The prognostic landscape of interactive biological processes presents treatment responses in cancer.

ABSTRACT:

Background

Differential gene expression patterns are commonly used as biomarkers to predict treatment responses among heterogeneous tumors. However, the link between response biomarkers and treatment-targeting biological processes remain poorly understood. Here, we develop a prognosis-guided approach to establish the determinants of treatment response.

Methods

The prognoses of biological processes were evaluated by integrating the transcriptomes and clinical outcomes of ~26,000 cases across 39 malignancies. Gene-prognosis scores of 39 malignancies (GEO datasets) were used for examining the prognoses, and TCGA datasets were selected for validation. The Oncomine and GEO datasets were used to establish and validate transcriptional signatures for treatment responses.

Findings

SUBMITTER: He B 

PROVIDER: S-EPMC6441875 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature