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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Second head and neck neuroendocrine carcinoma (NEC) after radical radiotherapy for nasopharyngeal carcinoma (NPC) treatment is rarely reported. The prognosis of second cancer is poor, and our research focuses on finding a breakthrough in the treatment. In this study, we aimed to investigate clinicopathological characteristics and to identify the genomic landscape of second head and neck NECs.Methods: We collected five second head and neck NEC cases in the recent three years from our patient database. Clinicopathological data and images were obtained. Genomic analysis was performed using high-throughput second generation sequencing. KEGG pathway enrichment analyses between high-frequency mutations were performed using the STRING database.Results: All patients had been diagnosed with second NEC, according to the pathological observations. The interval between diagnosis of NPC and NEC ranged from 10 to 18 years. Two patients had brain or liver metastasis at three and nine months, respectively, after the diagnosis of NEC. Three patients died of the disease with the overall survival time ranging from three to nine months. Commonly altered genes (50%) in second head and neck NECs included TP53, RB1, NOTCH2, PTEN, POLG, KMT2C, U2AF1, EPPK1, ELAC2, DAXX, COL22A1, and ABL1. Those genetic lesions might affect p53 signaling, MAPK signaling, PI3K-Akt signaling, sphingolipid signaling, and neurotrophin signaling pathways.Conclusions: Second head and neck NECs had poor prognosis. We revealed, for the first time, the mutational landscape, high-frequency somatic mutations, and potential signaling pathways of second head and neck NECs. Its optimal treatment model needs to be further studied in future clinical trials. [ABSTRACT FROM AUTHOR]