Multimodal histopathologic models stratify hormone receptor-positive early breast cancer

Kevin M. Boehm, Omar S. M. El Nahhas, Antonio Marra, Michele Waters, Justin Jee, Lior Braunstein, Nikolaus Schultz, Pier Selenica, Hannah Y. Wen, Britta Weigelt, Evan D. Paul, Pavol Cekan, Ramona Erber, Chiara M. L. Loeffler, Elena Guerini-Rocco, Nicola Fusco, Chiara Frascarelli, Eltjona Mane, Elisabetta Munzone, Silvia Dellapasqua, Paola Zagami, Giuseppe Curigliano, Pedram Razavi, Jorge S. Reis-Filho, Fresia Pareja, Sarat Chandarlapaty (), Sohrab P. Shah () and Jakob Nikolas Kather ()
Additional contact information
Kevin M. Boehm: Memorial Sloan Kettering Cancer Center
Omar S. M. El Nahhas: Technical University Dresden
Antonio Marra: Memorial Sloan Kettering Cancer Center
Michele Waters: Memorial Sloan Kettering Cancer Center
Justin Jee: Memorial Sloan Kettering Cancer Center
Lior Braunstein: Memorial Sloan Kettering Cancer Center
Nikolaus Schultz: Memorial Sloan Kettering Cancer Center
Pier Selenica: Memorial Sloan Kettering Cancer Center
Hannah Y. Wen: Memorial Sloan Kettering Cancer Center
Britta Weigelt: Memorial Sloan Kettering Cancer Center
Evan D. Paul: Comenius University Science Park
Pavol Cekan: Comenius University Science Park
Ramona Erber: Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN)
Chiara M. L. Loeffler: Technical University Dresden
Elena Guerini-Rocco: European Institute of Oncology IRCCS
Nicola Fusco: European Institute of Oncology IRCCS
Chiara Frascarelli: European Institute of Oncology IRCCS
Eltjona Mane: European Institute of Oncology IRCCS
Elisabetta Munzone: European Institute of Oncology IRCCS
Silvia Dellapasqua: European Institute of Oncology IRCCS
Paola Zagami: European Institute of Oncology IRCCS
Giuseppe Curigliano: European Institute of Oncology IRCCS
Pedram Razavi: Memorial Sloan Kettering Cancer Center
Jorge S. Reis-Filho: Memorial Sloan Kettering Cancer Center
Fresia Pareja: Memorial Sloan Kettering Cancer Center
Sarat Chandarlapaty: Memorial Sloan Kettering Cancer Center
Sohrab P. Shah: Memorial Sloan Kettering Cancer Center
Jakob Nikolas Kather: Technical University Dresden

Nature Communications, 2025, vol. 16, issue 1, 1-14

Abstract: Abstract The Oncotype DX® Recurrence Score (RS) is an assay for hormone receptor-positive early breast cancer with extensively validated predictive and prognostic value. However, its cost and lag time have limited global adoption, and previous attempts to estimate it using clinicopathologic variables have had limited success. To address this, we assembled 6172 cases across three institutions and developed Orpheus, a multimodal deep learning tool to infer the RS from H&E whole-slide images. Our model identifies TAILORx high-risk cases (RS > 25) with an area under the curve (AUC) of 0.89, compared to a leading clinicopathologic nomogram with 0.73. Furthermore, in patients with RS ≤ 25, Orpheus ascertains risk of metastatic recurrence more accurately than the RS itself (0.75 vs 0.49 mean time-dependent AUC). These findings have the potential to guide adjuvant therapy for high-risk cases and tailor surveillance for patients at elevated metastatic recurrence risk.

Date: 2025
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DOI: 10.1038/s41467-025-57283-x

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