ijms-20-05762-v2.pdf (2.66 MB)
Defining signatures of arm-wise copy number change and their associated drivers in kidney cancers
journal contribution
posted on 2023-06-09, 20:09 authored by Graeme Benstead-Hume, Sarah Wooller, Jessica Downs, Frances PearlFrances PearlUsing pan-cancer data from The Cancer Genome Atlas (TCGA), we investigated how patterns in copy number alterations in cancer cells vary both by tissue type and as a function of genetic alteration. We find that patterns in both chromosomal ploidy and individual arm copy number are dependent on tumour type. We highlight for example, the significant losses in chromosome arm 3p and the gain of ploidy in 5q in kidney clear cell renal cell carcinoma tissue samples. We find that specific gene mutations are associated with genome-wide copy number changes. Using signatures derived from non-negative matrix factorisation (NMF), we also find gene mutations that are associated with particular patterns of ploidy change. Finally, utilising a set of machine learning classifiers, we successfully predicted the presence of mutated genes in a sample using arm-wise copy number patterns as features. This demonstrates that mutations in specific genes are correlated and may lead to specific patterns of ploidy loss and gain across chromosome arms. Using these same classifiers, we highlight which arms are most predictive of commonly mutated genes in kidney renal clear cell carcinoma (KIRC).
Funding
MR/N50189X/1; Medical Research Council
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Publication status
- Published
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- Published version
Journal
International Journal of Molecular SciencesISSN
1661-6596Publisher
MDPIExternal DOI
Issue
22Volume
20Article number
a5762Department affiliated with
- Biochemistry Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2020-01-08First Open Access (FOA) Date
2020-01-08First Compliant Deposit (FCD) Date
2020-01-07Usage metrics
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