In cancer biology it has become evident that requirements for specific gene activities can vary widely across cancer types. These differences presumably arise from context-specific molecular constrains intrinsic to the tissue or cell type of origin and to the process of cancer development itself. Our current lack of knowledge of cancer-specific gene requirements and the processes driving their requirement has hampered development of targeted therapeutic strategies for cancer. However, in the past five years significant progress has been made in the development of culture systems for patient cancers that allow unprecedented access to cancer- evolved molecular pathways and cellular phenotypes. Over the past three years, we have developed a strategy for defining the nature of gene requirements in patient cancer samples. Our approach integrates data from functional genetic screens in patient derived cancer stem cells with network models constructed from """"""""cancer- omics"""""""" data sets to make gene requirement predictions. In proof of concept studies for Glioblastoma multiforme (GBM), an incurable form of brain cancer, we have demonstrated the existence of GBM-lethal genes, which when inhibited render patient GBM tumor cells sensitive to cellular stresses that arise as a consequence of cellular transformation. In this application w use this cancer-lethal prediction paradigm to address Provocative Question 8: Why do certain mutational events promote cancer phenotypes in some tissues and not others? We test the hypothesis that GBM-specific requirements for gene activities arise from one of three context-specific constraints: (a) the tissue of origin (i.e., neural-specific activity);(b) a GBM-specific evolution process;or (c) cellular transformation process in general. Our experimental approach will combine data from functional genetic screen in human GBM stem cells (of multiple subtypes) with pre-existing Bayesian network models for GBM and other cancers including, breast, lung, ovarian, and prostate (generated from The Cancer Genome Atlas patient data sets). If successful, these studies will reveal the extent and origin of GBM-specific requirements for gene activities in GBM patient samples. In addition to providing key insight into brain tumor biology, these studies will significantly aid in identifying new targeted therapeutic strategies fo GBM and other cancers with standard of care therapies suffering from poor therapeutic windows.

Public Health Relevance

This application attempts to model variation in the behavior of brain tumors through experimentation with patient-derived cells and manipulation of previously generated molecular data sets for five cancers including brain, breast, lung, ovarian and prostate. If successful, the experimental aims and results will create a new paradigm for the study of cancer biology and therapeutics. In addition to providing key insight into brain tumor biology, these studies will significantly aid in identifying new targeted therapeutic strategies fo brain and other cancers.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21CA170722-01
Application #
8384782
Study Section
Special Emphasis Panel (ZCA1-SRLB-D (M1))
Program Officer
Couch, Jennifer A
Project Start
2012-08-20
Project End
2014-07-31
Budget Start
2012-08-20
Budget End
2013-07-31
Support Year
1
Fiscal Year
2012
Total Cost
$241,720
Indirect Cost
$85,120
Name
Fred Hutchinson Cancer Research Center
Department
Type
DUNS #
078200995
City
Seattle
State
WA
Country
United States
Zip Code
98109
Wang, Qin; Lin, Luan; Yoo, Seungyeul et al. (2016) Impact of non-neoplastic vs intratumoural hepatitis B viral DNA and replication on hepatocellular carcinoma recurrence. Br J Cancer 115:841-7
Toledo, Chad M; Ding, Yu; Hoellerbauer, Pia et al. (2015) Genome-wide CRISPR-Cas9 Screens Reveal Loss of Redundancy between PKMYT1 and WEE1 in Glioblastoma Stem-like Cells. Cell Rep 13:2425-39
Herman, Jacob A; Toledo, Chad M; Olson, James M et al. (2015) Molecular pathways: regulation and targeting of kinetochore-microtubule attachment in cancer. Clin Cancer Res 21:233-9
Zhu, Jun; Chen, Congying; Yang, Bin et al. (2015) A systems genetics study of swine illustrates mechanisms underlying human phenotypic traits. BMC Genomics 16:88
Narayanan, Manikandan; Huynh, Jimmy L; Wang, Kai et al. (2014) Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases. Mol Syst Biol 10:743
Toledo, Chad M; Herman, Jacob A; Olsen, Jonathan B et al. (2014) BuGZ is required for Bub3 stability, Bub1 kinetochore function, and chromosome alignment. Dev Cell 28:282-94
Yoo, Seungyeul; Huang, Tao; Campbell, Joshua D et al. (2014) MODMatcher: multi-omics data matcher for integrative genomic analysis. PLoS Comput Biol 10:e1003790
Ding, Yu; Hubert, Christopher G; Herman, Jacob et al. (2013) Cancer-Specific requirement for BUB1B/BUBR1 in human brain tumor isolates and genetically transformed cells. Cancer Discov 3:198-211
Wu, Chao; Zhu, Jun; Zhang, Xuegong (2013) Network-based differential gene expression analysis suggests cell cycle related genes regulated by E2F1 underlie the molecular difference between smoker and non-smoker lung adenocarcinoma. BMC Bioinformatics 14:365
Hubert, Christopher G; Bradley, Robert K; Ding, Yu et al. (2013) Genome-wide RNAi screens in human brain tumor isolates reveal a novel viability requirement for PHF5A. Genes Dev 27:1032-45