- Overall The overall goal of the Measuring, Modeling and Controlling Heterogeneity Center in the Cancer Systems Biol- ogy Consortium (M2CH-CSBC Center) is to improve management of triple negative breast cancer (TNBC) by developing systems level strategies to prevent the emergence of cancer subpopulations that are resistant to treatment. We postulate that heterogeneity arising from epigenomic instability intrinsic to cancer cells and di- verse signals from extrinsic microenvironments in which cancer cells reside are root causes of resistance. We will learn how intrinsic and extrinsic factors influence differentiation state, proliferation and therapeutic re- sponse in TNBC through experimental manipulation and computational modeling of cancer cell lines, 3D engi- neered multicellular systems, xenografts and clinical specimens. We will deploy single cell `omic and imaging technologies that allow quantitative assessment of molecular, cellular, and structural heterogeneity. We will interpret these data using computational models that define control networks and structures in heterogeneous systems as well as transitions between states of therapeutic resistance and sensitivity. This will be accom- plished in three related Projects and three Cores. Project 1 will focus on measuring and managing resistance- associated heterogeneity intrinsic to cancer cells. Project 2 will focus on identifying resistance-associated sig- nals from the microenvironment and on mitigating effects from these signals on therapeutic response. Project 3 will apply spatial systems biology approaches to TNBC specimens and multicell type models thereof to dis- cover molecular control networks that influence how cell intrinsic plasticity and microenvironment signaling al- ter therapeutic responses in complex tissues. All three Projects will include analysis of 5 core cell lines (HCC1143, HCC1599, MDA-MB-468, SUM149PT, and HCC1806), 5 patient derived cultures, and 6 FDA ap- proved, pathway-targeted drugs (afatinib, ruxolotinib, trametinib, BYL719, cabozantinib, and everolimus). The computational network discovery, data integration, spatial systems analysis and modeling approaches are the same in all Projects and serve to integrate the work of the overall M2CH-CSBC Center. Multiple integrative computational strategies are proposed to identify candidate heterogeneity control networks. These include analysis of existing genomic, epigenomic, pharmacologic response, and metabolomic characteristics of prima- ry tumors and models thereof. An Imaging Management and Analysis Core will provide infrastructure and image analytics that will enable efficient image data management, quantitative analysis of image features, and visualization of images and metadata generated using multiscale light and electron microscopy. An Outreach Core will make educational materials, experimental and computational tools and data available to the CSB Consortium, to the CSBC/PS-ON Coordinating Center and to the broader scientific community. An Administrative Core serves as the organization, integration, and evaluation hub of the M2CH-CSBC Center.

Public Health Relevance

This Project will improve management of triple negative breast cancer (TNBC) by understanding and managing heterogeneity arising from epigenomic instability intrinsic to cancer cells and from diverse signals from extrinsic microenvironments in which cancer cells reside.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
1U54CA209988-01A1
Application #
9350715
Study Section
Special Emphasis Panel (ZCA1-RTRB-R (J2))
Program Officer
Hughes, Shannon K
Project Start
2017-05-22
Project End
2022-04-30
Budget Start
2017-05-22
Budget End
2018-04-30
Support Year
1
Fiscal Year
2017
Total Cost
$1,876,979
Indirect Cost
$601,154
Name
Oregon Health and Science University
Department
Biomedical Engineering
Type
Schools of Medicine
DUNS #
096997515
City
Portland
State
OR
Country
United States
Zip Code
97239
Archer, Tenley C; Ehrenberger, Tobias; Mundt, Filip et al. (2018) Proteomics, Post-translational Modifications, and Integrative Analyses Reveal Molecular Heterogeneity within Medulloblastoma Subgroups. Cancer Cell 34:396-410.e8
Gray, Elliot; Mitchell, Elizabeth; Jindal, Sonali et al. (2018) A METHOD FOR QUANTIFICATION OF CALPONIN EXPRESSION IN MYOEPITHELIAL CELLS IN IMMUNOHISTOCHEMICAL IMAGES OF DUCTAL CARCINOMA IN SITU. Proc IEEE Int Symp Biomed Imaging 2018:796-799
Davis, Ryan J; Gönen, Mehmet; Margineantu, Daciana H et al. (2018) Pan-cancer transcriptional signatures predictive of oncogenic mutations reveal that Fbw7 regulates cancer cell oxidative metabolism. Proc Natl Acad Sci U S A 115:5462-5467
Burlingame, Erik A; Margolin, Adam A; Gray, Joe W et al. (2018) SHIFT: speedy histopathological-to-immunofluorescent translation of whole slide images using conditional generative adversarial networks. Proc SPIE Int Soc Opt Eng 10581:
Chang, Young Hwan; Heo, You Jeong; Cho, Junhun et al. (2018) Computational measurement of tumor immune microenvironment in gastric adenocarcinomas. Sci Rep 8:13887
Risom, Tyler; Langer, Ellen M; Chapman, Margaret P et al. (2018) Differentiation-state plasticity is a targetable resistance mechanism in basal-like breast cancer. Nat Commun 9:3815
Su, Yulong; Pelz, Carl; Huang, Tao et al. (2018) Post-translational modification localizes MYC to the nuclear pore basket to regulate a subset of target genes involved in cellular responses to environmental signals. Genes Dev 32:1398-1419
Chang, Young Hwan; Thibault, Guillaume; Johnson, Brett et al. (2017) Integrative Analysis on Histopathological Image for Identifying Cellular Heterogeneity. Proc SPIE Int Soc Opt Eng 10140:
Azimi, Vahid; Chang, Young Hwan; Thibault, Guillaume et al. (2017) BREAST CANCER HISTOPATHOLOGY IMAGE ANALYSIS PIPELINE FOR TUMOR PURITY ESTIMATION. Proc IEEE Int Symp Biomed Imaging 2017:1137-1140
Tsujikawa, Takahiro; Kumar, Sushil; Borkar, Rohan N et al. (2017) Quantitative Multiplex Immunohistochemistry Reveals Myeloid-Inflamed Tumor-Immune Complexity Associated with Poor Prognosis. Cell Rep 19:203-217