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Defining signatures of arm-wise copy number change and their associated drivers in kidney cancers

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posted on 2023-06-09, 20:09 authored by Graeme Benstead-Hume, Sarah Wooller, Jessica Downs, Frances PearlFrances Pearl
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 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

History

Publication status

  • Published

File Version

  • Published version

Journal

International Journal of Molecular Sciences

ISSN

1661-6596

Publisher

MDPI

Issue

22

Volume

20

Article number

a5762

Department affiliated with

  • Biochemistry Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2020-01-08

First Open Access (FOA) Date

2020-01-08

First Compliant Deposit (FCD) Date

2020-01-07

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