The overall goal ofthis proposal is to build a multi-scale modeling platform for investigation ofthe breast cancer, with special emphasis on the roles ofthe tumor-initiating cells (TIC). This modeling platform will mainly consist of two closely related components: biological experiments and mathematical computational modeling. For the experiment component, we seek to use newly developed experimental and imaging methodologies to identify, localize, purify and characterize TIC. Further experiments will be designed to discover the spatial localization and movement, and specific changes in gene expression and cellular signaling of breast cancer TIC. Combined functional genomics and data mining strategies will allow us to characterize novel growth regulators. Further, our combined experimental and systems biology approach will allow us to evaluate responses to experimental therapeutics that may inhibit or kill TIC specifically in a manner not possible before. For the mathematical modeling component, we will develop bioinformatics and bio-imaging models to integrate and analyze the data generated from biological experiments, and make use ofthe information obtained from data analysis, biological knowledge to build in silico models to model TIC behavior, cancer cell apoptosis, cell migration, cycle and drug treatment response. Besides providing a basic framework for understanding the mechanism underlying breast cancer stem cell evolution, the models can also give birth to hypotheses or experimental design. More important, these models will allow one to predict the biological state under investigation and predict how the natural process will behave in various circumstances. Iterative feedback between these two components will refine our proposed platform further. The ultimate goal is an integrated modeling platform of breast cancer biology that can mimic in vivo processes faithfully enough to serve as a h5TDOthesis-generation and screening tool, and in the distant future, as a tool for evaluating clinical procedures and their expected outcomes.

Public Health Relevance

This project will be a substantial contribution to the public health by understanding the mechanism of cancer initial cells or cancer stem cells. More importantly, the completion ofthis screening project will help to answer some critical questions related to breast caner. Such understanding will in turn advance our knowledge in tumor biology and open up the possibility of novel treatments in the future.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA149196-05
Application #
8628779
Study Section
Special Emphasis Panel (ZCA1-SRLB-C (J1))
Program Officer
Gallahan, Daniel L
Project Start
2010-05-01
Project End
2015-02-28
Budget Start
2014-05-19
Budget End
2015-02-28
Support Year
5
Fiscal Year
2014
Total Cost
$1,650,165
Indirect Cost
$293,527
Name
Methodist Hospital Research Institute
Department
Type
DUNS #
185641052
City
Houston
State
TX
Country
United States
Zip Code
77030
Leung, Cecilia S; Yeung, Tsz-Lun; Yip, Kay-Pong et al. (2018) Cancer-associated fibroblasts regulate endothelial adhesion protein LPP to promote ovarian cancer chemoresistance. J Clin Invest 128:589-606
Wang, Hai; Tian, Lin; Liu, Jun et al. (2018) The Osteogenic Niche Is a Calcium Reservoir of Bone Micrometastases and Confers Unexpected Therapeutic Vulnerability. Cancer Cell 34:823-839.e7
Yu, Yaping; Kong, Ren; Cao, Huojun et al. (2018) Two birds, one stone: hesperetin alleviates chemotherapy-induced diarrhea and potentiates tumor inhibition. Oncotarget 9:27958-27973
Liu, Yi; Choi, Dong Soon; Sheng, Jianting et al. (2018) HN1L Promotes Triple-Negative Breast Cancer Stem Cells through LEPR-STAT3 Pathway. Stem Cell Reports 10:212-227
Rosato, Roberto R; Dávila-González, Daniel; Choi, Dong Soon et al. (2018) Evaluation of anti-PD-1-based therapy against triple-negative breast cancer patient-derived xenograft tumors engrafted in humanized mouse models. Breast Cancer Res 20:108
Ren, Ding; Zhu, Xiaoping; Kong, Ren et al. (2018) Targeting Brain-Adaptive Cancer Stem Cells Prohibits Brain Metastatic Colonization of Triple-Negative Breast Cancer. Cancer Res 78:2052-2064
Guven, Adem; Villares, Gabriel J; Hilsenbeck, Susan G et al. (2017) Carbon nanotube capsules enhance the in vivo efficacy of cisplatin. Acta Biomater 58:466-478
Chen, Suyun; Ibrahim, Nuhad K; Yan, Yuanqing et al. (2017) Complete Metabolic Response on Interim18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography to Predict Long-Term Survival in Patients with Breast Cancer Undergoing Neoadjuvant Chemotherapy. Oncologist 22:526-534
Neelakantan, Deepika; Zhou, Hengbo; Oliphant, Michael U J et al. (2017) EMT cells increase breast cancer metastasis via paracrine GLI activation in neighbouring tumour cells. Nat Commun 8:15773
Hosoya, Hitomi; Dobroff, Andrey S; Driessen, Wouter H P et al. (2016) Integrated nanotechnology platform for tumor-targeted multimodal imaging and therapeutic cargo release. Proc Natl Acad Sci U S A 113:1877-82

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