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Synapse
September 12, 20250 citationsOpen Access

Translating clinical gene sequencing into a foundational representation of tumor subtype

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JKJungHo KongILIngoo LeeDBDean Boecher

Key Points

  • MutationProjector accurately reconstructs genetic profiles and determines cancer subtype representations, enhancing interpretability.
  • Evaluation across tasks shows leading performance in predicting immunotherapy response and identifying key biomarkers.
  • Integrating genomic alterations from over 30,000 tumors results in a robust model capable of generalization.
  • Key biomarkers like KMT2A and KRAS-STK11 significantly influence responses to immunotherapy, highlighting treatment implications.

Abstract

While gene sequencing is routine in cancer care, translating sequences into treatment decisions remains a challenge. Here we introduce MutationProjector, an AI foundation model that transforms tumor mutation profiles into a compact representation of cancer subtype, with broad implications for diagnosis and therapy. MutationProjector is pre-trained by integrating genomic alterations from >30,000 tumors with extensive molecular knowledge, yielding a model that accurately reconstructs held-out genetic profiles (demonstrating strong generalization) and determines subtype representations from altered molecular pathways (enabling model interpretability). We evaluate MutationProjector in independent tasks related to prediction of immunotherapy response, prediction of chemotherapy response, and classification of metastasis, recording leading performance in all areas. Each task identifies key biomarkers of interest, including KMT2A and KRAS-STK11 alterations which govern immunotherapy response.

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Cite This Study

Kong et al. (2025) studied this question.

synapsesocial.com/papers/68d44c3d31b076d99fa555fbhttps://doi.org/10.1101/2025.09.08.674723
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