Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model.

ABSTRACT: Serous ovarian cancer is the most common type of ovarian epithelial cancer and usually has a poor prognosis. The objective of this study was to construct an individualized prognostic model for predicting overall survival in serous ovarian cancer. Based on the relative expression orderings (Ea > Eb/Ea ≤ Eb) of gene pairs closely associated with serous ovarian prognosis, we tried constructing a potential individualized qualitative biomarker by the greedy algorithm and evaluated the performance in independent validation datasets. We constructed a prognostic biomarker consisting of 20 gene pairs (SOV-P20). The overall survival between high- and low-risk groups stratified by SOV-P20 was statistically significantly different in the training and independent validation datasets from other platform

SUBMITTER: Luo F 

PROVIDER: S-EPMC9777083 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature