Genome-wide association studies in cancer.
ABSTRACT Genome-wide association studies (GWAS) provide a powerful approach to identify common, low-penetrance disease loci without prior knowledge of location or function. GWAS have been conducted in five of the commonest cancer types: breast, prostate, colorectal and lung, and melanoma, and have identified more than 20 novel disease loci, confirming that susceptibility to these diseases is polygenic. Many of these loci were detected at low power, indicating that many further loci will probably be detected with larger studies. For the most part, the loci were not previously suspected to be related to carcinogenesis, and point to new disease mechanisms. The risks conferred by the susceptibility alleles are low, generally 1.3-fold or less. The combined effects may, however, be sufficiently large to be useful for risk prediction, and targeted screening and prevention, particularly as more loci are identified.
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ABSTRACT: Epistasis helps to explain how multiple single-nucleotide polymorphisms (SNPs) interact to cause disease. A variety of tools have been developed to detect epistasis. In this article, we explore the strengths and weaknesses of an information theory approach for detecting epistasis and compare it to the logistic regression approach through simulations. We consider several scenarios to simulate the involvement of SNPs in an epistasis network with respect to linkage disequilibrium patterns among them and the presence or absence of main and interaction effects. We conclude that the information theory approach more efficiently detects interaction effects when main effects are absent, whereas, in general, the logistic regression approach is appropriate in all scenarios but results in higher false positives. We compute epistasis networks for SNPs in the FSD1L gene using a two-phase head and neck cancer genome-wide association study involving 2,185 cases and 4,507 controls to demonstrate the practical application of the methods.Cancer informatics 02/2015; 14(Suppl 2):17-23. DOI:10.4137/CIN.S17289
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ABSTRACT: Carcinogenesis is a multistep and also a multifactorial process that involves agents like genetic and environmental factors. Matrix metalloproteinases (MMPs) are major proteolytic enzymes which are involved in cancer cell migration, invasion, and metastasis. Genetic variations in genes encoding the MMPs were shown in human studies to influence cancer risk and phenotypic features of a tumor. The complex role of MMPs seems to be important in the mechanism of carcinogenesis, but it is not well recognized. Rodent studies concentrated particularly on the better understanding of the biological functions of the MMPs and their impact on the pathological process, also through the modification of Mmp genes. This review presents current knowledge and the existing evidence on the importance of selected MMPs in genetic mouse models of cancer and human genetic association studies. Further, this work can be useful for scientists studying the role of the genetic impact of MMPs in carcinogenesis.Tumor Biology 10/2014; DOI:10.1007/s13277-014-2747-6 · 2.84 Impact Factor