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posted on 14.04.2022, 04:05 authored by Chunfang Hao, Chen Wang, Ning Lu, Weipeng Zhao, Shufen Li, Li Zhang, Wenjing Meng, Shuling Wang, Zhongsheng Tong, Yanwu Zeng, Leilei Lu

Clinical characteristics including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 (HER2) are important biomarkers in the treatment of breast cancer, but how genomic mutations affect their status is rarely studied. This study aimed at finding genomic mutations associated with these clinical characteristics.


There were 160 patients with breast cancer enrolled in this study. Samples from those patients were used for next-generation 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 the status of clinical characteristics including ER, PR, HER2, and a family history of cancer (FH) in terms of the mutations in patients.


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; and gene cluster 4 was significantly negatively associated with age. Patients were classified into four corresponding groups. Patient groups 1, 2, 3, and 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.


This study 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 patients with endocrine therapy resistance.