All cancers are caused by somatic mutations. However, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here, we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, kataegis, is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer with potential implications for understanding of cancer etiology, prevention and therapy.

Chronic lymphocytic leukaemia (CLL) is a frequent disease in which the genetic alterations determining the clinicobiological behaviour are not fully understood. Here we describe a comprehensive evaluation of the genomic landscape of 452 CLL cases and 54 patients with monoclonal B-lymphocytosis, a precursor disorder. We extend the number of CLL driver alterations, including changes in ZNF292, ZMYM3, ARID1A and PTPN11. We also identify novel recurrent mutations in non-coding regions, including the 3' region of NOTCH1, which cause aberrant splicing events, increase NOTCH1 activity and result in a more aggressive disease. In addition, mutations in an enhancer located on chromosome 9p13 result in reduced expression of the B-cell-specific transcription factor PAX5. The accumulative number of driver alterations (0 to ≥4) discriminated between patients with differences in clinical behaviour. This study provides an integrated portrait of the CLL genomic landscape, identifies new recurrent driver mutations of the disease, and suggests clinical interventions that may improve the management of this neoplasia.

Mantle cell lymphoma (MCL) is an aggressive tumor, but a subset of patients may follow an indolent clinical course. To understand the mechanisms underlying this biological heterogeneity, we performed whole-genome and/or whole-exome sequencing on 29 MCL cases and their respective matched normal DNA, as well as 6 MCL cell lines. Recurrently mutated genes were investigated by targeted sequencing in an independent cohort of 172 MCL patients. We identified 25 significantly mutated genes, including known drivers such as ataxia-telangectasia mutated (ATM), cyclin D1 (CCND1), and the tumor suppressor TP53; mutated genes encoding the anti-apoptotic protein BIRC3 and Toll-like receptor 2 (TLR2); and the chromatin modifiers WHSC1, MLL2, and MEF2B. We also found NOTCH2 mutations as an alternative phenomenon to NOTCH1 mutations in aggressive tumors with a dismal prognosis. Analysis of two simultaneous or subsequent MCL samples by whole-genome/whole-exome (n = 8) or targeted (n = 19) sequencing revealed subclonal heterogeneity at diagnosis in samples from different topographic sites and modulation of the initial mutational profile at the progression of the disease. Some mutations were predominantly clonal or subclonal, indicating an early or late event in tumor evolution, respectively. Our study identifies molecular mechanisms contributing to MCL pathogenesis and offers potential targets for therapeutic intervention.next-generation sequencing | cancer genetics | cancer heterogeneity M antle cell lymphoma (MCL) is a mature B-cell neoplasm characterized by the t(11;14)(q13;q32) translocation leading to the overexpression of cyclin D1 (1). CCND1 is a weak oncogene that requires the cooperation of other oncogenic events to transform lymphoid cells (2). Molecular studies have identified alterations in components of the cell-cycle regulation, DNA damage response, and cell survival pathways (3, 4), but the profile of mutated genes contributing to the pathogenesis of MCL and cooperating with CCND1 is not well defined (1). Most MCL cases have a rapid evolution and an aggressive behavior with an unfavorable outcome with current therapies (5). Paradoxically, a subset of patients follows an indolent clinical evolution with stable disease even in the absence of chemotherapy (6, 7). This favorable behavior has been associated with IGHV-mutated (8, 9) and lack of expression of SOX11 (10, 11), a transcription factor highly specific of MCL that contributes to the aggressive behavior of this tumor (12). However, the molecular mechanisms responsible for this clinical heterogeneity are not well understood.To gain insight into the molecular pathogenesis of MCL we performed whole-genome sequencing (WGS) and whole-exome sequencing (WES) of 29 MCL and further investigated mutated genes in an expanded series of patients. We also analyzed the subclonal heterogeneity of the tumors and their modulation during the evolution of the disease. Results Landscape of Mutations in MCL.We performed WGS and WES of 4 and 29 MCL, respectively. These patients were re...

22 secondary bile acids as a possible mechanism for the beneficial effects of reestablishing 51 a healthy microbiome. Our results demonstrate that correction of the accelerated aging-52 associated intestinal dysbiosis is beneficial, suggesting the existence of a link between 53 aging and the gut microbiota that provides a rationale for microbiome-based interventions 54 against age-related diseases. 55 56 57

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.