aceMachine learning uncovers previously undetectable genetic deletions in cancer panel sequencing
Missed genetic deletions can prevent cancer patients from receiving effective targeted therapy. Standard pipelines, such as TSO500, use bin count averaging for copy number variation detection but often overlook focal events. To address this, we developed a machine learning (ML) pipeline for deletion detection and zygosity evaluation within the MASTERsg precision oncology program. We focused on the tumor suppressor gene PTEN, whose loss confers sensitivity to mTOR/Akt inhibition. An Extreme Gradient Boosting mode…
An XGBoost model flagged focal PTEN deletions in 33 of 204 profiled tumors that TSO500 had called wild-type, and most stainable cases tested showed reduced or absent PTEN protein.
Protein validation was possible only in 20 stainable cases out of 33 newly detected deletions, and the work centres on a single gene, PTEN.
Evidence
- Peer-reviewednpj Precision Oncology2026-10-16
How should this claim be treated?
Truvace Impact Record TRV-2026-1962, v1: “Machine learning uncovers previously undetectable genetic deletions in cancer panel sequencing.” Truvace, 2026-10-20. /record/TRV-2026-1962 (accessed at citation time). sha256 56d5e65486bdd5dc…
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