AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Year: 2026
Type: article
Abstract: PURPOSE: The ENZAMET trial established that enzalutamide added to androgen deprivation therapy (ADT) improves overall survival (OS) in metastatic hormone-sensitive prostate cancer (mHSPC), but treatment response is heterogeneous. We tested whether the Artificial Intelligence Pathology Image Classifier (APIC), previously developed and locked in CHAARTED, predicts overall survival benefit from enzalutamide in ENZAMET. EXPERIMENTAL DESIGN: This biomarker study applied APIC to digitized hematoxylin and eosin specimens from ENZAMET (ANZUP 1304, NCT02446405). ENZAMET randomized participants with mHSPC to ADT plus enzalutamide or non-steroidal antiandrogen (NSAA), with early concurrent docetaxel permitted. APIC was applied without modification or retraining. The prespecified primary analysis evaluated the treatment-by-APIC interaction for OS using Cox models adjusted for standard clinical factors. Prespecified sensitivity analysis excluded participants receiving early concurrent docetaxel. RESULTS: Among 1125 participants, 492 with digitized tissue (median follow-up 68.8 months) were eligible. APIC classified 316 (64.0%) as APIC-negative and 176 (36.0%) as APIC-positive. APIC significantly modified enzalutamide benefit (interaction p=0.014). APIC-negative disease showed improved survival with enzalutamide versus NSAA (HR=0.50, 95%CI:0.35-0.73; 60-month OS 76.5% vs 58.3%), while APIC-positive showed limited evidence of benefit (HR=1.04, 95%CI:0.67-1.62; 60-month OS 55.6% vs 58.8%). In low-volume disease, enzalutamide improved survival in APIC-negative (HR=0.31, 95%CI:0.16-0.62) but not APIC-positive (HR=1.04, 95%CI:0.53-2.06; interaction p=0.015). For non-docetaxel-treated participants, enzalutamide benefit was greater in APIC-negative (HR=0.40; 60-month OS 82.0% vs 61.0%) than APIC-positive (HR=0.79; 60-month OS 62.8% vs 57.6%). CONCLUSIONS: The presence of APIC negative disease identified participants with a major improvement in OS with addition of enzalutamide to ADT compared with addition of NSAA.
Source: Clinical Cancer Research
Authors: Sebastian Medina, Naoto Tokuyama, Vaishnavi Putcha, Tilak Pathak, Pingfu Fu, Hayley Thomas, Vinod V. Subhash, Sonia Yip, Hui-Ming Lin, Lisa G. Horvath, James G. Kench, Alison Zhang, Martin R. Stockler, Anthony M. Joshua, Arun Azad, Samantha R. Oakes, Ian D. Davis, Christopher J. Sweeney, Anant Madabhushi
Institutions: Georgia Institute of Technology, Emory University, The Wallace H. Coulter Department of Biomedical Engineering, Atlanta VA Medical Center, Case Western Reserve University, The University of Sydney, National Health and Medical Research Council, Australian and New Zealand Urogenital and Prostate Cancer Trials Group, Garvan Institute of Medical Research, Chris O’Brien Lifehouse, Royal Prince Alfred Hospital, NSW Health Pathology, The Kinghorn Cancer Centre, Peter MacCallum Cancer Centre, Monash University, Adelaide University, The University of Adelaide
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Funders: Advanced Research Projects Agency for Health, AstraZeneca United States, U.S. Department of Veterans Affairs, Breast Cancer Research Foundation, Prevent Cancer Foundation, Bristol-Myers Squibb, Scott R. MacKenzie Foundation, Fund for Innovation in Cancer Informatics, Astellas Pharma, Australian and New Zealand Urogenital and Prostate Cancer Trials Group, National Health and Medical Research Council, National Institute on Aging, National Heart, Lung, and Blood Institute, NIH Office of the Director, National Cancer Institute, National Institute of Allergy and Infectious Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Biomedical Imaging and Bioengineering, U.S. National Library of Medicine
Awards: G1046651757, G1057899285, G1365000891, G1735930626, G1909130050, G2100643341, G278880248, G3137332008, Integration of novel biological targets/biomarkers in the treatment of lethal prostate cancer, G3517288931, G3541864657, G3603121960, G4250298150, More accurate disease assessment and improved clinical decision-making for patients with urothelial cancers, G4628867921, G5679709768, G6142425281, G639364663, G7105568102, Computer-Assisted Histologic Evaluation of Cardiac Allograft Rejection, G7552881036, G8796037806, Novel Radiomics for Predicting Response to Immunotherapy for Lung Cancer, Multi-Consortia Coordinating Center (MC2 Center) for Cancer Biology: Building Interdisciplinary Scientific Communities, Coordinating Impactful Resource Sharing, and Advancing Cancer Research, Quantitative imaging phenotypic classifier for distinguishing radiation effects from tumor recurrence in Glioblastoma, P-CARRS-BRAIN: Multi-domain (genetic, socio-behavioral, vascular) risk factors and prediction of Alzheimer’s Disease continuum in South Asians in India
OpenAlex ID: W7166108928