Grant Number:	5R03CA115062-02 Interpret this number
Primary Investigator:	Landi, Stefano
Organization:	University Of Pisa
Project Title:	Microarray-Based Genotyping for Studying Susceptibility to Mesothelioma
Fiscal Year:	2007

DESCRIPTION (provided by applicant): Asbestos-exposed people are at high risk to develop pleural mesothelioma (PM). However, there are proofs indicating an important role of the individual's genetic background in determining the actual risk. For example, previous studies showed a higher risk for people with GSTM1 null genotype and NAT2 slow acetylators The aim of the present project is to dissect the influence of genes in the etiology of this disease as this kind of knowledge is scarce, mostly because the collection of patients is difficult, as this type of tumor is very rare. We plan to include into the study 150 DNA samples from PM patients, 150 "exposed controls", and 300 "normal controls". All the controls are people genetically representative of the population than cases. Most of the "exposed controls" were recruited within the same work place than cases. Those are people with a similar history of exposure than cases, having similar job type and duration of occupational exposure, but who did not develop PM. The exposure levels are assessed by expert occupational hygienists matching the information from questionnaires administered to the subjects (no "next-of-kin method" was used) and those from the measurements of pollution levels in the occupational environments, measured from the Public Health Service of Liguria during the past years. The samples proposed here represent a peculiar population: all cases and controls have been well characterized for their history of exposures, come from a limited region of the Northern Italy and, likely, are quite homogeneous under a genetic point of view. A micro-array containing 218 single nucleotide polymorphisms (SNPs) in selected genes of phase I, phase II of xenobiotic metabolism, DNA repair, control of cell cycle, cell growth regulators, and inflammation will be used. The genetic polymorphisms constellation in neoplastic patients and in controls will be analysed by multivariate methods based on logistic regression analyses, and methods for adjusting for multiple testing.





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