Integrated analysis of single-cell RNA-seq and bulk RNA-seq unveils heterogeneity and establishes a novel signature for prognosis and tumor immune microenvironment in ovarian cancer.

ABSTRACT: Ovarian cancer is a highly heterogeneous gynecological malignancy that seriously affects the survival and prognosis of female patients. Single-cell sequencing and transcriptome analysis can effectively characterize tumor heterogeneity to better study the mechanism of occurrence and development. In this study, we identified differentially expressed genes with different differentiation outcomes of tumor cells by analyzing a single-cell dataset. Based on the differentially expressed genes, we explored the differences in function and tumor microenvironment among clusters via consensus clustering. Meanwhile, WGCNA was employed to obtain key genes related to ovarian cancer. On the basis of the TCGA and GEO datasets, we constructed a risk model consisting of 7 genes using the LASSO regression mod

SUBMITTER: Wang Z 

PROVIDER: S-EPMC9841625 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature