Unbiased data mining identifies cell cycle transcripts that predict non-indolent Gleason score 7 prostate cancer.

ABSTRACT:

Background

Patients with newly diagnosed non-metastatic prostate adenocarcinoma are typically classified as at low, intermediate, or high risk of disease progression using blood prostate-specific antigen concentration, tumour T category, and tumour pathological Gleason score. Classification is used to both predict clinical outcome and to inform initial management. However, significant heterogeneity is observed in outcome, particularly within the intermediate risk group, and there is an urgent need for additional markers to more accurately hone risk prediction. Recently developed web-based visualization and analysis tools have facilitated rapid interrogation of large transcriptome datasets, and querying broadly across multiple large datasets should identify predictors that are widel

SUBMITTER: Johnston WL 

PROVIDER: S-EPMC6322345 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature