Tumor transcriptome-wide expression classifiers predict treatment sensitivity in advanced prostate cancers

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<sup>-37</sup>) 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.

Authors

Institutions

Publication Details

Journal
Cell
Published
2025-08-26
DOI
https://doi.org/10.1016/j.cell.2025.07.042
Citations
14
Primary Topic
Prostate Cancer Treatment and Research
Type
article
Field-Weighted Citation Impact
21.26

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Tumor transcriptome-wide expression classifiers predict treatment sensitivity in advanced prostate cancers

Gerhardt Attard, Teresa Marafioti, Christopher J. Sweeney, Ashwin Sachdeva et al.
14 citations
Cell
Prostate Cancer Treatment and Research
21.26
article

Tumor transcriptome-wide expression classifiers predict treatment sensitivity in advanced prostate cancers

Gerhardt Attard, Teresa Marafioti, Christopher J. Sweeney, Ashwin Sachdeva, Tamara L. Lotan, Silke Gillessen, Larissa Mendes, Edward M. Schaeffer, Mahesh Parmar, Elai Davicioni, Laura Murphy, Sarah Howlett, Anna Wingate, Felix Yi-Chung Feng, Hing Y. Leung, Nicholas David James, Oluwademilade Dairo, Marina Parry, Emily Grist, Alfonso Urbanucci, William Cross, Claire Amos, Leila Zakka, Stefanie Friedrich, Robert J. Jones, David Waugh, Matthew R. Sydes, Noel W. Clarke, Matthew W. Fittall, Sharanpreet Lall, Thomas Powles, Anis Hamid, Daniel M. Berney, Daniel Eidelberg Spratt, Hannah L. Rush, Louise Brown, Peter Dutey‐Magni, Nafisah B Atako, Daniel Wetterskog, Chris Brawley, Karolina Nowakowska, Yang Liu, Chris Parker, Mazlina Ismail, Lia DePaula Oliveira, James A. Proudfoot, Victoria Wang
article en
14 citations

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<sup>-37</sup>) 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.

CellVol. 188(20)
Northwestern University (US), University College Hospital (GB), Royal Marsden NHS Foundation Trust (GB), Memorial Sloan Kettering Cancer Center (US), Institute of Cancer Research (GB), Johns Hopkins University (US), Tampere University of Applied Sciences (FI), Queen Mary University of London (GB), University of South Australia (AU), University of California, San Francisco (US), Guy's and St Thomas' NHS Foundation Trust (GB), Johns Hopkins Medicine (US), Beatson West of Scotland Cancer Centre (GB), St James's University Hospital (GB), MRC Clinical Trials Unit at UCL (GB), Dana-Farber Cancer Institute (US), University Hospitals Seidman Cancer Center (US), Veracyte (United States) (US), Tampere University (FI), The Christie NHS Foundation Trust (GB), Centre for Cancer Biology (AU), University College London (GB), The University of Adelaide (AU), Università della Svizzera italiana (CH), Case Western Reserve University (US), University of Glasgow (GB)
U.S. Department of Defense, Prostate Cancer Foundation, Veracyte, Cancer Research UK, National Institute for Health and Care Research, Prostate Cancer UK, John Black Charitable Foundation, National Institutes of Health, Medical Research Council
Good health and well-being
Openalex Percentile: Top 0%
Prostate Cancer Treatment and Research
21.26
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.