Our general strategy is to take advantage of novel tools and methodologies that we have developed during our first CTD^2 funding period- more specifically pioneering and applying CRISPR based technologies to aid the discovery and characterization of novel cancer targets and their modulators? using innovative high throughput screening methods. Our end goal is to uncover optimal combinations of perturbagens with the potential to eliminate all cancer cells, despite their clonal heterogeneity and environmental context. One goal is to elucidate new molecular targets with the goal to overcome acquired drug resistance. We build upon an exciting system allowing us to quantitate genotypic and phenotypic cell heterogeneity for hundreds of thousands of single cancer cells. We propose a battery of therapeutic small molecule screens to identify candidate driver genes associated with drug resistance and with recurrent mutations from TCGA, TARGET, CGCI, ICGC and related initiatives. The overall goal is to identify synthetic gene combinations necessary for clinical resistance and related to inter- and intra-tumor heterogeneity. We will develop and apply methodologies for the identification of genes influencing heterotypic cell-cell interactions in tumors. Tumor evolution is a challenging area of research, largely due to the complexity of cell types and behaviors. In this aim, high-throughput screens will be performed to identify non-cell autonomous synthetic lethal and synthetic viable interactions relevant to tumor microenvironment interactions. These studies will include primary T-effector/cancer cell interactions to identify new therapeutic targets and cancer associated macrophage and fibroblast/cancer cell screens to identify genes mediating therapeutic resistance. These systems are made possible by using a currently unpublished screening platform that may help to identify genes important for cancer initiation, maintenance, and possibly metastasis. Since we will use primary and cancer tissue, our unique platform will recapitulate as much as possible the characteristics of tumors in patients and address an important challenge in cancer research. We have developed a novel means to establish genetic epistatic interactions in mammalian cells and will expand upon our efforts to generate specific libraries to map the subset of targets identified in the above screens. In this aim, we will address targets and mechanisms by delineating where targets act in the pathway by probing cancer-defining molecular interdependencies, using the novel targets and screening systems described above. The end goal is to uncover the optimal combination of perturbagens with the potential to eliminate all cancer cells, despite their clonal heterogeneity.

Public Health Relevance

The goal of this proposal is directly to bridge the gap between the enormous volumes of data generated by the comprehensive molecular characterization of a number of cancer types? and the ability to use these data for the development of human cancer therapeutics.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01CA217882-01
Application #
9363592
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Gerhard, Daniela
Project Start
2017-08-10
Project End
2022-07-31
Budget Start
2017-08-10
Budget End
2018-07-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94118
Neel, Dana S; Allegakoen, David V; Olivas, Victor et al. (2018) Differential subcellular localization regulates oncogenic signaling by ROS1 kinase fusion proteins. Cancer Res :
Webber, James T; Kaushik, Swati; Bandyopadhyay, Sourav (2018) Integration of Tumor Genomic Data with Cell Lines Using Multi-dimensional Network Modules Improves Cancer Pharmacogenomics. Cell Syst 7:526-536.e6
Jost, Marco; Weissman, Jonathan S (2018) CRISPR Approaches to Small Molecule Target Identification. ACS Chem Biol 13:366-375
Martinko, Alexander J; Truillet, Charles; Julien, Olivier et al. (2018) Targeting RAS-driven human cancer cells with antibodies to upregulated and essential cell-surface proteins. Elife 7:
Wangensteen, Kirk J; Wang, Yue J; Dou, Zhixun et al. (2018) Combinatorial genetics in liver repopulation and carcinogenesis with a in vivo CRISPR activation platform. Hepatology 68:663-676
Nichols, Robert J; Haderk, Franziska; Stahlhut, Carlos et al. (2018) RAS nucleotide cycling underlies the SHP2 phosphatase dependence of mutant BRAF-, NF1- and RAS-driven cancers. Nat Cell Biol 20:1064-1073
Donnella, Hayley J; Webber, James T; Levin, Rebecca S et al. (2018) Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer. Nat Chem Biol 14:768-777
Hu, Hsien-Ming; Zhao, Xin; Kaushik, Swati et al. (2018) A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance. Cell Rep 23:918-929
Shah, Khyati N; Bhatt, Roma; Rotow, Julia et al. (2018) Aurora kinase A drives the evolution of resistance to third-generation EGFR inhibitors in lung cancer. Nat Med :
Tak, Y Esther; Kleinstiver, Benjamin P; Nuñez, James K et al. (2017) Inducible and multiplex gene regulation using CRISPR-Cpf1-based transcription factors. Nat Methods 14:1163-1166

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