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bioRxiv · 10.1101/2024.12.11.627785

An artificial intelligence-based model for prediction of Clonal Hematopoiesis mutants in cell-free DNA samples

Arango-Argoty, G.·Haghighi, M.·Sun, G. J.·Markovets, A.·Barrett, J. C.·Lai, Z.·Jacob, E.
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Abstract

Circulating tumor DNA is a critical biomarker in cancer diagnostics, but its accurate interpretation requires careful consideration of clonal hematopoiesis (CH), which can contribute to variants in cell-free DNA and potentially obscure true tumor-derived signals. Accurate detection of somatic variants of CH origin in plasma samples remains challenging in the absence of matched white blood cells sequencing. Here we present an open-source machine learning framework (MetaCHIP) which classifies variants in cfDNA from plasma-only samples as CH or tumor origin, surpassing state-of-the-art classification rates.

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Arango-Argoty, G., Haghighi, M., Sun, G. J., Markovets, A., Barrett, J. C., Lai, Z., Jacob, E.. 2024-12-16. An artificial intelligence-based model for prediction of Clonal Hematopoiesis mutants in cell-free DNA samples. https://doi.org/10.1101/2024.12.11.627785

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