Biomarker-based outcome prediction in prostate adenocarcinoma depends on the TMPRSS2-ERG status

2019 
Background: Prostate adenocarcinoma (PCa) with/without the TMPRSS2-ERG (T2E) fusion represent distinct molecular subtypes. Objective: To investigate gene-signatures associated with metastasis in T2E-positive and -negative PCa, and to identify and validate subtype-specific prognostic biomarkers. Design, setting and participants: Gene expression and clinicopathological data of two discovery PCa cohorts (total n=783) were separately analyzed regarding the T2E status. Selected subtype-specific biomarkers were validated in two additional cohorts (total n=405). Outcome measurements and statistical analysis: From both discovery cohorts, we generated two gene lists ranked by their differential intratumoral expression in patients with/without metastases stratified by T2E-status, which were subjected to gene set enrichment and leading edge analyses. The resulting top 20 gene-signatures of both gene lists associated with metastasis were analyzed for overlaps between T2E-positive and -negative cases. Genes shared by several functional gene-signatures were tested for their association with event-free survival using the Kaplan-Meier method in a validation cohort. Immunohistochemistry was performed in another validation cohort. Results and limitations: Metastatic T2E-positive and -negative PCa are characterized by different gene-signatures. Five genes (ASPN, BGN, COL1A1, RRM2 and TYMS) were identified whose high expression was significantly associated with worse outcome exclusively in T2E-negative PCa. This was validated in an independent cohort for all genes and additionally for RRM2 by immunohistochemistry in a separate validation cohort. No prognostic biomarkers were identified exclusively for T2E-positive tumors. Conclusions: Our study demonstrates that the prognostic value of biomarkers critically depends on the molecular subtype, i.e. the T2E-status, which should be considered when screening for and applying novel prognostic biomarkers for outcome prediction in PCa. Patient summary: Outcome prediction for PCa is complex. The results of this study highlight that the validity of prognostic biomarkers depends on the molecular subtype, specifically the presence/absence of T2E. The reported new subtype-specific biomarkers exemplify that biomarker based outcome prediction in PCa should consider the T2E-status.
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