Cancer is classically modeled as a malignant transformation with genetic mutation of oncogenes or tumorsuppressor genes driving uncontrolled cellular growth. However, epigenefic or even stochasfic endogenous variations in the expression levels of these genes may be sufficient to disregulate proliferation and apoptosis pathways, and drive tumorigenesis. Thus, there may exist cancers whose origin and maintenance stem from non-genefic perturbafions of normal pathways. In this project, we focus on Chronic Lymphocytic Leukemia (CLL), a lymphoproliferative disease characterized by the clonal expansion of mature B lymphocytes arrested in the G0/G1 phase of the cell cycle. To date, there is no known mutafion conferring dominant-positive or dominant negative activifies to signaling regulators that would account for the resistance to apoptosis and enhanced proliferafion of B cells in CLL. Differenfial expression of signaling components (e.g. upregulation of CDS and ZAP70) is used to predict clinical prospects for CLL patients, but there is limited understanding of their relevance to the growth dysregulation and disease progression. The goal of this research project is to study the heterogeneity of B cell signaling sustaining proliferation and apoptosis in CLL. For that purpose, we will introduce a systems biology platform that combines theoretical modeling of B cell signaling (under activation by antigens, cytokines or others) with experimental measurements on single primary cells. More specifically, we plan to rely on the natural heterogeneity of B cells (in CLL pafients or in healthy individuals), to map out the variability of CLL disease states. We will develop a theorefical biochemical model, to identify key signaling regulators in B cell signaling. We will also apply a new experimental methodology to correlate, at the single cell level, B cell responsiveness with expression levels of these key signaling regulators. Ulfimately, we aim at introducing multivariate parameters of individual cells within a population (from markers to functional response) to better characterize CLL phenotypes and offer new therapeufic approaches taking into account the variability in CLL B cells.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA148967-03
Application #
8377739
Study Section
Special Emphasis Panel (ZCA1-SRLB-C)
Project Start
Project End
Budget Start
2012-03-01
Budget End
2013-02-28
Support Year
3
Fiscal Year
2012
Total Cost
$426,349
Indirect Cost
$259,985
Name
Sloan-Kettering Institute for Cancer Research
Department
Type
DUNS #
064931884
City
New York
State
NY
Country
United States
Zip Code
10065
Argyropoulos, K V; Vogel, R; Ziegler, C et al. (2016) Clonal B cells in Waldenström's macroglobulinemia exhibit functional features of chronic active B-cell receptor signaling. Leukemia 30:1116-25
Gao, Sizhi P; Chang, Qing; Mao, Ninghui et al. (2016) JAK2 inhibition sensitizes resistant EGFR-mutant lung adenocarcinoma to tyrosine kinase inhibitors. Sci Signal 9:ra33
Quail, Daniela F; Bowman, Robert L; Akkari, Leila et al. (2016) The tumor microenvironment underlies acquired resistance to CSF-1R inhibition in gliomas. Science 352:aad3018
Vogel, Robert M; Erez, Amir; Altan-Bonnet, Grégoire (2016) Dichotomy of cellular inhibition by small-molecule inhibitors revealed by single-cell analysis. Nat Commun 7:12428
Buffie, Charlie G; Bucci, Vanni; Stein, Richard R et al. (2015) Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile. Nature 517:205-8
Korkut, Anil; Wang, Weiqing; Demir, Emek et al. (2015) Perturbation biology nominates upstream-downstream drug combinations in RAF inhibitor resistant melanoma cells. Elife 4:
Voisinne, Guillaume; Nixon, Briana G; Melbinger, Anna et al. (2015) T Cells Integrate Local and Global Cues to Discriminate between Structurally Similar Antigens. Cell Rep 11:1208-19
Klemm, Florian; Joyce, Johanna A (2015) Microenvironmental regulation of therapeutic response in cancer. Trends Cell Biol 25:198-213
Prill, Robert J; Vogel, Robert; Cecchi, Guillermo A et al. (2015) Noise-driven causal inference in biomolecular networks. PLoS One 10:e0125777
Kaushik, Poorvi; Molinelli, Evan J; Miller, Martin L et al. (2014) Spatial normalization of reverse phase protein array data. PLoS One 9:e97213

Showing the most recent 10 out of 33 publications