A Foundation Model of Cancer Genotype Enables Precise Predictions of Therapeutic Response

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Authors: JungHo Kong, Ingoo Lee, Dean Boecher, Akshat Singhal, Marcus R. Kelly, Jimin Moon, Chang Ho Ahn, Chan‐Young Ock, Dexter Pratt, Tannavee Kumar, Timothy J. Sears, David Laub
+5 more Sarah Wright, Patrick Wall, Hannah Carter, Zhen Wang, Trey Ideker
Cited by: 1
References: 125

Abstract

Abstract Although genetic sequencing is routine in cancer care, translating a tumor’s complex mutation profile into actionable treatment decisions remains a central challenge. MutationProjector is pretrained on a large corpus of genomic alterations across more than 30,000 tumors, integrated with extensive molecular knowledge. The resulting projection reveals a tumor’s altered molecular pathways, facilitating model interpretation, and it accurately reconstructs held-out mutations, demonstrating model generalization. When applied to predict immunotherapy or chemotherapy resistance across multiple cancer types and cohorts, MutationProjector achieves or exceeds state-of-the-art performance in all contexts. It identifies unexpected biomarkers, including KMT2D mutation in immunotherapy sensitivity and joint alteration of SMARCA4 and STK11 in immunotherapy resistance. These results establish a unifying framework for connecting tumor genotypes to biological mechanisms and therapeutic outcomes. Significance: This work describes MutationProjector, a tumor genomic foundation model pretrained on more than 30,000 tumors. It maps mutations to biological states for diagnosis and treatment, achieving state-of-the-art performance in predicting therapy resistance and identifying biomarkers such as KMT2D (sensitivity) and SMARCA4/STK11 coalterations (resistance).

Fields of Study & Subjects

Chromatin Remodeling and Cancer Protein Degradation and Inhibitors Melanoma and MAPK Pathways

Publication details

Journal / source
Cancer Discovery
Publisher
American Association for Cancer Research (AACR)
Volume
16
Issue
10
Pages
OF1–OF16
Publication date
26 May 2026
Language
EN