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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.

Onchocerciasis (river blindness) is a neglected tropical disease that has been successfully targeted by mass drug treatment programs in the Americas and small parts of Africa. Achieving the long-term goal of elimination of onchocerciasis, however, requires additional tools, including drugs, vaccines, and biomarkers of infection. Here, we describe the transcriptome and proteome profiles of the major vector and the human host stages (L1, L2, L3, molting L3, L4, adult male, and adult female) of Onchocerca volvulus along with the proteome of each parasitic stage and of its Wolbachia endosymbiont (wOv). In so doing, we have identified stage-specific pathways important to the parasite’s adaptation to its human host during its early development. Further, we generated a protein array that, when screened with well-characterized human samples, identified novel diagnostic biomarkers of O. volvulus infection and new potential vaccine candidates. This immunomic approach not only demonstrates the power of this postgenomic discovery platform but also provides additional tools for onchocerciasis control programs., IMPORTANCE The global onchocerciasis (river blindness) elimination program will have to rely on the development of new tools (drugs, vaccines, biomarkers) to achieve its goals by 2025. As an adjunct to the completed genomic sequencing of O. volvulus, we used a comprehensive proteomic and transcriptomic profiling strategy to gain a comprehensive understanding of both the vector-derived and human host-derived parasite stages. In so doing, we have identified proteins and pathways that enable novel drug targeting studies and the discovery of novel vaccine candidates, as well as useful biomarkers of active infection.

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.

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.

Human onchocerciasis is a serious neglected tropical disease caused by the filarial nematode Onchocerca volvulus that can lead to blindness and chronic disability. Control of the disease relies largely on mass administration of a single drug, and the development of new drugs and vaccines depends on a better knowledge of parasite biology. Here, we describe the chromosomes of O. volvulus and its Wolbachia endosymbiont. We provide the highest-quality sequence assembly for any parasitic nematode to date, giving a glimpse into the evolution of filarial parasite chromosomes and proteomes. This resource was used to investigate gene families with key functions that could be potentially exploited as targets for future drugs. Using metabolic reconstruction of the nematode and its endosymbiont, we identified enzymes that are likely to be essential for O. volvulus viability. In addition, we have generated a list of proteins that could be targeted by Federal-Drug-Agency-approved but repurposed drugs, providing starting points for anti-onchocerciasis drug development.

Soil-transmitted nematodes, including the Strongyloides genus, cause one of the most prevalent neglected tropical diseases. Here we compare the genomes of four Strongyloides species, including the human pathogen Strongyloides stercoralis, and their close relatives that are facultatively parasitic (Parastrongyloides trichosuri) and free-living (Rhabditophanes sp. KR3021). A significant paralogous expansion of key gene families - families encoding astacin-like and SCP/TAPS proteins - is associated with the evolution of parasitism in this clade. Exploiting the unique Strongyloides life cycle, we compare the transcriptomes of the parasitic and free-living stages and find that these same gene families are upregulated in the parasitic stages, underscoring their role in nematode parasitism.

ChEBI (http://www.ebi.ac.uk/chebi) is a database and ontology of chemical entities of biological interest. Over the past few years, ChEBI has continued to grow steadily in content, and has added several new features. In addition to incorporating all user-requested compounds, our annotation efforts have emphasized immunology, natural products and metabolites in many species. All database entries are now ‘is_a’ classified within the ontology, meaning that all of the chemicals are available to semantic reasoning tools that harness the classification hierarchy. We have completely aligned the ontology with the Open Biomedical Ontologies (OBO) Foundry-recommended upper level Basic Formal Ontology. Furthermore, we have aligned our chemical classification with the classification of chemical-involving processes in the Gene Ontology (GO), and as a result of this effort, the majority of chemical-involving processes in GO are now defined in terms of the ChEBI entities that participate in them. This effort necessitated incorporating many additional biologically relevant compounds. We have incorporated additional data types including reference citations, and the species and component for metabolites. Finally, our website and web services have had several enhancements, most notably the provision of a dynamic new interactive graph-based ontology visualization.

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.

Background Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein sets annotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis. Results We describe BiNChE, an enrichment analysis tool for small molecules based on the ChEBI Ontology. BiNChE displays an interactive graph that can be exported as a high-resolution image or in network formats. The tool provides plain, weighted and fragment analysis based on either the ChEBI Role Ontology or the ChEBI Structural Ontology. Conclusions BiNChE aids in the exploration of large sets of small molecules produced within Metabolomics or other Systems Biology research contexts. The open-source tool provides easy and highly interactive web access to enrichment analysis with the ChEBI ontology tool and is additionally available as a standalone library. Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0486-3) contains supplementary material, which is available to authorized users.

Background Sparganosis is an infection with a larval Diphyllobothriidea tapeworm. From a rare cerebral case presented at a clinic in the UK, DNA was recovered from a biopsy sample and used to determine the causative species as Spirometra erinaceieuropaei through sequencing of the cox1 gene. From the same DNA, we have produced a draft genome, the first of its kind for this species, and used it to perform a comparative genomics analysis and to investigate known and potential tapeworm drug targets in this tapeworm. Results The 1.26 Gb draft genome of S. erinaceieuropaei is currently the largest reported for any flatworm. Through investigation of β-tubulin genes, we predict that S. erinaceieuropaei larvae are insensitive to the tapeworm drug albendazole. We find that many putative tapeworm drug targets are also present in S. erinaceieuropaei, allowing possible cross application of new drugs. In comparison to other sequenced tapeworm species we observe expansion of protease classes, and of Kuntiz-type protease inhibitors. Expanded gene families in this tapeworm also include those that are involved in processes that add post-translational diversity to the protein landscape, intracellular transport, transcriptional regulation and detoxification. Conclusions The S. erinaceieuropaei genome begins to give us insight into an order of tapeworms previously uncharacterized at the genome-wide level. From a single clinical case we have begun to sketch a picture of the characteristics of these organisms. Finally, our work represents a significant technological achievement as we present a draft genome sequence of a rare tapeworm, and from a small amount of starting material. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0510-3) contains supplementary material, which is available to authorized users.