In vivo phosphoproteomics reveals kinase activity profiles that predict treatment outcome in triple-negative breast cancer

Triple-negative breast cancer (TNBC) lacks prognostic and predictive markers. We used high-throughput phosphoproteomics to build a functional TNBC taxonomy. A cluster of 159 phosphosites was upregulated in relapsed cases of a training set (n=34 patients). Eleven hyperactive kinases accounted for this phosphoprofile. A massspectrometry-to-immunohistochemistry translation step that assessed 113 TNBC validation specimens revealed that 6/12 kinases (PRKCE, KIT, PNKP, ERK, CDK6, and P70S6K) preserved independent prognostic value. The kinases split the validation set into two patterns: one (0/6 hyperactive kinases; 29% of the patients) associated with a 93.5% cure rate. The other (≥1 hyperactive kinase; 37 subpatterns) was associated with a 9.5-fold higher relapse risk. Each kinase pattern agglutinated different mutational patterns. Drug regimens designed based on these six kinases showed synergistic activity in vitro and in vivo. Our results elucidated novel phosphosites/kinases that are implicated in TNBC and provide a ready-to-use, actionable target-based clinical classification system for TNBC