PanCNV Explorer: A pan-cancer database for copy number variations.
Kornrumpf, K.; Dönitz, J.
Show abstract
IntroductionCopy number variations (CNVs) are structural genomic alterations that involve changes in the number of copies of specific DNA regions. These variations can include deletions, duplications, and more complex rearrangements, and play a critical role in cancer progression by amplifying oncogenes, deleting tumor suppressor genes, or altering other key genomic regions. Despite the importance of CNVs in cancer biology, there is a lack of comprehensive resources that aggregate CNV data across multiple cancer types, impeding the exploration of their role in different malignancies. The PanCNV-Explorer was developed to fill this gap by providing a pan-cancer resource that integrates CNV data for over 21 cancer types. MethodsThe PanCNV-Explorer was developed, utilizing data from repositories such as COSMIC, DepMap, DGV, and dbVAR. Amplifications and deletions can be visualized, with detailed chromosome-specific plots highlighting CNV patterns. In addition, a genome browser has been implemented to display regions of interest for searching for genes of potential relevance. ResultsThe database contains over 5 million CNVs from 15,809 samples, spanning 21 primary cancer types. Pathogenic CNVs from ClinVar and DepMap were compared to benign data from DGV and dbVAR, allowing a comprehensive analysis across tissues. CNV patterns were visualized for individual cancers. We demonstrate with use cases, focusing on common oncogenes such as MYC and tumor suppressor genes such as TP53, the ability of the resource to search for cancer driver genes. For example, chromosome 12 in pancreatic cancer showed frequent amplifications in the region containing the KRAS oncogene. In another example, we show how driver gene candidates already described in certain cancer entities can also be found with high frequency in other entities. ConclusionThe PanCNV-Explorer provides a valuable resource for pan-cancer CNV analysis, facilitating the exploration of CNV-driven tumor heterogeneity. The integrated visualization tools and genome browser enable detailed exploration of genomic regions, enhancing cancer research. As a valuable and easy-to-use platform that allows researchers to quantify and compare CNVs across cancer types, the PanCNV-Explorer is an essential tool for advancing cancer genomics research. The main page is available at https://mtb.bioinf.med.uni-goettingen.de/pancnv-explorer/.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Prevalence and spectrum of germline BRCA1 and BRCA2 mutations in multiethnic cohort of breast cancer patients in Brunei Darussalam 94%
- Comparative analysis of novel MGISEQ-2000 sequencing platform vs Illumina HiSeq 2500 for whole-genome sequencing 94%
- Novel candidates of pathogenic variants of the BRCA1 and BRCA2 genes in a 3,552 Japanese whole-genome sequence dataset (3.5KJPNv2) 94%
Similar papers in this journal
- A comparison of tools for copy-number variation detection in germline whole exome and whole genome sequencing data 93%
- Development of a Single Molecule Counting Assay to Differentiate Chromophobe Renal Cancer and Oncocytoma in Clinics 93%
- Deep sequencing of early T stage colorectal cancers reveals disruption of homologous recombination repair in microsatellite stable tumours with high mutational burdens 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.