Abstract:
:Somatic copy number alterations (SCNAs) affecting oncogenic drivers have a firmly established role in promoting cancer. However, no agreed-upon standard exists for calling locus-specific amplifications and deletions in each patient sample. Here, we report the correlative analysis of copy number amplitude and length with gene expression across 6,109 samples from The Cancer Genome Atlas (TCGA) dataset across 16 cancer types. Using specificity, sensitivity, and precision-based scores, we assigned optimized amplitude and length cutoffs for nine recurrent SCNAs affecting known oncogenic drivers, using mRNA expression as a functional readout. These cutoffs captured the majority of SCNA-driven, highly-expression-altered samples. The majority of oncogenes required only amplitude cutoffs, as high amplitude samples were almost invariably focal; however, CDKN2A and PTEN uniquely required both amplitude and length cutoffs as primary predictors. For PTEN, these extended to downstream AKT activation. In contrast, SCNA genes located peri-telomerically or in fragile sites showed poor expression-copy number correlations. Overall, our analyses identify optimized amplitude and length cutoffs as efficient predictors of gene expression changes for specific oncogenic SCNAs, yet warn against one-size-fits-all interpretations across all loci. Our results have implications for cancer data analyses and the clinic, where copy number and mutation data are increasingly used to personalize cancer therapy.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Roszik J,Wu CJ,Siroy AE,Lazar AJ,Davies MA,Woodman SE,Kwong LNdoi
10.1038/srep19649subject
Has Abstractpub_date
2016-01-20 00:00:00pages
19649issn
2045-2322pii
srep19649journal_volume
6pub_type
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