Abstract:We recently developed a machine learning (ML) based program to predict cancer hotspots. Here, we applied the ML program to 32 non‐receptor tyrosine kinases (NRTKs) and identified 36 potential cancer driver mutations, with high probability mutations in 10 genes, including ABL1, ABL2, JAK1, JAK3, and ACK1. Interestingly among all the NRTKs, ACK1 is the only kinase that, when altered, shows a significant drop in overall survival, supporting the idea that ACK1 is an oncogenic tyrosine kinase. ACK1 is a member of t… Show more
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