EPAS1, a hypoxia- and ferroptosis-related gene, promotes malignant behaviour of cervical cancer by ceRNA and super-enhancer.

Hypoxia and Ferroptosis are associated with the malignant behaviour of cervical cancer. Endothelial PAS domain-containing protein 1 (EPAS1) contributes to the progression of cervical cancer. EPAS1 plays important roles in hypoxia and ferroptosis. Using the GEO dataset, machine-learning algorithms were used to screen for hypoxia- and ferroptosis-related genes (HFRGs) in cervical cancer. EPAS1 was identified as the hub gene. qPCR and WB were used to investigate the expression of EPAS1 in normal and cervical cancer tissues. The proliferation, invasion and migration of EPAS1 cells in HeLa and SiHa cell lines were detected using CCK8, transwell and wound healing assays, respectively. Apoptosis was detected by flow cytometry. A dual-luciferase assay was used to analyse the MALAT1-miR-182-5P-EPAS1 mRNA axis and core promoter elements of the super-enhancer. EPAS1 was significantly overexpressed in cervical cancer tissues. EPAS1 could increase the proliferation, invasion, migration of HeLa and SiHa cells and reduce the apoptosis of HeLa and SiHa cell. According to the double-luciferase assay, EPAS1 expression was regulated by the MALAT1-Mir-182-5p-EPAS1 mRNA axis. EPAS1 is associated with super-enhancers. Double-luciferase assay showed that the core elements of the super-enhancer were E1 and E3. EPAS1, an HFRG, is significantly overexpressed in cervical cancer. EPAS1 promotes malignant behaviour of cervical cancer cells. EPAS1 expression is regulated by super-enhancers and the MALAT1-miR-182-5P- EPAS1 mRNA axis. EPAS1 may be a target for the diagnosis and treatment of cervical cancer.

Identification of stemness subtypes and features to improve endometrial cancer treatment using machine learning.

Endometrial cancer is one of the most common malignant tumours in women, and cancer stem cells are known to play an important role in its growth, invasion, metastasis, and drug resistance. Immunotherapy for endometrial cancer is still under research. In this study, a total of 547 endometrial cancer cases were randomly divided into training set (351 cases) set and test set (196 cases). The stemness index of patients was calculated using the One-Class Logistic Regression (OCLR) machine learning algorithm to explore the clinicopathological differences between index levels. Stemness subtypes were determined according to the characteristics of cancer stemness and their clinicopathological characteristics, immune features, and therapeutic effects were described. Our study suggests that endometrial cancer is classified into two stemness subtypes. Stemness subtypes, which are associated with its clinical features, may be independent prognostic factors for endometrial cancer. The stemness subtypes differed significantly in immune activity, immune cell infiltration, and the immune microenvironment, including sensitivity to chemotherapeutic drugs and potential therapeutic compounds. Algorithms were utilised to construct a stemness subtype prediction model and predictor. These findings will provide guidance for the clinical diagnosis, treatment, and prognosis of endometrial cancer.

Prognosis, immune microenvironment, and personalized treatment prediction in Rho GTPase-activating protein 4-mutant cervical cancer: Computer strategies for precision oncology.

AIMS: Cervical cancer with different mutations is associated with specific genomic differences. We developed a new mutation prediction model of the ARHGAP4 gene for cervical cancer. MAIN METHODS: We conducted a panoramic analysis of CESC mutations based on The Cancer Genome Atlas-Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (TCGA-CESC) database. We made copy number variation analysis and correlation analysis of somatic mutations and tumor mutation load fraction. Then we established a prediction model of ARHGAP4 mutation, screened related genes based on the risk scores, calculated the correlation between the risk score and immune microenvironment, and analyzed drug sensitivity. KEY FINDINGS: The prediction model of ARHGAP4 mutation based on mRNA expression is closely related to the survival rate of cervical cancer patients and to the effect of immunotherapy. The prediction model is also related to the infiltration of immune cells and human leukocyte antigen family expression in the immune microenvironment. After computational analysis, three drugs (cytarabine, docetaxel, imatinib) were identified as potential agents for the ARHGAP4 mutation high-risk group, and two drugs (erlotinib, methotrexate) were shown to have therapeutic significance for patients in the low-risk group. The expression of ARHGAP4 was higher in cervical cancer tissues. The proliferation ability of HeLa and SiHa cells decreased after ARHGAP4 knockdown. SIGNIFICANCE: This study provides not only a new approach for the prediction of the response of the cervical cancer patients to targeted drug therapy but also a new strategy for combining risk stratification with precision treatment.

High MutS homolog 2 expression predicts poor prognosis and is related to immune infiltration in endometrial carcinoma.

Several studies have shown that MutS homolog 2 (MSH2) is highly expressed in many cancer tissues. Transcriptome expression data were collected from the Cancer Genome Atlas (TCGA) database. We analyzed the expression of MSH2 in normal and tumor tissues, the relationship between MSH2 expression and various prognostic factors, and the relationship between MSH2 expression and overall survival, disease specific survival, and progression free interval. We also examined MSH2 promoter methylation between endometrial cancer and normal endometrial tissues, and identified the prognostic value of MSH2 methylation in endometrial cancer. MSH2 was highly expressed in endometrial cancer tumor tissues compared with normal tissues. High MSH2 expression might be an independent prognostic factor for OS, DSS, and PFI. Further, high MSH2 expression was correlated with age and histological type, but not with BMI, clinical stage, tumor invasion, or other clinical features. MSH2 promoter methylation in endometrial cancer was significantly lower than in normal tissues. Additionally, MSH2 levels, OS, DSS, and PFI were associated with BMI, age, tumor invasion, and histological type. ssGSEA showed that MSH2 expression was positively correlated with the infiltration of Th2 cells, Tcm cells, T helper cells, and Tgd cells, whereas it was negatively correlated with NK CD56 bright cells, pDC cells, iDC cells, cytotoxic cells, and neutrophils. Increased MSH2 expression and reduced MSH2 methylation in endometrial cancer predicts poor prognosis. MSH2 may be used as a biomarker for the diagnosis and prognosis of endometrial cancer and as an immunotherapy target.

Gene signatures, immune infiltration, and drug sensitivity based on a comprehensive analysis of m6a RNA methylation regulators in cervical cancer.

BACKGROUND: Cervical cancer is the fourth most common cancer in women. N6-dimethyladenosine (m6A) mRNA methylation is closely associated with cervical cancer. METHODS: Using TCGA database, we studied the expression and mutation of m6A-related genes in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) and obtained genetic characteristics based on an m6A risk model and prognostic value of m6A. We studied the effects of the m6A risk score on immune features and genomic changes of patients with CESC, evaluated the sensitivity of patients with CESC to different small-molecule drugs based on the m6A risk score, and established a clinical prediction model. RESULTS: Ten m6A-related genes were differentially expressed between CESC and normal tissues. High-risk patients had a low overall survival (OS) and significantly low immune scores but showed no significantly altered stromal scores. The tumor mutation burden (TMB) and tumor neoantigen levels significantly differed between the high- and low-risk groups. In the high-risk group, copy number variation (CNV) changes mainly led to gene amplification, while in the low-risk group, CNV changes primarily manifested as gene copy number deletions. ZC3H13 expression was low in CESC tissues. ZC3H13 knockdown promoted CESC cell proliferation, migration, and invasion, reducing the RNA methylation levels. Rapamycin suppressed the CESC cell proliferation, migration, and invasion abilities, increasing the m6A levels. CONCLUSION: m6A mRNA methylation is closely related to the occurrence, development, immune invasion, drug sensitivity, and prognosis of cervical cancer. The prognostic m6A feature model of m6A signature genes can accurately predict the OS of patients with CESC. Drugs targeting factors regulating m6A mRNA methylation might offer a good prospect for treating cervical cancer.

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

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