Defining Signatures of Arm-Wise Copy Number Change and Their Associated Drivers in Kidney Cancers.
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ICR Authors
Authors
Benstead-Hume, G
Wooller, SK
Downs, JA
Pearl, FMG
Wooller, SK
Downs, JA
Pearl, FMG
Document Type
Journal Article
Date
2019-11-16
Date Accepted
2019-11-14
Abstract
Using 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 factorisation, 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).
Citation
International Journal of Molecular Sciences, 2019, 20 (22), pp. E5762 -
Source Title
International Journal of Molecular Sciences
Publisher
MDPI
ISSN
1422-0067
eISSN
1422-0067
1422-0067
1422-0067
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Research Team
Genome Stability