The long-term goal of this project is to develop mathematical and physico-chemical models that describe the cellular response to DNA damage at the network and systems biology level. The work involves the tight integration of focused rigorously quantitative experimental studies monitoring the activity of a large number of intracellular protein kinase signaling pathways and correlating their activity with the cellular phenotypes of DNA damage-induced cell cycle arrest and re-entry, apoptosis or senescence using a variety of quantitative mathematical models. These models capture the relevant signaling information, and provide new insights into the underlying biology. Experiments focus on human lymphoma and breast cancer cells with direct translational relevance, and build directly on our prior experimental and modeling work performed during the previous funding period. In lymphoma cells our focus includes t h e connection between DNA damage signaling, cellular response, and transcriptional regulation since our preliminary data suggests that transcriptional changes are likely to be especially important in predicting the response of this tumor type to treatment. In breast cancer cells, we focus on t h e interactions and cross-talk between the EGFR and DNA damage signaling pathways, since our preliminary data suggests that these signals can b e manipulated advantageously to enhance tumor cell killing using agents that are currently in wide clinical use. The computational models that result from this work illuminate which components of the various signaling pathways are most important for the different cellular responses at various times after the genotoxic stress, thereby defining the critical pathways through which cellular signaling information flows. Predictions from the models for both of these tumor types are then explored and tested at a variety of scales, including in vitro cell culture systems, murine xenografts, and mouse cancer models. Guided by t h e models, key nodes in the signaling pathways implicated as being critically important at particular time points after DNA damage will be identified, providing a mechanistic molecular basis underlying the observed cellular phenotype induced by genotoxic stress. The result of these experiments will be a significantly enhanced understanding of the global DNA damage response at the systems level including mechanisms underlying cancer predisposition and therapeutic resistance, and the identification of critical signaling pathways and molecules that should be targets for therapeutic manipulation in cancer treatment.

Public Health Relevance

The ultimate goal is to apply these models to predict and optimize the responsiveness of human tumors to DNA damaging therapies and therapy combinations, identify patient- and tumor-specific treatments based on the status of their DNA repair and signal transduction networks, and define new targets and drug combinations that enhance the chemotherapeutic response and improve patient survival.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA112967-08
Application #
8375828
Study Section
Special Emphasis Panel (ZCA1-SRLB-C)
Project Start
Project End
Budget Start
2012-04-17
Budget End
2013-02-28
Support Year
8
Fiscal Year
2012
Total Cost
$273,967
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code
02139
Kulkarni, Madhura; Tan, Tuan Zea; Syed Sulaiman, Nurfarhanah Bte et al. (2018) RUNX1 and RUNX3 protect against YAP-mediated EMT, stem-ness and shorter survival outcomes in breast cancer. Oncotarget 9:14175-14192
Oudin, Madeleine J; Barbier, Lucie; Schäfer, Claudia et al. (2017) MENA Confers Resistance to Paclitaxel in Triple-Negative Breast Cancer. Mol Cancer Ther 16:143-155
Bruno, Peter M; Liu, Yunpeng; Park, Ga Young et al. (2017) A subset of platinum-containing chemotherapeutic agents kills cells by inducing ribosome biogenesis stress. Nat Med 23:461-471
Werbin, Jeffrey L; Avendaño, Maier S; Becker, Verena et al. (2017) Multiplexed Exchange-PAINT imaging reveals ligand-dependent EGFR and Met interactions in the plasma membrane. Sci Rep 7:12150
Miller, Miles A; Sullivan, Ryan J; Lauffenburger, Douglas A (2017) Molecular Pathways: Receptor Ectodomain Shedding in Treatment, Resistance, and Monitoring of Cancer. Clin Cancer Res 23:623-629
Nagel, Zachary D; Kitange, Gaspar J; Gupta, Shiv K et al. (2017) DNA Repair Capacity in Multiple Pathways Predicts Chemoresistance in Glioblastoma Multiforme. Cancer Res 77:198-206
Zhao, Boyang; Hemann, Michael T; Lauffenburger, Douglas A (2016) Modeling Tumor Clonal Evolution for Drug Combinations Design. Trends Cancer 2:144-158
Tuncbag, Nurcan; Milani, Pamela; Pokorny, Jenny L et al. (2016) Network Modeling Identifies Patient-specific Pathways in Glioblastoma. Sci Rep 6:28668
Carmona, G; Perera, U; Gillett, C et al. (2016) Lamellipodin promotes invasive 3D cancer cell migration via regulated interactions with Ena/VASP and SCAR/WAVE. Oncogene 35:5155-69
Zhao, Boyang; Sedlak, Joseph C; Srinivas, Raja et al. (2016) Exploiting Temporal Collateral Sensitivity in Tumor Clonal Evolution. Cell 165:234-246

Showing the most recent 10 out of 222 publications