85 research outputs found

    Systematic Genetic Analysis Identifies Cis-eQTL Target Genes Associated with Glioblastoma Patient Survival

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    <div><p>Prior expression quantitative trait locus (eQTL) studies have demonstrated heritable variation determining differences in gene expression. The majority of eQTL studies were based on cell lines and normal tissues. We performed cis-eQTL analysis using glioblastoma multiforme (GBM) data sets obtained from The Cancer Genome Atlas (TCGA) to systematically investigate germline variation’s contribution to tumor gene expression levels. We identified 985 significant cis-eQTL associations (FDR<0.05) mapped to 978 SNP loci and 159 unique genes. Approximately 57% of these eQTLs have been previously linked to the gene expression in cell lines and normal tissues; 43% of these share cis associations known to be associated with functional annotations. About 25% of these cis-eQTL associations are also common to those identified in Breast Cancer from a recent study. Further investigation of the relationship between gene expression and patient clinical information identified 13 eQTL genes whose expression level significantly correlates with GBM patient survival (p<0.05). Most of these genes are also differentially expressed in tumor samples and organ-specific controls (p<0.05). Our results demonstrated a significant relationship of germline variation with gene expression levels in GBM. The identification of eQTLs-based expression associated survival might be important to the understanding of genetic contribution to GBM cancer prognosis.</p></div

    Kaplan-Meier survival plots for cis-eQTL target genes TAPBPL, SEMA3E, H1F0 and SERPINB9.

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    <p>The overall survival of GBM patients was used for the survival analysis. Expression values of a gene were dichotomized into high and low expression using the median as a cutoff. Green line: low expression and red line: high expression.</p

    Correlation of gene expression and genotypes.

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    <p><b>A.</b> Correlation between TAPBPL gene expression and different genotype groups of cis-eQTLs in GBM samples. Eight cis-eQTLs were significantly associated with TAPBPL expression. All of these cis-eQTLs have been reported to be shared between GBM tumors and monocytes/lymphoblastoid. <b>B.</b> Correlation between SERPINB9 gene expression and different genotype groups of cis-eQTLs in GBM samples. Three cis-eQTLs were significantly associated with SERPINB9 expression with cis-eQTL rs380779 be reported to beshared between GBM tumors and monocytes; and rs1052886 shared between GBM tumors and monocytes/T-cells.</p

    cis-eQTL/TAPBPL associations shared between GBM and cell lines in Regulome DB.

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    <p>Note: These 8 significant cis-eQTL/TAPBPL associations are also common to those identified from Breast Cancer<sup>7</sup> (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105393#pone.0105393.s010" target="_blank">Table S6</a>).</p

    TAPBPL expression in GBM tumors and organ-specific controls.

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    <p>TAPBPL expression was significant higher in GBM tumor samples compared to organ-specific control samples (p = 3.27E-08).</p

    Sharing of cis-eQTL associations among different studies.

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    <p><b>A.</b> cis-eQTL associations shared between GBM tumors and normal tissues/cell lines in RegulomeDB. Of 985 significant transcript-genotype associations in GBM, 57.1% (24.5%+32.7%) shared the same cis-eQTL/gene pair with cell lines or normal tissues (“Match”); 13.2% (5.3%+7.9%) shared the same cis-eQTLs which are associated with the gene in the neighbor of the target gene identified from GBM (“Match Neighbor”). ReguomeDB variant classification: category 1- known eQTLs for genes; category 6–unknown. <b>B.</b> cis-eQTL associations shared between GBM tumors identified from this study and breast cancer samples identified from a published study. Of 985 significant transcript-genotype associations in GBM, 242 (24.57%) shared the same cis-eQTL associations with breast cancer samples.</p

    Discovery Analysis of TCGA Data Reveals Association between Germline Genotype and Survival in Ovarian Cancer Patients

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    <div><p>Background</p><p>Ovarian cancer remains a significant public health burden, with the highest mortality rate of all the gynecological cancers. This is attributable to the late stage at which the majority of ovarian cancers are diagnosed, coupled with the low and variable response of advanced tumors to standard chemotherapies. To date, clinically useful predictors of treatment response remain lacking. Identifying the genetic determinants of ovarian cancer survival and treatment response is crucial to the development of prognostic biomarkers and personalized therapies that may improve outcomes for the late-stage patients who comprise the majority of cases.</p> <p>Methods</p><p>To identify constitutional genetic variations contributing to ovarian cancer mortality, we systematically investigated associations between germline polymorphisms and ovarian cancer survival using data from The Cancer Genome Atlas Project (TCGA). Using stage-stratified Cox proportional hazards regression, we examined 650,000 SNP loci for association with survival. We additionally examined whether the association of significant SNPs with survival was modified by somatic alterations.</p> <p>Results</p><p>Germline polymorphisms at rs4934282 (AGAP11/C10orf116) and rs1857623 (DNAH14) were associated with stage-adjusted survival ( = 1.12e-07 and 1.80e-07, FDR  = 1.2e-04 and 2.4e-04, respectively). A third SNP, rs4869 (C10orf116), was additionally identified as significant in the exome sequencing data; it is in near-perfect LD with rs4934282. The associations with survival remained significant when somatic alterations.</p> <p>Conclusions</p><p>Discovery analysis of TCGA data reveals germline genetic variations that may play a role in ovarian cancer survival even among late-stage cases. The significant loci are located near genes previously reported as having a possible relationship to platinum and taxol response. Because the variant alleles at the significant loci are common (frequencies for rs4934282 A/C alleles = 0.54/0.46, respectively; rs1857623 A/G alleles = 0.55/0.45, respectively) and germline variants can be assayed noninvasively, our findings provide potential targets for further exploration as prognostic biomarkers and individualized therapies.</p> </div

    Stage and age at diagnosis, organized by 5-year survival.

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    <p>Stage and age at diagnosis of samples, organized by 5-year survival. Median age is reported, with the first and third quartiles given in parentheses. values for the univariate association between stage and survival and age and survival (logrank test) are also given.</p

    Stage-adjusted survival.

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    <p>Significant survival associations after stratification by stage; rs4934282 and rs1857623 are from SNP6 data, rs4869 is from exome/capture data (29 SNPs tested). All tests of Schoefeld residuals had , meeting the proportional hazards assumption.</p
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