The phenotypic heterogeneity of human cancers presents major challenges to advancing our understanding of disease mechanisms as well as to developing effective strategies for therapeutic design. This heterogeneity is also reflected in the variation in activity of cell signaling pathways that control cell growth and determine cell fate, processes critical for driving the cancer phenotype. The primary goal of the work described in this proposal is to take advantage of recent developments in the use of genome-scale measures of gene expression, together with advanced computational tools, to develop a more detailed understanding of the gene regulatory networks associated with the action of various oncogenic activities. Our focus is two-fold: develop a better understanding of the function and inter-connection of cell signaling pathways and second, utilize this information to translate to opportunities in clinical practice. A central focus of our work has been the development of expression signatures as a representation of a biological state, in this instance the activation of a pathway. These signatures will be expanded to a large collection of pathways relevant for cancer phenotypes;we will also develop and utilize novel statistical methodologies to dissect the complexity of cell signaling pathways, developing a library of verified pathway sub-signatures. In addition, the gene expression signatures reflecting cell signaling pathway activation, including pathway sub-signatures, will be used to define subgroups of cancer as the basis for defining distinct mechanisms of disease. And finally, genome-wide siRNA targeting will be used to identify cellular that influence the activity of cell signaling pathways.
Recent studies describing in-depth analyses of gene mutations in a number of human cancers have emphasized the complexity and heterogeneity of cancer and the importance of placing such analyses in pathway-specific contexts. A major focus of our work has been the use of gene expression signatures to define and predict the activity of a variety of cell signaling pathways that contribute to the oncogenic phenotype. Importantly, not only do these signatures provide a mechanism to dissect the heterogeneity of human cancers but they also provide an understanding of the events associated with this heterogeneity. Furthermore, since these signatures also predict sensitivity to various targeted therapeutics, these tools provide a framework for developing a strategy for treatment of individual patients.
|Tang, X; Ding, C-K; Wu, J et al. (2017) Cystine addiction of triple-negative breast cancer associated with EMT augmented death signaling. Oncogene 36:4235-4242|
|Tang, Xiaohu; Wu, Jianli; Ding, Chien-Kuang et al. (2016) Cystine Deprivation Triggers Programmed Necrosis in VHL-Deficient Renal Cell Carcinomas. Cancer Res 76:1892-903|
|Syu, Jhih-Pu; Chi, Jen-Tsan; Kung, Hsiu-Ni (2016) Nrf2 is the key to chemotherapy resistance in MCF7 breast cancer cells under hypoxia. Oncotarget 7:14659-72|
|Keenan, Melissa M; Liu, Beiyu; Tang, Xiaohu et al. (2015) ACLY and ACC1 Regulate Hypoxia-Induced Apoptosis by Modulating ETV4 via ?-ketoglutarate. PLoS Genet 11:e1005599|
|Bhattacharyya, Jayanta; Bellucci, Joseph J; Weitzhandler, Isaac et al. (2015) A paclitaxel-loaded recombinant polypeptide nanoparticle outperforms Abraxane in multiple murine cancer models. Nat Commun 6:7939|
|LaGory, Edward L; Wu, Colleen; Taniguchi, Cullen M et al. (2015) Suppression of PGC-1? Is Critical for Reprogramming Oxidative Metabolism in Renal Cell Carcinoma. Cell Rep 12:116-127|
|Kephart, Julie J G; Tiller, Rosanne G J; Crose, Lisa E S et al. (2015) Secreted Frizzled-Related Protein 3 (SFRP3) Is Required for Tumorigenesis of PAX3-FOXO1-Positive Alveolar Rhabdomyosarcoma. Clin Cancer Res 21:4868-80|
|Tang, Xiaohu; Keenan, Melissa M; Wu, Jianli et al. (2015) Comprehensive profiling of amino acid response uncovers unique methionine-deprived response dependent on intact creatine biosynthesis. PLoS Genet 11:e1005158|
|Horton, Janet K; Siamakpour-Reihani, Sharareh; Lee, Chen-Ting et al. (2015) FAS Death Receptor: A Breast Cancer Subtype-Specific Radiation Response Biomarker and Potential Therapeutic Target. Radiat Res 184:456-69|
|Mo, Lihong; Bachelder, Robin E; Kennedy, Margaret et al. (2015) Syngeneic Murine Ovarian Cancer Model Reveals That Ascites Enriches for Ovarian Cancer Stem-Like Cells Expressing Membrane GRP78. Mol Cancer Ther 14:747-56|
Showing the most recent 10 out of 42 publications