Integrative radiogenomics analysis for predicting molecular features and survival in clear cell renal cell carcinoma.

ABSTRACT:

Objectives

To assess the feasibility of predicting molecular characteristics by computed tomography (CT) radiomics features, and predicting overall survival (OS) using combination of omics data in clear cell renal cell carcinoma (ccRCC).

Methods

Genetic data of 207 ccRCC patients was retrieved from The Cancer Genome Atlas (TCGA) and matched contrast-enhanced CT images were obtained from The Cancer Imaging Archive (TCIA). Another cohort of 175 ccRCC patients from West China Hospital was used as external validation. We first applied radiomics features and machine learning algorithms to predict genetic mutations and mRNA-based molecular subtypes. Next, we established predictive models for OS based on single omics, combined omics (radiomics+genomics, radiomics+transcriptomics, r

SUBMITTER: Zeng H 

PROVIDER: S-EPMC8064160 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature