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Contains fulltext : 251996.pdf (Publisher’s version ) (Open Access) We report an autosomal recessive, multi-organ tumor predisposition syndrome, caused by bi-allelic loss-of-function germline variants in the base excision repair (BER) gene MBD4. We identified five individuals with bi-allelic MBD4 variants within four families and these individuals had a personal and/or family history of adenomatous colorectal polyposis, acute myeloid leukemia, and uveal melanoma. MBD4 encodes a glycosylase involved in repair of G:T mismatches resulting from deamination of 5'-methylcytosine. The colorectal adenomas from MBD4-deficient individuals showed a mutator phenotype attributable to mutational signature SBS1, consistent with the function of MBD4. MBD4-deficient polyps harbored somatic mutations in similar driver genes to sporadic colorectal tumors, although AMER1 mutations were more common and KRAS mutations less frequent. Our findings expand the role of BER deficiencies in tumor predisposition. Inclusion of MBD4 in genetic testing for polyposis and multi-tumor phenotypes is warranted to improve disease management.

To characterise the somatic alterations in colorectal cancer (CRC), we conducted whole-genome sequencing analysis of 2,023 tumours. We provide the most detailed high-resolution map to date of somatic mutations in CRC, and demonstrate associations with clinicopathological features, in particular location in the large bowel. We refined the mutational processes and signatures acting in colorectal tumorigenesis. In analyses across the sample set or restricted to molecular subtypes, we identified 185 CRC driver genes, of which 117 were previously unreported. New drivers acted in various molecular pathways, including Wnt (CTNND1, AXIN1, TCF3), TGF-β/BMP (TGFBR1) and MAP kinase (RASGRF1, RASA1, RAF1, and several MAP2K and MAP3K loci). Non-coding drivers included intronic neo-splice site alterations in APC and SMAD4. Whilst there was evidence of an excess of mutations in functionally active regions of the non-coding genome, no specific drivers were called with high confidence. Novel recurrent copy number changes included deletions of PIK3R1 and PWRN1, as well as amplification of CCND3 and NEDD9. Putative driver structural variants included BRD4 and SOX9 regulatory elements, and ACVR2A and ANKRD11 hotspot deletions. The frequencies of many driver mutations, including somatic Wnt and Ras pathway variants, showed a gradient along the colorectum. The Pks-pathogenic E. coli signature and TP53 mutations were primarily associated with rectal cancer. A set of unreported immune escape driver genes was found, primarily in hypermutated CRCs, most of which showed evidence of genetic evasion of the anti-cancer immune response. About 25% of cancers had a potentially actionable mutation for a known therapy. Thirty-three of the new driver genes were predicted to be essential, 17 possessed a druggable structure, and nine had a bioactive compound available. Our findings provide further insight into the genetics and biology of CRC, especially tumour subtypes defined by genomic instability or clinicopathological features.

Recurrence of somatic mutations at the exact same position across patients (hotspots) are often identified as potential cancer drivers, assuming that they are unlikely to be generated by neutral mutagenesis. Recent studies have challenged this by identifying examples of mutational processes that generate passenger hotspots. However, no comprehensive study to identify and quantify the determinants of hotspots formation across tumours has been carried out to date. In this work, we conducted a systematic analysis of passenger hotspot events across more than 7,500 whole genome sequences from different malignancies. We found that mutational signatures 1 (SBS1) and 17 (SBS17a and SBS17b) have the highest propensity to form hotspots, generating 5-80 times more than other common somatic mutational processes. The trinucleotide mutational probabilities and genomic sequence composition partially explain the high SBS1 hotspot propensity. Strikingly, the vast majority of hotspots (46-96%) contributed by different signatures remain unexplained after correcting for their sequence context preferences and the large-scale mutation rate variability. This finding reveals the extension of our lack of knowledge about how mutations occur, and highlights the need of identifying and subsequently modelling additional sequence and chromatin features that influence mutation rate at base resolution. This is key to accurately modelling the mutation rate under neutrality, an essential step for identifying cancer drivers, and –given the known activity of SBS1 across other organisms and in germ cells– also for reconstructing evolutionary histories and studying genome evolution.

The glycolytic modulator TP53-Inducible Glycolysis and Apoptosis Regulator (TIGAR) is overexpressed in several types of cancer and has a role in metabolic rewiring during tumor development. However, little is known about the role of this enzyme in proliferative tissues under physiological conditions. In the current work, we analysed the role of TIGAR in primary human lymphocytes stimulated with the mitotic agent Concanavalin A (ConA). We found that TIGAR expression was induced in stimulated lymphocytes through the PI3K/AKT pathway, since Akti-1/2 and LY294002 inhibitors prevented the upregulation of TIGAR in response to ConA. In addition, suppression of TIGAR expression by siRNA decreased the levels of the proliferative marker PCNA and increased cellular ROS levels. In this model, TIGAR was found to support the activity of glucose 6-phosphate dehydrogenase (G6PDH), the first enzyme of the pentose phosphate pathway (PPP), since the inhibition of TIGAR reduced G6PDH activity and increased autophagy. In conclusion, we demonstrate here that TIGAR is upregulated in stimulated human lymphocytes through the PI3K/AKT signaling pathway, which contributes to the redirection of the carbon flux to the PPP.

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer.

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer.

Neoantigens are now recognized drivers of the antitumor immune response. Recurrent neoantigens, shared among groups of patients, have thus become increasingly coveted therapeutic targets. Here, we report on the data-driven identification of a robustly presented, immunogenic neoantigen that is derived from the combination of HLA-A*01:01 and RAS.Q61K. Analysis of large patient cohorts indicated that this combination applies to 3% of patients with melanoma. Using HLA peptidomics, we were able to demonstrate robust endogenous presentation of the neoantigen in 10 tumor samples. We detected specific reactivity to the mutated peptide within tumor-infiltrating lymphocytes (TILs) from 2 unrelated patients, thus confirming its natural immunogenicity. We further investigated the neoantigen-specific clones and their T cell receptors (TCRs) via a combination of TCR sequencing, TCR overexpression, functional assays, and single-cell transcriptomics. Our analysis revealed a diverse repertoire of neoantigen-specific clones with both intra- and interpatient TCR similarities. Moreover, 1 dominant clone proved to cross-react with the highly prevalent RAS.Q61R variant. Transcriptome analysis revealed a high association of TCR clones with specific T cell phenotypes in response to cognate melanoma, with neoantigen-specific cells showing an activated and dysfunctional phenotype. Identification of recurrent neoantigens and their reactive TCRs can promote "off-the-shelf" precision immunotherapies, alleviating limitations of personalized treatments.

Motivation: Identification of the genomic alterations driving tumorigenesis is one of the main goals in oncogenomics research. Given the evolutionary principles of cancer development, computational methods that detect signals of positive selection in the pattern of tumor mutations have been effectively applied in the search for cancer genes. One of these signals is the abnormal clustering of mutations, which has been shown to be complementary to other signals in the detection of driver genes. Results: We have developed OncodriveCLUSTL, a new sequence-based clustering algorithm to detect significant clustering signals across genomic regions. OncodriveCLUSTL is based on a local background model derived from the simulation of mutations accounting for the composition of tri- or penta-nucleotide context substitutions observed in the cohort under study. Our method can identify known clusters and bona-fide cancer drivers across cohorts of tumor whole-exomes, outperforming the existing OncodriveCLUST algorithm and complementing other methods based on different signals of positive selection. Our results indicate that OncodriveCLUSTL can be applied to the analysis of non-coding genomic elements and non-human mutations data. Availability and implementation: OncodriveCLUSTL is available as an installable Python 3.5 package. The source code and running examples are freely available at https://bitbucket.org/bbglab/oncodriveclustl under GNU Affero General Public License. Supplementary information: Supplementary data are available at Bioinformatics online. This work was supported by funding from the Spanish Ministry of Economy and Competitiveness [SAF2015-66084-R, MINECO/FEDER, UE] and by the European Research Council [Consolidator Grant 68239]. IRB Barcelona is the recipient of a Severo Ochoa Centre of Excellence Award from the Spanish Ministry of Economy and Competitiveness (MINECO; Government of Spain) and is supported by CERCA (Generalitat de Catalunya). A.G.-P. is supported by a Ramón y Cajal contract from the Spanish Ministry of Economy and Competitiveness [RYC-2013-1455]. C.A.-P. is supported by “la Caixa” Foundation (ID 100010434) with code [LCF/BQ/ES18/11670011].