Influence of BRCA1 Germline Mutations in the Somatic Mutational Burden of Triple-Negative Breast Cancer.

The majority of the hereditary triple-negative breast cancers (TNBCs) are associated with BRCA1 germline mutations. Nevertheless, the understanding of the role of BRCA1 deficiency in the TNBC tumorigenesis is poor. In this sense, we performed whole-exome sequencing of triplet samples (leucocyte, tumor, and normal-adjacent breast tissue) for 10 cases of early-onset TNBC, including 5 hereditary (with BRCA1 germline pathogenic mutation) and 5 sporadic (with no BRCA1 or BRCA2 germline pathogenic mutations), for assessing the somatic mutation repertoire. Protein-affecting somatic mutations were identified for both mammary tissues, and Ingenuity Pathway Analysis was used to investigate gene interactions. BRCA1 and RAD51C somatic promoter methylation in tumor samples was also investigated by bisulfite sequencing. Sporadic tumors had higher proportion of driver mutations (≥25% allele frequency) than BRCA1 hereditary tumors, whereas no difference was detected in the normal breast samples. Distinct gene networks were obtained from the driver genes in each group. The Cancer Genome Atlas data analysis of TNBC classified as hereditary and sporadic reinforced our findings. The data presented here indicate that in the absence of BRCA1 germline mutations, a higher number of driver mutations are required for tumor development and that different defective processes are operating in the tumorigenesis of hereditary and sporadic TNBC in young women.

SurfaceomeDB: a cancer-orientated database for genes encoding cell surface proteins.

Cell surface proteins (CSPs) are excellent targets for the development of diagnostic and therapeutic reagents, and it is estimated that 10-20% of all genes in the human genome encode CSPs. In an effort to integrate all data publicly available for genes encoding cell surface proteins, a database (SurfaceomeDB) was developed. SurfaceomeDB is a gene-centered portal containing different types of information, including annotation for gene expression, protein domains, somatic mutations in cancer, and protein-protein interactions for all human genes encoding CSPs. SurfaceomeDB was implemented as an integrative and relational database in a user-friendly web interface, where users can search for gene name, gene annotation, or keywords. There is also a streamlined graphical representation of all data provided and links to the most important data repositories and databases, such as NCBI, UCSC Genome Browser, and EBI.