Literature DB >> 18840713

Functional proteomic profiling of AML predicts response and survival.

Steven M Kornblau1, Raoul Tibes, Yi Hua Qiu, Wenjing Chen, Hagop M Kantarjian, Michael Andreeff, Kevin R Coombes, Gordon B Mills.   

Abstract

Because protein function regulates the phenotypic characteristics of cancer, a functional proteomic classification system could provide important information for pathogenesis and prognosis. With the goal of ultimately developing a proteomic-based classification of acute myeloid leukemia (AML), we assayed leukemia-enriched cells from 256 newly diagnosed AML patients, for 51 total and phosphoproteins from apoptosis, cell-cycle, and signal-transduction pathways, using reverse-phase protein arrays. Expression in matched blood and marrow samples were similar for 44 proteins; another 7 had small fold changes (8%-55%), suggesting that functional proteomics of leukemia-enriched cells in the marrow and periphery are similar. Protein expression patterns were independent of clinical characteristics. However, 24 proteins were significantly different between French-American-British subtypes, defining distinct signatures for each. Expression signatures for AML with cytogenetic abnormalities involving -5 or -7 were similar suggesting mechanistic commonalities. Distinct expression patterns for FMS-like tyrosine kinase 3-internal tandem duplication were also identified. Principal component analysis defined 7 protein signature groups, with prognostic information distinct from cytogenetics that correlated with remission attainment, relapse, and overall survival. In conclusion, protein expression profiling patterns in AML correlate with known morphologic features, cytogenetics, and outcome. Confirmation in independent studies may also provide pathophysiologic insights facilitating triage of patients to emerging targeted therapies.

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Year:  2008        PMID: 18840713      PMCID: PMC2951831          DOI: 10.1182/blood-2007-10-119438

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


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