Listen

Description

Grist E et al., Cell - Large-scale transcriptome profiling of 1,523 diagnostic prostate tumors from randomized STAMPEDE phase 3 trials linked expression signatures and immunohistochemistry to 14-year survival. The Decipher RNA classifier was both prognostic and predicted survival benefit from docetaxel in metastatic disease, and a transcriptome-based PTEN inactivity classifier identified docetaxel-sensitive, metabolically perturbed tumors. High tumor androgen receptor signaling associated with longer survival while increased proliferation predicted shorter survival. These results support clinical implementation of transcriptome classifiers to guide treatment selection in advanced prostate cancer. Key terms: prostate cancer, transcriptome, Decipher, docetaxel, PTEN.

Study Highlights:
The study generated transcriptome-wide expression profiles and Ki-67/PTEN immunohistochemistry for 1,523 patients (832 metastatic) from STAMPEDE phase 3 trials with 14-year follow-up. High Decipher scores were prognostic and pre-specified predictive for docetaxel benefit in metastatic disease (interaction p = 0.039). A PTEN_loss_Liu transcriptome classifier identified PTEN-inactive tumors that had shorter survival on hormone therapies but significant survival benefit from docetaxel (interaction p = 0.002). Tumor AR signaling associated with longer survival and proliferation signatures (and Ki-67) with shorter survival.

Conclusion:
Clinical-grade transcriptome classifiers (notably Decipher and a PTEN inactivity signature) predict which metastatic prostate cancers derive survival benefit from docetaxel and could be implemented to improve treatment selection.

Music:
Enjoy the music based on this article at the end of the episode.

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

First author:
Grist E

Journal:
Cell

DOI:
10.1016/j.cell.2025.07.042

Reference:
Grist E., Dutey-Magni P., Parry M.A., et al. Tumor transcriptome-wide expression classifiers predict treatment sensitivity in advanced prostate cancers. Cell. 2025;188:1–18. https://doi.org/10.1016/j.cell.2025.07.042

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
Base by Base is independent and ad-free — no sponsors, no paywall. If an episode was worth your time, chip in and keep the papers audited and the original songs coming:
❤️ Support monthly: https://buy.stripe.com/cNifZhclVebvagk2JDgEg01
☕ One-time donation: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00
More at basebybase.com

On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/tumor-transcriptome-classifiers-predict-treatment-sensitivity-in-advanced-prostate-cancer

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-09-09.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited transcript segments describing the STAMPEDE biomarker cohort, transcriptome-wide profiling methods, prognostic vs predictive biomarkers, Decipher predicting docetaxel benefit, PTEN inactivity predicting docetaxel sensitivity, statistical design and level of evidence, and study limitations.
- transcript topics: Clinical treatment landscape for metastatic prostate cancer (ADT, docetaxel, abiraterone); Formalin-fixed, paraffin-embedded tissue transcriptome profiling and 59 signatures; Prognostic vs predictive biomarkers in STAMPEDE trials; Decipher classifier a...