Assessing concordance among human, in silico predictions and functional assays on genetic variant classification.

MOTIVATION: A variety of in silico tools have been developed and frequently used to aid high-throughput rapid variant classification, but their performances vary, and their ability to classify variants of uncertain significance were not systemically assessed previously due to lack of validation data. This has been changed recently by advances of functional assays, where functional impact of genetic changes can be measured in single-nucleotide resolution using saturation genome editing (SGE) assay. RESULTS: We demonstrated the neural network model AIVAR (Artificial Intelligent VARiant classifier) was highly comparable to human experts on multiple verified datasets. Although highly accurate on known variants, AIVAR together with CADD and PhyloP showed non-significant concordance with SGE function scores. Moreover, our results indicated that neural network model trained from functional assay data may not produce accurate prediction on known variants. AVAILABILITY AND IMPLEMENTATION: All source code of AIVAR is deposited and freely available at https://github.com/TopGene/AIvar. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Germline TP53 and MSH6 mutations implicated in sporadic triple-negative breast cancer (TNBC): a preliminary study.

BACKGROUND: Germline BRCA1/2 prevalence is relatively low in sporadic triple-negative breast cancer (TNBC). We hypothesized that non-BRCA genes may also have significant germline contribution to Chinese sporadic TNBC, and the somatic mutational landscape of TNBC may vary between ethnic groups. We therefore conducted this study to investigate germline and somatic mutations in 43 cancer susceptibility genes in Chinese sporadic TNBC. PATIENTS AND METHODS: Sixty-six Chinese sporadic TNBC patients were enrolled in this study. Germline and tumor DNA of each patient were subjected to capture-based next-generation sequencing using a 43-gene panel. Standard bioinformatic analysis and variant classification were performed to identify deleterious/likely deleterious germline mutations and somatic mutations. Mutational analysis was conducted to identify significantly mutated genes. RESULTS: Deleterious/likely deleterious germline mutations were identified in 27 (27/66, 40.9%) patients. Among the 27 patients, 9 (9/66, 13.6%) were TP53 carriers, 5 (5/66, 7.6%) were MSH6 carriers, and 5 (5/66, 7.6%) were BRCA1 carriers. Somatic mutations were identified in 64 (64/66, 97.0%) patients. TP53 somatic mutations occurred in most of the patients (45/66, 68.2%) and with highest mean allele frequency (28.1%), while NF1 and POLE were detected to have the highest mutation counts. CONCLUSIONS: Our results supported our hypotheses and suggested great potentials of TP53 and MSH6 as novel candidates for TNBC predisposition genes. The high frequency of somatic NF1 and POLE mutations in this study showed possibilities for clinical benefits from androgen-blockade therapies and immunotherapies in Chinese TNBC patients. Our study indicated necessity of multi-gene testing for TNBC prevention and treatment.