IC50) of chemotherapy and targeted medicines for individual patients. Cell assays were determined to test the migration of the miRNA‐target genes and western blotting was used to test the correlation of the miRNA‐target genes and the pathways.ResultsWe finally identified hormone secretion regulation axis‐related 13 microRNAs to build a risk model. The validation of observed and anticipated values revealed a fair level of agreement. To evaluate the molecular pathways between various groups in accordance with the GO and KEGG analyses, we then discovered 173 DEGs between distinct risk groups. The risk score was shown to be inversely related to the number of immune cells, including myeloid dendritic, granulocytes, M1 and M2 macrophages, B cells, t‐lymphocytes, and CD4+ and CD8+ cells, suggesting that immune cells are more frequent in the low‐risk group. Immune cell infiltration investigation yielded these results. Finally, we recognized 11 chemotherapeutic drugs and 30 novels targeted drugs on the basis of IC50 between the different risk groups. GJB5 was determined to be the mir‐219 target gene and was identified as promoting the cell cycle process. In addition, hormone secretion regulation axis related miRNAs were reported to affects the heterogeneity of endocrine microenvironment and anti‐tumor immune pattern.ConclusionsIn conclusion, a 13‐miRNA prognostic model was constructed to know the immune status, prognosis, immunotherapeutic response and anti‐tumor drug sensitivity for OV, which provides theoretical guidance for the effective and individualized treatment of OV patients.

Integrative analysis of cuproptosis‐associated genes for predicting immunotherapy response in single‐cell and multi‐cohort studies

AbstractBackgroundThe role of genes associated with the cuproptosis cell signaling pathway in prognosis and immunotherapy in ovarian cancer (OC) has been extensively investigated. In this study, we aimed to explore these mechanisms and establish a prognostic model for patients with OC using bioinformatics techniques.MethodsWe obtained the single cell sequencing data of ovarian cancer from the Gene Expression Omnibus (GEO) database and preprocessed the data. We analyzed a variety of factors including cuproptosis cell signal score, transcription factors, tumorigenesis and progression signals, gene set variation analysis (GSVA) and intercellular communication. Differential gene analysis was performed between groups with high and low cuproptosis cell signal scores, as well as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Using bulk RNA sequencing data from The Cancer Genome Atlas, we used the least absolute shrinkage and selection operator (LASSO)‐Cox algorithm to develop cuproptosis cell signaling pathword‐related gene signatures and validated them with GEO ovarian cancer datasets. In addition, we analyzed the inherent rules of the genes involved in building the model using a variety of bioinformatics methods, including immune‐related analyses and single nucleotide polymorphisms. Molecular docking is used to screen potential therapeutic drugs. To confirm the analysis results, we performed various wet experiments such as western blot, cell counting kit 8 (CCK8) and clonogenesis tests to verify the role of the Von Willebrand Factor (VWF) gene in two ovarian cancer cell lines.ResultsBased on single‐cell data analysis, we found that endothelial cells and fibroblasts showed active substance synthesis and signaling pathway activation in OC, which further promoted immune cell suppression, cancer cell proliferation and metastasis. Ovarian cancer has a high tendency to metastasize, and cancer cells cooperate with other cells to promote disease progression. We developed a signature consisting of eight cuproptosis‐related genes (CRGs) (MAGEF1, DNPH1, RARRES1, NBL1, IFI27, VWF, OLFML3 and IGFBP4) that predicted overall survival in patients with ovarian cancer. The validity of this model is verified in an external GEO validation set. We observed active infiltrating states of immune cells in both the high‐ and low‐risk groups, although the specific cells, genes and pathways of activation differed. Gene mutation analysis revealed that TP53 is the most frequently mutated gene in ovarian cancer. We also predict small molecule drugs associated with CRGs and identify several potential candidates. VWF was identified as an oncogene in ovarian cancer, and the protein was expressed at significantly higher levels in tumor samples than in normal samples. The high‐score model of the cuproptosis cell signaling pathway was associated with the sensitivity of OC patients to immunotherapy.ConclusionsOur study provides greater insight into the mechanisms of action of genes associated with the cuproptosis cell signaling pathway in ovarian cancer, highlighting potential targets for future therapeutic interventions.

Anisomycin inhibits the activity of human ovarian cancer stem cells via regulating antisense RNA NCBP2‐AS2/MEK/ERK/STAT3 signaling

AbstractBackgroundOvarian cancer stem cells (OCSCs) are the main cause of relapse and drug resistance in patients with ovarian cancer. Anisomycin has been shown to be an effective antitumor agent, but its mechanism of action in ovarian cancer remains elusive.MethodsCD44+/CD133+ human OCSCs were isolated from human ovarian cancer tissues. OCSCs were interfered with using anisomycin and specific small‐interfering RNA (siRNA). Microarray assay, MTT, in vivo tumorigenic experiments, transwell assay, cell cycle assay, colony formation assay, angiogenesis assay, and hematoxylin and eosin staining were used to detect the mechanism of anisomycin with respect to inhibiting the activity of OCSCs. Expression of the NCBP2‐AS2/mitogen‐activated protein kinase kinase (MEK)/extracellular signal‐regulated kinase (ERK)/signal transducer and activator of transcription 3 (STAT3) pathway was examined using western blotting, a quantitative real‐time PCR (RT‐qPCR) and immunofluorescence staining. Bioinformatics analysis was used for predictive analysis of NCBP2‐AS2 expression in urogenital tumors.ResultsMicroarray analysis showed that treatment with anisomycin significantly decreased the expression of antisense RNA NCBP2‐AS2 in OCSCs. In vitro cellular experiments showed that interfering with endogenous antisense RNA NCBP2‐AS2 using siRNA distinctly inhibited the proliferation, migration and angiogenesis of OCSCs, whereas in vivo animal experiments revealed decreased tumorigenesis in nude mice. Moreover, the results of RT‐qPCR and western blotting demonstrated that both anisomycin treatment and NCBP2‐AS2 silencing led to significant reductions in the mRNA and protein expression levels of NCBP2‐AS2, MEK, ERK and STAT3. From a bioinformatic point of view, antisense RNA NCBP2‐AS2 exhibited significantly differential expression between urogenital tumors and normal controls, and a similar expression pattern was found in the genes NCBP2, RPL35A, DNAJC19 and ECE2, which have similarity to NCBP2‐AS2.ConclusionsAnisomycin suppresses the in vivo and in vitro activity of human OCSCs by downregulating the antisense RNA NCBP2‐AS2/MEK/ERK/STAT3 signaling pathway, whereas the antisense RNA NCBP2‐AS2 and genes with similarity have the potential to serve as markers for clinical diagnosis and prognosis of urogenital tumors.

Single‐cell RNA‐sequencing analysis reveals divergent transcriptome events between platinum‐sensitive and platinum‐resistant high‐grade serous ovarian carcinoma

AbstractBackgroundTumor resistance is one of the main reasons leading to the failure of ovarian cancer treatment. Overcoming platinum resistance remains the greatest challenge in the management of high‐grade serous ovarian carcinoma (HGSC).MethodsSmall conditional RNA‐sequencing is a powerful method for exploring the complexity of the cellular components and their interactions in the tumor microenvironment. We profiled the transcriptomes of 35,042 cells from two platinum‐sensitive and three platinum resistance HGSC clinical cases downloaded from Gene Expression Omnibus (GSE154600) and annotated tumor cells as platinum‐resistant or sensitive based on the clinical trait. The study systematically investigated the inter‐tumoral (using differential expression analysis, CellChat, and SCENIC) and intra‐tumoral heterogeneity (using enrichment analysis such as gene set enrichment analysis, as well as gene set variation analysis, weighted gene correlation network analysis, and Pseudo‐time analysis) of HGSC.ResultsA cellular map of HGSC generated by profiling 30,780 cells was revisualized using Uniform Manifold Approximation and Projection. The inter‐tumoral heterogeneity was demonstrated with intercellular ligand–receptor interactions of major cell types and regulons networks. FN1, SPP1, and COLLAGEN play important roles in the cross‐talk between tumor cells and the tumor microenvironment. HOXA7, HOXA9_extended, TBL1XR1_extended, KLF5, SOX17, and CTCFL regulons consistent with the distribution of platinum‐resistant HGSC cells were the high activity regions. The intra‐tumoral heterogeneity of HGSC was presented with corresponding functional pathway characteristics, tumor stemness features, and the cellular lineage transition from platinum‐sensitive to resistant condition. Epithelial–mesenchymal transition played an important role in platinum resistance, whereas oxidative phosphorylation was the opposite. There was a small subset of cells in platinum‐sensitive samples that had transcriptomic characteristics similar to platinum‐resistant cells, suggesting that the progression of platinum resistance in ovarian cancer is inevitable.ConclusionsThe present study describes a view of HGSC at single‐cell resolution that reveals the characteristics of the HGSC heterogeneity and provides a useful framework for future investigation of platinum‐resistant.

A comprehensive study of oxidative stress‐related effects on the prognosis and drug therapy of cervical cancer

AbstractBackgroundCervical cancer (CC) is a serious global disease with poor prognoses and a significant recurrence rate in patients with advanced disease. Oxidative stress (OS) greatly influences many types of human cancers, making it crucial to understand the functional mechanisms of OS‐related genes in CC.MethodsThe transcriptome and clinical data of three normal samples and 306 patients with CC were obtained from The Cancer Genome Atlas dataset. The GSE44001 dataset was acquired from the Gene Expression Omnibus database. OS‐related subtypes in the cohort with CC were identified using unsupervised hierarchical clustering, univariate Cox analysis, gene set enrichment analysis (GSEA), and least absolute shrinkage and selection operator regression analysis. Additionally, molecular pathways that differ across subtypes were determined and OS‐related genes linked to the prognosis of patients of CC were determined. Finally, a clinical prognostic gene signature was developed and validated. The relative infiltration level of immune cell subpopulations in different risk groups and subtypes was evaluated using the cell‐type identification by estimating relative subsets of RNA transcripts (CIBERPORT) algorithm and single‐sample GSEA (ssGSEA) techniques.ResultsThe present study established two distinct OS subtypes (OS clusters A and B). Analysis using ssGSEA and CIBERSPORT revealed that OS cluster B exhibited a significant level of immune infiltration. A clinical prognostic gene signature was established using OS‐related characteristic genes identified by examining the differentially expressed genes across both subtypes. Furthermore, patients with CC were grouped into high‐ and low‐risk groups, with the low‐risk group showing higher survival rates. Additionally, these individuals exhibited significant advantages in terms of survival and immunotherapy. Receiver operating characteristic curve analysis demonstrated the higher predictive value of the clinical prognostic gene signature. The outcomes of the validation group depicted congruence with those recorded in the training group.ConclusionsA new model was constructed based on eight OS‐related characteristic genes to aid the prediction of the survival rates of individuals with CC. The present study contributes to the existing literature on the mechanisms of OS genes in CC and offers a fresh perspective for future advancements in immunotherapy for such individuals.

Cross‐talk of pyroptosis‐based subtypes, the development of a risk classifier and immune responses in cervical cancer

AbstractBackgroundCervical cancer (CC) is one of the most common gynecology malignancies and has a dismal survival outcome. The prognostic value of pyroptosis and its role in the regulation of immune metabolism in CC remain unclear.MethodsTwo independent CC cohorts collected from public databases were integrated for unsupervised cluster analysis. All CC cases were assigned to different subsets based on the pyroptosis‐related genes (PRGs). The differentially expressed genes (DEGs) between different subclusters were included in stepwise Cox regression for the risk classifier establishment. Next, single‐cell sequencing analysis was conducted to explore the cellular location of each model gene. The CIBERSORT algorithm was applied to estimate immunocytes infiltration. Finally, a series of functional experiments were performed to detect the role of CDH3 in CC.ResultsBased on the 52 PRGs, the combined CC cohort was clustered into two subsets (C1 (n = 259) and C2 (n = 242)). Survival and Cox regression methods were used to create a pyroptosis‐based risk classifier including four PRGs (PEG3, FSCN1, CDH3 and SLC2A1). For the immune environment in CC, the high‐risk group had a lower infiltration level of B cells, memory‐activated CD4 T cells and CD8 T cells and a higher infiltration abundance of neutrophils. The expression pattern of model genes was confirmed in CC cell lines by PCR assay. Furthermore, we observed that knockdown of CDH3 could suppress CC cell proliferation.ConclusionOur project could offer promising reference for prognosis assessment, immune metabolism prediction and clinical decision‐making of patients with CC.

CXCL14 Promotes Ovarian Cancer Progression and Autophagy Through the IKBKE/NF‐κB Pathway

ABSTRACT Ovarian cancer remains a leading cause of gynecological malignancy‐related deaths, necessitating the identification of novel molecular pathways driving tumor progression. Utilizing a data‐driven approach, we conducted bioinformatic analyses of TCGA and GEO datasets, identifying a significant upregulation of CXCL14 in ovarian cancer tissues, which correlates with poor patient survival. Functional assays demonstrated that overexpression of CXCL14 enhances ovarian cancer cell proliferation, invasion, and autophagy. Mechanistically, CXCL14 activates the canonical NF‐κB signaling pathway by inducing phosphorylation and degradation of IκBα, leading to phosphorylation and nuclear translocation of p65. Importantly, we identified IKBKE as a critical kinase mediating CXCL14‐induced activation of the canonical NF‐κB pathway through phosphorylation of IκBα. Knockdown of IKBKE effectively attenuates CXCL14‐driven NF‐κB activation, thereby suppressing cell proliferation, invasion, and autophagy. In vivo, CXCL14 overexpression markedly enhances ovarian tumor growth, accompanied by increased levels of IKBKE and phosphorylated p65. These findings elucidate a novel regulatory axis, CXCL14/IKBKE/NF‐κB, in ovarian cancer progression, highlighting CXCL14 as a potential therapeutic target for ovarian cancer treatment.

Identification of immunogenic cell death‐associated subtypes and characterization of the tumor microenvironment in endometrial cancer

AbstractImmunogenic cell death (ICD) is one of the mechanisms regulating cell death, which activates adaptive immunity in immunocompetent hosts and is associated with tumor progression, prognosis and therapeutic response. Endometrial cancer (EC) is one of the most common malignancies of the female genital tract, and the potential role of immunogenic cell death‐related genes (IRGs) in the tumor microenvironment (TME) remains unclear. We describe the variation of IRGs and assess the expression patterns in EC samples from The Cancer Genome Atlas and Gene Expression Omnibus cohorts. Based on the expression of 34 IRGs, we identified two different ICD‐related clusters and subsequently differentially expressed genes between the two ICD‐related clusters were used for the identification of two ICD gene clusters. We identified the clusters and found that alterations in the multilayer IRG were associated with patient prognosis and TME cell infiltration characteristics. On this basis, ICD score risk scores were calculated, and ICD signatures were constructed and validated for their predictive power in EC patients. To help clinicians better apply the ICD signature, an accurate nomogram was constructed. The low ICD risk group was characterized by high microsatellite instability, high tumor mutational load, high IPS score and stronger immune activation. Our comprehensive analysis of IRGs in EC patients suggested a potential role in the tumor immune interstitial microenvironment, clinicopathological features and prognosis. These findings may improve our understanding of the role of ICDs, and provide a new basis for assessing prognosis and developing more effective immunotherapeutic strategies in EC.

Comprehensive profiling of endocrine metabolism identifies a novel signature with robust predictive value in ovarian cancer

AbstractBackgroundThe cell endocrine pathway is a critical physiological process composed of the endoplasmic reticulum, Golgi apparatus and associated vesicles. Loss of enzymes or proteins can cause dysfunction of endoplasmic reticulum and Golgi apparatus and affect secretion pathways leading to a variety of human diseases, including cancer.MethodsThe single‐cell RNA sequencing and single nucleotide variant principal component analysis data of ovarian cancer were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) datasets. Eighty‐four genes from SECRETORY_PATHWAYs were obtained from the gene set enrichment analysis (GSEA) website. Univariate cox regression analyses and ConsensusClusterPlus were used to identify prognostic genes and molecular subtypes, which were validated using the tumor immune dysfunction and exclusion (i.e. TIDE) analysis and gene mutation analysis. A prognosis model was established by randomForestSRC. Abundant infiltrated immune cells and pathway enrichment analyses were carried out, respectively, through ssGSEA, ESTIMATE, MCP‐counter and GSEA. The drug sensitive analysis was performed using pRRophetic package. Immunotherapy datasets and pan‐carcinoma analysis were used to examine the performance of prognostic model.ResultsEighteen prognostic genes from SECRETORY_PATHWAYs were found in both TCGA and GEO datasets. Next, two clusters (C1 and C2) were determined, for which C1 with a poor prognosis had higher immune infiltration. Tumor‐related pathways, such as PATHWAYS_IN_CANCER and B_CELL_RECEPTOR_SIGNALING_PATHWAY, were enriched in C1. Moreover, C2 was suitable for immunotherapy. A four‐gene (DNAJA1, NDRG3, LUZP1 and ZCCHC24) signature was developed and successfully validated. RiskScore of higher levels were significantly associated with worse prognoses. An enhanced immune infiltration, increased pathways score and inappropriate immunotherapy were observed in the high RiskScore group. The high‐ and low‐RiskScore groups had different drug sensitivities. Immunotherapy datasets and pan‐carcinoma analysis indicated that the low RiskScore group may benefit from immunotherapy.ConclusionsBased on the perspective of the secretory signaling pathway, a robust prognostic signature with great performances was determined, which may provide clues for clinical precision treatment of ovarian cancer.

RNA sequencing and bioinformatics analysis revealed PACSIN3 as a potential novel biomarker for platinum resistance in epithelial ovarian cancer

AbstractBackgroundFailure to respond to treatment in epithelial ovarian cancer can often be attributed to platinum‐based chemotherapy resistance. However, the possible mechanisms or candidate biomarkers associated with platinum resistance are yet to be elucidated, even though many researchers have performed related studies.MethodsWe performed RNA sequencing of clinical specimens obtained from patients with platinum‐sensitive or resistant epithelial ovarian cancer (EOC). Furthermore, various bioinformatics approaches, including spatial analysis of functional enrichment, were used to identify key regulators and associated underlying mechanisms of platinum resistance in EOC.ResultsThrough RNA‐sequencing, we identified 263 differentially expressed genes (98 upregulated and 165 downregulated) and subjected them to Gene Oncology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, which were characterized to the traditional platinum‐resistant characteristics. Subsequently, the gene interaction network and module analysis by spatial analysis of functional enrichment software demonstrated protein kinase C and casein kinase substrate in neurons 3 (PACSIN3) as the only upregulated hub gene, and neurotensin (NTS) and KIAA0319 as downregulated hub genes in platinum‐resistant EOC. We selected PACSIN3 for further analysis because it has not been studied in relation to response to platinum‐based chemotherapy. PACSIN3 was significantly upregulated in ovarian cancer cells compared to immortalized human ovarian surface epithelial cells. In addition, cisplatin‐induced apoptosis was measured in PACSIN3 knockout OVCA433 and BRCA‐mutated EOC cell line, SNU251, by a fluorescence‐activated cell sorting‐based Annexin‐V/propium iodide double staining assay, which revealed a significant increase in apoptosis.ConclusionsTaken together, the present study presents PACSIN3 as a promising predictive biomarker associated with platinum resistance, especially in BRCA‐mutated epithelial ovarian cancers.

LINC01089 inhibits the progression of cervical cancer via inhibiting miR‐27a‐3p and increasing BTG2

AbstractBackgroundIncreasing evidence confirms that long non‐coding RNA (lncRNA) has a vital impact on the procession of cervical cancer (CC). The present study aimed to investigate the clinical significance of LINC01089 in CC, as well as explore its biological functions and potential molecular mechanisms.MethodsA quantitative real‐time polymerase chain reaction (qRT‐PCR) was utilized to investigate the expression of LINC01089 and miR‐27a‐3p in CC cells and tissues. Analysis of the correlation between the expression level of LINC01089 and the clinical pathological parameters of CC was then conducted. The human CC cell lines HeLa and SiHa were utilized for transfection to establish a gain‐of‐function model and loss‐of‐function models. Western blotting and a qRT‐PCR were performed to detect B‐cell translocation gene‐2 (BTG2) expression in CC cells. Cell counting kit (CCK)‐8 and 5‐bromo‐2‐deoxyuridine (BrdU) assays were performed to detect the proliferation of CC cells. The transwell method was employed to evaluate the migration and invasion of CC cells. The interactions between LINC01089 and miR‐27a‐3p were verified by bioinformatics, a dual luciferase reporter gene experiment and a RNA immunoprecipitation experiment, respectively.ResultsThe expression of LINC01089 in CC was markedly down‐regulated. The low expression of LINC01089 in CC was closely associated with a larger tumor size and positive lymph node metastasis. Moreover, overexpression of LINC01089 impeded the proliferation and metastasis of CC cells, whereas knockdown of LINC01089 had the opposite biological functions. In terms of mechanism, LINC01089 could sponge miR‐27a‐3p and indirectly up‐regulate BTG2 expression.ConclusionsLINC01089, as a tumor suppressor, impedes the development of CC by targeting miR‐27a‐3p to up‐regulate BTG2 expression.

miR‐587 promotes cervical cancer by repressing interferon regulatory factor 6

AbstractBackgroundInterferon regulatory factor 6 (IRF6) exhibits tumor‐suppressive functions in several cancer types. In the present study, the antitumor properties and related pathway mechanism of IRF6 were investigated in cervical cancer.MethodsForty‐one pairs of cervical cancer specimens and para‐carcinoma tissues were collected to evaluate IRF6 expression using immunohistochemical staining and miR‐587. The effects of miR‐587 and IRF6 on cervical cancer cell growth were explored by MTT assays and in a HeLa tumor xenograft mouse model. The migration and invasion of cervical cancer cells were monitored using transwell assays.ResultsIRF6 expression in cervical cancer specimens and cell lines was significantly reduced compared to that in the corresponding control group. In addition, IRF6 expression was negatively correlated with miR‐587 in cervical cancer tissues. Bioinformatics algorithms and luciferase assays revealed that IRF6 is a potential target of miR‐587, and miR‐587 mimic transfection led to a significant repression of IRF6 protein levels in cervical cancer cells. We also discovered that the antineoplastic properties of IRF6 could be reversed by overexpressing miR‐587 in cervical cancer cells. The up‐regulation of miR‐587 was correlated with poor overall survival in cervical cancer. In an in vivo experiment, miR‐587 silencing induced HeLa tumor growth inhibition, which was associated with the up‐regulation of IRF6 protein in the tumor.ConclusionsmiR‐587 post‐transcriptionally represses IRF6 protein expression to abrogate the antineoplastic activity of IRF6. The miR‐587/IRF6 signaling pathway plays a crucial role in the progression of cervical cancer and serves as a potential therapeutic target for the treatment of cervical cancer.

Inhibition of the long non‐coding RNA UNC5B‐AS1/miR‐4455/RSPO4 axis reduces cervical cancer growth in vitro and in vivo

AbstractBackgroundLong non‐coding RNAs (lncRNAs) are significant regulatory factors for the initiation and development of numerous malignant tumors, including cervical cancer (CC). The expression of lncRNA unc‐5 netrin receptor B antisense RNA 1 (UNC5B‐AS1, also known as UASR1) is up‐regulated in tissues of cervical squamous cell carcinoma and endocervical adenocarcinoma compared to in normal tissues based on the GEPIA database. In the present study, we explored the functions of UNC5B‐AS1 and its underlying mechanism with respect to CC development.MethodsA real‐time quantitative polymerase chain reaction was applied for the detection of UNC5B‐AS1 expression in CC cells. Cell counting kit‐8, colony formation and transwell assays, as well as western blot and flow cytometry analyses, were employed to detect the biological effects of UNC5B‐AS1 knockdown on malignant phenotypes of CC cells in vitro. In addition, the combination between microRNA‐4455 (miR‐4455) and UNC5B‐AS1 or R‐spondin 4 (RSPO4) was explored by RNA immunoprecipitation, luciferase reporter and RNA pulldown assays. A tumor xenograft nude mice model was established to explore the effect of UNC5B‐AS1 depletion or miR‐4455 overexpression on tumor growth.ResultsUNC5B‐AS1 is up‐regulated in CC tissues and cells. The knockdown of UNC5B‐AS1 inhibits CC cell proliferation, migration and invasion and promotes CC cell apoptosis. Mechanistically, UNC5B‐AS1 binds with miR‐4455 to up‐regulate RSPO4 expression. RSPO4 is targeted by miR‐4455 and its expression is negatively regulated by miR‐4455 expression. In vivo assays revealed that UNC5B‐AS1 depletion or miR‐4455 overexpression inhibits tumor growth by regulating RSPO4 expression.ConclusionsInhibition of UNC5B‐AS1/miR‐4455/RSPO4 reduces CC growth both in vitro and in vivo, furnishing new insights into molecular studies on UNC5B‐AS1 with respect to CC development.

miRNA‐Directed Anticancer Strategies: The Emerging Role of Natural Products in Ovarian Cancer

ABSTRACT Ovarian cancer (OC) is still one of the most serious gynecologic malignancies in the world. It is characterized by a significant likelihood of recurrence and resistance to conventional therapies and a lack of efficient screening techniques. MicroRNAs (miRNAs) are small, noncoding RNA molecules that exert pivotal functions in modulating gene expression. miRNAs are improperly regulated in OC, contributing to tumor onset, progression, metastasis, and resistance to chemotherapeutics. As a result, miRNAs are promising therapeutic targets for the treatment of OC. Recently, natural products derived from plants and other sources have drawn more interest because of their potential to modulate miRNA expression. A variety of bioactive substances, such as curcumin, quercetin, and others, have shown the ability to either promote tumor‐suppressing miRNAs or suppress tumor‐promoting miRNAs. These substances have a great deal of promise for improving the effectiveness of traditional chemotherapy, lowering adverse effects, and providing more individualized treatment plans. Additionally, their capacity to target several miRNAs implicated in cancer‐related pathways offers a multimodal strategy for treating OC. We can upgrade the potential therapeutic options for OC and other cancers by exploring novel natural products with miRNA‐modulating effects. However, further research is needed to clinically translate miRNA‐based therapeutics employing natural compounds, especially in the areas of safety, bioavailability, and drug delivery methods. This review emphasized the implications of miRNAs in OC, the impact of natural products on miRNA regulations, and the potential for incorporating these natural substances into clinical practice for individualized and successful OC treatments.

Anisomycin Induces Senescence and Death of Ovarian Cancer Stem Cells Through the MicroRNA‐340/SENP6/SUMOylation Pathway

ABSTRACT Ovarian cancer remains a leading cause of gynecologic cancer mortality, in part due to the persistence of ovarian cancer stem cells (OCSCs) that drive tumor recurrence, metastasis, and drug resistance. Anisomycin, a natural antibiotic derived from Streptomyces coelicolor , has previously been shown to exert antitumor effects, but the mechanisms by which it targets OCSCs remain unclear. In this study, primary human OCSCs were isolated and treated with anisomycin to investigate its biological and molecular effects. Cell proliferation, apoptosis, migration, and colony formation were assessed in vitro, and tumorigenicity was evaluated in xenograft mouse models. Transcriptomic, biochemical, and molecular assays were performed to identify downstream pathways. Anisomycin treatment markedly inhibited proliferation and promoted senescence and cell death of OCSCs. Mechanistically, anisomycin induced upregulation of microRNA‐340, which in turn suppressed the deSUMOylating enzyme SENP6. This repression increased SUMOylation of key senescence‐related proteins, including p53 and p16, leading to stabilization of their expression and enforcement of cell‐cycle arrest. Overexpression of microRNA‐340 reproduced these effects, both in vitro and in vivo, confirming its central role in mediating anisomycin activity. Bioinformatic analyses further revealed that expression of SENP6 and senescence‐associated genes correlated with disease progression and patient survival in ovarian cancer cohorts. These findings identify a previously unrecognized epigenetic mechanism by which anisomycin induces senescence and death in OCSCs, suggesting that targeting the microRNA‐340/SENP6/SUMOylation pathway may represent a promising therapeutic approach.

THBS1 Contributes to Chemoresistance in Ovarian Clear Cell Carcinoma via Promoting Epithelial–Mesenchymal Transition

ABSTRACT Objective Ovarian clear cell carcinoma (OCCC) is prone to primary platinum resistance and has a poor prognosis in advanced stages. Understanding the mechanisms underlying chemoresistance is essential to improving treatment outcomes. This study aimed to identify and validate molecular targets linked to platinum sensitivity in OCCC and explore their clinical and biological relevance. Methods The mRNA sequencing was performed on fresh‐frozen tumor tissues from six OCCC patients (three platinum‐resistant and three platinum‐sensitive). Differentially expressed genes (DEGs) were identified using edgeR and DESeq2. A random forest model ranked candidate genes by their predictive value, and prognostic associations with progression‐free survival (PFS) and overall survival (OS) were assessed via the database of the Cancer Science Institute of Singapore (CSIOVDB). The protein expression of THBS1 was compared between groups using immunohistochemistry. Functional effects of THBS1 knockdown were assessed through CCK‐8, colony formation, wound healing, transwell assays, and tube formation assays using HUVECs. Results A total of 1592 DEGs were identified, with 43 overlapping with GSEA‐defined platinum resistance pathways. Enrichment analysis indicated significant enrichment of cancer‐related signaling pathways and biological processes were enriched in the platinum‐resistant group. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) highlighted the platelet‐associated biological processes and immune relative pathway. The immune infiltration landscape indicated a prominent immunosuppressive microenvironment in the platinum‐resistant group. THBS1 ranked highly in the random forest model and was associated with shorter PFS ( p  = 0.0012) and OS ( p  = 0.0046) in CSIOVDB analysis. Immunohistochemistry confirmed elevated THBS1 expression in the platinum‐resistant group ( p  < 0.0001). In vitro, THBS1 knockdown reduced cell migration, invasion, angiogenesis, and cisplatin resistance. It also downregulated E‐cadherin while upregulating N‐cadherin and vimentin, suggesting EMT pathway involvement. Conclusion THBS1 promotes platinum resistance in OCCC through EMT activation and may serve as a prognostic biomarker and therapeutic target.

Construction and validation of molecular subtype and signature of immune cell‐related telomeric genes and prediction of prognosis and immunotherapy efficacy in ovarian cancer patients

AbstractBackgroundOvarian cancer (OVC) has emerged as a fatal gynecological malignancy as a result of a lack of reliable methods for early detection, limited biomarkers and few treatment options. Immune cell‐related telomeric genes (ICRTGs) show promise as potential biomarkers.MethodsICRTGs were discovered using weighted gene co‐expression network analysis (WGCNA). ICRTGs were screened for significant prognosis using one‐way Cox regression analysis. Subsequently, molecular subtypes of prognosis‐relevant ICRTGs were constructed and validated for OVC, and the immune microenvironment's landscape across subtypes was compared. OVC prognostic models were built and validated using prognosis‐relevant ICRTGs. Additionally, chemotherapy susceptibility drugs for OVC patients in the low‐ and high‐risk groups of ICRTGs were screened using genomics of drug susceptibility to cancer (GDSC). Finally, the immunotherapy response in the low‐ and high‐risk groups was detected using the data from GSE78220. We conducted an immune index correlation analysis of ICRTGs with significant prognoses. The MAP3K4 gene, for which the prognostic correlation coefficient is the highest, was validated using tissue microarrays for a prognostic‐immune index correlation.ResultsWGCNA analysis constructed a gene set of ICRTGs and screened 22 genes with prognostic significance. Unsupervised clustering analysis revealed the best molecular typing for two subtypes. The Gene Set Variation Analysis algorithm was used to calculate telomere scores and validate the molecular subtyping. A prognostic model was constructed using 17 ICRTGs. In the The Cancer Genome Atlas‐OVC training set and the Gene Expression Omnibus validation set (GSE30161), the risk score model's predicted risk groups and the actual prognosis were shown to be significantly correlated. GDSC screened Axitinib, Bexarotene, Embelin and the GSE78220 datasets and demonstrated that ICRTGs effectively distinguished the group that responds to immunotherapy from the non‐responsive group. Additionally, tissue microarray validation results revealed that MAP3K4 significantly predicted patient prognosis. Furthermore, MAP3K4 exhibited a positive association with PD‐L1 and a negative relationship with the M1 macrophage markers CD86 and INOS.ConclusionsICRTGs may be reliable biomarkers for the molecular typing of patients with OVC, enabling the prediction of prognosis and immunotherapy efficacy.

Prognostic evaluation of the novel blueprint of DNA methylation sites by integrating bulk RNA‐sequencing and methylation modification data in endometrial cancer

AbstractIntroductionEndometrial cancer (EC) is a prevalent malignancy affecting the female population, with an increasing incidence among younger age groups. DNA methylation, a common epigenetic modification, is well‐established to play a key role in cancer progression. We suspected whether DNA methylation could be used as biomarkers for EC prognosis.MethodsIn the present study, we analyzed bulk RNA‐sequencing data from 544 EC patients and DNA methylation data from 430 EC patients in the TCGA‐UCEC cohort. We applied weighted correlation network analysis to select a key gene set associated with panoptosis. We conducted correlation analysis between transcriptomic data of the selected key genes and DNA methylation data to identify valuable DNA methylation sites. These sites were further screened by Cox regression and least absolute shrinkage and selection operator analysis. Immune microenvironment differences between high‐risk and low‐risk groups were assessed using single‐sample gene set enrichment analysi, xCell and MCPcounter algorithms.ResultsOur results identified five DNA methylation sites (cg03906681, cg04549977, cg06029846, cg10043253 and cg15658376) with significant prognostic value in EC. We constructed a prognostic model using these sites, demonstrating satisfactory predictive performance. The low‐risk group showed higher immune cell infiltration. Notably, methylation of site cg03906681 was negatively related to CD8 T cell infiltration, whereas cg04549977 exhibited positive correlations with immune infiltration, particularly in macrophages, activated B cells, dendritic cells and myeloid‐derived suppressor cells. PD0325901_1060 was strongly correlated with risk scores, indicating a potential therapeutic response for high‐risk EC patients.ConclusionWe have developed a robust DNA methylation‐based prognostic model for EC, which holds promise for improving prognosis prediction and personalized treatment approaches. These findings may contribute to better management of EC patients, particularly in identifying those at higher risk who may benefit from tailored interventions.

hsa_circ_0001610 knockdown modulates miR‐646‐STAT3 axis to suppress endometrial carcinoma progression

AbstractBackgroundEndometrial carcinoma (EC) development is associated with dysregulated circular RNA profiles. The purpose of the current research is to study the role and mechanism of hsa_circ_0001610 (circ_0001610) in EC progression.Methodscirc_0001610, microRNA (miR)‐646, and signal transducer and activator of transcription 3 (STAT3) expression levels were measured in EC. Functional analyses were performed using Cell Counting Kit‐8, colony formation, transwell, wound healing, flow cytometry, glycolysis, and xenograft analyses. Binding association was evaluated with dual‐luciferase reporter assay.Resultscirc_0001610 levels were upregulated in EC samples (n = 30) and cells. circ_0001610 interference restrained cell proliferation, migration, and invasion, and promoted apoptosis. circ_0001610 downregulation constrained glycolysis through reducing glucose consumption, lactate production, and levels of adenosine triphosphate, extracellular acidification, hexokinase 2, and lactate dehydrogenase A, and increasing oxygen consumption rate. miR‐646 is targeted by circ_0001610, and miR‐646 inhibition attenuated interference of circ_0001610‐mediated suppression of EC development. STAT3 was modulated by miR‐646, and miR‐646 upregulation restrained EC progression by decreasing STAT3. circ_0001610 silencing reduced STAT3 levels by sponging miR‐646 and reduced the growth of xenograft tumor established by EC cells.Conclusioncirc_0001610 knockdown represses EC progression through modulating the miR‐646‐STAT3 axis.

Molecular mechanisms of miR‐1236 in the assessment of tumor lymphangiogenesis in human ovarian cancer patients

AbstractBackgroundTumor lymphangiogenesis is a critical component in the progression of cancers and specific microRNAs have been reported to be implicated in this process. Recent studies revealed the involvement of miR‐1236 in lymphangiogenic signaling by targeting vascular endothelial growth factor receptor 3 (VEGFR3). However, the prognostic importance of miR‐1236 and its clinical relevance for lymphangiogenesis in ovarian cancer (OC) remains unclear.MethodsThe study included 52 ovarian tumors and 28 normal ovarian tissues. Quantitative real‐time PCR was utilized to analyze the VEGFR3, VEGF‐C, LYVE‐1 and PROX1 mRNA expression as well as miR‐1236. VEGFR3 protein expression was measured by immunohistochemistry staining. Immunohistochemistry for the podoplanin marker (D2‐40) was performed to measure lymphatic vessel density (LVD). In addition, diagnostic evaluation based on the receiver‐operating characteristic (ROC) curve was performed. The influence of miR‐1236 on overall survival was evaluated by Kaplan–Meier method.ResultsHere, we show that miR‐1236 expression was significantly decreased in ovarian tumors compared with control tissues (p < 0.001) and correlated with advanced clinical stage, lymph node metastasis, distant metastasis and patient survival (All P < 0.05). Moreover, in ovarian tumors, LVD as well as the gene expression of VEGFR3, VEGF‐C and LYVE‐1, but not PROX1, were found to be remarkably higher compared with control tissues. We also detected a more robust positive staining for VEGFR3 in OC tissues than in control tissues. Furthermore, our results demonstrated an inverse association of miR‐1236 expression with LVD, VEGFR3, LYVE‐1 and PROX1 expression in OC tissues. The ROC curve analysis indicated that miR‐1236 expression has the potential to be used as a diagnostic and prognostic biomarker in OC. Survival analysis further verified a lowered overall survival rate in patients with low miR‐1236 expression than in those with high expression.ConclusionsOur results provide evidence for the translational involvement of miR‐1236 in the lymphangiogenesis of OC by regulating lymphangiogenesis‐related factors and support the clinical importance of miR‐1236 as a new diagnostic and prognostic biomarker for OC.

Identification of prognostic biomarkers for cervical cancer based on programmed cell death‐related genes and assessment of their immune profile and response to drug therapy

AbstractBackgroundProgrammed cell death (PCD) has been widely investigated in various human diseases. The present study aimed to identify a novel PCD‐related genetic signature in cervical squamous cell carcinoma (CESC) to provide clues for survival, immunotherapy and drug sensitization prediction.MethodsSingle‐sample gene set enrichment analysis (ssGSEA) was used to quantify the PCD score and assess the distribution of PCD in clinicopathological characteristics in The Cancer Genome Atlas (TCGA)‐CESC samples. Then, the ConsensusClusterPlus method was used to identify molecular subtypes in the TCGA‐CESC database. Genomic mutation analysis, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment, as well as tumor microenvironment (TME) infiltration analysis, were performed for each molecular subtype group. Finally, a prognostic model by Uni‐Cox and least absolute shrinkage and selection operator‐Cox analysis was established based on differentially expressed genes from molecular subtypes. ESTIMATE (i.e. Estimation of STromal and Immune cells in MAlignantTumours using Expression data) and ssGSEA were performed to assess the correlation between the model and TME. Drug sensitization prediction was carried out with the oncoPredict package.ResultsPreliminary analysis indicated that PCD had a potential association clinical characteristics of the TCGA‐CESC cohort, and PCD‐related genes mutated in 289 (70.59%) CESC patients. Next, four groups of CESC molecular typing were clustered based on 63 significantly prognostic PCD‐related genes. Among four subtypes, C1 group displayed the worst prognosis combined with over expressed PCD genes and enriched cell cycle‐related pathways. C4 group exhibited the best prognosis accompanied with high degree of immune infiltration. Finally, a five‐gene (SERPINE1, TNF, CA9, CX3CL1 and JAK3) prognostic model was constructed. Patients in the high‐risk group displayed unfavorable survival. Immune infiltration analysis found that the low‐risk group had significantly higher levels of immune cell infiltration such as T cells, Macrophages_M1, relative to the high‐risk group, and were significantly enriched in apoptosis‐associated pathways, which predicted a higher level of immunity. Drug sensitivity correlation analysis revealed that the high‐risk group was resistant to conventional chemotherapeutic drugs and sensitive to the Food and Drug Administration‐approved drugs BI.2536_1086 and SCH772984_1564.ConclusionsIn the present study, we first found that PCD‐related gene expression patterns were correlated with clinical features of CESC patients, which predicts the feasibility of subsequent mining of prognostic features based on these genes. The five‐PCD‐associated‐gene prognostic model showed good assessment ability in predicting patient prognosis, immune response and drug‐sensitive response, and provided guidance for the elucidation of the mechanism by which PCD affects CESC, as well as for the clinical targeting of drugs.

An m1A/m6A/m5C‐associated long non‐coding RNA signature: Prognostic and immunotherapeutic insights into cervical cancer

AbstractBackgroundCervical cancer (CC) remains a significant clinical challenge, even though its fatality rate has been declining in recent years. Particularly in developing countries, the prognosis for CC patients continues to be suboptimal despite numerous therapeutic advances.MethodsUsing The Cancer Genome Atlas database, we extracted CC‐related data. From this, 52 methylation‐related genes (MRGs) were identified, leading to the selection of a 10 long non‐coding RNA (lncRNA) signature co‐expressed with these MRGs. R programming was employed to filter out the methylation‐associated lncRNAs. Through univariate, least absolute shrinkage and selection operator (i.e. LASSO) and multivariate Cox regression analysis, an MRG‐associated lncRNA model was constructed. The established risk model was further assessed via the Kaplan–Meier method, principal component analysis, functional enrichment annotation and a nomogram. Furthermore, we explored the potential of this model with respect to guiding immune therapeutic interventions and predicting drug sensitivities.ResultsThe derived 10‐lncRNA signature, linked with MRGs, emerged as an independent prognostic factor. Segmenting patients based on their immunotherapy responses allowed for enhanced differentiation between patient subsets. Lastly, we highlighted potential compounds for distinguishing CC subtypes.ConclusionsThe risk model, associated with MRG‐linked lncRNA, holds promise in forecasting clinical outcomes and gauging the efficacy of immunotherapies for CC patients.

Autophagy‐related risk signature based on CDNK2A to facilitate survival prediction of patients with endometrial cancer

AbstractBackgroundAutophagy plays an important role in immunity and inflammation. The present study aimed to explore the prognostic significance of autophagy‐related genes (ARGs) in endometrial cancer (EC) using bioinformatics.MethodsThe list of ARGs was obtained from the Human Autophagy Database. The differentially expressed ARGs (DEARGs) between the EC and normal endometrial tissue samples were screened from The Cancer Genome Atlas database. Cox regression analysis was performed on the DEARGs to screen the prognostic ARGs and construct risk signatures for overall survival (OS) and progression‐free survival (PFS). The hub ARGs were identified from a protein–protein interaction network, and CDKN2A was obtained from the intersection of prognostic ARGs and hub ARGs. The association of CDKN2A expression with clinical characteristics and immune infiltration were analyzed. Finally, the role of CDKN2A in autophagy was confirmed in EC cell lines.ResultsCDKN2A, PTK6 and DLC1 were used to establish risk signatures for predicting the survival of EC patients. Receiver operating characteristic curve analysis indicated that the risk signatures can accurately predict both OS and PFS. CDKN2A was the only hub prognostic ARG, and showed significant association with the age, survival status, grade, histological type, body mass index and FIGO (i.e. International Federation of Gynecology and Obstetrics) stage (p < 0.05). Furthermore, CDKN2A expression was also correlated with the infiltration of immune cells, indicating that CDKN2A might play a critical role in regulating the immune microenvironment and immune responses in EC. In addition, silencing of CDKN2A gene promoted autophagy in the HEC‐1A cell line and upregulated the expression levels of autophagy‐related proteins.ConclusionsCDKN2A is a prognostic factor and therapeutic target in EC, and is likely associated with the tumor immune landscape and autophagy.

Extracellular vesicle‐packaged miR‐181c‐5p from epithelial ovarian cancer cells promotes M2 polarization of tumor‐associated macrophages via the KAT2B/HOXA10 axis

AbstractObjectivesThe molecular mechanistic actions of tumor‐derived extracellular vesicles (EVs) in modulating macrophage polarization in the tumor microenvironment of epithelial ovarian cancer (EOC) is largely unknown. The study was performed to clarify the effect and downstream mechanism of microRNA‐181c‐5p (miR‐181c‐5p)‐containing EVs from EOC cells in the M2 polarization of tumor‐associated macrophages (TAMs).MethodsEVs were isolated from normoxic and hypoxic human EOC cells SKOV3. Human mononuclear cell THP‐1 was induced by phorbol‐12‐myristate‐13‐acetate to differentiate into TAMs. The targeting relationship between miR‐181c‐5p and KAT2B was verified by dual luciferase reporter gene assay. The interaction between KAT2B and HOXA10 was detected by immunofluorescence, Co‐IP and ChIP assays. EdU staining, the scratch test and Transwell assay were used to assess the resultant cell proliferation, migration and invasion. The mouse xenograft model and the pulmonary metastasis model were developed through intraperitoneal injection of SKOV3 cells and tail vein injection of THP‐1 cells, respectively.ResultsHypoxic SKOV3 cell‐derived EVs could be internalized by TAMs. SKOV3 cell‐derived EVs induced by hypoxia (H‐EVs) promoted M2 polarization of TAMs and facilitated the proliferation, migration and invasion of SKOV3 cells. miR‐181c‐5p was highly expressed in H‐EVs and promoted the M2 polarization of TAMs. Further, miR‐181c‐5p targeted KAT2B, upregulated HOXA10 and activated the JAK1/STAT3 pathway, thereby promoting the M2 polarization of TAMs. In both mouse models, H‐EV‐derived miR‐181c‐5p promoted growth and metastasis of EOC cells.ConclusionThe miR‐181c‐5p‐containing EVs from hypoxic EOC cells may upregulate HOXA10 by targeting KAT2B and activate the JAK1/STAT3 pathway to promote the M2 polarization of TAMs, ultimately promoting growth and metastasis of EOC cells in vitro and in vivo.

LINC00641 hinders the progression of cervical cancer by targeting miR‐378a‐3p/CPEB3

AbstractBackgroundLINC00641 was found to act in anti‐tumor manner in several types of cancers. Nonetheless, the detailed functions of LINC00641 have not been determined in cervical cancer (CC).MethodsThe expression of LINC00641, miR‐378a‐3p and CPEB3 was examined using a quantitative reverse transcriptase‐polymerase chain reaction. The relationships between LINC00641 and its downstream mechanism were illustrated by RNA pull‐down and luciferase reporter experiments.ResultsLINC00641 was found to be under‐expressed in CC cell lines. By overexpressing LINC00641, cell proliferative, migratory and invasive abilities, as well as epithelial mesenchymal transition (EMT) characteristics, were inhibited, whereas the rate of apoptosis was increased. Next, a starBase search (http://starbase.sysu.edu.cn) was applied to select microRNAs that had binding sequences with LINC00641. By up‐regulating LINC00641 expression, miR‐378a‐3p expression displayed the strongest decline. Moreover, miR‐378a‐3p was found to be up‐regulated in CC cell lines. In addition, LINC00641 hindered the progression of CC by decreasing miR‐378a‐3p expression. CPEB3 was discovered as a downstream target of miR‐378a‐3p and was under‐expressed in CC cells. Furthermore, knockdown of CPEB3 could counter the influence of an overexpression of LINC00641 with respect to CC progression.ConclusionsLINC00641 suppressed the progression of CC by targeting miR‐378a‐3p/CPEB3, suggesting that LINC00641 may have positive therapeutic impact for treatment for CC.

NLRP12 is a prognostic biomarker and correlated with immune infiltrates in epithelial ovarian cancer

AbstractBackgroundNLRP12 is a member of the intracellular Nod‐like receptor (NLR) family, suggesting it is an innate immune receptor for the initiation and progression of several cancers. However, its role on prognosis and immune infiltrates in epithelial ovarian cancer (EOC) is still unknown. The present study aimed to evaluate its prognostic value and its association with immune infiltrates in EOC.MethodsThe mRNA expression of NLRP12 of EOC from The Cancer Genome Atlas (TCGA) was analyzed. The association between NLRP12 and clinicopathological characters was evaluated with logistic regression. The association between NLRP12 expression and survival was analyzed by Cox regression and Kaplan–Meier analyses. A nomogram was used to predict the impact of NLRP12 on prognosis. Gene Ontology term analysis and gene set enrichment analysis (GSEA) were performed to identify the signaling pathways related to NLRP12 expression. Immune cells infiltration for NLRP12 was analyzed using single‐sample GSEA. The relationship between NLRP12 and tumor‐infiltrating immune cells (TICs) was investigated by a Wilcoxon rank sum test. The expression of NLRP12 were also further verified in EOC tissues and cell lines. Additionally, we confirmed the biological function of NLRP12 in vitro.ResultsNLRP12 was highly expressed in patients with EOC from TCGA. High NLRP12 expression correlated with poor disease‐specific survival (p < 0.001) and overall survival (p < 0.001). Multivariate analysis revealed that NLRP12 expression was an independent prognostic marker for overall survival (p = 0.042). The C‐indexes and calibration plots of the nomogram based on multivariate analysis indicated an effective predictive performance for EOC patients. GSEA showed enrichment of cell adhesion, tumorigenesis and immune response in the NLRP12 high expression group. Increased NLRP12 expression correlated positively with several TICs, including macrophages, neutrophils, T effector memory cells and immature dendritic cells (p < 0.001). In addition, NLRP12 silencing inhibited cell proliferation and migration in EOC cells.ConclusionsIn conclusion, increased NLRP12 expression correlated significantly with poor survival and immune infiltration in EOC.

miR‐451a suppresses the proliferation and migration of high‐grade serous ovarian cancer by targeting RAB5A through the Ras/Raf/MEK/ERK pathway

AbstractBackgroundOvarian cancer is one of the most common cancers in women. Profiles changes of microRNAs (miRNAs) are closely linked to malignant tumors. In the present study, we investigated expression of miR‐451a in high‐grade serous ovarian cancer (HGSOC). We also investigated the potential pathological roles and the likely mechanism of miR‐451a in the development of HGSOC using animal models and cell lines.MethodsUsing bioinformatics techniques and a real‐time PCR, we analyzed differently expressed miRNAs in HGSOC compared to normal tissue. MTT (i.e. 3‐[4, 5‐dimethyl thiazol‐2‐yl]‐2,5‐diphenyl tetrazolium bromide), EDU (i.e. 5‐ethynyl‐2′‐deoxyuridine) and transwell assays were performed to investigate the effect of miR‐451a on the proliferation and migration of HGSOC SKOV‐3 cells. A dual luciferase reporter assay was performed to verify the targeting relationship of miR‐451 and RAB5A (one of the Rab GTPase proteins that regulates endocytosis and vesicle transport). Also, we analyzed levels of the RAB5A mRNA and protein by real‐time PCR, western blotting and immunohistochemistry assays in HGSOC cells and tissues. Finally, we performed in vivo experiments using HGSOC mice.ResultsmiR‐451a was substantially upregulated in HGSOC and associated with favorable clinical characteristics. miR‐451a knockdown significantly increased growth and metastasis of HGSOC cell line SKOV‐3 through Ras/Raf/mitogen‐activated protein kinase kinase (MEK)/extracellular signal‐regulated kinase (ERK) signaling. In addition, RAB5A, an early endosome marker, was shown to be a direct target of miR‐451a. Moreover, RAB5A is correlated with unfavorable clinical features and shows independent prognostic significance in HGSOC.ConclusionsWe found that the miR‐451a/RAB5A axis is associated with tumorigenesis and progression through the Ras/Raf/MEK/ERK pathway, providing prognostic indicators and therapeutic targets for patients with HGSOC.

The inflammatory response‐related robust machine learning signature in endometrial cancer: Based on multi‐cohort studies

AbstractUterine corpus endometrial carcinoma (UCEC) is a prevalent form of cancer in women, affecting the inner lining of the uterus. Inflammation plays a crucial role in the progression and prognosis of cancer, making it important to identify inflammatory response‐related subtypes in UCEC for targeted therapy and personalized medicine. This study discovered significant variation in immune response within UCEC tumors based on molecular subtypes of inflammatory response‐related genes. Subtype A showed a more favorable prognosis and better response to immunotherapies like anti‐CTLA4 and anti‐PDCD1 therapy. Functional analysis revealed subtype‐specific differences in immune response, with subtype A exhibiting higher expression of genes related to cytokine signaling pathways, NK cell‐mediated cytotoxicity pathways and inflammatory processes. Subtype A also showed increased sensitivity to three chemotherapeutic agents. A 12‐gene inflammatory response‐related signature was found to have prognostic value for 1, 2 and 3 year survival in UCEC patients. Additionally, a validated machine learning‐based signature demonstrated significant differences in clinical traits between low‐risk and high‐risk cohorts. Elevated risk scores were associated with higher pathological grading, older age, advanced stage and immune subtype C2. Low‐risk groups had higher infiltration of immune cell types such as CD8 + T cells and activated CD4 + cells. However, the abundance of cytotoxic immune cells decreased with increasing risk scores. Finally, PCR was applied to test the different expression in P2PX4. P2RX4 knockdown inhibited the proliferation and proliferation of the endometrial carcinoma Ishikawa cell line. In conclusion, this developed signature can serve as a clinical prediction index and reveal distinct immune expression patterns. Ultimately, this study has the potential to enhance targeted therapy and personalized medicine for UCEC patients.

LINC00958 promotes endometrial cancer cell proliferation and metastasis by regulating the miR‐145‐3p/TCF4 axis

AbstractBackgroundLong noncoding RNAs (lncRNAs) exert an essential regulatory role in cancer progression. This work focuses on the role of LINC00958 in endometrial cancer (EC).MethodsLINC00958 expression in EC tissues was examined by GEPIA database and TCGA‐UCEC dataset. LINC00958, miR‐145‐3p, and TCF4 mRNA expression levels in EC tissues and cells were examined by qRT‐PCR. Western blot was employed to determine TCF4, E‐cadherin, and N‐cadherin protein expression levels. After LINC00958 was overexpressed or silenced, cell proliferation was determined using Cell Counting Kit 8 (CCK‐8) and bromodeoxyuridine (BrdU) incorporation experiments. Cell migration and invasion were examined by Transwell experiment. Dual‐luciferase reporter gene or RNA immunoprecipitation (RIP) experiments were executed to validate the targeting relationships among LINC00958 and miR‐145‐3p and TCF4. The effects of LINC00958 on EC cell proliferation and metastasis were investigated in vivo using a nude mouse subcutaneous graft model and a caudal vein injection model.ResultsLINC00958 was remarkably upmodulated in EC. Moreover, its overexpression was strongly linked to unfavorable overall survival of the patients. Functional experiments confirmed that in vitro knockdown of LINC00958 suppressed EC cell proliferation and metastasis. LINC00958 was validated to decoy miR‐145‐3p and repressed its expression, and TCF4 was uncovered to be a target gene of miR‐145‐3p and negatively modulated by miR‐145‐3p. Furthermore, the function of LINC00958 was dependent on its regulation of miR‐145‐3p and TCF4.ConclusionsLINC00958 acts as an oncogenic lncRNA to regulate EC progression by modulating the miR‐145‐3p/TCF4 axis. Knockdown of LINC00958 impedes tumor growth and metastasis in vitro and in vivo, opening a new avenue for therapeutic intervention.