Spatial transcriptomics-guided pathology biomarker as a predictor of benefit of adjuvant docetaxel in high-risk localized prostate cancer: NRG/RTOG 0521 (NCT00288080).
Abstract
5111 Background: The NRG/RTOG 0521 trial evaluated adding adjuvant docetaxel (DTX) to standard radiotherapy plus androgen deprivation therapy (ADT) in high-risk localized prostate cancer. Adjuvant DTX modestly improved overall survival (OS) in the trial, but the benefit was limited and not all patients benefited. Thus, biomarkers are needed to identify patients most likely to benefit from chemotherapy intensification. ST-DoxPCa (Spatial Transcriptomics–Guided Docetaxel Therapy Stratification in Prostate Cancer) is a novel artificial intelligence (AI) driven histology biomarker that predicts gene expression from H&E slides (virtual spatial transcriptomics). We assessed whether ST-DoxPCa can stratify patients in RTOG 0521 for differential benefit from adjuvant DTX. Methods: A Vision Transformer trained on paired histology–spatial transcriptomics (HEST1K) predicts a 208-gene prostate panel at spot level; predictions are distilled into a biologically informed 26-gene signature and aggregated into patient-level features. A prognostic Cox model and fixed median threshold were developed independently in a Cleveland Clinic radical prostatectomy cohort (CCF, n=352; endpoint: biochemical recurrence-free survival). This locked model and threshold were applied unchanged (no refitting or recalibration) to digitized pretreatment diagnostic biopsies from NRG/RTOG 0521 (n=350; RT+ADT n=169, RT+ADT+DTX n=181) to stratify patients into ST-DoxPCa-positive (high-risk) and ST-DoxPCa-negative (low-risk) groups. Overall survival (OS) was compared between treatment arms within each stratum. Results: ST-DoxPCa stratified patients into biomarker-defined risk groups using aggregated spatial-expression features from a biologically informed gene panel; key genes included PTEN, NKX3-1, ACPP, FASN and TMPRSS2. ST-DoxPCa-positive (high-risk) patients experienced a significant OS benefit from adding DTX to RT+ADT versus RT+ADT alone (HR=0.38, 95% CI 0.18–0.83; p=0.012), whereas ST-DoxPCa-negative (low-risk) patients derived no OS benefit (HR=1.05, 95% CI 0.67–1.63; p=0.84). Conclusions: The ST-DoxPCa model identified a subgroup with substantial OS benefit from adjuvant DTX and a subgroup with no benefit within RTOG 0521, supporting risk-aligned chemotherapy intensification using routine histology. Clinical trial information: NRG/RTOG 0521 ( NCT00288080 ) .
Article Details
Journal Info
Journal of Clinical Oncology
Lippincott Williams & Wilkins
Authors (20)
Md Mamunur Rahaman
School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia
Amritpal Singh
Sebastian R. Medina
Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University, Atlanta, GA
Naoto Tokuyama
Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, GA
Kamal Hammouda
Emory University, Atlanta, GA
Pingfu Fu
6Case Western Reserve University, Cleveland, United States
Howard M. Sandler
Cedars-Sinai Medical Center, Los Angeles, CA
Rohann Jonathan Mark Correa
London Health Sciences Centre, London, ON, Canada
Susan Chafe
Cross Cancer Institute, Edmonton, AB, Canada
Amit I. Shah
WellSpan Health, York, PA
Jason A. Efstathiou
Massachusetts General Hospital, Boston, MA
Karen E. Hoffman
Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
Michael Wayne Straza
Medical College of Wisconsin, Milwaukee, WI
Mark A. Hallman
Fox Chase Cancer Center, Philadelphia, PA
Richard Jordan
NRG Oncology Biospecimen Bank, San Francisco, CA
Ewan KA MIllar
Department of Anatomical Pathology, NSW Health Pathology, St. George Hospital, Syndey, NSW, Australia
Erik Meijering
Stephanie L. Pugh
NRG Oncology, Philadelphia, PA
Paul Nguyen
Department of Physics, University of Washington 2 , Seattle, Washington 98195,
Anant Madabhushi