Multimodal histopathologic models stratify hormone receptor-positive early breast cancer

Boehm KM, El Nahhas OS, Marra A, Waters M, Jee J, Braunstein L, Schultz N, Selenica P, Wen HY, Weigelt B, Paul ED, Cekan P, Erber R, Loeffler CM, Guerini-Rocco E, Fusco N, Frascarelli C, Mane E, Munzone E, Dellapasqua S, Zagami P, Curigliano G, Razavi P, Reis-Filho JS, Pareja F, Chandarlapaty S, Shah SP, Kather JN (2025)

Publication Type: Journal article

Publication year: 2025

Journal

Nature Communications Nature Publishing Group: Nature Communications

Book Volume: 16

Article Number: 2106

Journal Issue: 1

DOI: 10.1038/s41467-025-57283-x

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.

Authors with CRIS profile

Ramona Erber Institute of Pathology

Involved external institutions

European Institute of Oncology / Istituto Europeo di Oncologia (IEO) IT Italy (IT) Memorial Sloan Kettering Cancer Center US United States (USA) (US) Universitätsklinikum Carl Gustav Carus Dresden DE Germany (DE) Comenius University Bratislava SK Slovakia (SK)

How to cite

APA:

Boehm, K.M., El Nahhas, O.S., Marra, A., Waters, M., Jee, J., Braunstein, L.,... Kather, J.N. (2025). Multimodal histopathologic models stratify hormone receptor-positive early breast cancer. Nature Communications, 16(1). https://doi.org/10.1038/s41467-025-57283-x

MLA:

Boehm, Kevin M., et al. "Multimodal histopathologic models stratify hormone receptor-positive early breast cancer." Nature Communications 16.1 (2025).

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