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Last Updated: 03/04/21

Molecular Signatures to Improve Diagnosis and Outcome Prediction in Lymphoma

U01 CA114778

Wing C. Chan, M.D.
University of Nebraska Medical Center

Dr. Chan’s program focused on refining and validating the diagnostic and prognostic profiles that characterize the major subclasses of non-Hodgkin lymphoma (NHL). Dr. Chan’s previous Director’s Challenge grant provided the support for the extramural components of the Leukemia and Lymphoma Molecular Profiling Project (LLMPP) headed by him and his NCI co-investigator, Dr. Lou Staudt. The LLMPP pooled tissue and other resources from an international collaborating consortium as shown below for previous studies and this effort will continue under the SPECS initiative. Without this consortium, the number of specimens of the less common subtypes of NHL required to carry out these studies would not be sufficient.

Collaborators:

  • The project included investigators from The University of Nebraska, NCI, the British Columbia Cancer Agency, the University of Barcelona, the University of Wurzburg, St. Bartholomew Hospital, Norwegian Radium Hospital and four institution from the Southwest Oncology Group (University of Rochester, University of Arizona, University of Oregon and Cleveland Clinics).

Projects:

  • Confirm and refine the lymphoma signatures by analyzing 2400 new lymphoma specimens accrued at the participating sites. These gene expression analyses will be carried out at all of the participating international sites. An important element of this aim is to determine the reproducibility of data generated in different sites.
  • Combine genomic data generated by array comparative genomic hybridization (CGH) with gene expression data to provide a more robust prognostic signature.
  • Develop a qRT-PCR assay using a subset of the genes so that the diagnostic and prognostic information can be applied to FFPE specimens.
  • Determine how changes in therapy will alter the predictive power of previously developed profiles using diffuse large B cell lymphoma as a model. The prognostic profile will be revised to more accurately predict response to the new therapeutic regimen.

Featured Publications:

Lenz G et al (2008) Stromal gene signatures in large-B-cell lymphomas. N Engl J Med 359: 2313-2323. PMID: 19038878

Lenz G et al (2008) Molecular subtypes of diffuse large B-cell lymphoma arise by distinct genetic pathways. Proc Natl Acad Sci U S A 105: 13520-13525. PMID: 18765795

These two papers present gene expression signatures developed by the Chan SPECS project that classify therapeutically important categories of adult lymphoma.

Molecular Profiling Can Accurately Diagnose Burkitt’s Lymphoma
NCI Cancer Bulletin; June 13, 2006 Exit Disclaimer

Geng, H., J. Iqbal, et al. (2011) Virtual CGH: an integrative approach to predict genetic abnormalities from gene expression microarray data applied in lymphoma. BMC Med Genomics 4: 32. PMCID: 3086850

Hartmann, E. M., E. Campo, et al. (2010) Pathway discovery in mantle cell lymphoma by integrated analysis of high-resolution gene expression and copy number profiling. Blood 116(6): 953-961. PMCID: 2924229

Iqbal, J., D. D. Weisenburger, et al. (2010) Molecular signatures to improve diagnosis in peripheral T-cell lymphoma and prognostication in angioimmunoblastic T-cell lymphoma. Blood 115(5): 1026-1036. PMCID: 2817630

Meyer, P. N., K. Fu, et al. (2011) Immunohistochemical methods for predicting cell of origin and survival in patients with diffuse large B-cell lymphoma treated with rituximab. J Clin Oncol 29(2): 200-207. PMCID: 3058275

Morin, R. D., M. Mendez-Lago, et al. (2011) Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma. Nature 476(7360): 298-303. PMCID: 3210554

Ngo, V. N., R. M. Young, et al. (2011) Oncogenically active MYD88 mutations in human lymphoma. Nature 470(7332): 115-119. PMID: 21179087

Ramachandrareddy, H., A. Bouska, et al. (2010) BCL6 promoter interacts with far upstream sequences with greatly enhanced activating histone modifications in germinal center B cells. Proc Natl Acad Sci USA 107(26): 11930-11935. PMCID: 2900701