Browsing by Subject "pathway analysis"

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    Genetic variants of the peroxisome proliferator-activated receptor (PPAR) signaling pathway genes and risk of pancreatic cancer.
    (Molecular carcinogenesis, 2020-05-05) Liu, Xiaowen; Qian, Danwen; Liu, Hongliang; Abbruzzese, James L; Luo, Sheng; Walsh, Kyle M; Wei, Qingyi
    Because the peroxisome proliferator-activated receptor (PPAR) signaling pathway is involved in development and progression of pancreatic cancer, we investigated associations between genetic variants of the PPAR pathway genes and pancreatic cancer risk by using three published genome-wide association study datasets including 8477 cases and 6946 controls of European ancestry. Expression quantitative trait loci (eQTL) analysis was also performed for correlations between genotypes of the identified genetic variants and messenger RNA (mRNA) expression levels of their genes by using available databases of the 1000 Genomes, TCGA, and GTEx projects. In the single-locus logistic regression analysis, we identified 1141 out of 17 532 significant single-nucleotide polymorphisms (SNPs) in 112 PPAR pathway genes. Further multivariate logistic regression analysis identified three independent, potentially functional loci (rs12947620 in MED1, rs11079651 in PRKCA, and rs34367566 in PRKCB) for pancreatic cancer risk (odds ratio [OR] = 1.11, 95% confidence interval [CI], [1.06-1.17], P = 5.46 × 10-5 ; OR = 1.10, 95% CI, [1.04-1.15], P = 1.99 × 10-4 ; and OR = 1.09, 95% CI, [1.04-1.14], P = 3.16 × 10-4 , respectively) among 65 SNPs that passed multiple comparison correction by false discovery rate (< 0.2). When risk genotypes of these three SNPs were combined, carriers with 2 to 3 unfavorable genotypes (NUGs) had a higher risk of pancreatic cancer than those with 0 to 1 NUGs. The eQTL analysis showed that rs34367566 A>AG was associated with decreased expression levels of PRKCB mRNA in 373 lymphoblastoid cell lines. Our findings indicate that genetic variants of the PPAR pathway genes, particularly MED1, PRKCA, and PRKCB, may contribute to susceptibility to pancreatic cancer.
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    Integrated pathway and epistasis analysis reveals interactive effect of genetic variants at TERF1 and AFAP1L2 loci on melanoma risk.
    (Int J Cancer, 2015-10-15) Brossard, Myriam; Fang, Shenying; Vaysse, Amaury; Wei, Qingyi; Chen, Wei V; Mohamdi, Hamida; Maubec, Eve; Lavielle, Nolwenn; Galan, Pilar; Lathrop, Mark; Avril, Marie-Françoise; Lee, Jeffrey E; Amos, Christopher I; Demenais, Florence
    Genome-wide association studies (GWASs) have characterized 13 loci associated with melanoma, which only account for a small part of melanoma risk. To identify new genes with too small an effect to be detected individually but which collectively influence melanoma risk and/or show interactive effects, we used a two-step analysis strategy including pathway analysis of genome-wide SNP data, in a first step, and epistasis analysis within significant pathways, in a second step. Pathway analysis, using the gene-set enrichment analysis (GSEA) approach and the gene ontology (GO) database, was applied to the outcomes of MELARISK (3,976 subjects) and MDACC (2,827 subjects) GWASs. Cross-gene SNP-SNP interaction analysis within melanoma-associated GOs was performed using the INTERSNP software. Five GO categories were significantly enriched in genes associated with melanoma (false discovery rate ≤ 5% in both studies): response to light stimulus, regulation of mitotic cell cycle, induction of programmed cell death, cytokine activity and oxidative phosphorylation. Epistasis analysis, within each of the five significant GOs, showed significant evidence for interaction for one SNP pair at TERF1 and AFAP1L2 loci (pmeta-int  = 2.0 × 10(-7) , which met both the pathway and overall multiple-testing corrected thresholds that are equal to 9.8 × 10(-7) and 2.0 × 10(-7) , respectively) and suggestive evidence for another pair involving correlated SNPs at the same loci (pmeta-int  = 3.6 × 10(-6) ). This interaction has important biological relevance given the key role of TERF1 in telomere biology and the reported physical interaction between TERF1 and AFAP1L2 proteins. This finding brings a novel piece of evidence for the emerging role of telomere dysfunction into melanoma development.
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    Potential Functional Variants in SMC2 and TP53 in the AURORA Pathway Genes and Risk of Pancreatic Cancer.
    (Carcinogenesis, 2019-02-22) Feng, Yun; Liu, Hongliang; Duan, Bensong; Liu, Zhensheng; Abbruzzese, James; Walsh, Kyle M; Zhang, Xuefeng; Wei, Qingyi
    The AURORA pathway participates in mitosis and cell division, and alterations in mitosis and cell division can lead to carcinogenesis. Therefore, genetic variants in the AURORA pathway genes may be associated with susceptibility to pancreatic cancer. To test this hypothesis, we used three large, publically available pancreatic cancer genome-wide association studies (GWASs) datasets (PanScan I, II/III and PanC4) to assess the associations of 7,168 single nucleotide polymorphisms (SNPs) in a set of 62 genes of this pathway with pancreatic cancer risk (8,477 cases and 6,946 controls of European ancestry). We identify 15 significant pancreatic cancer risk-associated SNPs in three genes (SMC2, ARHGEF7 and TP53) after correction for multiple comparisons by a false discovery rate (FDR) < 0.20. Through further linkage disequilibrium analysis, SNP functional prediction and stepwise logistic regression analysis, we focused on three SNPs: rs3818626 in SMC2, rs79447092 in ARHGEF7 and rs9895829 in TP53. We found that these three SNPs were associated with pancreatic cancer risk [odds ratio (OR) = 1.12, 95% confidence interval (CI) = 1.07-1.17 and P = 2.20E-06 for the rs3818626 C allele; OR = 0.76, CI = 0.66-0.88 and P = 1.46E-04 for the rs79447092 A allele; and OR = 0.82, CI = 0.74-0.91 and P = 1.51E-04 for the rs9895829 G allele]. Their joint effect as the number of protective genotypes (NPGs) also showed a significant association with pancreatic cancer risk (trend test P ≤ 0.001). Finally, we performed an eQTL analysis and found that rs3818626 and rs9895829 were significantly associated with SMC2 and TP53 mRNA expression levels in 373 lymphoblastoid cell lines, respectively. In conclusion, these three representative SNPs may be potentially susceptibility loci for pancreatic cancer and warrant additional validation.