Development of a predictive model for stromal content in prostate cancer samples to improve signature performance.

ABSTRACT: Prostate cancer is heterogeneous in both cellular composition and patient outcome, and development of biomarker signatures to distinguish indolent from aggressive tumours is a high priority. Stroma plays an important role during prostate cancer progression and undergoes histological and transcriptional changes associated with disease. However, identification and validation of stromal markers is limited by a lack of datasets with defined stromal/tumour ratio. We have developed a prostate-selective signature to estimate the stromal content in cancer samples of mixed cellular composition. We identified stromal-specific markers from transcriptomic datasets of developmental prostate mesenchyme and prostate cancer stroma. These were experimentally validated in cell lines, datasets of known strom

SUBMITTER: Boufaied N 

PROVIDER: S-EPMC6900085 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature