ArticleGenes, chromosomes & cancer2023
A cloud-based resource for genome coordinate-based exploration and large-scale analysis of chromosome aberrations and gene fusions in cancer.
Article in Genes, chromosomes & cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- A Practical Compass to Biological Digital Resources and Omics Integration in Ewing Sarcoma.Methods in molecular biology (Clifton, N.J.) · 2027Article
- Cancer-associated fusion transcripts: mechanisms, functional roles, and clinical implications.Clinical and experimental medicine · 2026Review
- Tumor heterogeneity: development, mechanisms, and therapeutic implications.Signal transduction and targeted therapy · 2026Review
- Pervasive chromosomal instability drives the karyotypic evolution of hypodiploid tumours.Genome medicine · 2026Article
- SCAN-ACT: adoptive T cell therapy target discovery through single-cell transcriptomics.Genome medicine · 2025Article
- A Guide to Extrachromosomal DNA: Cancer's Dynamic Circular Genome.Cancer discovery · 2025Review
- Autosomal-dominant macular dystrophy linked to a chromosome 17 tandem duplication.JCI insight · 2024Article
- NCI Cancer Research Data Commons: Cloud-Based Analytic Resources.Cancer research · 2024Review
- Chromosomal Aberration t(14;17)(q32;q21) Simultaneously Activates HOXB5 and miR10a in Triple-Hit B-Cell Lymphoma.Biomedicines · 2023Article
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Authors and funding
13 authors at 7 institutions in 3 countries.
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Abstract
Cytogenetic analysis provides important information on the genetic mechanisms of cancer. The Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer (Mitelman DB) is the largest catalog of acquired chromosome aberrations, presently comprising >70 000 cases across multiple cancer types. Although this resource has enabled the identification of chromosome abnormalities leading to specific cancers and cancer mechanisms, a large-scale, systematic analysis of these aberrations and their downstream implications has been difficult due to the lack of a standard, automated mapping from aberrations to genomic coordinates. We previously introduced CytoConverter as a tool that automates such conversions. CytoConverter has now been updated with improved interpretation of karyotypes and has been integrated with the Mitelman DB, providing a comprehensive mapping of the 70 000+ cases to genomic coordinates, as well as visualization of the frequencies of chromosomal gains and losses. Importantly, all CytoConverter-generated genomic coordinates are publicly available in Google BigQuery, a cloud-based data warehouse, facilitating data exploration and integration with other datasets hosted by the Institute for Systems Biology Cancer Gateway in the Cloud (ISB-CGC) Resource. We demonstrate the use of BigQuery for integrative analysis of Mitelman DB with other cancer datasets, including a comparison of the frequency of imbalances identified in Mitelman DB cases with those found in The Cancer Genome Atlas (TCGA) copy number datasets. This solution provides opportunities to leverage the power of cloud computing for low-cost, scalable, and integrated analysis of chromosome aberrations and gene fusions in cancer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.