Gene Set Analysis of Survival Following Ovarian Cancer Implicates Macrolide Binding and Intracellular Signaling Genes

Fridley, Brooke L.; Jenkins, Gregory D.; Tsai, Ya Yu; Song, Honglin; Bolton, Kelly L.; Fenstermacher, David; Tyrer, Jonathan P.; Ramus, Susan J.; Cunningham, Julie M.; Vierkant, Robert A.; Chen, Zhihua; Chen, Y. Ann; Iversen, Ed; Menon, Usha; Gentry‐Maharaj, Aleksandra; Schildkraut, Joellen M.; Sutphen, Rebecca; Gayther, Simon A.; Hartmann, Lynn C.; Pharoah, Paul D.P.; Sellers, Thomas A.; Goode, Ellen L.

doi:10.1158/1055-9965.epi-11-0741

Cited by 7 publications

(5 citation statements)

References 39 publications

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“…In completing the mapping, SNPs could be mapped to multiple genes, and genes could be mapped to multiple GSs. Once the mapping of SNPs to genes and genes to GSs was completed, GSA was completed using PC-GM approach (Biernacka et al, 2011;Fridley et al, 2012), which uses a principal component analysis (PCA) (Gauderman et al, 2007;Mardia et al, 1979) in FIG. 1.…”

Section: Integrative Gene Set Analysismentioning

confidence: 99%

Integrative Gene Set Analysis: Application to Platinum Pharmacogenomics

Fridley

Abo

Tan

et al. 2014

OMICS: A Journal of Integrative Biology

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Integrative genomics has the potential to uncover relevant loci, as clinical outcome and response to chemotherapies are most likely not due to a single gene (or data type) but rather a complex relationship involving genetic variation, mRNA, DNA methylation, and copy number variation. In addition to this complexity, many complex phenotypes are thought to be controlled by the interplay of multiple genes within the same molecular pathway or gene set (GS). To address these two challenges, we propose an integrative gene set analysis approach and apply this strategy to a cisplatin (CDDP) pharmacogenomics study involving lymphoblastoid cell lines for which genome-wide SNP and mRNA expression data was collected. Application of the integrative GS analysis implicated the role of the RNA binding and cytoskeletal part GSs. The genes LMNB1 and CENPF, within the cytoskeletal part GS, were functionally validated with siRNA knockdown experiments, where the knockdown of LMNB1 and CENPF resulted in CDDP resistance in multiple cancer cell lines. This study demonstrates the utility of an integrative GS analysis strategy for detecting novel genes associated with response to cancer therapies, moving closer to tailored therapy decisions for cancer patients.

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Section: Integrative Gene Set Analysismentioning

confidence: 99%

Integrative Gene Set Analysis: Application to Platinum Pharmacogenomics

Fridley

Abo

Tan

et al. 2014

OMICS: A Journal of Integrative Biology

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“…chemotherapy) could not be included as covariates or stratification factors due to a large amount of missing data; both should be examined in future genetic studies to assess their impact on survival outcomes. Finally, it should be noted that some of the data analyzed here were not independent from previous OCAC EOC overall survival reports (5, 10, 38); specifically, some variants on the exome arrays were also on GWAS or candidate gene arrays which had previously been used on a subset of the current patients. However, the vast majority of the current array content was largely used to test the novel rare variant hypothesis.…”

Section: Discussionmentioning

confidence: 92%

Investigation of Exomic Variants Associated with Overall Survival in Ovarian Cancer

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2016

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background While numerous susceptibility loci for epithelial ovarian cancer (EOC) have been identified, few associations have been reported with overall survival. In the absence of common prognostic genetic markers, we hypothesize that rare coding variants may be associated with overall EOC survival and assessed their contribution in two exome-based genotyping projects of the Ovarian Cancer Association Consortium (OCAC). Methods The primary patient set (Set 1) included 14 independent EOC studies (4293 patients) and 227,892 variants, and a secondary patient set (Set 2) included six additional EOC studies (1744 patients) and 114,620 variants. Because power to detect rare variants individually is reduced, gene-level tests were conducted. Sets were analyzed separately at individual variants and by gene, and then combined with meta-analyses (73,203 variants and 13,163 genes overlapped). Results No individual variant reached genome-wide statistical significance. A SNP previously implicated to be associated with EOC risk and, to a lesser extent, survival, rs8170, showed the strongest evidence of association with survival and similar effect size estimates across sets (Pmeta=1.1E-6, HRSet1=1.17, HRSet2=1.14). Rare variants in ATG2B, an autophagy gene important for apoptosis, were significantly associated with survival after multiple testing correction (Pmeta=1.1E-6; Pcorrected=0.01). Conclusions Common variant rs8170 and rare variants in ATG2B may be associated with EOC overall survival, although further study is needed. Impact This study represents the first exome-wide association study of EOC survival to include rare variant analyses, and suggests that complementary single variant and gene-level analyses in large studies are needed to identify rare variants that warrant follow-up study.

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“…In summary, we implemented three different GSEA methods as internal validation to identify the biological pathways consistently associated with bladder cancer risk and also validated our results in an independent NCI population, which may reduce false discovery in our findings. GSEA is a complementary tool to identify additional genetic contributions to the heritability of bladder cancer, and may also be applicable to clinical outcome studies [ 50 ] by incorporating the biological pathway information into GWAS analysis. Our findings may pinpoint potential pathway targets for cancer prevention and treatment and to improve the risk prediction model of bladder cancer.…”

Section: Discussionmentioning

confidence: 99%

Pathway analysis of bladder cancer genome-wide association study identifies novel pathways involved in bladder cancer development

Chen

Rothman

et al. 2016

Genes Cancer

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Genome-wide association studies (GWAS) are designed to identify individual regions associated with cancer risk, but only explain a small fraction of the inherited variability. Alternative approach analyzing genetic variants within biological pathways has been proposed to discover networks of susceptibility genes with additional effects. The gene set enrichment analysis (GSEA) may complement and expand traditional GWAS analysis to identify novel genes and pathways associated with bladder cancer risk. We selected three GSEA methods: Gen-Gen, Aligator, and the SNP Ratio Test to evaluate cellular signaling pathways involved in bladder cancer susceptibility in a Texas GWAS population. The candidate genetic polymorphisms from the significant pathway selected by GSEA were validated in an independent NCI GWAS. We identified 18 novel pathways (P < 0.05) significantly associated with bladder cancer risk. Five of the most promising pathways (P ≤ 0.001 in any of the three GSEA methods) among the 18 pathways included two cell cycle pathways and neural cell adhesion molecule (NCAM), platelet-derived growth factor (PDGF), and unfolded protein response pathways. We validated the candidate polymorphisms in the NCI GWAS and found variants of RAPGEF1, SKP1, HERPUD1, CACNB2, CACNA1C, CACNA1S, COL4A2, SRC, and CACNA1C were associated with bladder cancer risk. Two CCNE1 variants, rs8102137 and rs997669, from cell cycle pathways showed the strongest associations; the CCNE1 signal at 19q12 has already been reported in previous GWAS. These findings offer additional etiologic insights highlighting the specific genes and pathways associated with bladder cancer development. GSEA may be a complementary tool to GWAS to identify additional loci of cancer susceptibility.

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Gene Set Analysis of Survival Following Ovarian Cancer Implicates Macrolide Binding and Intracellular Signaling Genes

Cited by 7 publications

References 39 publications

Integrative Gene Set Analysis: Application to Platinum Pharmacogenomics

Integrative Gene Set Analysis: Application to Platinum Pharmacogenomics

Investigation of Exomic Variants Associated with Overall Survival in Ovarian Cancer

Pathway analysis of bladder cancer genome-wide association study identifies novel pathways involved in bladder cancer development

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