Pharmacogenetics of the human glutathione S-transferase P1 gene in the metabolism and therapeutic efficacy of cis-diamminedichloroplatinum

The human GSTP1 gene has been shown, conclusively, to be polymorphic. The three main GSTP1 alleles, GSTP1*A, GSTP1*B, and GSTP1*C, encode proteins which differ in the 3-dimensional structure of their active sites and in their function in phase II metabolism of carcinogens, mutagens, and anticancer agents. Although, it is well established that GSTP1 is over expressed in many human tumors and that the levels of GSTP1 expression correlate directly with tumor resistance to chemotherapy and inversely with patient survival, the significance of the polymorphic GSTP1 gene locus on tumor response to chemotherapy remains unclear. The goal of this project was to define the role and significance of the polymorphic GSTP1 gene locus in GSTP1-based tumor drug resistance and as a determinant of patient response to chemotherapy. The hypothesis to be tested was that the polymorphic GSTP1 gene locus will confer to tumors a differential ability to metabolize cisplatin resulting in a GSTP1 genotype-based sensitivity to cisplatin. The study examined: (a) whether the different GSTP 1 alleles confer different levels of cellular protection against cisplatin-induced cytotoxicity, (b) whether the allelic GSTP1 proteins metabolize cisplatin with different efficiencies, and (c) whether the GSTP1 genotype is a determinant of tumor response to cisplatin therapy. The results demonstrate that the GSTP1 alleles differentially protect tumors against cisplatin-induced apoptosis and clonogenic cell kill in the rank order: GSTP1*C > GSTP1*B > GSTP1*A. The same rank order was observed for the kinetics of GSTP1-catalyzed cisplatin metabolism, both in cell-free and cellular systems, to the rate-limiting monoglutathionyl-platinum metabolite, which was characterized, for the first time, by mass spectral analysis. Finally, this study demonstrates that both GSTP1 genotype and the level of GSTP1 expression significantly contribute to tumor sensitivity to cisplatin treatment. Overall, the results of this project show that the polymorphic GSTP1 gene locus plays a significant role in tumor sensitivity to cisplatin treatment. Furthermore, these studies have contributed to the overall understanding of the significance of the polymorphic GSTP1 gene locus in tumor resistance to cancer chemotherapy and have provided the basis for further investigations into how this can be utilized to optimize and individualize cancer chemotherapy for cancer patients. ^

DNA nucleotide excision repair gene single nucleotide polymorphisms and hereditary nonpolyposis colorectal cancer

Hereditary nonpolyposis colorectal cancer (HNPCC) is an autosomal dominant disease caused by germline mutations in DNA mismatch repair(MMR) genes. The nucleotide excision repair(NER) pathway plays a very important role in cancer development. We systematically studied interactions between NER and MMR genes to identify NER gene single nucleotide polymorphism (SNP) risk factors that modify the effect of MMR mutations on risk for cancer in HNPCC. We analyzed data from polymorphisms in 10 NER genes that had been genotyped in HNPCC patients that carry MSH2 and MLH1 gene mutations. The influence of the NER gene SNPs on time to onset of colorectal cancer (CRC) was assessed using survival analysis and a semiparametric proportional hazard model. We found the median age of onset for CRC among MMR mutation carriers with the ERCC1 mutation was 3.9 years earlier than patients with wildtype ERCC1(median 47.7 vs 51.6, log-rank test p=0.035). The influence of Rad23B A249V SNP on age of onset of HNPCC is age dependent (likelihood ratio test p=0.0056). Interestingly, using the likelihood ratio test, we also found evidence of genetic interactions between the MMR gene mutations and SNPs in ERCC1 gene(C8092A) and XPG/ERCC5 gene(D1104H) with p-values of 0.004 and 0.042, respectively. An assessment using tree structured survival analysis (TSSA) showed distinct gene interactions in MLH1 mutation carriers and MSH2 mutation carriers. ERCC1 SNP genotypes greatly modified the age onset of HNPCC in MSH2 mutation carriers, while no effect was detected in MLH1 mutation carriers. Given the NER genes in this study play different roles in NER pathway, they may have distinct influences on the development of HNPCC. The findings of this study are very important for elucidation of the molecular mechanism of colon cancer development and for understanding why some mutation carriers of the MSH2 and MLH1 gene develop CRC early and others never develop CRC. Overall, the findings also have important implications for the development of early detection strategies and prevention as well as understanding the mechanism of colorectal carcinogenesis in HNPCC. ^

Systems Biology Approaches to Probe Gene Regulation in Bacteria

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb). First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses and survive within resting macrophages. As a result, the method unveiled transcriptional regulators and associated regulons utilized by Mtb to establish a successful infection of macrophages throughout the first 14 days of infection. Additionally, this network-based analysis identified the production of Fe-S proteins coupled to lipid metabolism through the alkane hydroxylase complex as a possible strategy employed by Mtb to survive in the host. Second, I developed a network inference method to infer the small non-coding RNA (sRNA) regulatory network in Mtb. The method identifies sRNA-mRNA interactions by integrating a priori knowledge of possible binding sites with structure-driven identification of binding sites. The reconstructed network was useful to predict functional roles for the multitude of sRNAs recently discovered in the pathogen, being that several sRNAs were postulated to be involved in virulence-related processes. Finally, I applied a combined experimental and computational approach to study post-transcriptional repression mediated by small non-coding RNAs in bacteria. Specifically, a probabilistic ranking methodology termed rank-conciliation was developed to infer sRNA-mRNA interactions based on multiple types of data. The method was shown to improve target prediction in Escherichia coli, and therefore is useful to prioritize candidate targets for experimental validation.