[Characteristic PIK3CA gene mutation in breast cancer].

Objective: To investigate the mutation spectrum of the PIK3CA gene in breast cancer, providing a new basis for the precise treatment of breast cancer with PIK3CA inhibitors. Methods: A retrospective analysis was conducted on 144 breast cancer patients who underwent biopsy before neoadjuvant therapy archived from 2015 to 2020 at the Fourth Hospital of Hebei Medical University. Next-generation sequencing (NGS) was utilized to detect the mutations of 520 genes closely related to the development of solid tumors and targeted therapies. The study compared the differences between reported mutation types and focused on analyzing the mutation status of the PIK3CA gene. The clinical and pathological characteristics, including age of onset, molecular subtypes, and Ki-67, were also analyzed. The correlation between PIK3CA mutations and clinicopathological characteristics was examined using Pearson×s chi-square test and Mann Whitney test. Logistic regression was employed to analyze factors influencing PIK3CA mutations. Kaplan-Meier survival analysis and Cox regression models were constructed using R programming. Results: Among the 144 breast cancer samples, 61 (42.3%, 61/144) exhibited PIK3CA gene mutations, of which 23 cases (53.5%, 23/43) were HER2-positive breast cancer, 28 cases (44.4%, 28/63) were luminal breast cancer, and 10 cases (27.8%, 10/36) were triple-negative breast cancer. Of the detected mutations, three hotspot mutations (H1047R, E545K, and E542K) accounted for 72.1% of the total PIK3CA mutations, with H1047R (52.4%), E545K (16.4%), and E542K (3.3%) most commonly detected. The remaining rare mutations accounted for 26.3%. Co-mutations involving PIK3CA and other genes were also observed in the cohort, occurring with TOP2A and FOXA1, while being mutually exclusive with GATA3 and BRCA2. PIK3CA mutations were significantly associated with HER2 status and were not significantly correlated with the patient's age, menopausal status, HR status, Ki-67 index, molecular typing, TNM stage or pCR status. Likewise, no significant correlation was found between different PIK3CA mutation status and overall survival. Conclusions: This cohort study shows the overall mutation rate of PIK3CA in breast cancer and the mutation frequencies across different molecular subtypes. The findings reveal a significant correlation between PIK3CA mutations and HER2 status, which provides a new basis for the precise treatment of breast cancer with PIK3CA inhibitors.