The Catalogue of Somatic Mutations in Cancer (COSMIC) Cancer Gene Census (CGC) is an expert-curated description of the genes driving human cancer that is used as a standard in cancer genetics across ...basic research, medical reporting and pharmaceutical development. After a major expansion and complete re-evaluation, the 2018 CGC describes in detail the effect of 719 cancer-driving genes. The recent expansion includes functional and mechanistic descriptions of how each gene contributes to disease generation in terms of the key cancer hallmarks and the impact of mutations on gene and protein function. These functional characteristics depict the extraordinary complexity of cancer biology and suggest multiple cancer-related functions for many genes, which are often highly tissue-dependent or tumour stage-dependent. The 2018 CGC encompasses a second tier, describing an expanding list of genes (currently 145) from more recent cancer studies that show supportive but less detailed indications of a role in cancer.
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, 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.
Curated scientific databases catalogue and amplify research findings to maximize their reach. Authors should write their papers with this in mind, ensuring that data are accurate, easy to extract, ...and presented in standardized formats.
Abstract
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.
Abstract
The Catalogue Of Somatic Mutations In Cancer (COSMIC), https://cancer.sanger.ac.uk/cosmic, is an expert-curated knowledgebase providing data on somatic variants in cancer, supported by a ...comprehensive suite of tools for interpreting genomic data, discerning the impact of somatic alterations on disease, and facilitating translational research. The catalogue is accessed and used by thousands of cancer researchers and clinicians daily, allowing them to quickly access information from an immense pool of data curated from over 29 thousand scientific publications and large studies. Within the last 4 years, COSMIC has substantially expanded its utility by adding new resources: the Mutational Signatures catalogue, the Cancer Mutation Census, and Actionability. To improve data accessibility and interoperability, somatic variants have received stable genomic identifiers that are associated with their genomic coordinates in GRCh37 and GRCh38, and new export files with reduced data redundancy have been made available for download.
Graphical Abstract
Graphical Abstract
Bio-ontologies provide terminologies for the scientific community to describe biomedical entities in a standardized manner. There are multiple initiatives that are developing biomedical terminologies ...for the purpose of providing better annotation, data integration and mining capabilities. Terminology resources devised for multiple purposes inherently diverge in content and structure. A major issue of biomedical data integration is the development of overlapping terms, ambiguous classifications and inconsistencies represented across databases and publications. The disease ontology (DO) was developed over the past decade to address data integration, standardization and annotation issues for human disease data. We have established a DO cancer project to be a focused view of cancer terms within the DO. The DO cancer project mapped 386 cancer terms from the Catalogue of Somatic Mutations in Cancer (COSMIC), The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium, Therapeutically Applicable Research to Generate Effective Treatments, Integrative Oncogenomics and the Early Detection Research Network into a cohesive set of 187 DO terms represented by 63 top-level DO cancer terms. For example, the COSMIC term 'kidney, NS, carcinoma, clear_cell_renal_cell_carcinoma' and TCGA term 'Kidney renal clear cell carcinoma' were both grouped to the term 'Disease Ontology Identification (DOID):4467 / renal clear cell carcinoma' which was mapped to the TopNodes_DOcancerslim term 'DOID:263 / kidney cancer'. Mapping of diverse cancer terms to DO and the use of top level terms (DO slims) will enable pan-cancer analysis across datasets generated from any of the cancer term sources where pan-cancer means including or relating to all or multiple types of cancer. The terms can be browsed from the DO web site (http://www.disease-ontology.org) and downloaded from the DO's Apache Subversion or GitHub repositories. Database URL: http://www.disease-ontology.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/.
Abstract only
The aim of the study was to explore novel tissue based techniques to generate gene expression profiles of both afferent (sensory) and efferent (motor) neurons that specifically ...innervate the rat bladder and urethra.
Retrograde neuronal tracing studies in combination with laser capture microdissection (LCM) and microarray analysis were used to generate gene expression profiles of both afferent and efferent neurons that specifically innervate the rat bladder and urethra. A complete rat study (n=12) was performed in which fluorescently labelled cholera toxin B was injected into the bladder and urethra. Traced neurons were isolated by LCM, RNA was extracted, amplified and analysed by microarray.
Extensive analysis of all the data derived from this study give very sensitive and powerful gene expression data from only 50–100 microdissected neurons. Expression of sensory neuron specific markers could be confirmed in dorsal root ganglion neurons whereas expression of genes involved in motor function of the lower urinary tract could be confirmed in efferent neurons e.g. Onuf's Nucleus.
The resulting gene expression profile will increase our understanding of signalling pathways involved in the control of the lower urinary tract. Data derived from this study will not only be relevant for safety and efficacy but will also enable us to identify targets for the treatment of urinary frequency and urge incontinence (UFUI).
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