Molecular Signature for Lymphatic Invasion Associated with Survival of Epithelial Ovarian Cancer.

ABSTRACT:

Purpose

We aimed to develop molecular classifier that can predict lymphatic invasion and their clinical significance in epithelial ovarian cancer (EOC) patients.

Materials and methods

We analyzed gene expression (mRNA, methylated DNA) in data from The Cancer Genome Atlas. To identify molecular signatures for lymphatic invasion, we found differentially expressed genes. The performance of classifier was validated by receiver operating characteristics analysis, logistic regression, linear discriminant analysis (LDA), and support vector machine (SVM). We assessed prognostic role of classifier using random survival forest (RSF) model and pathway deregulation score (PDS). For external validation,we analyzed microarray data from 26 EOC samples of Samsung Medical Center and curatedO

SUBMITTER: Paik ES 

PROVIDER: S-EPMC5912145 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature