Pathway Analysis of Single-Nucleotide Polymorphisms Potentially Associated with Glioblastoma Multiforme Susceptibility Using Random Forests

Chang, Jeffrey S.; Yeh, Ru-Fang; Wiencke, John K.; Wiemels, Joseph L.; Смирнов, Иван; Pico, Alexander R.; Tihan, Tarık; Patoka, Joe; Miike, Rei; Sison, Jennette D.; Rice, Terri; Wrensch, Margaret

doi:10.1158/1055-9965.epi-07-2830

Cited by 74 publications

(68 citation statements)

References 29 publications

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“…To date, a few molecular epidemiological studies have investigated the association between the EXO1 Glu589Lys polymorphism and the cancer risk including lung cancer (Zienolddiny et al, 2006;Jin et al, 2008;Hsu et al, 2008), glioma (Chang et al, 2008), breast cancer , gastric cancer (Bau et al, 2009), oral cancer , melanoma (Ibarrola-Villava et al, 2011), cervical (Luo et al, 2012), hepatocellular cancer (Bayram et al, 2012). However, no consistent conclusion has been drawn.…”

Section: Research Articlementioning

confidence: 99%

“…The study selection process is shown in Figure 1. A total of 10 case-control studies including 4391 cases and 4339 controls were analyzed in this metaanalysis (Zienolddiny et al, 2006;Chang et al, 2008;Hsu et al, 2008;Jin et al, 2008;Wang et al, 2009;Bau et al, 2009;Tsai et al, 2009;Ibarrola-Villava et al, 2011;Luo et al, 2012;Bayram et al, 2012). The characteristics of Exonuclease 1 Glu589Lys Gene Polymorphism and Cancer Susceptibility: Evidence Based on a Meta-Analysis selected studies are summarized in Table 1.…”

Section: Characteristics Of Eligible Studiesmentioning

confidence: 99%

“…The sample size in these case-control studies varied considerably (range 110-1272). All studies were case-control studies, including three lung cancer studies (Zienolddiny et al, 2006;Jin et al, 2008;Hsu et al, 2008), and the others including glioma (Chang et al, 2008), breast cancer ), gastric cancer (Bau et al, 2009), oral cancer , melanoma (Ibarrola-Villava et al, 2011), cervical cancer (Luo et al, 2012), hepatocellular carcinoma (Bayram et al, 2012). 6 studies conducted in the Asian population, and 4 in Caucasian population.…”

Section: Characteristics Of Eligible Studiesmentioning

confidence: 99%

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The Exonuclease 1 Glu589Lys Gene Polymorphism and Cancer Susceptibility: Evidence Based on a Meta-analysis

Bayram

2014

Asian Pacific Journal of Cancer Prevention

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Background: Published studies on the association between the exonuclease 1 (EXO1) Glu589Lys polymorphism and cancer susceptibility have yielded conflicting results. Thus, a meta-analysis of published studies was performed to assess the possible association. Materials and Methods: All eligible case-control studies published up to January 2013 on the association between the EXO1 Glu589Lys polymorphism and cancer susceptibility were identified by searching PubMed, Web of Science, Science Direct and hand search. Either fixed-effect or random-effect models were used to calculate pooled odds ratios (ORs) with 95% confidence intervals (CIs) using the Comprehensive Meta-Analysis software version 2.2. Results: A total of 4,391 cancer cases and 4,339 controls from 10 studies were included. Overall, no significant association between the EXO1 Glu589Lys polymorphism and cancer susceptibility was observed in either genetic model. However; in subgroup analyses by cancer type, a significant association between EXO1 Glu589Lys and lung cancer risk was found (Lys

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Section: Research Articlementioning

confidence: 99%

Section: Characteristics Of Eligible Studiesmentioning

confidence: 99%

Section: Characteristics Of Eligible Studiesmentioning

confidence: 99%

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The Exonuclease 1 Glu589Lys Gene Polymorphism and Cancer Susceptibility: Evidence Based on a Meta-analysis

Bayram

2014

Asian Pacific Journal of Cancer Prevention

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“…We have listed about 20 epidemiological studies reporting positive associations between DNA repair polymorphisms and cancer risk (Table 1 [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45] ). Only a small proportion of studies were large (five studies were more than 500 pair cases and controls) and population based; however, some consistencies in results are apparent.…”

Section: Pbts Molecular Epidemiologic Studies With Focus On Dna Repairmentioning

confidence: 99%

Molecular Epidemiology of Primary Brain Tumors

Liu

Kyritsis

et al. 2009

Neurotherapeutics

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Summary:Although primary brain tumors (PBTs) are generally considered to be a multifactorial disorder, understanding the genetic basis and etiology of the disease is essential for PBT risk assessment. Understanding of the genetic susceptibility for PBT has come from studies of rare genetic syndromes, linkage analysis, family aggregation, early-onset pediatric cases, and mutagen sensitivity. There are currently no effective markers to assess biological dose of exposures and genetic heterogeneity. The priorities recently recommended by the Brain Tumor Epidemiology Consortium emphasized the need for expanding research in genetics and molecular epidemiology. In this article, we review the literature to identify molecular epidemiologic case-control studies of PBTs that were hypothesis-driven and focused on four hypothesized candidate pathways: DNA repair, cell cycle, metabolism, and inflammation. We summarize the results in terms of genetic associations of single nucleotide polymorphisms of these pathways. We also discuss future research directions based on available evidence and technologies, and conclude that high resolution whole genome approach with significantly large sample size could rapidly advance our understanding of the genetic etiology of PBTs. Literature searches were done on PubMed in March 2009 with the terms glioma, glioblastoma, brain tumor, association, and polymorphism, and we only reviewed English language publications.

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“…[9][10][11] Overall, random forests is among the best approaches for analyzing survival time using gene expression data. [12][13][14] In this article, we introduce one of the first methods to correlate SNP with survival outcomes.…”

Section: Introductionmentioning

confidence: 99%

Pathway-based identification of SNPs predictive of survival

2011

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In recent years, several association analysis methods for case-control studies have been developed. However, as we turn towards the identification of single nucleotide polymorphisms (SNPs) for prognosis, there is a need to develop methods for the identification of SNPs in high dimensional data with survival outcomes. Traditional methods for the identification of SNPs have some drawbacks. First, the majority of the approaches for case-control studies are based on single SNPs. Second, SNPs that are identified without incorporating biological knowledge are more difficult to interpret. Random forests has been found to perform well in gene expression analysis with survival outcomes. In this paper we present the first pathway-based method to correlate SNP with survival outcomes using a machine learning algorithm. We illustrate the application of pathway-based analysis of SNPs predictive of survival with a data set of 192 multiple myeloma patients genotyped for 500 000 SNPs. We also present simulation studies that show that the random forests technique with log-rank score split criterion outperforms several other machine learning algorithms. Thus, pathway-based survival analysis using machine learning tools represents a promising approach for the identification of biologically meaningful SNPs associated with disease.

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Pathway Analysis of Single-Nucleotide Polymorphisms Potentially Associated with Glioblastoma Multiforme Susceptibility Using Random Forests

Cited by 74 publications

References 29 publications

The Exonuclease 1 Glu589Lys Gene Polymorphism and Cancer Susceptibility: Evidence Based on a Meta-analysis

The Exonuclease 1 Glu589Lys Gene Polymorphism and Cancer Susceptibility: Evidence Based on a Meta-analysis

Molecular Epidemiology of Primary Brain Tumors

Pathway-based identification of SNPs predictive of survival

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