Tumor transcriptome-wide expression classifiers predict treatment sensitivity in advanced prostate cancers
Emily Grist, Peter Dutey‐Magni, Marina Parry, Larissa Mendes, Ashwin Sachdeva, James A. Proudfoot, Anis Hamid, Mazlina Ismail, Sarah Howlett, Stefanie Friedrich, Lia DePaula Oliveira, Laura Murphy, Chris Brawley, Oluwademilade Dairo, Sharanpreet Lall, Yang Liu, Daniel Wetterskog, Anna Wingate, Karolina Nowakowska, Leila Zakka, Claire Amos, Nafisah B Atako, Victoria Wang, Hannah Rush, Robert J. Jones, Hing Y. Leung, William Cross, Silke Gillessen, Chris Parker, Teresa Marafioti, Alfonso Urbanucci, Matthew W. Fittall, Edward M. Schaeffer, Daniel E. Spratt, David Waugh, Thomas Powles, Matthew R. Sydes, Felix Y. Feng, Daniel M. Berney, Mahesh Parmar, Noel W. Clarke, Elai Davicioni, Tamara L. Lotan, Christopher J. Sweeney, Louise Brown, Nicholas D. James, Gerhardt Attard
Abstract
Advanced prostate cancers respond to hormone therapy but outcomes vary and no predictive tests exist for informed treatment selection. To identify novel biomarker-treatment pairings, we examined associations between biological pathways and 14-year survival outcomes of patients randomized in practice-changing phase 3 trials (testing docetaxel or abiraterone). We included transcriptome-wide expression signatures and immunohistochemistry markers (Ki-67 and PTEN) on prostate tumors from 1,523 patients (832 metastatic). Tumor androgen receptor signaling is associated with longer survival, whereas increased proliferation predicted shorter survival. In a pre-specified analysis, the previously identified decipher RNA signature was both prognostic and predicted survival benefit from docetaxel for metastatic cancers (biomarker-docetaxel interaction p = 0.039). Additionally, transcriptome-based classification of PTEN inactivation identified tumors more likely to have PTEN protein loss ( p = 4 × 10 −37 ) and metabolically perturbed metastatic cancers that had shorter survival with hormone therapies ( p < 0.001) but exhibited docetaxel sensitivity (biomarker-docetaxel interaction p = 0.002). Transcriptome classifiers predict docetaxel benefit and could be clinically implemented for improved patient management.