Background: Few studies have discussed the contradictory roles of mutated-PI3Kα in HER2-positive (HER2+) breast cancer. Thus, we characterised the adaptive roles of PI3Kα mutations among HER2+ tumour progression.
Methods: We conducted prospective clinical sequencing of 1923 Chinese breast cancer patients and illustrated the clinical significance of PIK3CA mutations in locally advanced and advanced HER2+ cohort. A high-throughput PIK3CA mutations-barcoding screen was performed to reveal impactful mutation sites in tumour growth and drug responses.
Results: PIK3CA mutations acted as a protective factor in treatment-naïve patients; however, advanced/locally advanced patients harbouring mutated-PI3Kα exhibited a higher progressive disease rate (100% vs. 15%, p = .000053) and a lower objective response rate (81.7% vs. 95.4%, p = .0008) in response to trastuzumab-based therapy. Meanwhile, patients exhibiting anti-HER2 resistance had a relatively high variant allele fraction (VAF) of PIK3CA mutations; we defined the VAF > 12.23% as a predictor of poor anti-HER2 neoadjuvant treatment efficacy. Pooled mutations screen revealed that specific PI3Kα mutation alleles mediated own biological effects. PIK3CA functional mutations suppressed the growth of HER2+ cells, but conferred anti-HER2 resistance, which can be reversed by the PI3Kα-specific inhibitor BYL719.
Conclusions: We proposed adaptive treatment strategies that the mutated PIK3CA and amplified ERBB2 should be concomitantly inhibited when exposing to continuous anti-HER2 therapy, while the combination of anti-HER2 and anti-PI3Kα treatment was not essential for anti-HER2 treatment-naïve patients. These findings improve the understanding of genomics-guided treatment in the different progressions of HER2+ breast cancer.
Keywords: early and advanced HER2-positive breast cancer; library screening; prospective sequencing; shifty PI3Kα treatment strategy.
© 2021 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.