Pan-cancer copy number variant analysis identifies optimized size thresholds and co-occurrence models for individualized risk-stratification

Author:

Raleigh David1ORCID,Nguyen Minh1,Chen William2ORCID,Zakimi Naomi3,Mirchia Kanish3ORCID,Lucas Calixto-Hope4ORCID

Affiliation:

1. University of California San Francisco

2. UCSF

3. Univeristy of California San Francisco

4. Johns Hopkins University

Abstract

Abstract Chromosome instability leading to accumulation of copy number gains or losses is a hallmark of cancer. Copy number variant (CNV) signatures are increasingly used for clinical risk-stratification, but size thresholds for defining CNVs are variable and the biological or clinical implications of CNV size heterogeneity or co-occurrence patterns are incompletely understood. Here we analyze CNV and clinical data from 565 meningiomas and 9,885 tumors from The Cancer Genome Atlas (TCGA) to develop tumor- and chromosome-specific CNV size-dependent and co-occurrence models for clinical outcomes. Our results reveal prognostic CNVs with optimized size thresholds and co-occurrence patterns that refine risk-stratification across a diversity of human cancers.

Publisher

Research Square Platform LLC

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