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Dataset Information

Construction and validation of a transcription factors-based prognostic signature for ovarian cancer.


ABSTRACT:

Background

Ovarian cancer (OC) is one of the most common and lethal malignant tumors worldwide and the prognosis of OC remains unsatisfactory. Transcription factors (TFs) are demonstrated to be associated with the clinical outcome of many types of cancers, yet their roles in the prognostic prediction and gene regulatory network in patients with OC need to be further investigated.

Methods

TFs from GEO datasets were collected and analyzed. Differential expression analysis, WGCNA and Cox-LASSO regression model were used to identify the hub-TFs and a prognostic signature based on these TFs was constructed and validated. Moreover, tumor-infiltrating immune cells were analyzed, and a nomogram containing age, histology, FIGO_stage and TFs-based signature were established. Potential

SUBMITTER: Cheng Q 

PROVIDER: S-EPMC8886838 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature