Defining Signatures of Arm-Wise Copy Number Change and Their Associated Drivers in Kidney Cancers.
Date
2019-11-16ICR Author
Author
Benstead-Hume, G
Wooller, SK
Downs, JA
Pearl, FMG
Type
Journal Article
Metadata
Show full item recordAbstract
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).
Collections
Subject
aneuploidy
copy number
machine learning
mutational signature
non-negative matrix factorisation
Area Under Curve
Carcinoma, Renal Cell
Chromosomes
DNA Copy Number Variations
Humans
Kidney Neoplasms
Machine Learning
Mutation
Ploidies
ROC Curve
Tumor Suppressor Protein p53
Von Hippel-Lindau Tumor Suppressor Protein
Research team
Genome Stability
Language
eng
Date accepted
2019-11-14
License start date
2019-11-16
Citation
International Journal of Molecular Sciences, 2019, 20 (22), pp. E5762 -
Publisher
MDPI