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The availability of drugs that are effective in cancer patients with specific somatic mutations is rapidly evolving. Finding the most recent information is not straightforward; clinical progress and drug approvals are recorded in clinical trial repositories, files from drug regulatory agencies, publications and conference abstracts. Often there is a delay between trials reaching their outcomes, publication and deposition of results in clinical trial databases. COSMIC Actionability is a new addition to COSMIC’s (Catalogue Of Somatic Mutations In Cancer) portfolio of navigational databases for precision oncology. It indicates the availability of drugs that target mutations and tracks the progress of novel drugs through clinical development. All stages of drug development are represented, through safety and clinical efficacy to market approval, with additional data from case studies expanding mutation coverage. For each mutation-cancer type combination, a simple tiered system indicates whether marketed drugs are available and if not, indicates the progress of drug development efforts. Trial records available in databases such as Clinical Trials.gov and EudraCT are supplemented with trials identified in publications. Trial progression and outcomes are recorded; details are sourced from clinical trial databases, publications, conference abstracts, corporate announcements and regulatory authorities such as the FDA. Curation identifies results for approximately 40% more trials than are available in clinical trial databases alone. Like other COSMIC resources, Actionability is manually curated by Ph.D. level experts. The current version of COSMIC Actionability (October 2021) has 49 fully curated genes with a further 237 having some clinical information. Details of 6244 drug-cancer type combinations are available, of which 2224 have clinical results. 963 drugs are represented, in 2224 treatment combinations. 149 point mutations and 520 further mutations or fusions are represented. This dataset will be made freely available in 2022 then released quarterly, with extended gene coverage and updates of previous content. Citation Format: Steven C. Jupe, Nidhi Bindal, Zbyslaw Sondka, Shicai Wang, Sumodh Nair, Laura Ponting, Doron Sondheimer, Charlie Hathaway, Simon A. Forbes. COSMIC Actionability: Supporting precision oncology through Identification of actionable mutations from clinical trials databases and publications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4093.

Somatic mutations accumulate in cells throughout their life. Most of them do not bring any negative effect. However, certain mutations change protein behaviour, structure, or level of expression. More importantly, some mutations are known to initiate and drive oncogenic transformation. These mutations often make good therapeutic targets but recognising this small subset in a cancer sample is a major challenge. The average cancer cell carries a life-long baggage of somatic mutations, and the mutational process is sped up in these cells through genomic instability (one of the hallmarks of cancer). As a result, there are hundreds of thousands of variants of unknown significance identified through sequencing of cancer DNA. COSMIC Cancer Mutation Census (CMC) answers this challenge by identifying coding mutations with a potential to drive cancer. This is achieved by combining manually curated information regarding cancer genes and genetic variants with data on variant frequencies in cancer and non-cancer populations, and algorithmic evaluation of variant significance. It applies a simple and transparent set of rules to the whole set of coding mutations in COSMIC to identify variants with the highest potential of clinical relevance. In current version (v95, November 2021) the CMC describes 4.7 million somatic variants and segregates them into four tiers. Tier 1 is the highest confidence set. This set includes 1558 mutations that are found in Cancer Gene Census genes and are also described as pathogenic in cancer by ClinVar. Tiers 2 and 3 contain variants with less extensive evidence of involvement in carcinogenesis. The dN/dS algorithm is used to include variants that are under positive selection in cancer cells. Finally, mutations without evidence for driving cancer are classified as Tier 4. In addition to this classification, CMC integrates and presents the information used to prioritise variants, including their frequencies in various cancer types (COSMIC), germline frequencies (gnomAD), ClinVar annotations, dN/dS analysis results, and nucleotide and amino acid conservation. Data can be accessed and scrutinised through a dedicated website at https://cancer.sanger.ac.uk/cmc. Citation Format: Zbyslaw Sondka, Bhavana Harsha, Helder Pedro, Nidhi Bindal Dhir, Charlie Hathaway, Sumodh Nair, Doron Sondheimer, Simon A. Forbes. COSMIC cancer mutation census: Classifying somatic coding variants by their potential to drive cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1200.

COSMIC, the Catalogue Of Somatic Mutations In Cancer (https://cancer.sanger.ac.uk) is the most detailed and comprehensive resource for exploring the effect of somatic mutations in human cancer. The latest release, COSMIC v86 (August 2018), includes almost 6 million coding mutations across 1.4 million tumour samples, curated from over 26 000 publications. In addition to coding mutations, COSMIC covers all the genetic mechanisms by which somatic mutations promote cancer, including non-coding mutations, gene fusions, copy-number variants and drug-resistance mutations. COSMIC is primarily hand-curated, ensuring quality, accuracy and descriptive data capture. Building on our manual curation processes, we are introducing new initiatives that allow us to prioritize key genes and diseases, and to react more quickly and comprehensively to new findings in the literature. Alongside improvements to the public website and data-download systems, new functionality in COSMIC-3D allows exploration of mutations within three-dimensional protein structures, their protein structural and functional impacts, and implications for druggability. In parallel with COSMIC’s deep and broad variant coverage, the Cancer Gene Census (CGC) describes a curated catalogue of genes driving every form of human cancer. Currently describing 719 genes, the CGC has recently introduced functional descriptions of how each gene drives disease, summarized into the 10 cancer Hallmarks.

COSMIC, the catalog of somatic mutations in cancer (https://cancer.sanger.ac.uk/) is the leading and most comprehensive global genetic resource for the exploration of somatic variation across all forms of human cancer. Since the initial inception of COSMIC 15 years ago, cancer genetics have seen substantial changes. Maintaining interoperability between COSMIC and various bioinformatics resources across the globe is a non-trivial task. Resources update at different intervals and as information is interdependent is difficult to keep synchronized. Standardization and adherence to FAIR principles have fueled the development of COSMIC DIAS (Data Integration and Annotation System).For all variants where the genomic location is known, DIAS using the ensembl VEP (Variant Effect Predictor) has ensured the re-annotation of all COSMIC variants, for all available genes and transcripts to a specific ensembl version, independently and for both the GRCh37 and GRCh38 assemblies. From release v90 we have created new stable cosmic genomic identifiers (COSV) for all simple nucleotide variants which point to the corresponding locations on the reference genome. A flip mechanism has been developed that maps the same COSV identifier to both GRCh37 and GRCh38 assemblies, easily searchable from the COSMIC website. The legacy COSM and COSN identifiers have been mapped to the COSV genomic identifiers for backwards compatibility. Additionally, where redundant variants have been identified, these were merged and website redirection has been implemented. Standardized variant annotations have been utilized that adhere to the most recent HGVS recommendations on genomic, transcriptomic and proteomic syntaxes.The cross-references between COSMIC genes and other widely-used databases, such as HGNC, RefSeq, UniProt and CCDS, have been updated and kept up-to-date.Curated cross references between COSMIC phenotypes, NCI terminologies and EFO codes are also available.All the information stored in COSMIC is easily accessible by the website where users are able to explore cancer genomics in high resolution, with the various views available in downloadable formats with a simple click (https://cancer.sanger.ac.uk/cosmic/download).The DIAS system, minimized redundancy of variants, and enhanced the interoperability of COSMIC with other variation resources enabling more precise analysis and easier integration with in-house systems for our users. Citation Format: Charalampos Boutselakis, Chai Kok, Bhavana Harsha, Nidhi Bindal, Shicai Wang, Siew-Yit Yong, Charlotte Cole, Zbyslaw Sondka, Simon Forbes. DIAS, the COSMIC data integration and annotation system [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3213.

COSMIC, the Catalogue Of Somatic Mutations In Cancer (http://cancer.sanger.ac.uk) is the world's largest and most comprehensive resource for exploring the impact of somatic mutations in human cancer. Our latest release (v70; Aug 2014) describes 2 002 811 coding point mutations in over one million tumor samples and across most human genes. To emphasize depth of knowledge on known cancer genes, mutation information is curated manually from the scientific literature, allowing very precise definitions of disease types and patient details. Combination of almost 20 000 published studies gives substantial resolution of how mutations and phenotypes relate in human cancer, providing insights into the stratification of mutations and biomarkers across cancer patient populations. Conversely, our curation of cancer genomes (over 12 000) emphasizes knowledge breadth, driving discovery of unrecognized cancer-driving hotspots and molecular targets. Our high-resolution curation approach is globally unique, giving substantial insight into molecular biomarkers in human oncology. In addition, COSMIC also details more than six million noncoding mutations, 10 534 gene fusions, 61 299 genome rearrangements, 695 504 abnormal copy number segments and 60 119 787 abnormal expression variants. All these types of somatic mutation are annotated to both the human genome and each affected coding gene, then correlated across disease and mutation types.

The COSMIC Cancer Gene Census (https://cancer.sanger.ac.uk/census) is a catalogue of genes that drive all forms of human cancer. Since 2004, a consistent curation approach to the scientific literature has grown this resource into a comprehensive description of 723 genes, detailing how each gene contributes to disease causation The entire Cancer Gene Census has been fully re-evaluated, and each gene has been classified as Oncogene, Tumour Suppressor and/or Fusion gene - depending on their somatic mutation profile and functional role in carcinogenesis. Genes included in the CGC are characterised by the presence of somatic or germline mutations, which change the activity or expression of the protein product in a way that promotes one or multiple hallmarks of cancer. The minimum level of evidence required for CGC inclusion are at least 2 publications from independent research groups showing increased mutation frequency in at least one type of cancer; and 2 or more published experimental evidence of functional involvement of a gene in promoting the hallmarks of cancer. The functional description of how each mutated gene causes cancer is now underway, with approximately half the Census now described in both functional and mechanistic terms. These characteristics clearly show that many genes can participate in oncogenesis in multiple ways that are highly dependent on the type of genetic alteration and tissue in which the gene is expressed, as well as disease stage. Alongside this evidence-based characterisation of genes we know drive cancer, a “second tier” of genes is now encompassed in the Census, to describe genes implicated in oncology, but with less robust published evidence. These genes, often revealed by combining whole-tumour-genome sequencing studies are increasing rapidly in number and often underpin exciting new targets in oncology. Inclusion of these in the Census completes its ability to describe the contribution of inherited and acquired genetics to human oncology. With substantial research ongoing, the Census is updated with additional content every three months, included with every new release of the COSMIC database (https://cancer.sanger.ac.uk/). Citation Format: Zbyslaw Sondka, Helen E. Speedy, Sally Bamford, Charlotte G. Cole, Sari A. Ward, Simon A. Forbes. The COSMIC Cancer Gene Census - a comprehensive study of all mutated cancer-driving genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2469.

COSMIC, the Catalogue Of Somatic Mutations In Cancer (http://cancer.sanger.ac.uk/cosmic) is a continual effort to integrate all available information on somatic mutations and other molecular alterations causing every form of human cancer. Being the world’s largest and most comprehensive database of somatic mutations in human cancer, it also provides web-based tools for exploration and interpretation of collected data. The content of the database is primarily obtained from the scientific literature by the team of experienced post-doctoral curators and combined with information from online sources, including the TCGA and ICGC. During thorough & exhaustive manual curation, all the available information about mutations and tumor samples (e.g. disease type, demographic data, treatments) are collected, standardized and integrated to allow for both creation of wide virtual cohorts and large-scale studies, as well as precise analysis at the level of a single sample, gene or mutation. The 87th release of COSMIC (Nov 2018) encompasses 5,992,260 coding mutations and 19,574 gene fusions, curated from 1,403,267 cancer samples, including 35,490 whole cancer exomes/genomes, primarily hand-curated data from 26,494 scientific publications. Additionally, COSMIC describes 1,179,545 Copy Number Variants, 9,147,833 gene expression variants, and 7,879,142 differentially methylated CPGs. In addition to this broad database, COSMIC includes a range of specialized projects highlighting specific aspects of cancer in order to emphasize events with a higher impact in disease etiology. This includes the Cancer Gene Census (http://cancer.sanger.ac.uk/census), which defines and describes genes (currently 719) and their dysfunctions driving oncogenesis, and characterizes their impact on hallmarks of cancer. COSMIC3D (http://cancer.sanger.ac.uk/cosmic3d) provides an interactive view of cancer mutations in the context of 3D protein structures, and predicts potential drug-binding sites. Significantly updated 4 times a year, COSMIC is available free-of-charge for academic and non-profit users via COSMIC webpage (http://cancer.sanger.ac.uk/cosmic) or to download through COSMIC downloads (http://cancer.sanger.ac.uk/cosmic/download). Citation Format: Simon Andrew Forbes, david beare, charalampos boutselakis, sally bamford, kate noble, claire rye, john tate, chai yin kok, charlie hathaway, laura ponting, christopher ramshaw, raymund stefancsik, samantha thompson, bhavana harsha, nidhi bindal, shicai wang, steven jupe, helen speedy, celestino creatore, peter fish, sari ward, charlotte cole, elisabeth dawson, zbyslaw sondka. COSMIC: Describing the world’s knowledge of somatic mutations in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 906.

We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.

COSMIC, the Catalogue of Somatic Mutations in Cancer (http://cancer.sanger.ac.uk) is a high-resolution resource for exploring targets and trends in the genetics of human cancer. Currently the broadest database of mutations in cancer, the information in COSMIC is curated by expert scientists, primarily by scrutinizing large numbers of scientific publications. Over 4 million coding mutations are described in v78 (September 2016), combining genome-wide sequencing results from 28 366 tumours with complete manual curation of 23 489 individual publications focused on 186 key genes and 286 key fusion pairs across all cancers. Molecular profiling of large tumour numbers has also allowed the annotation of more than 13 million non-coding mutations, 18 029 gene fusions, 187 429 genome rearrangements, 1 271 436 abnormal copy number segments, 9 175 462 abnormal expression variants and 7 879 142 differentially methylated CpG dinucleotides. COSMIC now details the genetics of drug resistance, novel somatic gene mutations which allow a tumour to evade therapeutic cancer drugs. Focusing initially on highly characterized drugs and genes, COSMIC v78 contains wide resistance mutation profiles across 20 drugs, detailing the recurrence of 301 unique resistance alleles across 1934 drug-resistant tumours. All information from the COSMIC database is available freely on the COSMIC website.

COSMIC (http://cancer.sanger.ac.uk) is an expert-curated database of somatic mutations in human cancer. Broad and comprehensive in scope, recent releases in 2016 describe over 4 million coding mutations across all human cancer disease types. Mutations are annotated across the entire genome, but expert curation is focused on over 400 key cancer genes. Now encompassing the majority of molecular mutation mechanisms in oncogenetics, COSMIC additionally describes 10 million non-coding mutations, 1 million copy-number aberrations, 9 million gene-expression variants, and almost 8 million differentially methylated CpGs. This information combines a consistent interpretation of the data from the major cancer genome consortia and cancer genome literature with exhaustive hand curation of over 22,000 gene-specific literature publications. This unit describes the graphical Web site in detail; alternative protocols overview other ways the entire database can be accessed, analyzed, and downloaded. © 2016 by John Wiley & Sons, Inc.

The murine homolog of the multiple endocrine neoplasia type 1 (MEN1) gene (men1), which in humans is associated with tumors of the parathyroids, pancreas, and pituitary, has been characterized by isolating 27 clones from a mouse embryonic stem cell cDNA library. The insert sizes ranged from 600-2500 bp, and sequence analysis identified a 1833 bp open reading frame encoding a 611 amino acid protein. In addition, two clones contained an unspliced intron 1, and another two clones contained 20-29 bp of an upstream sequence, which suggested the presence of an alternate exon 1. This was supported by an analysis of the homologous human sequence. The mouse and human coding regions had 89% and 96% identity of the nucleotide and amino acid sequences, respectively. Investigation of clones isolated from a 129ola mouse genomic library, revealed the men1 gene to consist of 10 exons that spanned approximately 6 kb. Northern blot analysis demonstrated the ubiquitous expression of 2.9 kb and 3. 4 kb transcripts in mouse adult tissues and embryos from 7 days. DNA sequence analysis of the larger 3.4 kb transcript revealed it to result from a retention of intron 1. In situ hybridization confirmed an early ubiquitous expression in whole mount mouse embryos and adult tissues, but in the latter, different levels of cellular expression were observed, e.g., men1 expression was higher in testicular Sertoli cells than in germ cells. Thus, the mouse men1 gene and the basis of alternative transcripts have been defined, and these will help to facilitate studies of a mouse model.

A Portuguese kindred with autosomal dominant isolated primary hyperparathyroidism (HPT) that was associated with parathyroid adenomas and carcinomas was investigated with the aim of determining the chromosomal location of this gene, designated HPTPort. Leukocyte DNA from 9 affected and 16 unaffected members and 7 parathyroid tumors from 4 patients was used in comparative genomic hybridization (CGH), tumor loss of heterozygosity (LOH), and family linkage studies. The CGH studies revealed abnormalities of chromosomes 1 and 13, and the results of LOH studies were consistent with the involvements of tumor suppressor genes from these regions. Family segregation studies mapped HPTPort to chromosome 1q22-q31 by establishing linkage with eight loci (D1S254, D1S222, D1S202, D1S238, D1S428, D1S2877, D1S422, and D1S412) (peak two-point LOD scores = 3. 46-5.14 at 0% recombination), and defined the location of HPT Port to a 21 cM region flanked centromerically by D1S215 and telomerically by D1S306. Thus, HPTPort has been mapped to chromosome 1q22-q31, and a characterization of this gene will help to elucidate further the mechanisms that are involved in the development of parathyroid tumors.

Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant familial cancer syndrome characterized by parathyroid, pancreatic, and anterior pituitary tumors. The MEN1 locus has been previously localized to chromosome 11q13, and a 2-Mb gene-rich region flanked by D11S1883 and D11S449 has been defined. We have pursued studies to facilitate identification of the MEN1 gene by narrowing this critical region to a 900-kb interval between the VRF and D11S1783 loci through meiotic mapping. This was achieved by investigating 17 cosmids for microsatellite polymorphisms, which defined two novel polymorphisms at the VRF and A0138 loci, and utilizing these to characterize recombinants in MEN1 families. In addition, we have established a 1200-kb sequence-ready contig consisting of 26 cosmids, eight BACs, and eight PACS that encompass this region. The precise locations for 19 genes and three ESTs within this contig have been determined, and three gene clusters consisting of a centromeric group (VRF, FKBP2, PNG, and PLCB3), a middle group (PYGM, ZFM1, SCG1, SCG2 (which proved to be the MEN1 gene), and PPP2R5B), and a telomeric group (H4B, ANG3, ANG2, ANG1, FON, FAU, NOF, NON, and D11S2196E) were observed. These results represent a valuable transcriptional map of chromosome 11q13 that will help in the search for disease genes in this region.

Myelodysplastic syndromes (MDS) are a heterogeneous group of chronic hematological malignancies characterized by dysplasia, ineffective hematopoiesis and a variable risk of progression to acute myeloid leukemia. Sequencing of MDS genomes has identified mutations in genes implicated in RNA splicing, DNA modification, chromatin regulation, and cell signaling. We sequenced 111 genes across 738 patients with MDS or closely related neoplasms (including chronic myelomonocytic leukemia and MDS-myeloproliferative neoplasms) to explore the role of acquired mutations in MDS biology and clinical phenotype. Seventy-eight percent of patients had 1 or more oncogenic mutations. We identify complex patterns of pairwise association between genes, indicative of epistatic interactions involving components of the spliceosome machinery and epigenetic modifiers. Coupled with inferences on subclonal mutations, these data suggest a hypothesis of genetic "predestination," in which early driver mutations, typically affecting genes involved in RNA splicing, dictate future trajectories of disease evolution with distinct clinical phenotypes. Driver mutations had equivalent prognostic significance, whether clonal or subclonal, and leukemia-free survival deteriorated steadily as numbers of driver mutations increased. Thus, analysis of oncogenic mutations in large, well-characterized cohorts of patients illustrates the interconnections between the cancer genome and disease biology, with considerable potential for clinical application.

COSMIC (http://www.sanger.ac.uk/cosmic) curates comprehensive information on somatic mutations in human cancer. Release v48 (July 2010) describes over 136 000 coding mutations in almost 542 000 tumour samples; of the 18 490 genes documented, 4803 (26%) have one or more mutations. Full scientific literature curations are available on 83 major cancer genes and 49 fusion gene pairs (19 new cancer genes and 30 new fusion pairs this year) and this number is continually increasing. Key amongst these is TP53, now available through a collaboration with the IARC p53 database. In addition to data from the Cancer Genome Project (CGP) at the Sanger Institute, UK, and The Cancer Genome Atlas project (TCGA), large systematic screens are also now curated. Major website upgrades now make these data much more mineable, with many new selection filters and graphics. A Biomart is now available allowing more automated data mining and integration with other biological databases. Annotation of genomic features has become a significant focus; COSMIC has begun curating full-genome resequencing experiments, developing new web pages, export formats and graphics styles. With all genomic information recently updated to GRCh37, COSMIC integrates many diverse types of mutation information and is making much closer links with Ensembl and other data resources.

In recent years there has been an explosion in cancer genomic data that has enabled understanding of the incidence and patterns of mutations in cancer patients. The challenge is to translate this vast resource of genomic research and data into precision medicines that target specific mutations in patient populations and improve clinical outcomes. Delivering personalised cancer medicines requires greater understanding of how cancer mutations impact the structure, function, and druggability of known and potential protein drug targets. In this study we annotate each missense mutation in COSMIC, via COSMIC-3D (http://cancer.sanger.ac.uk/cosmic3d), with protein structural features derived from the wwPDB, and rich functional features derived from the UniProt protein database. The structural features include small molecule binding sites (including drug binding sites), protein-protein interaction interfaces, protein-nucleic acid interactions, solvent inaccessible protein “core” versus solvent exposed areas, and predicted small-molecule druggability. The UniProt-derived functional features represent high quality functional site annotations, including post-translational modification sites, functional domains and motifs, and regions of biological interest. In addition, we explore the relationship between mutation occurrence in protein structural and functional sites, and recurrence in cancer. We found that recurrent missense mutations are significantly enriched in specific structural and functional environments, including small-molecule binding sites and predicted druggable pockets. These results provide promising hypotheses that recurrent, cancer driving mutations may be targeted by small-molecule drugs. We posit that further characterisation of the structure-function implications of each mutation in COSMIC-3D will increasingly aid mutation-guided target discovery and drug design. Citation Format: Harry C. Jubb, Harpreet K. Saini, Marcel L. Verdonk, Simon A. Forbes. COSMIC-3D: Impacts of cancer mutations on protein structure, function, and druggability [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3285.

COSMIC, the Catalogue Of Somatic Mutations In Cancer (http://cancer.sanger.ac.uk/cosmic) is a long-term sustainable effort to collect, standardise and integrate information on somatic mutations and other molecular alterations that cause human cancer. Being the world's largest and most comprehensive database of somatic mutations in cancer, it also provides web-based tools for exploration and interpretation of collected data. The content of the database is obtained primarily by careful curation of the scientific literature by a team of experienced post-doctoral curators, allowing mutations to be described across every form of human cancer at high resolution (covering 1,706 cancer phenotypes). This is then combined with data from a number of on-line sources, including the TCGA and ICGC web portals. During exhaustive manual curation, all the available information about mutations and samples (e.g. disease type, demographic data, treatments) are collected, standardised and integrated to allow for both creation of wide virtual cohorts and large-scale studies, as well as precise analysis at the level of a single sample, gene or mutation. To support investigations into how genes dysfunction to drive cancer, the 83rd release of COSMIC (Nov 2017) encompasses 5,366,273 coding mutations and 18,845 gene fusions in 1,343,214 cancer samples, hand-curated from 25,501 scientific publications, including 32,514 whole cancer genomes. Further curations support examination of gene dysregulation in cancer, including 16,961,605 non-coding variants, 1,180,789 Copy Number Variants, 9,176,464 gene expression variants, and 7,879,142 differentially methylated CpGs. Specialised COSMIC projects highlight specific knowledge of cancer in order to characterise events with a higher impact in disease aetiology. The Cancer Gene Census (http://cancer.sanger.ac.uk/census), currently defines and describes 699 genes, how their dysfunctions drive oncogenesis, and characterises their impact on hallmarks of cancer. COSMIC-3D (http://cancer.sanger.ac.uk/cosmic3d) provides an interactive view of cancer mutations in the context of 3D protein structures, and predicts potential drug-binding sites. Mutations causing drug resistance are now described as a new resource (http://cancer.sanger.ac.uk/cosmic/drug_resistance). To allow for the incorporation of new data exploration tools, the COSMIC web page layouts have been updated and their usability has been improved, giving more options to filter webpage content. COSMIC is significantly updated 4 times a year, and is available free-of-charge for academic and non-profit users via COSMIC webpage (http://cancer.sanger.ac.uk/cosmic) or to download through COSMIC downloads (http://cancer.sanger.ac.uk/cosmic/download) Citation Format: Zbyslaw Sondka, Sally Bamford, Charlotte G. Cole, Elisabeth Dawson, Laura Ponting, Raymund Stefancsik, Sari Ward, Harry C. Jubb, Sam Thompson, Dave Beare, Nidhi Bindal, Charambulos Boutselakis, Peter Fish, Bhavana Harsha, Chai Yin Kok, Chris Ramshaw, Claire Rye, John Tate, Shicai Wang, Peter J. Campbell, Simon A. Forbes. COSMIC: Integrating and interpreting the world's knowledge of somatic mutations in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3284.

International audience; The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

An activating point mutation in codon 12 of the HRAS gene was the first somatic point mutation identified in a human cancer and established the role of somatic mutations as the common driver of oncogenesis. Since then, there have been over 11,000 mutations in the three RAS (HRAS, KRAS and NRAS) genes in codons 12, 13 and 61 reported in the literature. We report here the identification of recurrent somatic missense mutations at alanine 146, a highly conserved residue in the guanine nucleotide binding domain. In two independent series of colorectal cancers from Hong Kong and the United States we detected KRAS A146 mutations in 7/126 and 2/94 cases, respectively, giving a combined frequency of 4%. We also detected KRAS A146 mutations in 2/40 (5%) colorectal cell lines, including the NCI-60 colorectal cancer line HCC2998. Codon 146 mutations thus are likely to make an equal or greater contribution to colorectal cancer than codon 61 mutations (4.2% in our combined series, 1% in the literature). Lung adenocarcinomas and large cell carcinomas did not show codon 146 mutations. We did, however, identify a KRAS A146 mutation in the ML-2 acute myeloid leukemia cell line and an NRAS A146 mutation in the NALM-6 B-cell acute lymphoblastic leukemia line, suggesting that the contribution of codon 146 mutations is not entirely restricted to colorectal cancers or to KRAS.

Summary background Familial isolated hyperparathyroidism (FIHP) is an autosomal dominant disorder characterized by uniglandular or multiglandular parathyroid tumours that occur in the absence of other endocrine tumours. The disorder may represent either an early stage of multiple endocrine neoplasia type 1 (MEN1), or an allelic variant of MEN1, or a distinct entity involving another locus. We have explored these possibilities in seven families in whom primary hyperparathyroidism occurred as the sole endocrinopathy. methods Seven FIHP families were ascertained and venous blood samples obtained from 35 members (17 affected and 18 unaffected) for DNA sequence analysis of the MEN1 gene. The mean (± SD) follow-up period in the 17 affected members was 15·06 (± 8·83) years. results Four heterozygous germline mutations of the MEN1 gene were identified. These consisted of two 4-bp intragenic deletions that would result in prematurely truncated proteins, and two missense (Asp153Val and Ala411Pro) mutations. Furthermore, analysis of parathyroid tumour DNA from one individual revealed a loss of the wild-type allele and retention of the mutant allele, consistent with Knudson's ‘two-hit’ model of hereditary cancer and a tumour suppressor role for MEN1 in FIHP. conclusions Our results provide further support for FIHP being a distinct allelic variant of MEN1, and an analysis of the 16 mutations reported to date indicate that FIHP is associated with a higher frequency of missense MEN1 mutations.

The Cancer Gene Census is an ongoing effort to catalogue genes for which somatic mutations have been causally implicated in cancer. The Census comprises manually curated summaries of the most relevant information for cancer-driving genes and their somatic mutations and brings together the expertise of a dedicated curation team, cancer scientists and the comprehensive resources of the COSMIC database. Current research focuses on characterising the participation of 609 census genes in hallmarks of cancer and identification of additional genes involved in these biological traits primarily via altered expression, CNA or epigenetic changes. New overviews of cancer gene function focused on hallmarks of cancer pull together manually curated information on the function of proteins coded by cancer genes and summarises the data in simple graphical form. It presents a condensed overview of most relevant facts with quick access to the literature source, aiming to provide summary characteristics of a cancer gene, rather than a full monography, to avoid information overload. This functional characterisation enables the creation of lists of genes of interest focused on the particular role they play in the development of cancer, as well as aiming to identify the cellular functions affected by mutations in particular tumours, and help to choose right targets for targeted therapy or synthetic lethality experiments. The Census is available from the COSMIC website for online use or download at: http://cancer.sanger.ac.uk/census. Citation Format: Zbyslaw Sondka, Sally Bamford, Charlotte G. Cole, Elisabeth Dawson, Laura Ponting, Raymund Stefancsik, Sari A. Ward, John Tate, Peter J. Campbell, Simon A. Forbes. COSMIC Cancer Gene Census: expert descriptions across genes in oncogenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2599. doi:10.1158/1538-7445.AM2017-2599

Explosions in the availability of cancer genomic data and protein structure data give us the potential to explore cancer molecular biology at an unprecedented scale, and in atomic detail. We present COSMIC-3D, which combines COSMIC, the most comprehensive cancer mutation database available (http://cancer.sanger.ac.uk), with the wealth of publicly available 3D protein structure data, to create a resource with which the protein-structural nature of cancer can be probed. COSMIC-3D will help us understand which cancer mutations drive the progression of cancers, by identifying which are in functional sites that have an effect on driving cell growth and proliferation, and where they are clustered in protein structures across the proteome, for specific cancer types. Through understanding the effects of cancer mutations on known and predicted drug binding sites, we aim to predict potential new drug targets in cancers, and improve the specificity and efficacy of new or existing drugs, by using protein structure with cancer mutation data to guide mutation-specific drug design. COSMIC-3D is available as a web interface at http://cancer.sanger.ac.uk/cosmic3d, and enables interactive exploration of the cancer mutome in a 3D peptide environment, showing all forms of exonic point mutation. Individual mutant locations can be highlighted as molecular surfaces, while recurrence across nonsynonymous substitutions is visualized as 3D heat-maps. Cancer mutations can also be visualised in combination with precalculated small-molecule “druggable” binding sites, providing a powerful visual approach for development of hypotheses across structural, functional, and drug-resistance impacts of cancer variants. COSMIC-3D shows, for example, the steric occlusion of the binding site of ATP-competitive small-molecule inhibitors in the EGFR kinase domain by the mutation of L858 to arginine; these kinds of insights can be applied to novel cancer targets for any protein-structural mutation of interest. The human cancer structural proteome comprising COSMIC-3D extends to nearly 8,500 human genes; 1/3rd of genes in COSMIC. Over 30,000 human protein structures are available across these genes, to which over 345,000 cancer mutations are mapped. From structure based druggability prediction, over 6,500 proteins in COSMIC are predicted to have small-molecule druggable binding sites, making COSMIC-3D a powerful and exciting resource for the exploration and guidance of drug design and discovery in oncology. Citation Format: Harry C. Jubb, Harpreet Saini, Marcel Verdonk, Simon Forbes. COSMIC-3D: exploring cancer mutations in three dimensions for drug design and discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2601. doi:10.1158/1538-7445.AM2017-2601

Somatically acquired epigenetic changes are present in many cancers. Epigenetic regulation is maintained via post-translational modifications of core histones. Here, we describe inactivating somatic mutations in the histone lysine demethylase gene UTX, pointing to histone H3 lysine methylation deregulation in multiple tumor types. UTX reintroduction into cancer cells with inactivating UTX mutations resulted in slowing of proliferation and marked transcriptional changes. These data identify UTX as a new human cancer gene.

The undertaking of large-scale DNA sequencing screens for somatic variants in human cancers requires accurate and rapid processing of traces for variants. Due to their often aneuploid nature and admixed normal tissue, heterozygous variants found in primary cancers are often subtle and difficult to detect. To address these issues, we have developed a mutation detection algorithm, AutoCSA, specifically optimized for the high throughput screening of cancer samples. Availability: http://www.sanger.ac.uk/genetics/CGP/Software/AutoCSA. Contact: [email protected]

In the process of identification of the multiple endocrine neoplasia type 1 gene, which was recently published, we isolated a novel gene in the 11q13 region. This gene (named ZFPL1, for zinc-finger protein-like 1) is expressed strongly in the exocrine pancreas as a 1.4-kb polyadenylated RNA encoding a putative protein of 310 amino acids. A mouse EST contig predicts an equally sized murine protein with 91% amino acid sequence identity to the human protein. No significant homology with known proteins could be found through database screening. However, zinc-finger-like domains and leucine-zipper-like motifs in the predicted ZFPL1 protein were identified, suggesting the presence of DNA-binding and dimerization domains possibly involved in transcription regulation. This notion is supported by the presence of a putative bipartite nuclear localization signal. This paper presents the full-length cDNA sequence for this gene, its genomic structure and chromosomal orientation, and expression studies by Northern blot hybridization and RNA in situ hybridization.

SummaryMultiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant disorder characterized by tumors of the parathyroids, pancreatic islets, and anterior pituitary. The MEN1 gene, on chromosome 11q13, has recently been cloned, and mutations have been identified. We have characterized such MEN1 mutations, assessed the reliability of SSCP analysis for the detection of these mutations, and estimated the age-related penetrance for MEN1. Sixty-three unrelated MEN1 kindreds (195 affected and 396 unaffected members) were investigated for mutations in the 2,790-bp coding region and splice sites, by SSCP and DNA sequence analysis. We identified 47 mutations (12 nonsense mutations, 21 deletions, 7 insertions, 1 donor splice-site mutation, and 6 missense mutations), that were scattered throughout the coding region, together with six polymorphisms that had heterozygosity frequencies of 2%–44%. More than 10% of the mutations arose de novo, and four mutation hot spots accounted for >25% of the mutations. SSCP was found to be a sensitive and specific mutational screening method that detected >85% of the mutations. Two hundred and one MEN1 mutant-gene carriers (155 affected and 46 unaffected) were identified, and these helped to define the age-related penetrance of MEN1 as 7%, 52%, 87%, 98%, 99%, and 100% at 10, 20, 30, 40, 50, and 60 years of age, respectively. These results provide the basis for a molecular-genetic screening approach that will supplement the clinical evaluation and genetic counseling of members of MEN1 families.

Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant disorder characterised by tumours of the parathyroids, pancreas and anterior pituitary. The MEN1 gene has been localised to a 2-Mb region of chromosome 11q13 by meiotic mapping studies in MEN1 families. Such studies may have a limited resolution of approximately 1 cM (i.e. 1 Mb) and we have therefore investigated 96 MEN1 families (40 British, 17 French, 12 Finnish, 7 Swedish, 7 Dutch, 7 North American, 2 Australian, 1 New Zealand, 1 German, 1 Spanish and 1 Danish) for linkage disequilibrium, in order to facilitate a finer mapping resolution. We have utilised five microsatellite DNA sequence polymorphisms from the candidate region and have accurately determined their allele sizes, which ranged from 161 bp to 272 bp. The heterozygosity and number of alleles (given in brackets), respectively, at the loci were: D11S1883 (76%, 11), D11S457 (55%, 5), PYGM (94%, 18), D11S1783 (10%, 4) and D11S449 (87%, 16). Allelic association was assessed by Chi-square 2 x n contingency tables, by Fisher exact 2 x n contingency tables and by a likelihood-based approach. The results of haplotype analysis revealed 91 different affected haplotypes in the 96 families, an identical affected haplotype being observed in no more than two families. These results indicate the absence of an ancestral affected haplotype. Significant linkage disequilibrium (P < 0.005) could be established amongst the microsatellite loci but not between the loci and MEN1 in either the total population or in any of the geographical sub-populations, The absence of linkage disequilibrium between MEN1 and the polymorphic loci is probably the result of the occurrence of multiple different disease-causing mutations in MEN1.

Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant disorder characterised by tumours of the parathyroids, pancreas and anterior pituitary that represents one of the familial cancer syndromes. The MEN1 locus has been previously localised to chromosome 11q13, and a

COSMIC (http://cancer.sanger.ac.uk) is an expert-curated database of somatic mutations causing human cancer. Broad and comprehensive in scope, its 75th release (Nov 2015) describes over 3.7 million coding mutations across all human cancer disease types. Mutations are annotated across the entire genome, but expert curation is focused on almost 200 key cancer genes. Now encompassing the majority of molecular mutation mechanisms in oncogenetics, COSMIC additionally describes 10 million non-coding mutations, 1 million copy number aberrations, 9 million gene expression variants and almost 8 million differentially methylated CpG’s. This information combines a consistent interpretation of the data from the major cancer genome consortia and cancer genome literature, with hand-curation of over 22,000 gene-specific literature publications. With such a large volume of data, it is increasingly important to indicate which information is most significant. All mutations in COSMIC are now given a functional significance score, calculated using the FATHMM algorithm. In addition, a mutation can also be tagged as low-impact if they are described as a polymorphism in normal human genomes. All this information is available for selection and exploration in the COSMIC website (http://cancer.sanger.ac.uk), and for download via COSMIC Downloads (http://cancer.sanger.ac.uk/download). In addition to this broad database, the Cancer Gene Census (http://cancer.sanger.ac.uk/census) is a project within COSMIC aiming to identify and characterize all genes known to cause cancer, currently describing over 570 genes. This Census is now a priority focus of development, with a dedicated curator explicitly defining the range of genes driving cancer, including primary alleles and mechanisms and the diseases which are induced, with detailed supporting evidence. In addition to these analytical websites, expert-curated lists and now a GA4GH Beacon, COSMIC also hosts a full Oncology Genome Browser (http://cancer.sanger.ac.uk/genome). This fully-featured system allows the exploration of all cancer somatic mutation data collected in COSMIC alongside genomic annotations including coding genes, ncRNAs, SNPs and regulatory features. All data is vertically integrated, allowing exploration of how these many genetic mechanisms might promote oncogenesis, and how similar activating/inactivating mechanisms correlate. Amongst many interesting examples, there is a clear cluster of structural rearrangements immediately upstream of the BRD4 epigenetic modifier gene, affecting a region of multiple transcription control elements, and a substantial accumulation of abnormally hypermethylated CpG islands in the HOXA gene cluster on chromosome 7 coinciding with a group of HOTAIR and HOTTIP miRNAs. With multiple filters and selections available, these visualizations will increasingly support the exploration of how a variety of mutation mechanisms may act together to cause specific cancer diseases. Citation Format: Simon A. Forbes, Nidhi Bindal, David Beare, Sally Bamford, Charlotte G. Cole, Sari Ward, Kenric Leung, Chai Yin Kok, Mingming Jia, Tisham De, Zbyslaw Sondka, Michael R. Stratton, Peter J. Campbell. COSMIC: comprehensively exploring oncogenomics. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5285.

Alterations in cancer genomes strongly influence clinical responses to treatment and in many instances are potent biomarkers for response to drugs. The Genomics of Drug Sensitivity in Cancer (GDSC) database (www.cancerRxgene.org) is the largest public resource for information on drug sensitivity in cancer cells and molecular markers of drug response. Data are freely available without restriction. GDSC currently contains drug sensitivity data for almost 75 000 experiments, describing response to 138 anticancer drugs across almost 700 cancer cell lines. To identify molecular markers of drug response, cell line drug sensitivity data are integrated with large genomic datasets obtained from the Catalogue of Somatic Mutations in Cancer database, including information on somatic mutations in cancer genes, gene amplification and deletion, tissue type and transcriptional data. Analysis of GDSC data is through a web portal focused on identifying molecular biomarkers of drug sensitivity based on queries of specific anticancer drugs or cancer genes. Graphical representations of the data are used throughout with links to related resources and all datasets are fully downloadable. GDSC provides a unique resource incorporating large drug sensitivity and genomic datasets to facilitate the discovery of new therapeutic biomarkers for cancer therapies.

COSMIC, The Catalogue Of Somatic Mutations In Cancer [http://cancer.sanger.ac.uk], is one of the largest repositories for somatic mutational events in human cancer. Data in COSMIC are curated from multiple sources, including from over 14,310 scientific publications, and are alongside data from the Cancer Genome Project at the Sanger Institute and global international consortia, such as The Cancer Genome Atlas and the International Cancer Genome Consortium. The COSMIC database currently accommodates over 300,000 mutations across 750,000 analyzed samples from 21,850 genes (COSMIC v60, July 2012). The Cancer Gene Census [http://cancer.sanger.ac.uk/cancergenome/projects/census/] is a list of almost 500 known cancer genes for which mutations have been identified as causally implicated in cancer. These genes are prioritized for full literature curation. The collection of whole exome and genome sequencing data in COSMIC continues to grow at a rapid pace. There are: 17,614 coding mutations, 84,747 non-coding variants in 396 whole genome screens; 121,619 coding mutations and 12,949 non-coding variants as result of 1,266 full exome sequencing; 3,512 structural mutations derived from 77 rearrangement screens. The data overview for each whole genome screen is presented using Circos, for example, the NCI-H209 Circos summary [http://cancer.sanger.ac.uk/cosmic/sample/overview?id=688013]. Analyzing information from whole genome sequencing can greatly enhance the chance of discovering novel genes implicated in human cancer. Unlike hot spot screening of gene regions where somatic mutations are most frequent, the use of whole genome data can identify all mutations in all genes, providing much more expansive annotations to recurrence analysis as used to discover new cancer genes. For instance, there are recurrent somatic mutations identified in genes, for example: SPOP in 19 prostate samples; SDK1 in 20 large-intestine samples. There are several ways to access and analyze the data in COSMIC. The website allows data viewing in a genomic context supported by GBrowse while maintaining our gene-centric perspective. New additional features include a filter for excluding identified SNPs from the 1000 Genomes Project, and displaying Pfam domains and links to biological pathways for selected genes. For mining a large dataset, COSMICmart (an instance of BioMart) is a tool for downloading user-customized datasets federated with external databases such as Ensembl and Uniprot. Moreover, we provide data export in multiple formats and Oracle database export through the FTP site [ftp://ftp.sanger.ac.uk/pub/CGP/cosmic]. In addition to somatic mutation data, we have integrated the data from the Genomics of Drug Sensitivity in Cancer Project [http://www.cancerrxgene.org], which is screening a wide range of anticancer therapeutics against over 1,000 genetically characterized human cancer cell lines. Data analysis is becoming increasingly challenging due to the rapid expansion in cancer genome sequencing capacity. COSMIC is a major cancer genetics resource aiming to help such investigations, providing a centralized somatic mutations database with a wide suite of tools for its examination.

International audience; BioMart Central Portal is a first of its kind, community-driven effort to provide unified access to dozens of biological databases spanning genomics, proteomics, model organisms, cancer data, ontology information and more. Anybody can contribute an independently maintained resource to the Central Portal, allowing it to be exposed to and shared with the research community, and linking it with the other resources in the portal. Users can take advantage of the common interface to quickly utilize different sources without learning a new system for each. The system also simplifies cross-database searches that might otherwise require several complicated steps. Several integrated tools streamline common tasks, such as converting between ID formats and retrieving sequences. The combination of a wide variety of databases, an easy-to-use interface, robust programmatic access and the array of tools make Central Portal a one-stop shop for biological data querying. Here, we describe the structure of Central Portal and show example queries to demonstrate its capabilities. Database URL: http://central.biomart.org.

Catalogue of Somatic Mutations in Cancer (COSMIC) (http://www.sanger.ac.uk/cosmic) is a publicly available resource providing information on somatic mutations implicated in human cancer. Release v51 (January 2011) includes data from just over 19 000 genes, 161 787 coding mutations and 5573 gene fusions, described in more than 577 000 tumour samples. COSMICMart (COSMIC BioMart) provides a flexible way to mine these data and combine somatic mutations with other biological relevant data sets. This article describes the data available in COSMIC along with examples of how to successfully mine and integrate data sets using COSMICMart. Database URL: http://www.sanger.ac.uk/genetics/CGP/cosmic/biomart/martview/

The locus responsible for X-linked, nonsyndromic cleft palate and/or ankyloglossia (CPX) has previously been mapped to the proximal long arm of the human X chromosome between Xq21.31 and q21.33 in an Icelandic kindred. We have extended these studies by analyzing an additional 14 informative markers in the family as well as including several newly investigated family members. Recombination analysis indicates that the CPX locus is more proximal than previously thought, within the interval Xq21.1-q21.31. Two recombinants place DXYS1X as the distal flanking marker, while one recombinant defines DXS326 as the proximal flanking marker, an interval of less than 5 cM. Each of the flanking markers recombines with the CPX locus, giving 2-point lod scores of Zmax = 4.16 at theta = 0.08 (DXS326) and Zmax = 5.80 at theta = 0.06 (DXYS1X).

"COSMIC, the Catalogue Of Somatic Mutations In Cancer":http://www.sanger.ac.uk/cosmic is designed to store and display somatic mutation information relating to human cancers, combining detailed information on publications, samples and mutation types. The information is curated both from the primary literature and the laboratories at the Cancer Genome Project, Sanger Institute, UK, and then semi-automatically entered into the COSMIC database. The v47 release (May 2010) contained the curation of 9202 papers describing 116,977 mutations across 466,851 samples. In order to provide consistent annotation of the data, COSMIC has developed a classification system for cancer histology and tissue ontology, and adapted HGVS mutation nomenclature recommendations to describe the multiple mutation types involved in cancer.Cancer genetics is moving from systematic screens of candidate gene sets to whole genome sequencing analyses, and COSMIC displays and navigates this new data; we have recently included systematic gene screens and whole genome sequencing studies. COSMIC will annotate and display somatic mutation data that will be emerging from the "International Cancer Genome Consortium (ICGC)":http://www.icgc.org/ and "The Cancer Genome Atlas (TCGA)":http://cancergenome.nih.gov/ projects. New tools are being developed to interpret this genomic data with coding mutation annotations. In addition COSMIC will be expanded to curate and display data from mouse insertional mutagenesis screening and mouse cancer model exome/genome sequencing in the future. The data within COSMIC is freely available without restriction via a website, in datasheets on the "FTP site":ftp://ftp.sanger.ac.uk/pub/CGP/cosmic and through the "COSMIC Biomart":http://www.sanger.ac.uk/genetics/CGP/cosmic/biomart/martview/, available from the "COSMIC homepage":http://www.sanger.ac.uk/cosmic

The catalogue of Somatic Mutations in Cancer (COSMIC) (http://www.sanger.ac.uk/cosmic/) is the largest public resource for information on somatically acquired mutations in human cancer and is available freely without restrictions. Currently (v43, August 2009), COSMIC contains details of 1.5-million experiments performed through 13 423 genes in almost 370 000 tumours, describing over 90 000 individual mutations. Data are gathered from two sources, publications in the scientific literature, (v43 contains 7797 curated articles) and the full output of the genome-wide screens from the Cancer Genome Project (CGP) at the Sanger Institute, UK. Most of the world’s literature on point mutations in human cancer has now been curated into COSMIC and while this is continually updated, a greater emphasis on curating fusion gene mutations is driving the expansion of this information; over 2700 fusion gene mutations are now described. Whole-genome sequencing screens are now identifying large numbers of genomic rearrangements in cancer and COSMIC is now displaying details of these analyses also. Examination of COSMIC’s data is primarily web-driven, focused on providing mutation range and frequency statistics based upon a choice of gene and/or cancer phenotype. Graphical views provide easily interpretable summaries of large quantities of data, and export functions can provide precise details of user-selected data.

Clear cell renal cell carcinoma (ccRCC) is the most common form of adult kidney cancer, characterized by the presence of inactivating mutations in the VHL gene in most cases, and by infrequent somatic mutations in known cancer genes. To determine further the genetics of ccRCC, we have sequenced 101 cases through 3,544 protein-coding genes. Here we report the identification of inactivating mutations in two genes encoding enzymes involved in histone modification-SETD2, a histone H3 lysine 36 methyltransferase, and JARID1C (also known as KDM5C), a histone H3 lysine 4 demethylase-as well as mutations in the histone H3 lysine 27 demethylase, UTX (KMD6A), that we recently reported. The results highlight the role of mutations in components of the chromatin modification machinery in human cancer. Furthermore, NF2 mutations were found in non-VHL mutated ccRCC, and several other probable cancer genes were identified. These results indicate that substantial genetic heterogeneity exists in a cancer type dominated by mutations in a single gene, and that systematic screens will be key to fully determining the somatic genetic architecture of cancer.

COSMIC is currently the most comprehensive global resource for information on somatic mutations in human cancer, combining curation of the scientific literature with tumor resequencing data from the Cancer Genome Project at the Sanger Institute, U.K. Almost 4800 genes and 250000 tumors have been examined, resulting in over 50000 mutations available for investigation. This information can be accessed in a number of ways, the most convenient being the Web-based system which allows detailed data mining, presenting the results in easily interpretable formats. This unit describes the graphical system in detail, elaborating an example walkthrough and the many ways that the resulting information can be thoroughly investigated by combining data, respecializing the query, or viewing the results in different ways. Alternate protocols overview the available precompiled data files available for download.

The human major histocompatibility complex (MHC) is contained within about 4 Mb on the short arm of chromosome 6 and is recognised as the most variable region in the human genome. The primary aim of the MHC Haplotype Project was to provide a comprehensively annotated reference sequence of a single, human leukocyte antigen-homozygous MHC haplotype and to use it as a basis against which variations could be assessed from seven other similarly homozygous cell lines, representative of the most common MHC haplotypes in the European population. Comparison of the haplotype sequences, including four haplotypes not previously analysed, resulted in the identification of >44,000 variations, both substitutions and indels (insertions and deletions), which have been submitted to the dbSNP database. The gene annotation uncovered haplotype-specific differences and confirmed the presence of more than 300 loci, including over 160 protein-coding genes. Combined analysis of the variation and annotation datasets revealed 122 gene loci with coding substitutions of which 97 were non-synonymous. The haplotype (A3-B7-DR15; PGF cell line) designated as the new MHC reference sequence, has been incorporated into the human genome assembly (NCBI35 and subsequent builds), and constitutes the largest single-haplotype sequence of the human genome to date. The extensive variation and annotation data derived from the analysis of seven further haplotypes have been made publicly available and provide a framework and resource for future association studies of all MHC-associated diseases and transplant medicine. © 2007 The Author(s). Fil: Horton, Roger. Wellcome Trust Sanger Institute; Reino Unido Fil: Gibson, Richard. Wellcome Trust Sanger Institute; Reino Unido Fil: Coggill, Penny. Wellcome Trust Sanger Institute; Reino Unido Fil: Miretti, Marcos Mateo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; Argentina. Wellcome Trust Sanger Institute; Reino Unido Fil: Allcock, Richard J.. University of Western Australia; Australia Fil: Almeida, Jeff. Wellcome Trust Sanger Institute; Reino Unido Fil: Forbes, Simon. Wellcome Trust Sanger Institute; Reino Unido Fil: Gilbert, James G. R.. Wellcome Trust Sanger Institute; Reino Unido Fil: Halls, Karen. Wellcome Trust Sanger Institute; Reino Unido. University of Cambridge; Reino Unido Fil: Harrow, Jennifer L.. Wellcome Trust Sanger Institute; Reino Unido Fil: Hart, Elizabeth. Wellcome Trust Sanger Institute; Reino Unido Fil: Howe, Kevin. Cruk Cambridge Research Institute; Reino Unido Fil: Jackson, David K.. Wellcome Trust Sanger Institute; Reino Unido Fil: Palmer, Sophie. Wellcome Trust Sanger Institute; Reino Unido Fil: Roberts, Anne N.. University of Cambridge; Reino Unido Fil: Sims, Sarah. Wellcome Trust Sanger Institute; Reino Unido Fil: Stewart, C. Andrew. National Cancer Institute At Frederick; Estados Unidos Fil: Traherne, James A.. University of Cambridge; Reino Unido Fil: Trevanion, Steve. Wellcome Trust Sanger Institute; Reino Unido Fil: Wilming, Laurens. Wellcome Trust Sanger Institute; Reino Unido Fil: Rogers, Jane. Wellcome Trust Sanger Institute; Reino Unido Fil: De Jong, Pieter J.. Children's Hospital Oakland Research Institute; Estados Unidos Fil: Elliott, John F.. University of Alberta; Canadá Fil: Sawcer, Stephen. University of Cambridge; Reino Unido Fil: Todd, John A.. University of Cambridge; Reino Unido Fil: Trowsdale, John. University of Cambridge; Reino Unido Fil: Beck, Stephan G.. Wellcome Trust Sanger Institute; Reino Unido

Cancers arise owing to mutations in a subset of genes that confer growth advantage. The availability of the human genome sequence led us to propose that systematic resequencing of cancer genomes for mutations would lead to the discovery of many additional cancer genes. Here we report more than 1,000 somatic mutations found in 274 megabases (Mb) of DNA corresponding to the coding exons of 518 protein kinase genes in 210 diverse human cancers. There was substantial variation in the number and pattern of mutations in individual cancers reflecting different exposures, DNA repair defects and cellular origins. Most somatic mutations are likely to be 'passengers' that do not contribute to oncogenesis. However, there was evidence for 'driver' mutations contributing to the development of the cancers studied in approximately 120 genes. Systematic sequencing of cancer genomes therefore reveals the evolutionary diversity of cancers and implicates a larger repertoire of cancer genes than previously anticipated.

COSMIC, the Catalogue Of Somatic Mutations In Cancer (http://cancer.sanger.ac.uk) is the world's largest and most comprehensive online resource for exploring the impact of somatic mutations in human cancer. Live since 2004, the 71st release (Nov 2014) describes over 2 million mutations in more than 1 million tumour samples across most human genes. To emphasise depth of knowledge on known cancer genes, mutation information is curated manually from the scientific literature, allowing very precise definitions of disease types and clinically relevant patient details. Combination of over 20,000 published studies gives substantial resolution of how mutations and phenotypes relate in human cancer, providing insights into the stratification of populations and new diseases behind known biomarkers. Conversely, our curation of over 15,000 cancer genome studies emphasises knowledge breadth, driving discovery of new unrecognised cancer-driving hotspots and molecular targets. Our high-resolution curation approach is globally unique, giving substantial insight into molecular biomarkers in human oncology. For example, BRAF is well characterized in skin melanoma, transiently treatable with inhibitors such as Vemurafenib. It is also well known in colorectal cancer, which is largely non-responsive to BRAF inhibitors. COSMIC's unique approach demonstrates the impact of BRAF mutations in much less well-known cancers, for instance, Hairy Cell Leukaemia (89% of samples mutated) and Langerhans Cell Histiocytosis (49%), both of which respond remarkably well to BRAF inhibitors. Converse to skin melanoma, our curations suggest BRAF has a minimal role in Uveal melanoma (6% of Uveal tumors mutated for BRAF), with higher mutation rates in other genes (particularly GNA11, BAP1 and GNAQ), suggesting different mechanisms behind this disease. In addition to describing over two million coding point mutations across cancer, COSMIC also details more than six million non-coding mutations, 10,567 gene fusions, 61,232 genome rearrangements, 702,652 abnormal copy number segments, and more than 6 million abnormal expression variants. All these types of somatic mutation are annotated to both the human genome and each affected coding gene, then correlated across disease and mutation types. As increasing amounts of genetic data are gathered into COSMIC across human cancer, our annotations are beginning to emphasise events with a higher impact in cancer, highlighting the more functional coding mutations and major amplifications and deletions. This concept of high-impact data is being extended across the entire COSMIC system, much more strongly defining genes and mutations which drive oncogenesis. Citation Format: Simon A. Forbes, Dave Beare, Prasad Gunasekaran, Kenric Leung, Charambulos Boutselakis, Minjie Ding, Mingming Jia, Tisham De, Nidhi Bindal, Chai Yin Kok, Sally Bamford, Sari Ward, Charlotte Cole, Jon Teague, Michael R. Stratton, Peter J. Campbell. COSMIC: Combining the world's knowledge of somatic mutation in human cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 62. doi:10.1158/1538-7445.AM2015-62

The panel of 60 human cancer cell lines (the NCI-60) assembled by the National Cancer Institute for anticancer drug discovery is a widely used resource. The NCI-60 has been characterized pharmacologically and at the molecular level more extensively than any other set of cell lines. However, no systematic mutation analysis of genes causally implicated in oncogenesis has been reported. This study reports the sequence analysis of 24 known cancer genes in the NCI-60 and an assessment of 4 of the 24 genes for homozygous deletions. One hundred thirty-seven oncogenic mutations were identified in 14 (APC, BRAF, CDKN2, CTNNB1, HRAS, KRAS, NRAS, SMAD4, PIK3CA, PTEN, RB1, STK11, TP53, and VHL) of the 24 genes. All lines have at least one mutation among the cancer genes examined, with most lines (73%) having more than one. Identification of those cancer genes mutated in the NCI-60, in combination with pharmacologic and molecular profiles of the cells, will allow for more informed interpretation of anticancer agent screening and will enhance the use of the NCI-60 cell lines for molecularly targeted screens. [Mol Cancer Ther 2006;5(11):2606–12]

Malignant gliomas have a very poor prognosis. The current standard of care for these cancers consists of extended adjuvant treatment with the alkylating agent temozolomide after surgical resection and radiotherapy. Although a statistically significant increase in survival has been reported with this regimen, nearly all gliomas recur and become insensitive to further treatment with this class of agents. We sequenced 500 kb of genomic DNA corresponding to the kinase domains of 518 protein kinases in each of nine gliomas. Large numbers of somatic mutations were observed in two gliomas recurrent after alkylating agent treatment. The pattern of mutations in these cases showed strong similarity to that induced by alkylating agents in experimental systems. Further investigation revealed inactivating somatic mutations of the mismatch repair gene MSH6 in each case. We propose that inactivating somatic mutations of MSH6 confer resistance to alkylating agents in gliomas in vivo and concurrently unleash accelerated mutagenesis in resistant clones as a consequence of continued exposure to alkylating agents in the presence of defective mismatch repair. The evidence therefore suggests that when MSH6 is inactivated in gliomas, alkylating agents convert from induction of tumor cell death to promotion of neoplastic progression. These observations highlight the potential of large scale sequencing for revealing and elucidating mutagenic processes operative in individual human cancers. (Cancer Res 2006; 66(8): 3987-91)

The protein kinase gene family is the most frequently mutated in human cancer. Previous work has documented activating mutations in the KIT receptor tyrosine kinase in testicular germ-cell tumors (TGCT). To investigate further the potential role of mutated protein kinases in the development of TGCT and to characterize the prevalence and patterns of point mutations in these tumors, we have sequenced the coding exons and splice junctions of the annotated protein kinase family of 518 genes in a series of seven seminomas and six nonseminomas. Our results show a remarkably low mutation frequency, with only a single somatic point mutation, a K277E mutation in the STK10 gene, being identified in a total of more than 15 megabases of sequence analyzed. Sequencing of STK10 in an additional 40 TGCTs revealed no further mutations. Comparative genomic hybridization and LOH analysis using SNP arrays demonstrated that the 13 TGCTs mutationally screened through the 518 protein kinase genes were uniformly aneuploid with consistent chromosomal gains on 12p, 8q, 7, and X and losses on 13q, 18q, 11q, and 4q. Our results do not provide evidence for a mutated protein kinase implicated in the development of TGCT other than KIT. Moreover, they demonstrate that the general prevalence of point mutations in TGCT is low, in contrast to the high frequency of copy number changes. © 2005 Wiley-Liss, Inc.

Protein kinases are frequently mutated in human cancer and inhibitors of mutant protein kinases have proven to be effective anticancer drugs. We screened the coding sequences of 518 protein kinases (∼1.3 Mb of DNA per sample) for somatic mutations in 26 primary lung neoplasms and seven lung cancer cell lines. One hundred eighty-eight somatic mutations were detected in 141 genes. Of these, 35 were synonymous (silent) changes. This result indicates that most of the 188 mutations were “passenger” mutations that are not causally implicated in oncogenesis. However, an excess of ∼40 nonsynonymous substitutions compared with that expected by chance (P = 0.07) suggests that some nonsynonymous mutations have been selected and are contributing to oncogenesis. There was considerable variation between individual lung cancers in the number of mutations observed and no mutations were found in lung carcinoids. The mutational spectra of most lung cancers were characterized by a high proportion of C:G > A:T transversions, compatible with the mutagenic effects of tobacco carcinogens. However, one neuroendocrine cancer cell line had a distinctive mutational spectrum reminiscent of UV-induced DNA damage. The results suggest that several mutated protein kinases may be contributing to lung cancer development, but that mutations in each one are infrequent.

We examined the coding sequence of 518 protein kinases, approximately 1.3 Mb of DNA per sample, in 25 breast cancers. In many tumors, we detected no somatic mutations. But a few had numerous somatic mutations with distinctive patterns indicative of either a mutator phenotype or a past exposure.

The discovery of mutations in cancer genes has advanced our understanding of cancer. These results are dispersed across the scientific literature and with the availability of the human genome sequence will continue to accrue. The COSMIC (Catalogue of Somatic Mutations in Cancer) database and website have been developed to store somatic mutation data in a single location and display the data and other information related to human cancer. To populate this resource, data has currently been extracted from reports in the scientific literature for somatic mutations in four genes, BRAF, HRAS, KRAS2 and NRAS. At present, the database holds information on 66 634 samples and reports a total of 10 647 mutations. Through the web pages, these data can be queried, displayed as figures or tables and exported in a number of formats. COSMIC is an ongoing project that will continue to curate somatic mutation data and release it through the website.

The future systematic mapping of variants that confer susceptibility to common diseases requires the construction of a fully informative polymorphism map. Ideally, every base pair of the genome would be sequenced in many individuals. Here, we report 4.75 Mb of contiguous sequence for each of two common haplotypes of the major histocompatibility complex (MHC), to which susceptibility to >100 diseases has been mapped. The autoimmune disease-associated-haplotypes HLA-A3-B7-Cw7-DR15 and HLA-A1-B8-Cw7-DR3 were sequenced in their entirety through a bacterial artificial chromosome (BAC) cloning strategy using the consanguineous cell lines PGF and COX, respectively. The two sequences were annotated to encompass all described splice variants of expressed genes. We defined the complete variation content of the two haplotypes, revealing >18,000 variations between them. Average SNP densities ranged from less than one SNP per kilobase to >60. Acquisition of complete and accurate sequence data over polymorphic regions such as the MHC from large-insert cloned DNA provides a definitive resource for the construction of informative genetic maps, and avoids the limitation of chromosome regions that are refractory to PCR amplification.