Education. Research Interests

Transcription

1 Sha Cao, PhD Department of Biochemistry and Molecular Biology A110 Davison Life Sciences Building, University of Georgia Phone: (706) Personal website: Education Ph.D., Statistics, University of Georgia Ph.D student in Bioinformatics, University of Georgia B.S., Mathematics, Beijing Normal University Research Interests I am interested in developing and applying statistical, mathematical and computational methods for mining cancer tissue omic data to tackle fundamental and challenging cancer biology questions including the following areas: Construction of Bayesian networks to infer the dependencies between microenvironmental stresses, key metabolic changes and explosive growth of postmetastatic cancers Bayesian biclustering based derivation of cell type-specific expression modules to digitally dissect mixture tissue expressions into sum of component cell types contributions Markov Chain Monte Carlo algorithm based metabolic flux estimation for cancer cells with priors on normal cells flux and cancer specific kinetic parameters Large scale association studies on epigenomic markers in cancers with detected micro-environmental stress markers of various types based on integrated studies of epigenomic and transriptomic data Working Experiences now Research Assistant, Computational Systems Biology Lab, University of Georgia, Athens, GA Graduate Research Assistant, Institute of Bioinformatics, University of Georgia, Athens, GA Undergraduate research assistant, Lab of Computational Molecular Biology, Beijing Normal University, Beijing, China Publications 1. Song T, Cao S, Sheng T, Liang S, Du W, Liang Y. A Novel Unsupervised Algorithm for Biological Process-based Analysis on Cancer. Scientific Reports. (2017) (In press).

2 2. Cao S+, Zhu X+, Zhang C, Qian H, Schuttler HB, Gong JP, Xu Y. Competition between DNA methylation, nucleotide synthesis and anti-oxidation in cancer versus normal tissues. Cancer Res. (2017) DOI: / CAN Song T, Wang Y, Du W, Cao S, Tian Y, Liang Y. The Method for Breast Cancer Grade Prediction and Pathway Analysis Based on Improved Multiple Kernel Learning. J. Bioinform. Comput. Biol. 15, (2017). 4. Zhang C, Sheng T, Cao S, Xu Y. Computational analysis of the impact of Autophagy in different stages of cancer progression, a chapter in book Autophagy and Cancer, Editor: Jin-Ming Yang, Springer, 2016 (in press). 5. Coothankandaswamy, V., Cao, S., Xu, Y., Prasad, P. D., Singh, P. K., Reynolds, C. P., Yang, S., Ogura, J., Ganapathy, V., and Bhutia, Y. D. (2016) Amino acid transporter SLC6A14 is a novel and effective drug target for pancreatic cancer. British Journal of Pharmacology. 173: doi: /bph Cao S +, Zhang C +, and Xu Y. Somatic Mutations May Not Be the Primary Drivers of Cancer Formation. International Journal of Cancer. (2015) DOI: /ijc Zhang C +, Chao L +, Cao S + and Xu Y. Elucidation of Divers of High-Level Production of Lactates throughout a Cancer Development. Journal of Molecular Cell Biology. (2015) doi: /jmcb/mjv Chou WC, Ma Q, Yang S, Cao S, Klingeman DM, Brown SD, Xu Y. (2015) Analysis of strand-specific RNA-seq data using machine learning reveals the structures of transcription units in Clostridium thermocellum. Nucleic Acids Research. doi: /nar/gkv Liu C+, Zhang C+, Su J, Zhang DS, Cao S *. (2015) Stresses drive a cancer's initiation, progression and metastasis: Critical comments on the book "Cancer Bioinformatics". Journal of Bioinformatics and Computational Biology. DOI: /S X 10. Zhang C, Cao S, Toole B, and Xu Y. (2014) Cancer may be a pathway to cell survival under persistent hypoxia and elevated ROS: A model for solid-cancer initiation and early development. International Journal of Cancer: DOI: /ijc Zhang C, Cao S and Xu Y. (2014) Population Dynamics inside Cancer Biomass Driven by Repeated Hypoxia-Reoxygenation Cycles. Quantitative Biology. Doi: /s Cui J, Yin Y, Ma Q, Wang G, Olman V, Zhang Y, Chou WC, Hong CS, Zhang C, Cao S, Mao X, Li Y, Qin S, Zhao S, Jiang J, Hastings P, Li F, Xu Y (2014) Comprehensive characterization of the genomic alterations in human gastric cancer. International Journal of Cancer. DOI: /ijc Bhutia YD, Coothankandaswamy V, Cao S, Xu Y, Ganapathy V. (2014) Abstract 4340: The amino acid transporter SLC6A14 is an effective drug target for treatment of pancreatic cancer. Cancer Research. doi: / am : co-first authors; *: corresponding author Manuscripts Submitted 1. Tian Y+, Du W+, Cao S+, Wu Y+, Dong N, Wang Y, Xu Y. A Systematic

3 Analysis of Glutamine and Glutamate Metabolisms across Different Cancer Types. (Submitted). 2. Zang Y, Guo B, Cao S. A Bayesian Adaptive Marker-stratified Design for Molecularly Targeted Agents with Customized Hierarchical Modeling. (submitted). Manuscripts in Preparation 1. Cao S, Yao F, Xu Y. De-convolution of tissue-based gene-expression data to cell type specific contributions and application to cancer tissue gene-expression data analyses, ready for submission. 2. Cao S, Dong N, Song TC, Xu Y. Two major contributors to cancer tissue-based gene-expression data: biological functions and anti-oxidation, and application to reliable prediction of gene-expression levels of protein complexes, in preparation. 3. Cao S, Zhang C, Liu C, Ji F, Szemprich A, Zhang Y, Yuan Y, Teng Q, Wang C, Jiang J, Gu J, Xu Y. Oxidized Cholesterol Plays a Key Role in Driving the Rapid Growth of Metastatic Cancer, in preparation. 4. Cao S, Zhou Y, Xu Y. Overcoming of micro-environmental stresses on methylation level regulation in cancer cells, in preparation. 5. Zhang C +, Cao S +, Ma Q *, Xu Y *. LTMG-QB: A probabilistic model based biclustering method for single cell transcriptomic data analysis, ready for submission. Grants and Awards Grimes Family Distinguished Graduate Fellowship in Natural Sciences, Poster award in Big Data Challenges in Life Sciences Symposium Statistics Department Travel Award Innovative and Interdisciplinary Research Grant Graduate School Assistantship Outstanding Graduate with honor. Beijing Normal University Invited Seminars Computational studies and modeling of cancer metastases in Center for Simulational Physics,, Athens, GA

4 Mathematical modeling of alterations in cancer cells' metabolic equilibrium in Professor Zhaohui Qin s group, Emory University, Atlanta, GA Role of oxidized cholesterols in metastatic cancer in Professor Yiwen Chen s lab, The University of Texas MD Anderson Cancer Center, Houston, TX Cancer tissue gene expression deconvolution of populations in different oxygen amount in Professor Wei Li s lab, Baylor College of Medicine, Houston, TX Understanding cancer in its full complexity via mining cancer tissue omic data in Center for Systems Biology, University of Texas at Dallas, Dallas, TX Genetic mutations may not be the primary driver of cancer formation in Professor Yi Li s lab, Baylor College of Medicine, Houston, TX Understanding cancer in its full complexity via mining cancer tissue omic data in Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX Conference Posters Oxidized Cholesterol Plays a Key Role in Driving the Rapid Growth of Metastatic Cancer in the 9th Georgia Tech and Emory University International Conference "Genome Biology and Bioinformatics.", Atlanta, GA A probabilistic model for decomposition of tumor tissue heterogeneity in Big Data Symposium, Athens, GA Application of a non-parametric deconvolution method in metastase tumor tissue gene expression in Georgia Research Alliance Retreat, Atlanta, GA. Teaching Experiences Teach five lectures on Ordinary differential equations for solving cancer biology problems in the graduate level course on Cancer Systems Biology in UGA Department of Biochemistry and Molecular Biology (Instructor: Professor Ying Xu) (planned) Taught 3 lectures in graduate level course BCMB8210 (Computational Methods in Bioinformatics) in UGA Department of Biochemistry and Molecular Biology (organizing instructor: Professor Ying Xu) Taught 1 lecture in graduate level course BCMB/CBIO/GENE8112 (Advanced Genetics, Cell, Biochemistry, and Molecular Biology) in UGA Department of Biochemistry and Molecular Biology (organizing instructor: Professor Kelley Moremen).

5 now Undergraduate Research Course (BIOL/BCMB 4960/4970L) in Computational Systems Biology Laboratory, UGA: Identify key events in metastatic cancer compared with non-metastatic cancers; three students Instructor of hands-on sessions in Cancer Bioinformatics A Dragon Star course at Jilin University, Changchun, China, totaling 15 hour lectures, and covered: Statistical analyzes in differential gene expression, gene set enrichment, biclustering, batch effect removal and tissue heterogeneity deconvolution; and introduction to R software, databases such as Msigdb and KEGG; 350 students Mentoring Experiences 1. Yue Wu ( present), visiting undergraduate student from College of Life Sciences, Nanjing University 2. Yi Zhou ( present), visiting undergraduate student from College of Life Sciences, China Agricultural University. 3. Shunhua Han ( ), rotating graduate student from Institute of Bioinformatics, UGA 4. Tao Sheng ( present), PhD student from Institute of Bioinformatics, UGA 5. Tianci Song ( present), PhD student from Department of computer Sciences, Jilin University 6. Jason Kwak ( present), pre-med student from UGA 7. Naqeeb Mohammed Faroqui ( ), pre-med student from UGA 8. Yen Xuan Le ( ), undergraduate student from College of Pharmacy, UGA Academic Services 2012-now Reviewer, PLOS One 2014 Reviewer, Nucleic Acid Research 2015-now Reviewer, IEEE TCBB 2015-now Reviewer, Mathematical Biosciences 2015-now Reviewer, Journal of Bioinformatics and Computational Biology 2016-now Reviewer, BIBM Grants application involvement May 2014 Oct 2014 Understanding the roles of oxidized cholesterol in metastatic cancer. NATIONAL INSTITUTES OF HEALTH / Collaborative Research in Integrative Cancer Biology (U01) / CA Contribute two pages of Preliminary Results and High Level Design, and one page of experimental design. Development of a Computational Infrastructure for Cancer Mechanism

6 Dec 2014 Jun 2016 Aug 2016 Studies through Omic Data Mining. NATIONAL INSTITUTES OF HEALTH / Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science (R01) / PA Contribute a half page of specific aim, two pages of Preliminary Results and High Level Design and one page of research strategy. Elucidation of Key Drivers of the Explosive Growth of Breast Metastatic Cancers. DEPARTMENT OF DEFENSE / Breast Cancer Research Program (level II)/ W81XWH-14-BCRP-BREAKTHROUGH2_FL12 Contribute a half page of specific aim, two pages of Preliminary Results and High Level Design and half page of research strategy. Development of a Deconvolution Algorithm for Tissue-Based Gene- Expression Data. NATIONAL INSTITUTES OF HEALTH / Early-Stage Development of Informatics Technologies for Cancer Research and Management (U01)/ PAR Contribute all the Preliminary Results, one pages of high-level design and research strategy. Systems Biology of Cancer Metastasis. NATIONAL INSTITUTES OF HEALTH / Research Centers for Cancer Systems Biology Consortium (U54) / RFA-CA Contribute all the Preliminary Results in project 3 and one page of specific aims an research strategy. Contact Information Mailing Address: Computational Systems Biology Lab A110 Davison Life Sciences Building, 120 E Green St Athens, GA 30605