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Background Mutational 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. Results In 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. Conclusions MuSiCa 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 .

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/. In most cases, human cells contain two copies of each of their genes, yet sometimes this can change, an effect called copy number alteration (CNA). Cancer is a genetic disease and thus, studying the DNA from tumor samples is crucial to improving diagnosis and choosing the right treatment. Most tumors contain cells with CNAs; however, the impact of CNAs in cancer progression is poorly understood. CNAs can be studied by examining the genome of tumor cells and finding which regions display an unusual number of copies. It may also be possible to gather information about different cancer types by analyzing the CNAs in a tumor, but this approach requires the analysis of large amounts of data. To aid the analysis of CNAs in cancer cells, Franch-Expósito, Bassaganyas et al. have created an online tool called CNApp, which is able to identify and count CNAs in genomic data and link them to features associated with different cancers. The hope is that a better understanding of the effect of CNAs in cancer could help better diagnose cancers, and improve outcomes for patients. Potentially, this could also predict what type of treatment would work better for a specific tumor. Besides, by using a machine-learning approach, the tool can also make predictions about specific cancer subtypes in order to facilitate clinical decisions. Franch-Expósito, Bassaganyas et al. tested CNApp using previously existing cancer data from 33 different cancer types to show how CNApp can help the interpretation of CNAs in cancer. Moreover, CNApp can also use CNAs to identify different types of bowel (colorectal) cancer in a way that could help doctors to make decisions about treatment. Together these findings show that CNApp provides an adaptable and accessible research tool for the study of cancer genomics, which could provide opportunities to inform medical procedures.

Lynch-like syndrome (LLS) is an increasingly common clinical challenge with an underlying molecular basis mostly unknown. To shed light onto it, we focused on a very young LLS early-onset colorectal cancer (CRC) cohort (diagnosis ≤ 40 y.o.), performing germline and tumor whole-exome sequencing (WES) of 15 patients, and additionally analyzing their corresponding tumor mutational burden (TMB) and mutational signatures. We identified four cases (27%) with double somatic putative variants in mismatch repair (MMR) core genes, as well as three additional cases (20%) with double MSH3 somatic alterations in tumors with unexplained MSH2/MSH6 loss of expression, and two cases (13%) with POLD1 potential biallelic alterations. Average TMB was significantly higher for LLS cases with double somatic alterations. Lastly, nine predicted deleterious variants in genes involved in the DNA repair functions and/or previously associated with CRC were found in nine probands, four of which also showed MMR biallelic somatic inactivation. In conclusion, we contribute new insights into LLS CRC, postulating MSH3 and POLD1 double somatic alterations as an underlying cause of a microsatellite instability (MSI) phenotype, proposing intrinsic biological differences between LLS with and without somatic alterations, and suggesting new predisposing candidate genes in this scenario.

Background: A substantial fraction of familial colorectal cancer (CRC) and polyposis heritability remains unexplained. This study aimed to identify predisposing loci in patients with these disorders. Methods: Homozygosity mapping was performed using 222 563 SNPs in 302 index patients with various colorectal neoplasms and 3367 controls. Linkage analysis, exome and whole-genome sequencing were performed in a family affected by microsatellite stable CRCs. Candidate variants were genotyped in 10 554 cases and 21 480 controls. Gene expression was assessed at the mRNA and protein level. Results: Homozygosity mapping revealed a disease-associated region at 1q32.3 which was part of the linkage region 1q32.2–42.2 identified in the CRC family. This includes a region previously associated with risk of CRC. Sequencing identified the p.Asp1432Glu variant in the MIA3 gene (known as TANGO1 or TANGO ) and 472 additional rare, shared variants within the linkage region. In both cases and controls the population frequency was 0.02% for this MIA3 variant. The MIA3 mutant allele showed predominant mRNA expression in normal, cancer and precancerous tissues. Furthermore, immunohistochemistry revealed increased expression of MIA3 in adenomatous tissues. Conclusions: Taken together, our two independent strategies associate genetic variations in chromosome 1q loci and predisposition to familial CRC and polyps, which warrants further investigation.

The serrated polyposis syndrome (SPS) is the most common and yet underdiagnosed colorectal polyposis syndrome. It is characterized by multiple and/or large colonic serrated polyps and a higher associated risk for colorectal cancer (CRC). The main objective of this study was to identify new candidate genes involved in the germline predisposition to SPS/CRC. Thirty-nine SPS patients from 16 families (≥2 patients per family) were recruited without alterations in well-known hereditary CRC genes, and germline and somatic whole-exome sequencing were performed. Germline rare variants with plausible pathogenicity, located in genes involved in cancer development, senescence and epigenetic regulation were selected. Somatic mutational profiling and signature analysis was pursued in one sample per family, when possible. After data filtering, ANXA10, ASXL1, CFTR, DOT1L, HIC1, INO80, KLF3, MCM3AP, MCM8, PDLIM2, POLD1, TP53BP1, WNK2 and WRN were highlighted as the more promising candidate genes for SPS germline predisposition with potentially pathogenic variants shared within families. Somatic analysis characterized mutational profiles in advanced serrated polyps/tumors, revealing a high proportion of hypermutated samples, with a prevalence of clock-like mutational signatures in most samples and the presence of DNA mismatch repair-defective signatures in some cases. In conclusion, we identified new candidate genes to be involved in familial SPS. Further functional studies and replication in additional cohorts are required to confirm the selected candidates.

Colorectal cancer (CRC) is one of the most common cancers worldwide. Lynch Syndrome (LS) is the most common form of hereditary CRC and it is caused by germline defects in the DNA-mismatch repair (MMR) pathway. It is of extreme importance for affected LS patients and their relatives to identify the germline causative alteration to provide intensified surveillance to those at risk and allow early diagnosis and cancer prevention. Current approaches for LS molecular diagnosis typically involve screening of the MMR genes by targeted gene-panel sequencing and rearrangement screening. We report the identification and characterization of a novel germline structural variant encompassing 48.757 kb, involving the 3’-ends of the MLH1 and LRRFIP2 genes, as the cause of LS in a family of Ecuador. Whole-genome sequencing and transcriptomics allowed the identification of the genomic rearrangement and highlights the importance of the use of these additional approaches to achieve a comprehensive molecular diagnosis in some LS patients.

Lynch syndrome is the most common cause of hereditary colorectal cancer (CRC), and it is characterized by DNA mismatch repair (MMR) deficiency. The term Lynch-like syndrome (LLS) is used for patients with MMR-deficient tumors and neither germline mutation in MLH1, MSH2, MSH6, PMS2, or EPCAM nor MLH1 somatic methylation. Biallelic somatic inactivation or cryptic germline MMR variants undetected during genetic testing have been proposed to be involved. Sixteen patients with early-onset LLS CRC were selected for germline and tumor whole-exome sequencing. Two potentially pathogenic germline MCM8 variants were detected in a male patient with LLS with fertility problems. A knockout cellular model for MCM8 was generated by CRISPR/Cas9 and detected genetic variants were produced by mutagenesis. DNA damage, microsatellite instability, and mutational signatures were monitored. DNA damage was evident for MCM8KO cells and the analyzed genetic variants. Microsatellite instability and mutational signatures in MCM8KO cells were compatible with the involvement of MCM8 in MMR. Replication in an independent familial cancer cohort detected additional carriers. Unexplained MMR-deficient CRC cases, even showing somatic biallelic MMR inactivation, may be caused by underlying germline defects in genes different than MMR genes. We suggest MCM8 as a gene involved in CRC germline predisposition with a recessive pattern of inheritance.

Common low-penetrance genetic variants have been consistently associated with colorectal cancer risk. To determine if these genetic variants are associated also with adenoma susceptibility and may improve selection of patients with increased risk for advanced adenomas and/or multiplicity (≥ 3 adenomas). We selected 1,326 patients with increased risk for advanced adenomas and/or multiplicity and 1,252 controls with normal colonoscopy from population-based colorectal cancer screening programs. We conducted a case-control association study analyzing 30 colorectal cancer susceptibility variants in order to investigate the contribution of these variants to the development of subsequent advanced neoplasia and/or multiplicity. We found that 14 of the analyzed genetic variants showed a statistically significant association with advanced adenomas and/or multiplicity: the probability of developing these lesions increased with the number of risk alleles reaching a 2.3-fold risk increment in individuals with ≥ 17 risk alleles. Nearly half of the genetic variants associated with colorectal cancer risk are also related to advanced adenoma and/or multiplicity predisposition. Assessing the number of risk alleles in individuals within colorectal cancer screening programs may help to identify better a subgroup with increased risk for advanced neoplasia and/or multiplicity in the general population.

Non-hereditary colorectal cancer (CRC) is a complex disorder resulting from the combination of genetic and non-genetic factors. Genome-wide association studies (GWAS) are useful for identifying such genetic susceptibility factors. However, the single loci so far associated with CRC only represent a fraction of the genetic risk for CRC development in the general population. Therefore, many other genetic risk variants alone and in combination must still remain to be discovered. The aim of this work was to search for genetic risk factors for CRC, by performing single-locus and two-locus GWAS in the Spanish population. A total of 801 controls and 500 CRC cases were included in the discovery GWAS dataset. 77 single nucleotide polymorphisms (SNP)s from single-locus and 243 SNPs from two-locus association analyses were selected for replication in 423 additional CRC cases and 1382 controls. In the meta-analysis, one SNP, rs3987 at 4q26, reached GWAS significant p-value (p = 4.02×10(-8)), and one SNP pair, rs1100508 CG and rs8111948 AA, showed a trend for two-locus association (p = 4.35×10(-11)). Additionally, our GWAS confirmed the previously reported association with CRC of five SNPs located at 3q36.2 (rs10936599), 8q24 (rs10505477), 8q24.21(rs6983267), 11q13.4 (rs3824999) and 14q22.2 (rs4444235). Our GWAS for CRC patients from Spain confirmed some previously reported associations for CRC and yielded a novel candidate risk SNP, located at 4q26. Epistasis analyses also yielded several novel candidate susceptibility pairs that need to be validated in independent analyses.