COSMIC: the Catalogue Of Somatic Mutations In Cancer

Nucleic Acids Research, Journal Year: 2018, Volume and Issue: 47(D1), P. D941 - D947

Published: Oct. 11, 2018

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

Language: Английский

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A compendium of mutational cancer driver genes

Nature reviews. Cancer, Journal Year: 2020, Volume and Issue: 20(10), P. 555 - 572

Published: Aug. 10, 2020

Language: Английский

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A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells

Cell, Journal Year: 2021, Volume and Issue: 184(3), P. 792 - 809.e23

Published: Feb. 1, 2021

Tumor-infiltrating myeloid cells (TIMs) are key regulators in tumor progression, but the similarity and distinction of their fundamental properties across different tumors remain elusive. Here, by performing a pan-cancer analysis single from 210 patients 15 human cancer types, we identified distinct features TIMs types. Mast nasopharyngeal were found to be associated with better prognosis exhibited an anti-tumor phenotype high ratio TNF+/VEGFA+ cells. Systematic comparison between cDC1- cDC2-derived LAMP3+ cDCs revealed differences transcription factors external stimulus. Additionally, pro-angiogenic tumor-associated macrophages (TAMs) characterized diverse markers composition appeared certain somatic mutations gene expressions. Our results provide systematic view highly heterogeneous suggest future avenues for rational, targeted immunotherapies.

Language: Английский

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Pluripotent Stem Cell-Based Cell Therapy—Promise and Challenges

Cell stem cell, Journal Year: 2020, Volume and Issue: 27(4), P. 523 - 531

Published: Oct. 1, 2020

Language: Английский

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Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma

Cell, Journal Year: 2020, Volume and Issue: 182(1), P. 200 - 225.e35

Published: July 1, 2020

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization 110 tumors 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, gender. Proteomic phosphoproteomic data illuminated downstream copy number aberrations, somatic fusions identified vulnerabilities associated with events involving KRAS, EGFR, ALK. Immune subtyping a complex landscape, reinforced association STK11 immune-cold behavior, underscored potential immunosuppressive role neutrophil degranulation. Smoking-associated LUADs showed correlation other environmental exposure signatures field effect in NATs. Matched NATs allowed identification differentially expressed proteins diagnostic utility. This proteogenomics dataset represents unique public resource for researchers clinicians seeking to better understand treat adenocarcinomas.

Language: Английский

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Targeted Disruption of HLA Genes via CRISPR-Cas9 Generates iPSCs with Enhanced Immune Compatibility

Cell stem cell, Journal Year: 2019, Volume and Issue: 24(4), P. 566 - 578.e7

Published: March 7, 2019

Language: Английский

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Small molecules, big impact: 20 years of targeted therapy in oncology

The Lancet, Journal Year: 2020, Volume and Issue: 395(10229), P. 1078 - 1088

Published: March 1, 2020

Language: Английский

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Open Targets Platform: new developments and updates two years on

Nucleic Acids Research, Journal Year: 2018, Volume and Issue: 47(D1), P. D1056 - D1065

Published: Oct. 26, 2018

The Open Targets Platform integrates evidence from genetics, genomics, transcriptomics, drugs, animal models and scientific literature to score rank target-disease associations for drug target identification. are displayed in an intuitive user interface (https://www.targetvalidation.org), available through a REST-API (https://api.opentargets.io/v3/platform/docs/swagger-ui) bulk download (https://www.targetvalidation.org/downloads/data). In addition associations, we also aggregate display data at the disease levels aid prioritisation. Since our first publication two years ago, have made eight releases, added new sources started including causal genetic variants non genome-wide targeted arrays, annotations, launched visualisations improved existing ones released web tool batch search of up 200 targets. We URL REST-API, REST endpoints removed need authorisation API fair use. Here, present latest developments Platform, expanding with sources, refining quality, enhancing website usability, increasing base training workshops, support, social media bioinformatics forum engagement.

Language: Английский

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Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: March 10, 2022

Abstract Identification of cell populations often relies on manual annotation clusters using established marker genes. However, the selection genes is a time-consuming process that may lead to sub-optimal annotations as markers must be informative both individual and various types present in sample. Here, we developed computational platform, ScType, which enables fully-automated ultra-fast cell-type identification based solely given scRNA-seq data, along with comprehensive database background information. Using six datasets from human mouse tissues, show how ScType provides unbiased accurate type by guaranteeing specificity positive negative across types. We also demonstrate distinguishes between healthy malignant populations, single-cell calling single-nucleotide variants, making it versatile tool for anticancer applications. The widely applicable method deployed an interactive web-tool ( https://sctype.app ), open-source R-package.

Language: Английский

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In vivo base editing rescues Hutchinson–Gilford progeria syndrome in mice

Nature, Journal Year: 2021, Volume and Issue: 589(7843), P. 608 - 614

Published: Jan. 6, 2021

Language: Английский

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