Integrative clinical transcriptome analysis reveals TMPRSS2‐ERG dependency of prognostic biomarkers in prostate adenocarcinoma

• Published in: International journal of cancer Vol. 146; no. 7; pp. 2036 - 2046
• Main Authors: Gerke, Julia S., Orth, Martin F., Tolkach, Yuri, Romero‐Pérez, Laura, Wehweck, Fabienne S., Stein, Stefanie, Musa, Julian, Knott, Maximilian M.L., Hölting, Tilman L.B., Li, Jing, Sannino, Giuseppina, Marchetto, Aruna, Ohmura, Shunya, Cidre‐Aranaz, Florencia, Müller‐Nurasyid, Martina, Strauch, Konstantin, Stief, Christian, Kristiansen, Glen, Kirchner, Thomas, Buchner, Alexander, Grünewald, Thomas G.P.
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01-04-2020; Wiley Subscription Services, Inc
• Subjects: Adenocarcinoma; Adenocarcinoma - diagnosis; Adenocarcinoma - genetics; Adenocarcinoma - mortality; Biomarkers; Biomarkers, Tumor; Cancer; Collagen (type I); Computational Biology; Gene expression; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Genes; Humans; Immunohistochemistry; Kaplan-Meier Estimate; Male; Medical research; Metastases; Metastasis; Neoplasm Grading; Neoplasm Metastasis; Neoplasm Staging; Oncogene Proteins, Fusion - genetics; personalized medicine; Prognosis; prognostic biomarker; Prostate; prostate adenocarcinoma; Prostate cancer; Prostatic Neoplasms - diagnosis; Prostatic Neoplasms - genetics; Prostatic Neoplasms - mortality; TMPRSS2‐ERG; Tumors; prostate adenocarcinoma; prognostic biomarker; metastasis; TMPRSS2-ERG; personalized medicine
• ISSN: 0020-7136; 1097-0215
• DOI: 10.1002/ijc.32792

In prostate adenocarcinoma (PCa), distinction between indolent and aggressive disease is challenging. Around 50% of PCa are characterized by TMPRSS2‐ERG (T2E)‐fusion oncoproteins defining two molecular subtypes (T2E‐positive/negative). However, current prognostic tests do not differ between both molecular subtypes, which might affect outcome prediction. To investigate gene‐signatures associated with metastasis in T2E‐positive and T2E‐negative PCa independently, we integrated tumor transcriptomes and clinicopathological data of two cohorts (total n = 783), and analyzed metastasis‐associated gene‐signatures regarding the T2E‐status. Here, we show that the prognostic value of biomarkers in PCa critically depends on the T2E‐status. Using gene‐set enrichment analyses, we uncovered that metastatic T2E‐positive and T2E‐negative PCa are characterized by distinct gene‐signatures. In addition, by testing genes shared by several functional gene‐signatures for their association with event‐free survival in a validation cohort (n = 272), we identified five genes (ASPN, BGN, COL1A1, RRM2 and TYMS)—three of which are included in commercially available prognostic tests—whose high expression was significantly associated with worse outcome exclusively in T2E‐negative PCa. Among these genes, RRM2 and TYMS were validated by immunohistochemistry in another validation cohort (n = 135), and several of them proved to add prognostic information to current clinicopathological predictors, such as Gleason score, exclusively for T2E‐negative patients. No prognostic biomarkers were identified exclusively for T2E‐positive tumors. Collectively, our study discovers that the T2E‐status, which is per se not a strong prognostic biomarker, crucially determines the prognostic value of other biomarkers. Our data suggest that the molecular subtype needs to be considered when applying prognostic biomarkers for outcome prediction in PCa.
What's new?
Genetic rearrangements involving androgen‐regulated transmembrane protease serine 2 and genes from the ETS transcription factor family (T2E), most commonly ERG and ETV1, occur in half of prostate cancers but are currently not considered in risk predictions. The authors integrate clinical and transcriptomic data from multiple studies and show that the prognostic value of biomarkers critically depends on the T2E‐status. They identify five biomarkers that predict negative outcome exclusively in T2E‐negative prostate cancers, which has implications for outcome prediction based on the molecular subtype.