Machine learning developed a PI3K/Akt pathway-related signature for predicting prognosis and drug sensitivity in ovarian cancer.

ABSTRACT:

Background

Ovarian cancer is one of the deadliest malignancies among females, generally having a poor prognosis. The PI3K/Akt pathway plays a vital role in the oncogenesis and progression of many types of cancer. Limited studies have fully clarified the role of PI3K/Akt pathway in the prognosis of ovarian cancer and its correlation with drug sensitivity.

Methods

A prognostic PI3K/Akt pathway related signature (PRS) was constructed with 10 machine learning algorithms using TCGA, GSE14764, GSE26193, GSE26712, GSE63885 and GSE140082 datasets. Gaussian mixture and logistic regression were performed to identify the optimal models for classifying lymphatic and venous invasion.

Results

The optimal prognostic PRS developed by Lasso + survivalSVM algorithm acted as an independ

SUBMITTER: Han X 

PROVIDER: S-EPMC10637788 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature