Wang, Liewei

With new technologies, multiple types of genomic data are commonly collected on a single set of samples. However, standard analysis methods concentrate on a single data type at a time and ignore the relationships between genes, proteins, and biochemical reactions that give rise to complex phenotypes. In this paper, we propose a novel integrative model to incorporate multiple types of genomic data into an association analysis with a complex phenotype. The method combines path analysis and stochastic search variable selection into a Bayesian hierarchical model that simultaneously identifies both direct and indirect genomic effects on the phenotype. Results from a simulation study and application of the Bayesian model to a pharmacogenomic study of the drug gemcitabine demonstrate greater sensitivity to detect genomic effects in some simulation scenarios, when compared to the standard single data type analysis. Further research is required to extend and modify this integrative modeling framework to increase computational efficiency to best capitalize on the wealth of information available across multiple genomic data types. Genet. Epidemiol. 36:352–359, 2012. © 2012 Wiley Periodicals, Inc.

Abstract Background and Aims: Cancer and Leukemia Group B 80303 was a randomized, phase III study in patients with advanced pancreatic cancer treated with gemcitabine plus either bevacizumab or placebo. We prospectively collected germline DNA and conducted a genome-wide association study (GWAS) using overall survival (OS) as the endpoint. Experimental Design: DNA from 351 patients was genotyped for more than 550,000 single-nucleotide polymorphisms (SNP). Associations between OS and SNPs were investigated using the log-linear 2-way multiplicative Cox proportional hazards model. The subset of 294 genetically European patients was used for the primary analysis. Results: A nonsynonymous SNP in interleukin (IL)17F (rs763780, H161R) and an intronic SNP in strong linkage disequilibrium (rs7771466) were associated with OS using genome-wide criteria (P ≤ 10−7). Median OS was significantly shorter (P = 2.61 × 10−8) for the rs763780 heterozygotes [3.1 months; 95% confidence interval (CI), 2.3–4.3] than for the patients without this variant (6.8 months; 95% CI, 5.8–7.3). After adjustment by stratification factors, the P value for the association was 9.51 × 10−7. Conclusions: The variant 161R form of IL-17F is a natural antagonist of the antiangiogenic effects of wild-type 161H IL-17F, and angiogenesis may play an important role in the metastatic spread of pancreatic cancer. In this preliminary study, we hypothesize that the angiogenetic potential of pancreatic cancers in patients with variant IL-17F is higher than that of tumors in patients with wild-type IL-17F, conferring worse prognosis. This exploratory GWAS may provide the foundation for testing the biology and clinical effects of novel genes and their heritable variants through mechanistic and confirmatory studies in pancreatic cancer. Clin Cancer Res; 18(2); 577–84. ©2011 AACR.

Abstract Purpose: Inherited variability in the prognosis of lung cancer patients treated with platinum-based chemotherapy has been widely investigated. However, the overall contribution of genetic variation to platinum response is not well established. To identify novel candidate single nucleotide polymorphisms (SNP)/genes, we carried out a genome-wide association study (GWAS) for cisplatin cytotoxicity by using lymphoblastoid cell lines (LCL), followed by an association study of selected SNPs from the GWAS with overall survival (OS) in lung cancer patients. Experimental Design: A GWAS for cisplatin was conducted with 283 ethnically diverse LCLs. A total of 168 top SNPs were genotyped in 222 small cell lung cancer (SCLC) and 961 non-SCLC (NSCLC) patients treated with platinum-based therapy. Association of the SNPs with OS was determined by using the Cox regression model. Selected candidate genes were functionally validated by siRNA knockdown in human lung cancer cells. Results: Among 157 successfully genotyped SNPs, 9 and 10 SNPs were top SNPs associated with OS for patients with NSCLC and SCLC, respectively, although they were not significant after adjusting for multiple testing. Fifteen genes, including 7 located within 200 kb up or downstream of the 4 top SNPs and 8 genes for which expression was correlated with 3 SNPs in LCLs were selected for siRNA screening. Knockdown of DAPK3 and METTL6, for which expression levels were correlated with the rs11169748 and rs2440915 SNPs, significantly decreased cisplatin sensitivity in lung cancer cells. Conclusions: This series of clinical and complementary laboratory-based functional studies identified several candidate genes/SNPs that might help predict treatment outcomes for platinum-based therapy of lung cancer. Clin Cancer Res; 17(17); 5801–11. ©2011 AACR.

Abstract Purpose: Variations in genes related to biological activity of anticancer drugs could influence treatment responses and lung cancer prognosis. Genetic variants in four biological pathways, that is, glutathione metabolism, DNA repair, cell cycle, and epidermal growth factor receptor (EGFR), were systematically investigated to examine their association with survival in advanced stage non–small cell lung cancer (NSCLC) treated with chemotherapy. Experimental Design: A total of 894 tagging single-nucleotide polymorphisms (SNP) in 70 genes from the four pathways were genotyped and analyzed in a 1,076-patient cohort. Association with overall survival was analyzed at SNP and whole-gene levels within all patients and major chemotherapy agent combination groups. Results: A poorer overall survival was observed in patients with genetic variations in GSS (glutathione pathway) and MAP3K1 (EGFR pathway; HR = 1.45; 95% CI = 1.20–1.77 and HR = 1.25; 95% CI = 1.05–1.50, respectively). In the stratified analysis on patients receiving platinum plus taxane treatment, we observed a hazardous effect on overall survival by the MAP3K1 variant (HR = 1.38; 95% CI = 1.11–1.72) and a protective effect by RAF1 (HR = 0.64; 95% CI = 0.50–0.82) in the EGFR pathway. In patients receiving platinum plus gemcitabine treatment, RAF1 and GPX5 (glutathione pathway) genetic variations showed protective effects on survival (HR = 0.54; 95% CI = 0.38–0.77; HR = 0.67; 95% CI = 0.52–0.85, respectively); in contrast, NRAS (EGFR pathway) and GPX7 (glutathione pathway) variations showed hazardous effects on overall survival (HR = 1.91; 95% CI = 1.30–2.80; HR = 1.83; 95% CI = 1.27–2.63, respectively). All genes that harbored these significant SNPs remained significant by whole-gene analysis. Conclusion: Common genetic variations in genes of EGFR and glutathione pathways may be associated with overall survival among patients with advanced stage NSCLC treated with platinum, taxane, and/or gemicitabine combinations. Clin Cancer Res; 17(11); 3830–40. ©2011 AACR.

Abstract Background Taxane, a class of common anticancer agent, is widely used to treat many cancers. Among the taxanes, paclitaxel and docetaxel are the most commonly used agents. The mechanism of action for taxane drugs is through stabilizing microtubules by enhancing tubulin assembly and against depolymerization, thereby disrupting the dynamics of the microtubule. Large inter-individual variation has been observed in response to taxane treatment. Therefore, in the present study, we conducted a genome-wide association (GWA) study to identify genetic polymorphisms that might contribute to variation in response to taxanes drugs using the “Human Variation Panel” lymphoblastoid cell line (LCL) model system that consists of 287 ethnically defined cell lines. Method Genome-wide SNP and basal gene expression data were obtained for 287 LCLs using Illumina HumanHap 550K, 510S BeadChips, Affymetix SNP Array 6.0 and Affymetrix U133 plus 2.0 GeneChip. Cytotoxicity assay was also performed in the same cell lines for both paclitaxel and docetaxel. Candidate genes were selected based on an integrated analysis of genome-wide SNPs, expression array data and IC50 values (a cytotoxicity phenotype indicating the drug concentration required for 50% inhibition of maximal cell growth) for paclitaxel and docetaxel. SiRNA screening was performed to functionally validate those top candidates, followed by MTS assay in a breast cancer cell line, MDA-MB231. Results Of the 54,000 probe sets considered, 390 probe sets, representing 272 unique annotated genes, were found to be associated with docetaxel cytotoxicity (IC50 value) with p value <10−3, while 176 probe sets, representing 124 unique genes, were associated with paclitaxel IC50. Of these probe sets, 50 probe sets were associated with IC50 for both drugs. Analysis of 1.3 million SNPs identified 11 loci, defined as a region containing at least 1 SNP of p value <10−5 and 1 SNP of p value <10−4 within 50kb, associated with docetaxel IC50, while 7 loci were associated with paclitaxel IC50. One locus was found to be associated with both drugs. Previous studies suggested that gene expression is regulated in a cell-type specific manner. Therefore, based on our analysis and biological implication, we selected 16 top candidate genes that were expressed in our LCLs to perform functional validation studies using siRNA, followed by MTS assay in a breast cancer cell line, MDA-MB231. Functional studies showed that knockdown of SLC44A1 and HSPA5 significantly desensitized the cancer cell to both taxanes treatment. Conclusion GWAS using LCL model system could provide potential pharmacogenomic candidates for future clinical translational studies. Functional validation in tumor cell lines may help determine the genomic mechanism contributing to the inter-individual variation of taxane response. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2599.

Abstract Background Radiation therapy is used to treat half of the all cancer patients. Response to radiation therapy varies widely, in terms of both response and toxicity related events. Previous studies suggested almost 80% of the variation in normal tissue response to radiation treatment was likely to be due to genetic factors. Therefore, we performed a genome-wide association study (GWAS) to identify biomarkers that might help predict radiation response using a the “Human Variation Panel” lymphoblastoid cell lines (LCLs) that consists 287 ethnically defined cell lines. Method Basal gene expression level, 1.3 million genome-wide SNP data were obtained for 287 human LCLs using Affymetrix U133 plus 2.0 GeneChip, Illumina HumanHap 550K, 510S BeadChips and Affymetix SNP Array 6.0. Radiation cytotoxicity assay was also performed to obtain the area under radiation dose response curve (AUC), a summary measure for cytotoxicity for the same cell lines. Functional validation of candidate genes, selected based on the integrated analysis of SNP, expression and AUC data, was performed in multiple cancer cell lines using specific siRNAs followed by MTS and colony formation assays. Results 27 loci, containing at least 2 SNPs of p values <10−4 within 50kb were associated with radiation AUC. 270 expression probe sets were associated with radiation AUC (p< 10−3). The integrated analysis of 27 loci, 54,000 basal expression probe sets and radiation AUC identified 50 unique SNPs associated with AUC were also associated with gene expression of 39 unique annotated genes. In addition, these 39 genes were associated with radiation AUC with p values <10−3. Based on the GWAS and integrated analysis of SNP, expression array and radiation AUC data, 22 genes were selected for functional validation studies using siRNA knock down followed by MTS and colony formation assays in multiple tumor cell lines. C13orf34 (Bora), MAD2L1, PLK4, TPD52 significantly altered the radiation sensitivity in at least 2 cancer cell lines for both MTS and colony formation assays (p<0.05). Knock down of DEPDC1B, a gene containing 2 SNPs at the 3′-end that was significantly related with Bora gene expression level (p<10−4) significantly desensitized cancer cells to radiation treatment. Both microarray data and QRT-PCR analysis indicated that expression levels for those two genes were significantly correlated. Conclusion Our results using the lymphoblastoid cell lines might help identify novel biomarkers that contribute to variation in response to radiation therapy and help understand the mechanisms underlying the association. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3602.

Purpose We performed a case-control genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with musculoskeletal adverse events (MS-AEs) in women treated with aromatase inhibitors (AIs) for early breast cancer. Patients and Methods A nested case-control design was used to select patients enrolled onto the MA.27 phase III trial comparing anastrozole with exemestane. Cases were matched to two controls and were defined as patients with grade 3 or 4 MS-AEs (according to the National Cancer Institute's Common Terminology Criteria for Adverse Events v3.0) or those who discontinued treatment for any grade of MS-AE within the first 2 years. Genotyping was performed with the Illumina Human610-Quad BeadChip. Results The GWAS included 293 cases and 585 controls. A total of 551,358 SNPs were analyzed, followed by imputation and fine mapping of a region of interest on chromosome 14. Four SNPs on chromosome 14 had the lowest P values (2.23E-06 to 6.67E-07). T-cell leukemia 1A (TCL1A) was the gene closest (926-7000 bp) to the four SNPs. Functional genomic studies revealed that one of these SNPs (rs11849538) created an estrogen response element and that TCL1A expression was estrogen dependent, was associated with the variant SNP genotypes in estradiol-treated lymphoblastoid cells transfected with estrogen receptor alpha and was directly related to interleukin 17 receptor A (IL17RA) expression. Conclusion This GWAS identified SNPs associated with MS-AEs in women treated with AIs and with a gene (TCL1A) which, in turn, was related to a cytokine (IL17). These findings provide a focus for further research to identify patients at risk for MS-AEs and to explore the mechanisms for these adverse events.

Abstract Aromatase (CYP19) is a critical enzyme in estrogen biosynthesis and aromatase inhibitors (AI) are employed widely for endocrine therapy in postmenopausal women with breast cancer. We hypothesized that single nucleotide polymorphisms (SNPs) in the CYP19 gene may alter the effectiveness of AI therapy in the neoadjuvant setting. Genomic DNA was obtained for sequencing from 52 women pre-AI and post-AI treatment in this setting. Additionally, genomic DNA obtained from 82 samples of breast cancer and 19 samples of normal breast tissue was subjected to resequencing. No differences in CYP19 sequence were observed between tumor and germ-line DNA in the same patient. A total of 48 SNPs were identified including 4 novel SNPs when compared with previous resequencing data. For genotype-phenotype association studies, we determined the levels of aromatase activity, estrone, estradiol, and tumor size in patients pre-AI and post-AI treatment. We defined two tightly linked SNPs (rs6493497 and rs7176005 in the 5'-flanking region of CYP19 exon 1.1) that were significantly associated with a greater change in aromatase activity after AI treatment. In a follow-up study of 200 women with early-stage breast cancer who were treated with adjuvant anastrozole, these same two SNPs were also associated with higher plasma estradiol levels in patients pre-AI and post-AI treatment. Electrophoretic mobility shift and reporter gene assays confirmed likely functional effects of these two SNPs on transcription of CYP19. Our findings indicate that two common genetic polymorphisms in the aromatase gene CYP19 vary the response of breast cancer patients to aromatase inhibitors. Cancer Res; 70(1); 319–28

Abstract Two cytidine analogues, gemcitabine (dFdC) and 1-β-d-arabinofuranosylcytosine (AraC), show significant therapeutic effect in a variety of cancers. However, response to these drugs varies widely. Evidence from tumor biopsy samples shows that expression levels for genes involved in the cytidine transport, metabolism, and bioactivation pathway contribute to this variation in response. In the present study, we set out to test the hypothesis that variation in gene expression both within and outside of this “pathway” might influence sensitivity to gemcitabine and AraC. Specifically, Affymetrix U133 Plus 2.0 GeneChip and cytotoxicity assays were performed to obtain basal mRNA expression and IC50 values for both drugs in 197 ethnically defined Human Variation Panel lymphoblastoid cell lines. Genes with a high degree of association with IC50 values were involved mainly in cell death, cancer, cell cycle, and nucleic acid metabolism pathways. We validated selected significant genes by performing real-time quantitative reverse transcription-PCR and selected two representative candidates, NT5C3 (within the pathway) and FKBP5 (outside of the pathway), for functional validation. Those studies showed that down-regulation of NT5C3 and FKBP5 altered tumor cell sensitivity to both drugs. Our results suggest that cell-based model system studies, when combined with complementary functional characterization, may help to identify biomarkers for response to chemotherapy with these cytidine analogues. [Cancer Res 2008;68(17):7050–8]