Abstract
Background Currently, immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in BC are not fully understood. Methods Comprehensive bioinformatic analyses were performed using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Survival curves were analyzed via Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were used for prognosis analysis. Gene set enrichment analysis (GSEA) was performed to explore regulatory mechanisms and functions. The CIBERSORT algorithm was used to calculate the tumor-infiltrating immune cell fractions. Results We analyzed somatic mutation data of BC from TCGA and ICGC datasets and found that 19 frequently mutated genes were reported in both cohorts, namely, SPTA1, TTN, MUC17, MAP3K1, CDH1, FAT3, SYNE1, FLG, HMCN1, RYR2 (ryanodine receptor 2), GATA3, MUC4, PIK3CA, KMT2C, TP53, PTEN, ZFHX4, MUC16, and USH2A. Among them, we observed that RYR2 mutation was significantly associated with higher TMB and better clinical prognosis. Moreover, GSEA revealed that RYR2 mutation-enriched signaling pathways were related to immune-associated pathways. Furthermore, based on the CIBERSORT algorithm, we found that RYR2 mutation enhanced the antitumor immune response by enriching CD8+ T cells, activated memory CD4+ T cells, and M1 macrophages. Conclusion RYR2 is frequently mutated in BC, and its mutation is related to increased TMB and promotes antitumor immunity; thus, RYR2 may serve as a valuable biomarker to predict the immune response.
Highlights
Breast cancer (BC) is the most common malignancy in women worldwide, with approximately 2.1 million new cases in 2018 [1]
The top 30 frequently mutated genes with high mutation frequency and the pattern of somatic mutation for the top 30 genes are illustrated in Figure 1(b), among which the five most frequently mutated genes were TP53 (35.6%), PIK3CA (29.9%), TTN (18.9%), GATA3 (8.1%), and MAP3K1 (7.5%)
Our results demonstrated that 19 frequently mutated genes reported in The Cancer Genome Atlas (TCGA) cohort were reported in the International Cancer Genome Consortium (ICGC) cohort, namely, SPTA1, TTN, MUC17, MAP3K1, CDH1, FAT3, SYNE1, FLG, HMCN1, RYR2, GATA3, MUC4, PIK3CA, KMT2C, TP53, PTEN, ZFHX4, MUC16, and USH2A (Figure 2(a))
Summary
Breast cancer (BC) is the most common malignancy in women worldwide, with approximately 2.1 million new cases in 2018 [1]. Immune checkpoint inhibition targeting programmed cell death receptor 1 (PD-1) and its ligand PD-L1 has been applied to a variety of solid tumors and significantly improved the overall survival (OS) of patients [4]. In terms of overall efficacy, BC patients do not benefit as much from immunotherapy as patients with other solid tumors, such as non-small-cell lung cancer and melanoma [6]. Immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. Specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in BC are not fully understood. Based on the CIBERSORT algorithm, we found that RYR2 mutation enhanced the antitumor immune response by enriching CD8+ T cells, activated memory CD4+ T cells, and M1 macrophages. RYR2 is frequently mutated in BC, and its mutation is related to increased TMB and promotes antitumor immunity; RYR2 may serve as a valuable biomarker to predict the immune response
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