OHSU

Joe Gray, Ph.D.

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Background

OHSU Center for Spatial Systems Biomedicine

The Gray Laboratory explores mechanisms by which genomic, transcriptional and proteomic abnormalities occur in selected cancers, elucidates how these abnormalities contribute to cancer pathophysiologies and assesses the ways in which these abnormalities influence responses to gene targeted therapies. Current studies focus on developing: (a) integrated analyses of the spectrum of recurrent abnormalities that influence cancer behavior (b) mathematical models that describe how cancer-associated molecular abnormalities influence individual responses to therapeutic inhibitors (c) novel therapeutic approaches to treat breast or ovarian cancer subpopulations that do not respond well to current aggressive chemotherapeutic strategies (d) proteomic strategies for early detection of breast cancer related proteins in blood (e) automated functional assessment of genes deregulated by genomic abnormalities in cancers, and (f) molecular imaging for early detection of metastasis prone breast cancer.

Integrated analysis We are assessing abnormalities associated with clinical outcome in breast cancers using a combination of comparative genomic hybridization (CGH), massively parallel sequencing (whole exome sequencing and RNA sequencing) and reverse phase protein lysate arrays to assess allele specific genome copy number, RNA expression, and protein and phosphoprotein levels in cancer related genes. These studies are supported by the NCI Bay Area Breast Cancer SPORE and The Cancer Genome Altas project.

Mathematical models We are developing mathematical methods to predict individual responses to therapeutic agents using information on responses to these agents in a collection of cell lines grown in vitro. Major emphasis in this project is on breast cancer. Current emphasis is on development of statistical, Bayesian and ODE models of Her-family signaling. Work in this area is supported by an NCI Center for Cancer Systems Biology award.

Novel therapeutic approaches We are using advanced genomic analysis and high content, high throughput imaging to assess responses to NCI and private sector compounds for our collection of ~100 breast, ovary, prostate and pancreas cancer cell lines. Our goal is to identify therapeutic agents that will be highly effective against tumor subtypes that do poorly on aggressive therapy. In addition, we are developing siRNA therapeutic approaches to treat tumors that amplify and over express transcripts to which the tumors become aaddicted. Current emphasis is on development of strategies to identify and inhibit functionally important genes in regions of amplification associated with poor outcome. This work is supported by an NCI Ovarian Cancer SPORE, the NCI Bay Area Breast Cancer SPORE, the NIH Foundation and an AACR Stand Up to Cancer Award.

Early detection We are using information about genomic and transcriptional abnormalities in breast cancer to guide the development of mass spectrometric strategies that can detect breast cancer subtype specific proteins in order to enable early detection of metastasis prone breast cancers. We are giving special attention to detection of aberrant proteins that result from cancer specific alternative splicing, glycosylation or phosphorylation. Mass spectrometry and capillary isoelectric focusing approaches are being developed to detect these proteins in the blood, MRI and PET imaging approaches are being developed for anatomic detection and scanned ion beam mass spectrometry is being developed for improved histopathological analysis. These studies are supported by grants from the NCI Clinical Proteomic Technologies for Cancer (CPTAC) program and a DOD Innovator award.


Selected Publications

"Amplification and over-expression of MAP3K3 gene in human breast cancer promotes formation and survival of breast cancer cells," Journal of Pathology (Vol: 232, Issue: 1, Page 75-86) - 2014

"CUL4A induces epithelial-mesenchymal transition and promotes cancer metastasis by regulating ZEB1 expression," Cancer Research (Vol: 74, Issue: 2, Page 520-531) - 2014

"A colorectal cancer classification system that associates cellular phenotype and responses to therapy," Nature Medicine (Vol: 19, Issue: 5, Page 619-625) - 2013

"A robust prognostic signature for hormone-positive node-negative breast cancer," Genome Medicine (Vol: 5, Issue: 10, ) - 2013

"CpG island shore methylation regulates caveolin-1 expression in breast cancer," Oncogene (Vol: 32, Issue: 38, Page 4519-4528) - 2013

 

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503 418-9302

Research Expertise Profile

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