Generalized singular value decomposition (GSVD) comparison of patient-matched normal and tumor aCGH profiles reveals global copy-number alterations predicting glioblastoma multiforme survival

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Publication Type thesis
School or College College of Engineering
Department Biomedical Engineering
Author Sankaranarayanan, Preethi
Title Generalized singular value decomposition (GSVD) comparison of patient-matched normal and tumor aCGH profiles reveals global copy-number alterations predicting glioblastoma multiforme survival
Date 2013-05
Description Despite recent large-scale profiling efforts, the best prognostic predictor of glioblastoma multiforme (GBM) remains the patient's age at diagnosis. We describe a global pattern of tumor-exclusive co-occurring copy-number alterations (CNAs) that is correlated, possibly coordinated with GBM patients' survival and response to chemotherapy. The pattern is revealed by generalized singular value decomposition (GSVD) comparison of patient-matched but probeindependent GBM and normal aCGH datasets from The Cancer Genome Atlas (TCGA). We find that, first, the GSVD, formulated as a framework for comparatively modeling two composite datasets, removes from the pattern copynumber variations (CNVs) that occur in the normal human genome (e.g., femalespecific X chromosome amplification) and experimental variations (e.g., in tissue batch, genomic center, hybridization date and scanner), without a-priori knowledge of these variations. Second, the pattern includes most known GBMassociated changes in chromosome numbers and focal CNAs, as well as several previously unreported CNAs in > 3% of the patients. These included the biochemically putative drug target, cell cycle-regulated serine/threonine kinaseencoding TLK2, the cyclin El-encoding CCNE1, and the Rb-binding histone demethylase-encoding KDM5A. Third, the pattern provides a better prognostic predictor than the chromosome numbers or any one focal CNA that it identifies, suggesting that the GBM survival phenotype is an outcome of its global genotype. The pattern is independent of age, and combined with age, makes a better predictor than age alone. GSVD comparison of matched profiles of a larger set of TCGA patients, inclusive of the initial set, confirms the global pattern. GSVD classification of the GBM profiles of an independent set of patients validates the prognostic contribution of the pattern.
Type Text
Publisher University of Utah
Subject Copy number; Glioblastoma multiforme; GSVD
Dissertation Institution University of Utah
Dissertation Name Master of Science
Language eng
Rights Management Copyright © Preethi Sankaranarayanan 2013
Format Medium application/pdf
Format Extent 919,183 bytes
ARK ark:/87278/s64f25j7
Setname ir_etd
ID 195796
Reference URL https://collections.lib.utah.edu/ark:/87278/s64f25j7