DiscussionAcknowledgementsI would like to thank Martyn Smith’s Molecular Epidemiology and Toxicology laboratory for letting me work in their lab. I would also like to thank my project supervisors John Latto, Matt Orr, and Donna Green. Thank you to the GSIs of ES 196: Manish DesReferencesCavalieri Ercole L., Li Kai-Ming, Bali Narayanan, Saeed Muhammad, Devanesan Prabu, Higginbotam Sheila, Zhao John, Gross Michail L., Rogan Eleanor G. Catechol ortho-quinones: the electrophilic compounds that form depurintating DNA adducts and could initiaSingle Nucleotide Polymorphisms and Incidence of Lymphoma Lucy Brining Abstract Lymphoma is the fifth most commonly diagnosed cancer in the United States and incidence levels are increasing with little new information on possible causes. Several cancers are known to be associated with genetic aberrations. This study investigates the relationship between developing lymphoma and genetic aberrations known as single nucleotide polymorphisms (SNPs), found in the MIF, CY1PA, APM1, and LEP genes. SNPs are single nucleotide base changes within a gene, whose presence is posited to interfere with the genes function. The study tested whether the presence of one or more of the SNPs in question and the interactions between two SNPs increases the risk of developing lymphoma. To investigate the hypothesis, DNA was isolated from 1,236 controls and subjects, with the subjects being cancer patients and analyzed for presence of the four SNPs using Real-Time PCR analysis. The data were tested for Hardy-Weinburg equilibrium to determine normalcy of the data set and analyzed using chi-squared analyses looking for associations between the presence of the SNPs and lymphoma. Results are expected to show that the presence of two of the SNPs will have synergistic interactions and are associated with the development of lymphoma. In addition, the results might show the presence of at least one of the SNPs correlates with the development of lymphoma. Findings from this study could serve as potential biomarkers for cancer in the future.Introduction With only a five year survival rate of 52% in the US, lymphomas are the fifth most common cancer affecting about 60,900 people a year (Chang et al. 2003). Despite diagnosis improvements and considerable efforts to identify possible risk factors, the causes of most lymphoma cases are unknown and the incidence of lymphoma is increasing (Chang et al. 2003). Since 1970, the incidence of lymphoma has nearly doubled (American Cancer Society, 2002). With rates of lymphoma increasing and little understanding why, there is a need for studies investigating possible factors. Previous studies have looked at associations between lymphoma and environmental and occupational exposures to chemicals including pesticides. Few of these studies however, resulted in consistent conclusions and in fact many contradicted one another (Zheeb and Blettner 1998). Medically-applied radio and chemotherapy have been reported as high-risk factors, however again inconsistently. Hereditary factors like chromosomal syndromes and genetically inherited diseases are proven to put an individual in a high-risk category; however, they are extremely rare in the population (Zheeb and Blettner 1998). Even though such studies correlate the development of the disease with certain factors, few of these studies draw solid conclusions about the known risks, for none of the risks are absolute. Conclusions drawn from such studies are inconsistent with one another due to the fact that cancers are not caused by exposure to one chemical or radiation treatment but rather a combination of events. In an attempt to investigate synergistic relationships between risk factors like smoking, drinking or diet, there have been case studies looking at whether the incidence of lymphomas is affected by such risk factors (Zheeb and Blettner 1998). However, there have been very few studies investigating synergistic relationships between genes. Thus, there have been few attempts at identifying groups of genes which could serve as potential biomarkers for lymphoma. The few that have been determined are genes that lead to breast cancer, pancreatic cancer and gastrointestinal cancer (Mimori et al 02, Kawakam et al 99, Chang et al 03). The aim of this study is to identify possible new biomarkers, so that in the future, populations can be tested to evaluate the risk of developing lymphoma. In order to develop such biomarkers, we need to investigate possible genes and the synergisticrelationships between genes. For this study we are looking specifically at single nucleotide polymorphisms or SNPs. SNPs are single nucleotide-base changes in a genetic sequence which on their own do not result in a change of phenotype. The SNP could, in theory, go unnoticed for an entire lifetime. However, it is posited that such base changes in combination with other factors could become the starting points for cancer development. For instance, if the SNP codes for a different amino acid within the protein and if there is some change in the gene environment, the amino acid coded by the SNP might act differently, changing the shape and thus the function of the protein (Skibola et al 2002). The change in function could lead to over or under-expression of the gene, resulting in the development of cancer. The presence of SNPs is not significant for all genes, only genes whose over or under-expression could result in cancerous growth. In our case, the specific genes in question for this study are: MIF, CYP1A, LEP, and AMP1. An interesting characteristic of the MIF gene is that it is thought to control cell proliferation, cell survival, angiogenesis, cell differentiation, T Lymphocytic activation and thus tumor progression (Chesney et al. 1998, Takahashi et al 1998, Wistow et al 1993). There are also reports that MIF is over-expressed in many cancers including leukemia (Chesney et al. 1998, Huggins and Fukunishi 1964). CYP1A encodes an enzyme that converts environmental pro-carcinogens to reactive intermediates with carcinogenic effects. Additionally, studies have shown that CYP1A catalyzes the oxidative metabolites of estrogens, another possible starting point for cancer (Chang et al 2003). Studies found that SNPs in the CYP1A gene are associated with increased cancer risks (Chang et al 2003). LEP is ubiquitous in recent literature correlating the gene with obesity. However, in addition to
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