Understanding emergent resistance to trastuzumab is inhibited by the inability to quantify aberrant cell signaling pathways among heterogeneous populations of breast cancer cells. Thus there is urgent need for multidisciplinary approaches to assess and interpret the clinical importance of cellular heterogeneity within breast cancer tumors. Our long-term goal is to improve the clinical management of cancer by establishing the scientific foundation for a prognostic technology that will identify individuals who will develop resistance to molecularly targeted therapies. Thus, the proposed research is relevant to NIH's mission by developing fundamental knowledge that will potentially help to reduce the burdens of human cancer. The overall objective of this application is to identify unique patterns of signaling proteins associated with drug sensitivity and apply the computational tools of reaction pathway analysis to interpret the significance of these patterns of protein expression. Our central hypothesis is that breast cancer cells that overexpress ErbB2 exhibit heterogeneity in response to trastuzumab. Furthermore, this heterogeneity is due to variations in expression of proteins that influence the ErbB2 signaling pathway. Prior studies identify such proteins that individually correlate with trastuzumab resistance. The challenge is inferring how these proteins act in concert to influence trastuzumab resistance. We plan to test our central hypothesis and accomplish the overall objective of this application by pursuing the following specific aims: 1) Establish that cellular heterogeneity in response to trastuzumab exists within established cell lines;and 2) Establish how reaction pathway analysis can be used to interpret differential patterns of protein expression within cellular signaling networks. Under the first aim, we expect to test our working hypothesis that cells within a tumor population, as represented by existing breast cancer cell lines, exhibit a variety of changes in protein expression that confer differential sensitivity to trastuzumab treatment. To address this hypothesis, we will select cell populations with varying sensitivity to trastuzumab from existing ErbB2-overexpressing breast cancer cell lines. These cell populations will be experimentally tested for variations in protein expression using 2D-gel electrophoresis. Under the second aim, our working hypothesis is that an unbiased model of the early signaling events in the ErbB2 signaling network can be constructed using an algorithm for the computer-assisted assembly of reaction mechanisms. The rationale that underlies the proposed research is that identifying patterns of signaling proteins that are correlated with sensitivity to trastuzumab will enable measuring these protein patterns at the single-cell level in tumor biopsy samples. The proposed research is innovative as it provides a novel approach that combines cutting-edge techniques in computational systems biology and proteomics to address the pressing issue of emergent resistance to trastuzumab in breast cancer patients.
The proposed studies are an important step towards understanding the implications of cellular heterogeneity within the ErbB2 signaling network on emergent resistance to trastuzumab in breast cancer patients. The proposed research is expected to have an important positive impact on public health, because the approach proposed will enable transcending the current genetic paradigm that limits progress toward eradicating breast cancer as a life-threatening disease. These studies will also provide training opportuni- ties for graduate and undergraduate students at the interface between reaction pathway analysis, cancer cell biology, and bioanalytical chemistry. This interdisciplinary project will expose the students to various facets of biological research and to cutting-edge techniques for solving biomedical problems. This unique training experience at WVU will help students to succeed in their future research careers.
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