Batzler, Anthony

Abstract BACKGROUND Metformin, a widely used anti-diabetic drug, is being considered as a highly promising agent for treatment and prevention of many types of cancer, including breast cancer. Although the exact mechanism of action of metformin is unknown, it is thought that metformin is an AMPK activator. To better individualize metformin therapy and explore additional underlying molecular mechanism associated with metformin action, we conducted a metformin pharmacogenomic study using 266 genomic data-enriched lymphoblastoid cell lines (LCLs). METHODS Genome-wide microarray data were generated for all LCLs, including 1.3 million SNPs, 485K DNA methylation probes and 54K mRNA expression probe sets. Metformin cytotoxicity assay was performed using MTS assay. Genome-wide association (GWA) analyses and integrated analyses using all the genomic data and metformin cytotoxicity (IC50 value) were performed to identify top candidate genes for functional validation in breast cancer cell lines, MDA-MB 231 and Hs578T, using siRNA screening approach. Further mechanistic study was performed to investigate the role of candidates in regulation of AMPK activity. RESULTS GWA analyses in LCLs identified 198 mRNA expression probe sets and 210 DNA methylation probes associated with metformin IC50 with p-value <10-4, respectively. Analysis of 1.3 million SNPs found 12 loci (a region containing at least 1 SNP of p-value <10-5 and 1 SNP of p-value <10-3 within 50kb) that were associated with metformin IC50. Integrated SNP loci-mRNA expression-IC50 analysis indicated that the SNP loci on chromosome 16 was associated with metformin IC50 through a trans-regulation of expression of 7 genes with p-value <10-4. Integrated methylation-mRNA expression-IC50 analysis showed that 15 DNA methylation probes in 6 genes were associated with metformin IC50 through both cis- and trans-regulation of expression of 48 genes with p-value <10-4, including 4 methylation probes in 3 of those 6 genes that were cis-correlated with its own gene expression. Ingenuity pathway analysis of top 62 candidate genes identified four major pathways and 55 genes within those pathways were selected for functional validation in breast cancer cell lines. The knockdown experiment showed that down regulation of 25 genes significantly altered metformin sensitivity in MDA-MB231, and 14 of them also showed the same effect in Hs578T. Preliminary mechanistic experiment indicated that knockdown of 7 genes significantly reduced AMPK activity in MDA-MB231 and 3 of them had same effect in Hs578T. CONCLUSIONS GWAS using a genomic data-enriched LCL model system, together with functional validation in breast cancer cell lines, could help us to identify novel genetic and epigenetic biomarkers involved in metformin response and help us to better understand the mechanisms of metformin in cancer treatment. Citation Format: Nifang Niu, Xianglin Tan, Brooke L. Fridley, Daniel J. Schaid, Ryan P. Abo, Anthony Batzler, Erin E. Carlson, Gregory Jenkins, Sebastian Moran, Holger Andrea Heyn, Manel Esteller Badosa, Liewei Wang. Metformin pharmacogenomics: A genome-wide associate study to identify genetic and epigenetic biomarkers involved in metformin response. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2271. doi:10.1158/1538-7445.AM2013-2271

Aims Citalopram ( CT ) and escitalopram ( S ‐ CT ) are among the most widely prescribed selective serotonin reuptake inhibitors used to treat major depressive disorder ( MDD ). We applied a genome‐wide association study to identify genetic factors that contribute to variation in plasma concentrations of CT or S ‐ CT and their metabolites in MDD patients treated with CT or S ‐ CT . Methods Our genome‐wide association study was performed using samples from 435 MDD patients. Linear mixed models were used to account for within‐subject correlations of longitudinal measures of plasma drug/metabolite concentrations (4 and 8 weeks after the initiation of drug therapy), and single‐nucleotide polymorphisms ( SNPs ) were modelled as additive allelic effects. Results Genome‐wide significant associations were observed for S ‐ CT concentration with SNPs in or near the CYP2C19 gene on chromosome 10 (rs1074145, P = 4.1 × 10 −9 ) and with S ‐didesmethylcitalopram concentration for SNPs near the CYP2D6 locus on chromosome 22 (rs1065852, P = 2.0 × 10 −16 ), supporting the important role of these cytochrome P450 ( CYP ) enzymes in biotransformation of citalopram. After adjustment for the effect of CYP2C19 functional alleles, the analyses also identified novel loci that will require future replication and functional validation. Conclusions In vitro and in vivo studies have suggested that the biotransformation of CT to monodesmethylcitalopram and didesmethylcitalopram is mediated by CYP isozymes. The results of our genome‐wide association study performed in MDD patients treated with CT or S ‐ CT have confirmed those observations but also identified novel genomic loci that might play a role in variation in plasma levels of CT or its metabolites during the treatment of MDD patients with these selective serotonin reuptake inhibitors.

Abstract 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.

Abstract The selective estrogen receptor modulators (SERM) tamoxifen and raloxifene can reduce the occurrence of breast cancer in high-risk women by 50%, but this U.S. Food and Drug Administration-approved prevention therapy is not often used. We attempted to identify genetic factors that contribute to variation in SERM breast cancer prevention, using DNA from the NSABP P-1 and P-2 breast cancer prevention trials. An initial discovery genome-wide association study identified common single-nucleotide polymorphisms (SNP) in or near the ZNF423 and CTSO genes that were associated with breast cancer risk during SERM therapy. We then showed that both ZNF423 and CTSO participated in the estrogen-dependent induction of BRCA1 expression, in both cases with SNP-dependent variation in induction. ZNF423 appeared to be an estrogen-inducible BRCA1 transcription factor. The OR for differences in breast cancer risk during SERM therapy for subjects homozygous for both protective or both risk alleles for ZNF423 and CTSO was 5.71. Significance: This study identified novel, functionally polymorphic genes involved in the estrogen-dependent regulation of BRCA1 expression, as well as a novel mechanism for genetic variation in SERM therapeutic effect. These observations, and definition of their underlying mechanisms, represent steps toward pharmacogenomically individualized SERM breast cancer prevention. Cancer Discov; 3(7); 812–25. ©2013 AACR. See related commentary by Machiela and Chanock, p. 728 This article is highlighted in the In This Issue feature, p. 705

Abstract Introduction: The NSABP P-1 and P-2 breast cancer prevention trials have demonstrated that the SERMs tamoxifen and raloxifene can reduce the risk of breast cancer in high risk women. Methods: We performed a nested matched case-control GWAS utilizing DNA from participants enrolled in P-1 and P-2. 592 participants developed invasive breast cancer or ductal carcinoma in situ, and were matched with 1171 controls who did not. Genome-wide genotyping with the Illumina 610-Quad chip and CYP2D6 genotyping for pertinent alleles were performed. Functional genomic studies involved the use of cultured cells, with siRNA knockdown, followed by qRT-PCR and Western blot analyses. Results: Eleven SNPs with p-values < 3E-05 were identified. Twenty one additional SNPs with p < 4E-05 were identified by imputation around the genotyped SNPs on chromosomes (Chrs) 4, 8, 9, 13, 16 and 22, which were then genotyped with the Invader platform. Initial functional genomic studies focused on 6 SNPs on Chr16 (p-values 1.81-9.55E-06), all of which were in ZNF423, a gene encoding a putative zinc-finger protein. The Chr16 minor variant SNP sequences had less risk than the common variant (OR=0.7). Our functional studies showed that incubation of Hs578T cells stably transfected with estrogen receptor (ER) α with 0.1 nM estradiol (E2) induced expression of ZNF423, BRCA1/2 for WT but not variant SNP sequences. There was also a striking difference between E2-induced ZNF423, BRCA1/2 expression for variant and WT SNPs in lymphoblastoid cell lines (LCLs) stably transfected with ERα, with only WT showing induction. ChIP assay showed that ZNF423 could bind to the 5’-flanking region of BRCA1, and reporter gene assays showed that ZNF423 could regulate BRCA1/2 transcription. In LCLs stably transfected with ERα and genotyped for ZNF423 SNPs, estrogen-dependent expression of all 3 genes occurred only in the presence of the WT, but not variant ZNF423 SNP sequences. Blockade of ERα with 4-OH tamoxifen prevented induction of expression in cells with WT sequences, but resulted in gene dose-dependent increases in BRCA1/2 expression in cells with variant SNP sequences-suggested that the minor variant has a “protective” effect during clinical SERM therapy and verified by ChIP assays. Conclusions: The SNPs in ZNF423 identified during GWAS were associated with differential E2-dependent induction of ZNF423, BRCA1 and BRCA2-implying that ZNF423 is “upstream” for the estrogen-dependent induction of BRCA1/2 expression. However, LCLs with variant SNP sequences showed greatly enhanced expression of ZNF423, BRCA1/2 during 4-OH tamoxifen exposure, while cells with WT sequences did not. These results may reveal a novel mechanism for SERM-dependent regulation of BRCA1/2 expression and may have implications for patient selection for SERM therapy. Funded by U10-CA37377, U10-CA69974 and U14-GM61388. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4727. doi:10.1158/1538-7445.AM2011-4727

Abstract Background: Candidate gene and candidate pathway-based pharmacogenomic studies have been used to investigate the inherited variability of prognosis of lung cancer treated with platinum-based chemoptherapy. In order to make it possible to conduct an ‘unbiased’ query across the entire genome, a genome-wide association study (GWAS) in 283 lymphoblastoid cell lines (LCLs) was carried out to help identify candidate SNPs associated with variation in cisplatin cytotoxicity. Furthermore, we set out to test the hypothesis that genetic variation resulting in differences in cisplatin cytotoxicity might influence the overall survival of patients with lung cancer treated with platinum-based antineoplastic agents. Material and Methods: We applied ethnically diverse Coriell “Human Variation Panel” LCLs for GWAS. Then, we picked 168 top significant SNPs selected from GWAS in 283 LCLs and genotyped these SNPs in 1183 lung cancer patients (222 SCLC and 961 NSCLC) who received platinum-based chemotherapy. Genotyping was performed using the Illumina Golden Gate platform. The association of SNPs with lung cancer overall survival was analyzed by Cox regression model after adjusting for disease stage. Functional validation of candidate genes was performed by siRNA screening in NSCLC cell lines CRL5872, H1299 and SCLC cell line CRL5823. Results: A total of 157 SNPs were successfully genotyped for 1183 lung cancer patient samples. The Cox regression analysis indicated that 9 and 10 different SNPs were associated with overall survival for NSCLC and SCLC patients, respectively (p value <0.05). Fifteen genes including 7 genes located in the region of 200kb up or downstream of 4 SNPs (rs11169748, rs2440915, rs5952066 and rs7620841) and 8 genes for which the expression was correlated with three SNPs (rs11169748, rs2440915 and rs5952066) were selected for siRNA screening. Knockdown of DAPK3 and METTL6, for which the expression levels were correlated with the SNPs rs11169748 and rs2440915, significantly decreased cisplatin sensitivity in lung cancer cell lines CRL5872, H1299 and CRL5823. Conclusions: This series of clinical and complementary laboratory-based functional studies identified several candidate genes and SNPs that might help predict treatment outcomes of platinum-based therapy in lung cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1285. doi:10.1158/1538-7445.AM2011-1285

Abstract Variation in drug response results from a combination of factors that include differences in gender, ethnicity, and environment, as well as genetic variation that may result in differences in mRNA and protein expression. This article presents two integrative analytic approaches that make use of both genome-wide SNP and mRNA expression data available on the same set of subjects: a step-wise integrative approach and a comprehensive analysis using sparse canonical correlation analysis (SCCA). In addition to applying standard SCCA, we present a novel modification of SCCA which allows different weighting for the various pair-wise relationships in the SCCA. These integrative approaches are illustrated with both simulated data and data from a pharmacogenomic study of the drug gemcitabine. Results from these analyses found little overlap in terms of genes detected, possibly detecting different biological mechanisms. In addition, we found the proposed weighted SCCA to outperform its unweighted counterpart in detecting associations between the genomic features and phenotype. Further research is needed to develop and assess new integrative methods for pharmacogenomic studies, as these types of analyses may uncover novel insights into the relationship between genomic variation and drug response.