Supplemental material for C. H. Lee,* B. O. Alpert,* P. Sankaranarayanan and O. Alter, "GSVD Comparison of Patient-Matched Normal and Tumor aCGH Profiles Reveals Global Copy-Number Alterations Predicting Glioblastoma Multiforme Survival," Public Library of Science (PLoS) One 7 (1), article e30098 (January 2012); doi: 10.1371/journal.pone.0030098.
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Abstract:
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 GSVD comparison of patient-matched but probe-independent 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 copy-number variations (CNVs) that occur in the normal human genome (e.g., female-specific 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 GBM-associated changes in chromosome numbers and focal CNAs, as well as several previously unreported CNAs in >3% of the patients. These include the biochemically putative drug target, cell cycle-regulated serine/threonine kinase-encoding TLK2, the cyclin E1-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.

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Lee_Alpert_et_al_PLoS_One_2012.pdf

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Lee_Alpert_et_al_PLoS_One_2012_Appendix.pdf

• Dataset S1: 251_Patients.txt

Initial set of 251 patients.
A tab-delimited text format file, readable by both Mathematica and Microsoft Excel, reproducing annotations of the initial set of 251 patients and the corresponding normal and tumor samples. The tumor and normal profiles of the initial set of 251 patients, in tab-delimited text format files, tabulating log₂ relative copy-number variation across 212,696 and 211,227 tumor and normal probes, respectively, are:

• 251_Tumor.txt

• 251_Normal.txt

• Dataset S2: 251_Segments.txt

Segments of the significant tumor and normal arraylets, computed by GSVD for the initial set of 251 patients.
A tab-delimited text format file, readable by both Mathematica and Microsoft Excel, tabulating segments identified by the circular binary segmentation (CBS) of Olshen et al. and Venkatraman and Olshen.

• Dataset S3: 251_Tumor_Arraylet_2.txt

Segments of the second tumor arraylet computed by GSVD for the initial set of 251 patients.
A tab-delimited text format file, readable by both Mathematica and Microsoft Excel, tabulating, for each of the 130 CBS segments of the second tumor arraylet, the segment's coordinates, the CBS P-value, and the log-rank test P-value corresponding to the Kaplan-Meier (KM) survival analysis of the initial set of 251 patients classified by either a gain or a loss of this segment.

• Dataset S4: 344_Patients.txt

Inclusive confirmation set of 344 patients.
A tab-delimited text format file, readable by both Mathematica and Microsoft Excel, reproducing the TCGA annotations of the inclusive confirmation set of 344 patients. The tumor and normal profiles of the inclusive confirmation set of 344 patients, in tab-delimited text format files, tabulating log₂ relative copy-number variation across 200,139 and 198,342 tumor and normal probes, respectively, are:

• 344_Tumor.txt

• 344_Normal.txt

• Dataset S5: 184_Patients.txt

Independent validation set of 184 patients.
A tab-delimited text format file, readable by both Mathematica and Microsoft Excel, reproducing the TCGA annotations of the independent validation set of 184 patients. The tumor profiles of the independent validation set of 184 patients, in a tab-delimited text format file, tabulating log₂ relative copy-number variation across 212,696 autosomal and X chromosome probes, are:

• 184_Tumor.txt