The variation among tumors in global gene expression patterns is orderly and systematic and it provides a distinctive and reproducible signature for each patient's tumor, and patients a picture of their biological differences. Moreover, we have found that variation in expression profiles can highlight unrecognized similarities and differences among tumors, and can provide a basis for systematic clustering of subsets of tumors. We therefore believe that underlying the apparent heterogeneity among cancers that we currently call by the same name, there may be a systematic """"""""taxonomy"""""""" that is not readily apparent from histology or the small set of markers usually used to define subgroups of tumors. We propose to characterize the molecular variations among lymphomas by systematically and quantitatively measuring variation in transcript abundance for at least 20,000 different genes, in several hundred independent tumor samples. We will use multi-variate clustering methods to search for ways to group tumors into clusters that are internally coherent in their expression patterns and thus, we hope, in their clinical behavior. We will apply this methodology to ask specific focused questions of relevance to lymphoma diagnosis, biology and clinical outcome. Specifically, we will (1) examine the progression from low grade malignancy to higher grade more aggressive disease both for B cell and for T cell lymphomas, 92) we will match gene expression patterns to chemical outcomes in EBV induced post transplant lymphoproliferative disease and (3) we will examine the gene expression patterns which occur as a consequence of signaling pathways important in lymphomagenesis, such as occurs upon binding of the hepatitis C virus to its cellular receptor, CD81, which may be a step in the development of B cell malignancy, and such as the Notch-12 signaling pathway which is involved in T cell malignancy.
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