CytoCellDB: A Resource Database For Classification and Analysis of Extrachromosomal DNA in Cancer
Fessler, J.; Ting, S.; Yi, H.; Haase, S.; Chen, J.; Gulec, S.; Wang, Y.; Smyers, N.; Goble, K.; Cannon, D.; Mehta, A.; Ford, C.; Brunk, E. C.
Show abstract
Extrachromosomal DNA (ecDNA), or double minute chromosomes, are established cytogenetic markers for malignancy and genome instability. More recently, the cancer community has gained a heightened awareness of the roles of ecDNA in cancer proliferation, drug resistance and epigenetic remodeling. A current hindrance to understanding the biological roles of ecDNA is the lack of available cell line model systems with experimental cytogenetic data that confirm ecDNA status. Although several recent landmark studies have identified common cell lines and tumor models with ecDNA, the current sample size limits our ability to detect ecDNA-driven molecular differences due to limitations in power. Increasing the number of model systems known to express ecDNA would provide new avenues for understanding the fundamental underpinnings of ecDNA biology and would unlock a wealth of potential targeting strategies for ecDNA-driven cancers. To bridge this gap, we created CytoCellDB, a resource that provides karyotype annotations and leverages publicly available global cell line data from the Cancer Dependency Map (DepMap) and the Cancer Cell Line Encyclopedia (CCLE). Here, we identify 139 cell lines that express ecDNA, which is a 200% increase from the current sample size. We expanded the total number of cancer cell lines with ecDNA annotations to 577, which is a 400% increase or 31% of cell lines in CCLE/ DepMap. We demonstrate that a strength of CytoCellDB is the ability to interrogate ecDNA, and a compendium of other chromosomal aberrations, in the context of cancer-specific vulnerabilities, drug sensitivities, and molecular data (genomics, transcriptomics, methylation, proteomics). We anticipate that CytoCellDB will advance cytogenomics research and population-scale discoveries related to ecDNA as well as provide insights into strategies and best practices for determining novel therapeutics that overcome ecDNA-driven drug resistance.
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