Abstract
Cancers are heterogeneous diseases with unifying features of abnormal and consuming cell growth, where the deregulation of normal cellular functions is initiated by the accumulation of genomic mutations in cells of - potentially - any organ. At diagnosis malignancies typically present with patterns of somatic genome variants on diverse levels of heterogeneity. Among the different types of genomic alterations, copy number variants (CNV) represent a distinct, near-ubiquitous class of structural variants. Cancer classifications are foundational for patient care and oncology research. Terminologies such as the National Cancer Institute Thesaurus provide large sets of hierarchical cancer classification vocabularies and promote data interoperability and ontology-driven computational analysis. To find out how categorical classifications correspond to genomic observations, we conducted a meta-analysis of inter-sample genomic heterogeneity for classification hierarchies on CNV profiles from 97,142 individual samples across 512 cancer entities, and evaluated recurring CNV signatures across diagnostic subsets. Our results highlight specific biological mechanisms across cancer entities with the potential for improvement of patient stratification and future enhancement of cancer classification systems and provide some indications for cooperative genomic events across distinct clinical entities.
Published Version
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