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Alizadeh leads a group interested in techniques and methods for understanding tumor behavior at molecular, cellular, organism and population levels. Using machine learning techniques, his lab studies how cellular compositional variation impacts cancer behavior and therapeutic response e.
My group's research is focused on attaining a better understanding of the initiation, maintenance, and progression of tumors, and their response to current therapies toward improving future treatment strategies. My group develops and applies genomic biomarkers of tumor cells, whether detected through biopsy of the primary neoplasm, or noninvasively through monitoring of the bodily fluids including blood.
We apply such genomic biomarkers for the early detection, diagnosis, and monitoring of diverse tumors including lymphomas and solid tumors. We are also interested in better molecular understanding of normal tissue stem cells and their malignant tumor-initiating counterparts cancer stem cells , toward identification of the underlying mechanisms relevant to specific cancers of the hematopoietic system.
These tumors include follicular lymphoma, diffuse large B-cell lymphoma, and mantle cell lymphoma. We have also worked to build prognostic and predictive models for clinical and therapeutic outcomes of diverse human malignancies, through large-scale bioinformatic meta-analysis of human tumor transcriptomes, including deconvolution of complex tumor admixtures including infiltrating leukocytes.