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We sought to define the genomic landscape of diffuse large B-cell lymphoma (DLBCL) by using formalin-fixed paraffin-embedded (FFPE) biopsy specimens. We used targeted sequencing of genes altered in hematologic malignancies, including DNA coding sequence for 405 genes, noncoding sequence for 31 genes, and RNA coding sequence for 265 genes (FoundationOne-Heme). Short variants, rearrangements, and copy number alterations were determined. We studied 198 samples (114 de novo, 58 previously treated, and 26 large-cell transformation from follicular lymphoma). Median number of GAs per case was 6, with 97% of patients harboring at least one alteration. Recurrent GAs were detected in genes with established roles in DLBCL pathogenesis (e.g. MYD88, CREBBP, CD79B, EZH2), as well as notable differences compared to prior studies such as inactivating mutations in TET2 (5%). Less common GAs identified potential targets for approved or investigational therapies, including BRAF, CD274 (PD-L1), IDH2, and JAK1/2. TP53 mutations were more frequently observed in relapsed/refractory DLBCL, and predicted for lack of response to first-line chemotherapy, identifying a subset of patients that could be prioritized for novel therapies. Overall, 90% (n = 169) of the patients harbored a GA which could be explored for therapeutic intervention, with 54% (n = 107) harboring more than one putative target.
Pubmed ID: 29895903 RIS Download
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A portal that provides visualization, analysis and download of large-scale cancer genomics data sets.
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Database to store and display somatic mutation information and related details and contains information relating to human cancers. The mutation data and associated information is extracted from the primary literature. In order to provide a consistent view of the data a histology and tissue ontology has been created and all mutations are mapped to a single version of each gene. The data can be queried by tissue, histology or gene and displayed as a graph, as a table or exported in various formats.
Some key features of COSMIC are:
* Contains information on publications, samples and mutations. Includes samples which have been found to be negative for mutations during screening therefore enabling frequency data to be calculated for mutations in different genes in different cancer types.
* Samples entered include benign neoplasms and other benign proliferations, in situ and invasive tumours, recurrences, metastases and cancer cell lines.
Database of human genes that provides concise genomic, proteomic, transcriptomic, genetic and functional information on all known and predicted human genes. Information featured in GeneCards includes orthologies, disease relationships, mutations and SNPs, gene expression, gene function, pathways, protein-protein interactions, related drugs and compounds and direct links to cutting edge research reagents and tools such as antibodies, recombinant proteins, clones, expression assays and RNAi reagents.
View all literature mentionsA dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.
View all literature mentionsPrecision oncology knowledge base which contains information about the effects and treatment implications of specific cancer gene alterations. OncoKB contains detailed information about specific alterations in 418 cancer genes. Each variant entry contains biological effect, prevalence, prognostic information, and treatment implications. Information is curated from various sources, such as guidelines from the FDA, ClinicalTrials.gov, and scientific literature by a network of clinical fellows, research fellows, and faculty members at Memorial Sloan Kettering Cancer Center.
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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