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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Myklebust, June H; Brody, Joshua; Kohrt, Holbrook E et al. (2017) Distinct patterns of B-cell receptor signaling in non-Hodgkin lymphomas identified by single-cell profiling. Blood 129:759-770
Anchang, Benedict; Hart, Tom D P; Bendall, Sean C et al. (2016) Visualization and cellular hierarchy inference of single-cell data using SPADE. Nat Protoc 11:1264-79
Casey, Stephanie C; Vaccari, Monica; Al-Mulla, Fahd et al. (2015) The effect of environmental chemicals on the tumor microenvironment. Carcinogenesis 36 Suppl 1:S160-83
O'Gorman, William E; Hsieh, Elena W Y; Savig, Erica S et al. (2015) Single-cell systems-level analysis of human Toll-like receptor activation defines a chemokine signature in patients with systemic lupus erythematosus. J Allergy Clin Immunol 136:1326-36
Yetil, Alper; Anchang, Benedict; Gouw, Arvin M et al. (2015) p19ARF is a critical mediator of both cellular senescence and an innate immune response associated with MYC inactivation in mouse model of acute leukemia. Oncotarget 6:3563-77
Casey, Stephanie C; Amedei, Amedeo; Aquilano, Katia et al. (2015) Cancer prevention and therapy through the modulation of the tumor microenvironment. Semin Cancer Biol 35 Suppl:S199-S223
Sagiv-Barfi, Idit; Kohrt, Holbrook E; Burckhardt, Laura et al. (2015) Ibrutinib enhances the antitumor immune response induced by intratumoral injection of a TLR9 ligand in mouse lymphoma. Blood 125:2079-86
Behbehani, Gregory K; Samusik, Nikolay; Bjornson, Zach B et al. (2015) Mass Cytometric Functional Profiling of Acute Myeloid Leukemia Defines Cell-Cycle and Immunophenotypic Properties That Correlate with Known Responses to Therapy. Cancer Discov 5:988-1003
Levine, Jacob H; Simonds, Erin F; Bendall, Sean C et al. (2015) Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis. Cell 162:184-97
Shroff, Emelyn H; Eberlin, Livia S; Dang, Vanessa M et al. (2015) MYC oncogene overexpression drives renal cell carcinoma in a mouse model through glutamine metabolism. Proc Natl Acad Sci U S A 112:6539-44

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