Dataset Information

A Pyroptosis-Related Gene Panel in Prognosis Prediction and Immune Microenvironment of Human Endometrial Cancer

ABSTRACT: As the second common diagnosed cancer among gynecological tumors, endometrial cancer (EC) has heterogeneous pathogenesis and clinical manifestations. Therefore, prognosis prediction that considers gene expression value and clinical characteristics, is helpful to patients with EC. We downloaded RNA expression and clinical data from the TCGA database. We achieved 4 DEPRGs and constructed the PRG panel by univariate, lasso and multivariate Cox analysis. Based on the median value of the risk score, patients were divided into two groups. The Kaplan–Meier curve suggested that the patients with lower risk scores had better clinical outcomes of EC. AUC of ROC curves suggested the panel can be used as an independent predictor. Future analysis indicated the positive correlations between risk score and clinical characteristics. What’s more, we performed GO and KEGG functional analysis and immune environment exploration to get an understanding of the potential molecular mechanism and immunotherapeutic target. To future validate the panel, we found that the relapse-free and overall survival probability of 4 prognostic DEPRGs between high-expression group and low-expression group were different through the Kaplan–Meier plotter in UCEC. In addition, GEPIA database and RT-PCR experiment indicated GPX4 and GSDMD were highly expressed in UCEC compared to normal endometrial tissue, and TIRAP and ELANE were downregulated. This study identified a PRG panel to predict the prognosis immune microenvironment in human EC. Then, Kaplan–Meier analysis and AUC below the ROC curves was used to validate the panel. In addition, Chi-square was used to show the clinical significance. GO, KEGG and GSEA were used to show the functional differences. Different immune-related databases were used to analyze the immune characteristics. The Kaplan–Meier plotter website was used to assess the effect of genes on survival. GEPIA and RT-PCR were used to analyze the expression level. In summary, we identified 4 prognosis-associated pyroptosis-related genes (ELANE, GPX4, GSDMD, and TIRAP). The panel can also predict prognosis prediction and immune microenvironment in human endometrial cancer.

SUBMITTER: Zhang X

PROVIDER: S-EPMC8551636 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Endometrial carcinoma (EC) is a common malignancy of female genital system which exhibits a unique immune profile. It is a promising strategy to quantify immune patterns of EC for predicting prognosis and therapeutic efficiency. Here, we attempted to identify the possible immune microenvironment-related prognostic markers of EC. We obtained the RNA sequencing and corresponding clinical data of EC from TCGA database. Then, 3 immune scores based on the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm were computed. Correlation between above ESTIMATE scores and other immune-related scores, molecular subtypes, prognosis, and gene mutation status (including BRCA and TP53) were further analyzed. Afterwards, gene modules associated with the ESTIMATE scores were screened out through hierarchical clustering analysis and weighted gene co-expression network analysis (WGCNA). Differentially expressed analysis was performed and genes shared by the most relevant modules were found out. KEGG pathway enrichment analysis was conducted to explore the biological functions of those genes. Survival analysis was carried out to identify prognostic immune-related genes and GSE17025 database was further used to confirm the correlation between immune-related genes and the ImmuneScore. The immune-related scores based on ESTIMATE algorithm was closely related to the immune microenvironment of EC. 3 gene modules that had the closest correlations with 3 ESTIMATE scores were obtained. 109 immune-related genes were preliminarily found out and 29 pathways were significantly enriched, most of which were associated with immune response. Univariate survival analysis revealed that there were 14 genes positively associated with both OS and PFS. Among which, 11 genes showed marked correlations with ImmuneScore values in GSE17025 database. Our current study profiled the immune status and identified 14 novel immune-related prognostic biomarkers for EC. Our findings may help to investigate the complicated tumor microenvironment and develop novel individualized therapeutic targets for EC.

Dataset Information

A Pyroptosis-Related Gene Panel in Prognosis Prediction and Immune Microenvironment of Human Endometrial Cancer

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets