I am a National Library of Medicine research postdoctoral fellow in the Department of Molecular Biophysics and Biochemistry at Yale University. With this training/research proposal, I am applying to the Career Development Award. I had degreed education in both Biology and Computer Science and started my training and research in Computational Biology, the field of my research interest, in 1998. My immediate career goal is to have an extensive training in functional genomics, both computational and experimental. My long-term career goal is to become an independent investigator at a research institution and to make a substantial contribution to health-related research field. To achieve these goals, I will first conduct mentored research in functional genomics for two years under the guidance of Profs Gerstein and Snyder at Yale University and then apply for a research position at another institution. The goal of my proposed research is to obtain and analyze the profiles of gene expression, transcription regulation, and DNA copy number variation related to tumor metastasis progression as the five-year research plan. This proposal builds on my experience in genomic analysis of microarray data as a part of the ENCODE Project. For a training grant, the proposed research projects include both experimental and computational components. Specifically, I propose to identify the DNA-binding sites of two key regulators of tumor metastasis (Twist and Snail) in both normal murine embryonic cells and four murine isogenic mammary carcinoma cell lines (67NR, 168FARN, 4T07, and 4T1). In parallel, I will develop new algorithms for analyzing perturbed gene expression profiles to build a regulatory sub-network specific to the EMT process and identify other EMT regulators for further ChlP-chip experiments. As the target genes of the identified EMT regulators could be duplicated or deleted as a result of chromosomal micro-rearrangements during tumor metastasis, I will also carry out computational studies to analyze array-based comparative genomic hybridization data to identify such DNA copy number variations. I feel the proposed research is quite relevant to public health, becaus cancer is responsible for about 25% of all deaths in the United States. 90% of human cancer deaths, however, can be attributed to metastases, during which tumor cells spread from the primary tumor mass to distant organs. Clearly it is very important to understand what makes metastasis possible for a cancerous tumor and unravel its molecular mechanism.
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| Cai, Ying; Nogales-Cadenas, Ruben; Zhang, Quanwei et al. (2017) Transcriptomic dynamics of breast cancer progression in the MMTV-PyMT mouse model. BMC Genomics 18:185 |
| Nogales-Cadenas, Ruben; Cai, Ying; Lin, Jhih-Rong et al. (2016) MicroRNA expression and gene regulation drive breast cancer progression and metastasis in PyMT mice. Breast Cancer Res 18:75 |
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| Lemetre, Christophe; Zhang, Quanwei; Zhang, Zhengdong D (2013) SubNet: a Java application for subnetwork extraction. Bioinformatics 29:2509-11 |
| Zhang, Zhengdong D; Du, Jiang; Lam, Hugo et al. (2011) Identification of genomic indels and structural variations using split reads. BMC Genomics 12:375 |
