Mediators of Inflammation

CLDN4 as a Novel Diagnostic and Prognostic Biomarker and Its Association with Immune Infiltrates in Ovarian Cancer

Ovarian cancer (OC) is the seventh most prevalent type of cancer in women and the second most common cause of cancer-related deaths in women worldwide. Because of the high rates of relapse, there is an immediate and pressing need for the discovery of innovative sensitive biomarkers for OC patients. Using TCGA and GSE26712 datasets, we were able to identify 17 survival-related DEGs in OC that had differential expression. CLDN4 was the gene that caught our attention the most out of the 17 important genes since its expression was much higher in OC samples than in nontumor samples. The findings of the ROC assays then confirmed the diagnostic utility of the test in screening OC specimens to differentiate them from nontumor specimens. Patients with high CLDN4 expression predicted a shorter overall survival (OS) and disease-specific survival (DSS) than those with low CLDN4 expression, according to clinical research. Patients with low CLDN4 expression predicted longer OS and DSS. Analysis using both univariate and multivariate techniques revealed that CLDN4 expression was an independent factor associated with a poor prognosis for OS and DSS. Based on multivariate analysis, the C -indexes and calibration plots of the nomogram suggested an effective predictive performance for OC patients. After that, we investigated whether or not there was a link between the infiltration of immune cells and the expression of the CLDN4 gene. We found that the expression of CLDN4 was positively associated with Th17 cells, NK CD56bright cells, while negatively associated with Th2 cells, pDC, and T helper cells. In the end, we carried out RT-PCR on our cohort and confirmed that the level of CLDN4 expression was noticeably elevated in OC specimens in comparison to nontumor tissues. The diagnostic usefulness of CLDN4 expression for OC was also validated by the findings of ROC tests. Thus, our findings revealed that CLDN4 may serve as a predictive biomarker in OC to assess both the clinical outcome of OC patients and the level of immune infiltration.

Silencing of NLRP3 Sensitizes Chemoresistant Ovarian Cancer Cells to Cisplatin

Background. Ovarian cancer is a fatal gynecological malignancy. The resistance to chemotherapy in ovarian cancer treatment has been a thorny issue. This study is aimed at probing the molecular mechanism of cisplatin (DDP) resistance in ovarian cancer. Methods. Bioinformatics analysis was conducted to examine the role of Nod-like receptor protein 3 (NLRP3) in ovarian cancer. The NLRP3 level in DDP-resistant ovarian cancer tumors and cell lines (SKOV3/DDP and A2780/DDP) was evaluated by applying immunohistochemical staining, western blot, and qRT-PCR. Cell transfection was conducted to regulate the NLRP3 level. Cell abilities to proliferate, migrate, invade, and apoptosis were measured employing colony formation, CCK-8, wound healing, transwell, and TUNEL assays, respectively. Cell cycle analysis was completed via flow cytometry. Corresponding protein expression was measured by western blot. Results. NLRP3 was overexpressed in ovarian cancer, correlated with poor survival, and upregulated in DDP-resistant ovarian cancer tumors and cells. NLRP3 silencing exerted antiproliferative, antimigrative, anti-invasive, and proapoptotic effects in A2780/DDP and SKOV3/DDP cells. Additionally, NLRP3 silencing inactivated NLRPL3 inflammasome and blocked epithelial-mesenchymal transition via enhancing E-cadherin and lowering vimentin, N-cadherin, and fibronectin. Conclusion. NLRP3 was overexpressed in DDP-resistant ovarian cancer. NLRP3 knockdown hindered the malignant process of DDP-resistant ovarian cancer cells, providing a potential target for DPP-based ovarian cancer chemotherapy.

STEAP3 Affects Ovarian Cancer Progression by Regulating Ferroptosis through the p53/SLC7A11 Pathway

Ovarian cancer (OC) is a common malignant cancer in women with a low overall survival rate, and ferroptosis may be a potential new strategy for treatment. Six-transmembrane epithelial antigen of prostate 3 (STEAP3) is a gene closely related to ferroptosis, yet the role of STEAP3 in OC has not yet been thoroughly investigated. Using biological information analysis, we first found that STEAP3 was highly expressed in OC, which was significantly associated with poor prognosis of patients and was an independent prognostic factor. Through cloning, scratch, and transwell experiments, we subsequently found that knockdown of STEAP3 significantly reduced the proliferation and migration ability of OC cells. Furthermore, we found that knockdown of STEAP3 induced ferroptosis in OC cells by detecting ferroptosis indicators. Mechanistically, we also found that knockdown of STEAP3 induced ferroptosis through the p53/SLC7A11 signaling pathway. Through tumorigenic experiments in nude mice, we finally verified that the knockdown of STEAP3 could inhibit tumor growth in vivo by promoting ferroptosis through the p53 pathway. Overall, our study identified a novel therapeutic target for ferroptosis in OC and explored its specific mechanism of action.

Contribution of m5C RNA Modification-Related Genes to Prognosis and Immunotherapy Prediction in Patients with Ovarian Cancer

Background. 5-Methylcytosine (m5C) RNA modification is closely implicated in the occurrence of a variety of cancers. Here, we established a novel prognostic signature for ovarian cancer (OC) patients based on m5C RNA modification-related genes and explored the correlation between these genes with the tumor immune microenvironment. Methods. Methylated-RNA immunoprecipitation sequencing helped us to identify candidate genes related to m5C RNA modification at first. Based on TCGA database, we screened the differentially expressed candidate genes related to the prognosis and constructed a prognostic model using LASSO Cox regression analyses. Notably, the accuracy of the model was evaluated by Kaplan–Meier analysis and receiver operator characteristic curves. Independent prognostic risk factors were investigated by Cox proportional hazard model. Furthermore, we also analyzed the biological functions and pathways involved in the signature. Finally, the immune response of the model was visualized in great detail. Results. Totally, 2,493 candidate genes proved to be involved in m5C modification of RNA for OC. We developed a signature with prognostic value consisting of six m5C RNA modification-related genes. Specially, samples have been split into two cohorts with low- and high-risk scores according to the model, in which the low-risk OC patients exhibited dramatically better overall survival time than those with high-risk scores. Besides, not only was this model a prognostic factor independent of other clinical characteristics but it predicted the intensity of the immune response in OC. Significantly, the accuracy and availability of the signature were verified by ICGC database. Conclusions. Our study bridged the gap between m5C RNA modification and the prognosis of OC and was expected to provide an effective breakthrough for immunotherapy in OC patients.

Detection of the Prognostic Gene CYB5D2 in Cervical Squamous Epithelial Lesions

CYB5D2 is a novel tumor suppressor gene that exhibits ectopic expression in various tumors. This study explored its significance in cervical cancer screening and prognosis by examining its expression in cervical precancerous lesions and cancer tissues and analyzing follow‐up data. CYB5D2 expression was comprehensively assessed in 112 clinical samples, combined with routine cervical cancer screening methods to evaluate its early detection potential. Postoperative survival data from cervical cancer patients were analyzed using Kaplan–Meier curves to examine the association between CYB5D2 protein expression and clinicopathological characteristics, as well as its prognostic implications. Results revealed a progressive downregulation of CYB5D2 expression with advancing cervical lesions. Immunohistochemical detection of CYB5D2 protein outperformed ThinPrep cytology test (TCT), DNA aneuploidy analysis, and HR‐HPV E6/E7 mRNA testing (mRNA expression of the E6 and E7 genes in high‐risk HPV virus) in diagnosing high‐grade squamous intraepithelial lesions (HSIL+) of the cervix. Combined testing of TCT, HR‐HPV E6/E7 mRNA, and CYB5D2 achieved 100% sensitivity and negative predictive value for HSIL+. In conclusion, low CYB5D2 expression was identified as an independent risk factor for progression‐free survival (PFS) in cervical cancer patients. Incorporating CYB5D2 testing into routine screening protocols for squamous cell lesions, along with TCT and HPV testing, may enhance diagnostic efficiency and provide prognostic value for adverse outcomes.

Integrative Analysis of Shared Pathogenic Genes and Potential Mechanisms in Gardnerella vaginalis and Persistent HPV16 Infection

Bacterial vaginosis, often accompanied by Gardnerella vaginalis (GV) overgrowth, is associated with persistent high‐risk human papillomavirus (HR‐HPV) infection, particularly HPV16. This study integrated transcriptomic data from in vitro GV infection experiments and a GEO dataset (GSE75132) of HPV16 persistence to elucidate shared pathogenic mechanisms. Differential expression analysis identified 4115 genes modulated by GV infection and 861 by HPV16 persistence, with 74 common differentially expressed genes (DEGs) displaying consistent trends. Enrichment analyses revealed that these DEGs participate in metabolic pathways, immune defense, host–pathogen interactions, and carcinogenesis. Protein–protein interaction networks and Random Forest (RF) feature selection pinpointed radical S‐adenosyl methionine domain containing 2 (RSAD2) and Interferon‐induced protein with tetratricopeptide repeats 1 (IFIT1) as central hub genes. Upstream transcription analysis identified the homer_AGTTTCAGTTTC_ISRE motif and established a ceRNA network involving hsa‐miR‐654‐5p, IFIT1/RSAD2, and lncRNAs. Mendelian randomization (MR) and colocalization analyses linked RSAD2 downregulation to an increased risk of cervical carcinoma in situ (rs2595163, PPH4 = 0.62), while ROC analysis demonstrated strong diagnostic potential for the combined hub gene expression. Notably, single‐cell transcriptomics revealed distinct RSAD2 and IFIT1 expression patterns in immune and epithelial cells during the progression from HPV infection to cervical cancer. Collectively, these findings support RSAD2 and IFIT1 as promising biomarkers and therapeutic targets for HPV‐related cervical lesions.

Attenuation of Inflammatory Responses in Breast and Ovarian Cancer Cells by a Novel Chalcone Derivative and Its Increased Potency by Curcumin

Background. Breast and ovarian cancers are two common malignancies in women and a leading cause of death globally. The aim of the present study was to explore the effects of a novel chalcone derivative 1-(4-(methylsulfonyl)phenyl)-3-(phenylthio)-3-(p-tolyl)propane-1-one (MPP) individually or combined with curcumin, a well-known herbal medicine with anticancer properties, as a new combination therapy on inflammatory pathways in breast and ovarian cancer cell lines. Methods. LPS-induced NF-κB DNA-binding activity and the levels of proinflammatory cytokines were measured in the MPP- and MPP-curcumin combination-treated MDA-MB-231 and SKOV3 cells by ELISA-based methods. The expression of COX2, INOS, and MMP9 genes and nitrite levels was also evaluated by real-time qRT-PCR and Griess method, respectively. IκB levels were evaluated by Western blotting. Results. MPP significantly inhibited the DNA-binding activity of NF-κB in each cell line and subsequently suppressed the expression of downstream genes including COX2, MMP9, and INOS. The levels of proinflammatory cytokines, as well as NO, were also decreased in response to MPP. All the effects of MPP were enhanced by the addition of curcumin. MPP, especially when combined with curcumin, caused a remarkable increase in the concentration of IκB. Conclusion. MPP and its coadministration with curcumin effectively reduced the activity of the NF-κB signaling pathway, leading to a reduced inflammatory response in the environment of cancer cells. Thus, MPP, either alone or combined with curcumin, might be considered an effective remedy for the suppression of inflammatory processes in breast and ovarian cancer cells.

Identification and Validation of NK Marker Genes in Ovarian Cancer by scRNA-seq Combined with WGCNA Algorithm

Background. As an innate immune system effector, natural killer cells (NK cells) play a significant role in tumor immunotherapy response and clinical outcomes. Methods. In our investigation, we collected ovarian cancer samples from TCGA and GEO cohorts, and a total of 1793 samples were included. In addition, four high-grade serous ovarian cancer scRNA-seq data were included for screening NK cell marker genes. Weighted gene coexpression network analysis (WGCNA) identified core modules and central genes associated with NK cells. The “TIMER,” “CIBERSORT,” “MCPcounter,” “xCell,” and “EPIC” algorithms were performed to predict the infiltration characteristics of different immune cell types in each sample. The LASSO-COX algorithm was employed to build risk models to predict prognosis. Finally, drug sensitivity screening was performed. Results. We first scored the NK cell infiltration of each sample and found that the level of NK cell infiltration affected the clinical outcome of ovarian cancer patients. Therefore, we analyzed four high-grade serous ovarian cancer scRNA-seq data, screening NK cell marker genes at the single-cell level. The WGCNA algorithm screens NK cell marker genes based on bulk RNA transcriptome patterns. Finally, a total of 42 NK cell marker genes were included in our investigation. Among which, 14 NK cell marker genes were then used to develop a 14-gene prognostic model for the meta-GPL570 cohort, dividing patients into high-risk and low-risk subgroups. The predictive performance of this model has been well-verified in different external cohorts. Tumor immune microenvironment analysis showed that the high-risk score of the prognostic model was positively correlated with M2 macrophages, cancer-associated fibroblast, hematopoietic stem cell, stromal score, and negatively correlated with NK cell, cytotoxicity score, B cell, and T cell CD4+Th1. In addition, we found that bleomycin, cisplatin, docetaxel, doxorubicin, gemcitabine, and etoposide were more effective in the high-risk group, while paclitaxel had a better therapeutic effect on patients in the low-risk group. Conclusion. By utilizing NK cell marker genes in our investigation, we developed a new feature that is capable of predicting patients’ clinical outcomes and treatment strategies.

Perspectives in HPV Secondary Screening and Personalized Therapy Basing on Our Understanding of HPV-Related Carcinogenesis Pathways

As cervical cancer is one of the most common malignancies in women worldwide even with present screening methods, the incidence in most developed countries is not decreasing for the last 15-20 years. A shift has been observed in the age of diagnosis in favour of younger women, and treatment of already developed cervical cancer is a challenge for surgeons. It is imperative to find new diagnostic methods for accurately pointing out patients at high risk of developing malignant disease and developing personalized treatment. Since cervical cancer is almost exclusively associated with HPV infection, understanding changes happening in an infected cell may prove invaluable for search of such methods, but it may also prove helpful in the diagnosis and treatment of other anogenital and nasopharyngeal region cancers. This review follows HPV-related changes in infected cell biology to point what potential markers and targets for therapy are in option when dealing with HPV-related diseases.

Comprehensive Single‐Cell Characterization of LDL in the Ovarian Cancer Microenvironment and Its Prognostic Implications

Background Low‐density lipoprotein (LDL) is a critical regulator of lipid metabolism and has been implicated in the development and progression of various malignancies. However, its specific roles and mechanisms in the ovarian cancer tumor microenvironment (TME) remain unclear. This study aimed to comprehensively elucidate the distribution, functional pathways, and prognostic value of LDL in ovarian cancer using single‐cell transcriptome analysis. Methods Single‐cell transcriptome data from ovarian cancer patients were analyzed. The AUCell algorithm was used to score LDL‐related gene expression in different cell subsets, dividing cells into high and low LDL score groups. Functional pathway enrichment (Gene Set Variation Analysis [GSVA]) and cell–cell communication (CellChat) analyses were performed. Differentially expressed genes (DEGs) identified between the two groups were combined with bulk RNA‐seq data from eight cohorts to construct the LDL‐related ovarian cancer prognostic signature (LDLOCPS) using machine learning. Prognostic performance and immune landscape differences were evaluated between high and low LDLOCPS groups. Results LDL was predominantly highly expressed in myeloid cells (macrophages and monocytes) and stromal cells (fibroblasts, smooth muscle cells, and endothelial cells) within the ovarian cancer TME. GSVA revealed that the high LDL score group was significantly enriched for pathways including epithelial‐mesenchymal transition (EMT), inflammatory response, coagulation, and angiogenesis. CellChat analysis demonstrated enhanced cell–cell communication involving IL6, CSF, and tenascin in the high LDL score group, with SPP1+ macrophages and monocytes showing stronger incoming and outgoing signals. The LDLOCPS model, constructed from bulk transcriptomic data and validated across eight cohorts, effectively stratified patients by risk; the high LDLOCPS group exhibited significantly worse overall survival. Receiver operating characteristic (ROC) and principal component analysis (PCA) analyses confirmed the robust predictive performance of LDLOCPS. Moreover, patients in the high LDLOCPS group showed reduced immune cell infiltration and lower expression of immune‐related genes, suggesting an immunosuppressive microenvironment. Conclusion This study systematically reveals the spatial distribution of LDL within the ovarian cancer microenvironment and uncovers its regulatory roles in tumor progression through multiple signaling pathways. The LDLOCPS model provides a valuable tool for risk stratification and prognosis prediction in ovarian cancer. LDL‐mediated microenvironmental and immunosuppressive effects may offer novel insights for developing targeted and immunomodulatory therapies in ovarian cancer.