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Nonsynonymous Coding Single-Nucleotide Polymorphisms Spanning the Genome in Relation to Glioblastoma Survival and Age at Diagnosis

Authors' Affiliations: ¹ Division of Neuroepidemiology, Department of Neurological Surgery, School of Medicine, University of California at San Francisco, San Francisco, California; ² Division of Biostatistics, Department of Health Research and Policy, School of Medicine, Stanford University, Stanford, California; ³ Department of Cancer Cell Biology, School of Public Health, Harvard University, Boston, Massachusetts; and ⁴ Affymetrix, Santa Clara, California

Requests for reprints: Margaret Wrensch, Neuroepidemiology Division, Department of Neurological Surgery, University of California at San Francisco, 44 Page Street, Suite 503, San Francisco, CA 94102. Phone: 415-476-1979; Fax: 415-502-1787; E-mail: margaret.wrensch{at}ucsf.edu.

Purpose: Our aim was to discover possible inherited factors associated with glioblastoma age at diagnosis and survival. Although new genotyping technologies allow greatly expanded exploration of such factors, they pose many challenges.

Experimental Design: In this pilot study, we (a) genotyped 112 newly diagnosed glioblastoma patients ascertained through a population-based study (group 1) with the ParAllele assay panel of 10,000 nonsynonymous coding single-nucleotide polymorphisms (SNP), (b) used several statistical and bioinformatic techniques to identify 17 SNPs potentially related to either glioblastoma age at diagnosis or survival, and (c) genotyped 16 of these SNPs using conventional PCR methods in an independent group of 195 glioblastoma patients (group 2).

Results: In group 2, only one of the 16 SNPs, rs8057643 (located on 16p13.2), was significantly associated with glioblastoma age at diagnosis (nominal P = 0.0017; Bonferroni corrected P = 0.054). Median ages at diagnosis for those with 0, 1, or 2 T alleles were 66, 57, and 59 years in group 1 and 64, 57, and 55 years in group 2 (combined P = 0.001). Furthermore, Cox regression analyses of time to death with number of T alleles adjusted for gender and patient group yielded a hazard ratio of 0.82 (95% confidence interval, 0.68-0.98; P = 0.03).

Conclusions: Although limited by a relatively small sample size, this pilot study, using well-characterized, unambiguous disease characteristics, illustrates the necessity of independent replication owing to the likelihood of false positives. Several other challenges are discussed, including attempts to incorporate information on the potential functional importance of SNPs in genome-disease association studies.

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