CGH IN HIV+ AND HIV-PATIENTS WITH NHL

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DESCRIPTION: (Applicant's Description) Non-Hodgkin's lymphoma (NHL) develops in 5-10% of HIV positive individuals. The elevated incidence of lymphomagenesis, histologic grade/stage and the clinical course of HIV positive patients with lymphoma suggests a more aggressive malignant disease than in HIV negative patients. However, the etiology and molecular events leading to lymphomagenesis are poorly defined. It is unclear whether the development and/or aggressiveness of malignant cells is due simply to the immunocompromised status of the individual or whether the immunocompromised status results in lymphomas that are genetically different from those that develop in the absence of HIV exposure. Complex and distinctive molecular cytogenetic aberrations are hallmarks of aggressive cancers. The investigators hypothesize that HIV infection facilitates emergence of premalignant and malignant clones that are genetically distinctive from spontaneous lymphomas. Comparative genomic hybridization (CGH) allows genome-wide surveys of molecular cytogenetic changes that occur in tumors. They will determine whether CGH discriminates between non-Hodgkin's lymphoma (NHL) in HIV positive and HIV negative patients. The goal of the pilot proposal is to perform CGH analyses on lymphoma specimens from 20 HIV positive and 20 grade matched HIV negative patients to establish the feasibility of tissue sample retrieval and genomic analysis and to obtain preliminary data to support the scientific merit of a larger study. The specific aims of the pilot project are to: (1) collect tissue samples for use in this pilot study and determine feasibility of collecting them for a larger study. Molecular characterization of EBV presence and lymphoma monoclonality will be measured by PCR and Southern blot to allow careful matching of HIV positive and HIV negative cases, (2) determine whether distinctive genomic changes discriminate between lymphomas obtained from HIV positive and HIV negative patients, (3) develop rapid, semi-automated approaches for CGH to facilitate genomic analysis of large populations.