Aberrant signaling events play a central role in cancer and other diseases. Elucidating the architecture of signaling networks is therefore essential for understanding both normal and malignant growth. Because signaling processes involve many interacting components that act in concert for functionally-relevant collective phenomena to emerge, it is often difficult to intuit mechanistic principles from experimental observations. Further confounding intuition is the inherently stochastic character of the pertinent processes. Recent studies of primary cells and well-characterized cell lines provide vivid examples of such complexity and heterogeneity of biological signaling networks. Our recent studies also illustrate how complementary theoretical and experimental studies can help elucidate complex features of Ras signaling in lymphocytes. The central theme of this project is to employ such an approach at the crossroads of the physical and life sciences to deconvolute the origins of aberrant Ras signaling and its consequences in the context of a specific T cell lymphoma observed in the clinic. We expect our findings to have broad implications for diverse cancers. This goal will be achieved by pursuing the following specific aims:
(Aim 1) To extend computational models of receptor induced Ras activation in normal T lymphocytes to include the downstream RAF/MEK/ERK-.PISkinase/Akt/mTOR/S6klnase-, and RalGDS-effector pathways, and cross-talk between these pathways. Model predictions will be used to design experiments that can discriminate sensitively between different hypotheses. We will then iterate between experiments and computational studies.
(Aim 2) To develop the models further by testing computational predictions against normal and oncogenic Ras mutant as well as oncogenic RasGRPI T cell lymphoma models. The paradigm of iteration between computational and experimental studies will be followed. Analyze the effects of complex cooperating genetic lesions.
(Aim 3) To use computational models to define critical oncogenic nodes within the networks and test the predicted lymphoma's vulnerability experimentally via chemical inhibitors, shRNA, and novel Kras alleles that are defective for PI3 kinase or RAF activation.

Public Health Relevance

Aberrant Ras signaling is a fundamental molecular lesion in many human cancers, but Ras proteins are widely regarded as undruggable. For this reason, attention has turned toward developing agents that target downstream kinase cascades such as Ral-GDS, Raf/MEK/ERK, and PI3 kinas/Akt/mTOR. Recent studies in our laboratories and by other groups have uncovered unexpected complexity and heterogeneity in these downstream signaling networks. Our goal is to bring together computational techniques from physical sciences with cancer biology to understand normal Ras-regulated signaling networks and characterize how these networks are remodeled and modulated in cancer. Our studies using T cell leukemia/lymphoma as a model for cancer in general should provide a framework for future preclinical and clinical trials aimed at improving survival while minimizing therapy-related toxicities.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA143874-04
Application #
8380500
Study Section
Special Emphasis Panel (ZCA1-SRLB-9)
Project Start
Project End
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
4
Fiscal Year
2012
Total Cost
$347,189
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code
02139
McFarland, Christopher D (2016) A modified ziggurat algorithm for generating exponentially- and normally-distributed pseudorandom numbers. J Stat Comput Simul 86:1281-1294
Cermak, Nathan; Olcum, Selim; Delgado, Francisco Feijó et al. (2016) High-throughput measurement of single-cell growth rates using serial microfluidic mass sensor arrays. Nat Biotechnol 34:1052-1059
Hosios, Aaron M; Hecht, Vivian C; Danai, Laura V et al. (2016) Amino Acids Rather than Glucose Account for the Majority of Cell Mass in Proliferating Mammalian Cells. Dev Cell 36:540-9
Stevens, Mark M; Maire, Cecile L; Chou, Nigel et al. (2016) Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate. Nat Biotechnol 34:1161-1167
Kimmerling, Robert J; Lee Szeto, Gregory; Li, Jennifer W et al. (2016) A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages. Nat Commun 7:10220
Hecht, Vivian C; Sullivan, Lucas B; Kimmerling, Robert J et al. (2016) Biophysical changes reduce energetic demand in growth factor-deprived lymphocytes. J Cell Biol 212:439-47
Akutagawa, J; Huang, T Q; Epstein, I et al. (2016) Targeting the PI3K/Akt pathway in murine MDS/MPN driven by hyperactive Ras. Leukemia 30:1335-43
Shaw Bagnall, Josephine; Byun, Sangwon; Miyamoto, David T et al. (2016) Deformability-based cell selection with downstream immunofluorescence analysis. Integr Biol (Camb) 8:654-64
Ramanan, Vyas; Trehan, Kartik; Ong, Mei-Lyn et al. (2016) Viral genome imaging of hepatitis C virus to probe heterogeneous viral infection and responses to antiviral therapies. Virology 494:236-47
Shaw Bagnall, Josephine; Byun, Sangwon; Begum, Shahinoor et al. (2015) Deformability of Tumor Cells versus Blood Cells. Sci Rep 5:18542

Showing the most recent 10 out of 81 publications