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Sci. STKE, 27 July 2004
Vol. 2004, Issue 243, p. tw267
[DOI: 10.1126/stke.2432004tw267]


CANCER BIOLOGY Revealing Signaling Network Heterogeneity

Irish et al. set out to determine whether the variation in the genetics and clinical phenotypes of human cancer correlated with altered responsiveness of signaling networks. They used multiparameter flow cytometry to quantify the amounts of various phosphorylated proteins in acute myeloid leukemia (AML) cells from multiple patients, normal CD33+ cells, and two cell lines, HL-60 AML cells and U937 lymphoma cells. They found substantial variation among the 30 AML patient samples in the basal phosphorylation state of the transcriptional regulators STAT1, STAT3, STAT5, and STAT6, extracellular signal-regulated protein kinases 1 and 2 (ERK1/2), and the stress-activated protein kinase p38. Furthermore, the AML samples showed differential responsiveness to various cytokines in terms of the change in phosphorylation state of the measured proteins. Using an unsupervised clustering algorithm, the authors classified the AML patient samples into four groups on the basis of their basal phosphorylation status and change in response to cytokine stimulation. The frequency with which a particular cytogenetic profile, Flt3 mutation (Flt3 is a receptor tyrosine kinase, and aberrant signaling through this receptor occurs in 30% of AML patients), the abundance of CD15, and response to chemotherapy occurred in each of the four groups was analyzed. From this analysis, particular alterations in phosphoprotein biosignature were statistically correlated with clinical and genetic phenotypes. This single cell analysis may allow the mechanisms for cancer cell heterogeneity to be matched to particular aberrant signaling networks and thus mechanism-based therapies can be developed.

J. M. Irish, R. Hovland, P. O. Krutzik, O. D. Perez, Ø. Bruserud, B. T. Gjertsen, G. P. Nolan, Single cell profiling of potentiated phospho-protein networks in cancer cells. Cell 118, 217-288 (2004). [Online Journal]

Citation: Revealing Signaling Network Heterogeneity. Sci. STKE 2004, tw267 (2004).

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