Niu, Nifang

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

Abstract Definitive radiotherapy combined with chemotherapy is associated with enhanced locoregional control and clinical outcomes in non-small cell lung cancer (NSCLC) patients who are not candidates for surgery. However, radiation-induced pneumonitis and esophagitis are common dose-limiting inflammatory conditions that occur in these patients. These events can compromise the effect of the overall treatment and reduce quality of life in these patients. It is not clear what factors contribute to differences in the development of toxicities among patients with same clinical or dosimetric parameters. In this study, we conducted a large scale pathway-based analysis to identify inflammation-related genetic variants associated with radiation-induced pneumonitis or esophagitis. In the initial discovery phase, 11,930 inflammation-related genetic variants were genotyped in 243 stage I-III NSCLC patients who were treated with definitive radiotherapy at MD Anderson Cancer Center. A fast-track validation was performed for the top candidate SNPs in an additional 212 NSCLC cases following the same criteria. A total of 14 SNPs and 12 SNPs were validated for pneumonitis and esophagitis, respectively. Meta-analysis was used to summarize the results from two phases. The most significant SNPs for esophagitis and pneumonitis mapped to chromosome 18p (OR=9.05, 95%CI=2.68-30.59, P-meta=3.90×10−4) and 14q (OR=4.75, 95%CI=2.17-10.41, P-meta =9.61×10−5), respectively. To explore the potential underlying mechanisms, we analyzed radiation sensitivity and eQTL relationships of the identified SNPs and their host genes in 277 ethnically defined human lymphoblastoid cell lines. Among the 24 host genes for the 26 identified SNPs, three genes (DDX58, GZMB, CDC2) showed significant association with radiation responses in these cell lines (P<0.05). Moreover, a significant eQTL relationship was identified between CDC2 expression and the genotype of the identified CDC2 SNP (P=0.022). Interestingly, this CDC2 SNP is predicted to create a new miRNA binding site. Luciferase reporter assays to test the influence of this SNP on miRNA regulation is currently ongoing. Our results provide evidence that inflammation-related genetic variants contribute to the development of radiation-induced pneumonitis and esophagitis. The results also suggest that gene expression changes through altered miRNA binding may be an underlying mechanism for these events. Citation Format: Xia Pu, Liewei Wang, Michelle AT Hildebrandt, Yuanqing Ye, Joe Y. Chang, Charles Lu, Heath D. Skinner, Nifang Niu, Gregory D. Jenkins, Ritsuko Komaki, John D. Minna, Jack A. Roth, Richard M. Weinshilboum, Xifeng Wu. Inflammation-related genetic variants predict radiation-induced toxicity following definitive radiotherapy for non-small cell lung cancer. [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 3626. doi:10.1158/1538-7445.AM2013-3626

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 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 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.