BackgroundMutational signatures have been proved as a valuable pattern in somatic genomics, mainly regarding cancer, with a potential application as a biomarker in clinical practice. Up to now, several bioinformatic packages to address this topic have been developed in different languages/platforms. MutationalPatterns has arisen as the most efficient tool for the comparison with the signatures currently reported in the Catalogue of Somatic Mutations in Cancer (COSMIC) database. However, the analysis of mutational signatures is nowadays restricted to a small community of bioinformatic experts.ResultsIn this work we present Mutational Signatures in Cancer (MuSiCa), a new web tool based on MutationalPatterns and built using the Shiny framework in R language. By means of a simple interface suited to non-specialized researchers, it provides a comprehensive analysis of the somatic mutational status of the supplied cancer samples. It permits characterizing the profile and burden of mutations, as well as quantifying COSMIC-reported mutational signatures. It also allows classifying samples according to the above signature contributions.ConclusionsMuSiCa is a helpful web application to characterize mutational signatures in cancer samples. It is accessible online at http://bioinfo.ciberehd.org/GPtoCRC/en/tools.html and source code is freely available at https://github.com/marcos-diazg/musica.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2234-y) contains supplementary material, which is available to authorized users.

Purpose:Colorectal cancer is an important cause of mortality in the developed world. Hereditary forms are due to germ-line mutations in APC, MUTYH, and the mismatch repair genes, but many cases present familial aggregation but an unknown inherited cause. The hypothesis of rare high-penetrance mutations in new genes is a likely explanation for the underlying predisposition in some of these familial cases.Methods:Exome sequencing was performed in 43 patients with colorectal cancer from 29 families with strong disease aggregation without mutations in known hereditary colorectal cancer genes. Data analysis selected only very rare variants (0–0.1%), producing a putative loss of function and located in genes with a role compatible with cancer. Variants in genes previously involved in hereditary colorectal cancer or nearby previous colorectal cancer genome-wide association study hits were also chosen.Results:Twenty-eight final candidate variants were selected and validated by Sanger sequencing. Correct family segregation and somatic studies were used to categorize the most interesting variants in CDKN1B, XRCC4, EPHX1, NFKBIZ, SMARCA4, and BARD1.Conclusion:We identified new potential colorectal cancer predisposition variants in genes that have a role in cancer predisposition and are involved in DNA repair and the cell cycle, which supports their putative involvement in germ-line predisposition to this neoplasm.

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Stably acquired mutations in hematopoietic cells represent substrates of selection that may lead to clonal hematopoiesis (CH), a common state in cancer patients that is associated with a heightened risk of leukemia development. Owing to technical and sample size limitations, most CH studies have characterized gene mutations or mosaic chromosomal alterations (mCAs) individually. Here we leverage peripheral blood sequencing data from 32,442 cancer patients to jointly characterize gene mutations (n = 14,789) and mCAs (n = 383) in CH. Recurrent composite genotypes resembling known genetic interactions in leukemia genomes underlie 23% of all detected autosomal alterations, indicating that these selection mechanisms are operative early in clonal evolution. CH with composite genotypes defines a patient group at high risk of leukemia progression (3-year cumulative incidence 14.6%, CI: 7–22%). Multivariable analysis identifies mCA as an independent risk factor for leukemia development (HR = 14, 95% CI: 6–33, P < 0.001). Our results suggest that mCA should be considered in conjunction with gene mutations in the surveillance of patients at risk of hematologic neoplasms.

Somatic copy number alterations (CNAs) are a hallmark of cancer, but their role in tumorigenesis and clinical relevance remain largely unclear. Here, we developed CNApp, a web-based tool that allows a comprehensive exploration of CNAs by using purity-corrected segmented data from multiple genomic platforms. CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to the TCGA pan-cancer dataset of 10,635 genomes showing that CNAs classify cancer types according to their tissue-of-origin, and that each cancer type shows specific ranges of broad and focal CNA scores. Moreover, CNApp reproduces recurrent CNAs in hepatocellular carcinoma and predicts colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and discrete genomic imbalances. In summary, CNApp facilitates CNA-driven research by providing a unique framework to identify relevant clinical implications. CNApp is hosted at https://tools.idibaps.org/CNApp/.

Colorectal cancer (CRC) is one of the most common neoplasms in the world. Fanconi anemia (FA) is a very rare genetic disease causing bone marrow failure, congenital growth abnormalities and cancer predisposition. The comprehensive FA DNA damage repair pathway requires the collaboration of 53 proteins and it is necessary to restore genome integrity by efficiently repairing damaged DNA. A link between FA genes in breast and ovarian cancer germline predisposition has been previously suggested. We selected 74 CRC patients from 40 unrelated Spanish families with strong CRC aggregation compatible with an autosomal dominant pattern of inheritance and without mutations in known hereditary CRC genes and performed germline DNA whole-exome sequencing with the aim of finding new candidate germline predisposition variants. After sequencing and data analysis, variant prioritization selected only those very rare alterations, producing a putative loss of function and located in genes with a role compatible with cancer. We detected an enrichment for variants in FA DNA damage repair pathway genes in our familial CRC cohort as 6 families carried heterozygous, rare, potentially pathogenic variants located in BRCA2/FANCD1, BRIP1/FANCJ, FANCC, FANCE and REV3L/POLZ. In conclusion, the FA DNA damage repair pathway may play an important role in the inherited predisposition to CRC.

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Background and Aims: Chromosomal instability is a hallmark of cancer that results in broad and focal copy number alterations (CNAs), two events associated with distinct molecular, immunological and clinical features. In hepatocellular carcinoma (HCC) the CNAs role has not been thoroughly assessed. Thus, we dissected the impact of CNA burdens on HCC molecular and immune features. Methods: We analyzed SNP-array data from 452 paired tumor/adjacent resected HCCs and 25 dysplastic nodules. For each sample, broad and focal CNA burdens were quantified using CNApp, and the resulting broad scores (BS) and focal scores (FS) were correlated with transcriptomic, mutational and methylation profiles, tumor immune composition, and with clinico-pathological data. Results: HCCs with low broad CNA burdens (defined as BS≤4; 17%) presented high inflammation, active infiltrate signalling, high cytolytic activity, and enrichment of the 'HCC-Immune-Class' and gene signatures related to antigen presentation. Conversely, tumors with chromosomal instability (high broad CNA loads, BS≥11; 40%), displayed immune excluded traits and were linked to proliferation, TP53 dysfunction, and DNA repair. Candidate determinants of the low cytotoxicity and immune exclusion features of high-BS tumors included alterations in antigen presenting machinery (i.e. HLA), widespread hypomethylation and decreased rates of observed/expected neoantigenic mutations. High focal scores were independent of tumor immune features, but were related to proliferation, TP53 dysfunction and progenitor cell traits. Research.