Multi-institutional Patient-level Comparison of Decipher Genomic Classifier and Artera Multimodal Artificial Intelligence (MMAI) in Prostate Cancer

Abstract Importance: The Decipher Prostate Genomic Classifier (GC) and ArteraAI Multimodal Artificial Intelligence (MMAI) platform are widely used prognostic tools for localized prostate cancer (PCa), yet no direct comparison has been performed within the same patient cohort. Methods: We sought to evaluate the concordance and prognostic value of GC and MMAI across multi-institutional cohorts totaling 688 patients with localized and oligometastatic PCa. These included populations enriched for African American and East Asian patients. GC and MMAI scores were stratified into risk groups based on specimen type (biopsy or radical prostatectomy (RP)). The primary endpoint was distant metastasis-free survival (DMFS), measured from diagnosis to last follow-up or event. Results: GC and MMAI scores were significantly correlated across multiple cohorts. In Moffitt RP, biopsy, and NCCS cohorts, both MMAI and GC were prognostic alone and after adjusting for clinical variables. Multivariable analysis including both biomarkers and clinical variables showed that MMAI was significant even accounting for GC in Moffitt RP, and borderline in Moffitt biopsy. Analysis of concordant/discordant cases showed that patients who were high-risk for both GC and MMAI did qualitatively worse. In pathway analysis, concordance with GC and MMAI was high for Moffitt RP and oligometastatic patients. Across both biopsy cohorts, while most biological pathways were concordant, there were consistent discordant signaling, metabolic, and DNA repair pathways. Conclusions: In the first direct patient-level comparison of GC and MMAI in PCa, these biomarkers were found to demonstrate moderate correlation, and both biomarkers demonstrated prognostic value across diverse populations and disease states.

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Publication Details

Journal
Clinical Cancer Research
Published
2026-10-08
DOI
https://doi.org/10.1158/1078-0432.ccr-26-2269
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
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article

Multi-institutional Patient-level Comparison of Decipher Genomic Classifier and Artera Multimodal Artificial Intelligence (MMAI) in Prostate Cancer

Michael Lian Chek Wang, Steven Jay Frank, Theodore L. DeWeese, Osama Mohamad et al.
Clinical Cancer Research
Prostate Cancer Diagnosis and Treatment
article

Multi-institutional Patient-level Comparison of Decipher Genomic Classifier and Artera Multimodal Artificial Intelligence (MMAI) in Prostate Cancer

Michael Lian Chek Wang, Steven Jay Frank, Theodore L. DeWeese, Osama Mohamad, Sei‐Won Laura Chang, Matthew Pierre Deek, Seungtaek Choi, Michael Kevin Rooney, Philip Anthony Sutera, Ozan Cem Güler, Enya H.W. Ong, Krishnan R. Patel, Henry Y.I. Mok, Elai Davicioni, Paul Linh Nguyen, Jasreman Dhillon, Chad Z. Tang, Loïg Vaugier, Felix Yi-Chung Feng, Jason K. Molitoris, Siyi Tang, Zaker Hamid Rana, Carole Mercier, Shalin J. Shah, Comron Hassanzadeh, Kae Jack Tay, Li Yan Khor, Jeffrey K. L. Tuan, Danielle C. Croucher, Stéphane Supiot, Rodrigo Rodrigues Pessoa, Matthew Ramotar, Audrey Blanc-Lapierre, Cem Önal, Mark Vikas Mishra, Julio M. Pow‐Sang, Rikiya Yamashita, Alexander K. Hakansson, Young Kwok, Yang Song, Daniel Y. Song, Boon Hao Hong, Amol Carl Shetty, George Daniel Grass, Kosj Yamoah, Esther N. Katende, Piet R. Dirix, Jong Y. Park, Phuoc T. Tran, Ana P. Kiess, Daniel Eidelberg Spratt, Shuang George Zhao, Melvin L.K. Chua, Kah Min Tan, Piet Ost, Riley Smith, Ryan Jin-hyung Park, Ryan M. Putney, Amparo N. Serna, Alejandro Berlín, Xiaolei Shi, Michael Adam Poch, Scott Edward Delacroix, Sean Eric McGuire, Jinhee Chang, Karen Elizabeth Hoffman, Yi Ren, Quyhn Nhu Nguyen, Claudia Datnow-Martinez, Lauren L. Mayo, Purvish Trivedi, Yang Liu, Huei-Chung Huang, Adeniyi A. Olabumuyi, Olivia G. Jordan
article en

Abstract

Abstract Importance: The Decipher Prostate Genomic Classifier (GC) and ArteraAI Multimodal Artificial Intelligence (MMAI) platform are widely used prognostic tools for localized prostate cancer (PCa), yet no direct comparison has been performed within the same patient cohort. Methods: We sought to evaluate the concordance and prognostic value of GC and MMAI across multi-institutional cohorts totaling 688 patients with localized and oligometastatic PCa. These included populations enriched for African American and East Asian patients. GC and MMAI scores were stratified into risk groups based on specimen type (biopsy or radical prostatectomy (RP)). The primary endpoint was distant metastasis-free survival (DMFS), measured from diagnosis to last follow-up or event. Results: GC and MMAI scores were significantly correlated across multiple cohorts. In Moffitt RP, biopsy, and NCCS cohorts, both MMAI and GC were prognostic alone and after adjusting for clinical variables. Multivariable analysis including both biomarkers and clinical variables showed that MMAI was significant even accounting for GC in Moffitt RP, and borderline in Moffitt biopsy. Analysis of concordant/discordant cases showed that patients who were high-risk for both GC and MMAI did qualitatively worse. In pathway analysis, concordance with GC and MMAI was high for Moffitt RP and oligometastatic patients. Across both biopsy cohorts, while most biological pathways were concordant, there were consistent discordant signaling, metabolic, and DNA repair pathways. Conclusions: In the first direct patient-level comparison of GC and MMAI in PCa, these biomarkers were found to demonstrate moderate correlation, and both biomarkers demonstrated prognostic value across diverse populations and disease states.

Clinical Cancer Research
Rutgers, The State University of New Jersey (US), HOGENT University of Applied Sciences and Arts (BE), University of Maryland, Baltimore (US), Brigham and Women's Hospital (US), University of Maryland Medical Center (US), The University of Texas MD Anderson Cancer Center (US), University of Wisconsin–Madison (US), Johns Hopkins University (US), University of California, San Francisco (US), University of Toronto (CA), Başkent University (TR), Singapore General Hospital (SG), University Hospitals of Cleveland (US), Johns Hopkins Medicine (US), Ghent University Hospital (BE), Princess Margaret Cancer Centre (CA), University of Rochester Medical Center (US), Moffitt Cancer Center (US), Ghent University (BE), Centre de Recherche en Cancérologie et Immunologie Intégrée Nantes Angers (FR), Institut de Cancérologie de l'Ouest (FR), Veracyte (United States) (US), Başkent University Hospital (TR), Iridium Kankernetwerk (BE), National Cancer Centre Singapore (SG), Mary Bird Perkins Cancer Center (US), Johns Hopkins Hospital (US), University of Baltimore (US), University of Maryland, College Park (US), University of San Francisco (US), Michigan State University (US)
Openalex Percentile: Top 12%
Prostate Cancer Diagnosis and Treatment
DOISourceOpenAlex
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