Gene Mutations Associated With Clinical Characteristics in the Tumors of Patients With Breast Cancer - Hao, Chunfang; Wang, Chen; Lu, Ning; Zhao, Weipeng; Li, Shufen; Zhang, Li; Meng, Wenjing; Wang, Shuling; Tong, Zhongsheng; Zeng, Yanwu; Lu, Leilei (Frontiers in Oncology, 2022)
Background: Clinical characters including ER, PR, and HER2 were important biomarkers in the treatment of breast cancer. But how genomic mutations affect their status was rarely studied. This study aimed to find out genomic mutations associated with these clinical characteristics. Methods: There were 160 breast cancer patients enrolled in this study. Samples from those patients were applied to next-generate sequencing targeting a panel of 624 pan-cancer genes. Short nucleotide mutations, copy number variations, and gene fusions were identified for each sample. Fisher’s exact test compared each pair of genes. A similarity score was constructed with the resulting P-values. Genes were clustered with the similarity scores. The identified gene clusters were compared to clinical character status including ER, PR, HER2, and a family history of cancer about the mutations in patients. Results: Gene-by-gene analysis found that CCND1 mutations were positively correlated with ER status while ERBB2 and CDK12 mutations were positively correlated with HER2 status. Mutation-based clustering identified four gene clusters. Gene cluster 1 (ADGRA2, ZNF703, FGFR1, KAT6A, and POLB) was significantly associated with PR status; gene cluster 2 (COL1A1, AXIN2, ZNF217, GNAS, and BRIP1) and gene cluster 3 (FGF3, FGF4, FGF19, and CCND1) were significantly associated with ER status; gene cluster 2 was also negatively associated with a family history of cancer; gene cluster 4 was significantly negatively associated with age. Patients were labeled into four corresponding groups. Patient groups 1, 2, 3, 4 had 24.1%, 36.5%, 38.7%, and 41.3% of patients with an FDA-recognized biomarker predictive of response to an FDA-approved drug, respectively. Conclusion: This study had identified genomic mutations positively associated with ER and PR status. These findings not only revealed candidate genes in ER and PR status maintenance but also provided potential treatment targets for the patients with endocrine therapy resistance.