Mechanism of action biomarkers predicting response to AKT inhibition in the I-SPY 2 breast cancer trial.
Denise M WolfChristina YauJulia WulfkuhleLamorna Brown-SwigartRosa I GallagherMark Jesus M MagbanuaNick O'GradyGillian L Hirstnull nullSmita AsareDebasish TripathyDon BerryLaura J EssermanA Jo ChienEmanuel F PetricoinLaura van 't VeerPublished in: NPJ breast cancer (2020)
The AKT inhibitor MK2206 (M) was evaluated in I-SPY 2 and graduated in the HER2+, HR-, and HR- HER2+ signatures. We hypothesized that AKT signaling axis proteins/genes may specifically predict response to M and tested 26 phospho-proteins and 10 genes involved in AKT-mTOR-HER signaling; in addition, we tested 9 genes from a previous study in the metastatic setting. One hundred and fifty patients had gene expression data from pretreatment biopsies available for analysis (M: 94, control: 56) and 138 had protein data (M: 87, control: 51). Logistic modeling was used to assess biomarker performance in pre-specified analysis. In general, phospho-protein biomarkers of activity in the AKT-mTOR-HER pathway appeared more predictive of response to M than gene expression or total protein biomarkers in the same pathway; however, the nature of the predictive biomarkers differed in the HER2+ and TN groups. In the HER2+ subset, patients achieving a pCR in M had higher levels of multiple AKT kinase substrate phospho-proteins (e.g., pmTOR, pTSC2). In contrast, in the TN subset responding patients had lower levels of AKT pathway phospho-proteins, such as pAKT, pmTOR, and pTSC2. Pathway mutations did not appear to account for these associations. Additional exploratory whole-transcriptome analysis revealed immune signaling as strongly associated with response to M in the HER2+ subset. While our sample size is small, these results suggest that the measurement of particular AKT kinase substrate phospho-proteins could be predictive of MK2206 efficacy in both HER2+ and TN tumors and that immune signaling may play a role in response in HER2+ patients.
Keyphrases
- end stage renal disease
- gene expression
- cell proliferation
- signaling pathway
- chronic kidney disease
- newly diagnosed
- ejection fraction
- prognostic factors
- magnetic resonance imaging
- peritoneal dialysis
- dna methylation
- magnetic resonance
- genome wide
- computed tomography
- binding protein
- transcription factor
- amino acid
- machine learning
- big data
- contrast enhanced
- patient reported