Chris Tsz-Kwong Man, Ph.D.
Associate Professor, Section of Hematology-Oncology
Department of Pediatrics
Baylor College of Medicine
Texas Children's Cancer and Hematology Centers, Texas Children's Hospital
Dan L. Duncan Cancer Center
Ph.D. Microbiology and Molecular Genetics, University of Texas, Houston (1997)
Postdoc, Genetics and Bioinformatics, Washington University, St. Louis (2001)
Dr. Man's laboratory is interested using a combined computational and -omic approach to understand pediatric cancers. The two main focuses of our lab are to discover clinically relevant biomarkers and to study mechanism of metastasis using a systems biology approach.
Our current research includes:
Molecular classification of cancer using a systems biology approach. We use a systems biology approach to generate genomic and proteomic profiles from various specimens of cancer patients, such as tumors and plasma. The goal of our laboratory is to integrate these diverse data by various classification algorithms to construct prediction models, which can better predict clinical phenotypes of pediatric cancer, such as drug resistance, metastatic potential, and prognosis. Ultimately, we aim to develop an easy-to-use and minimally invasive blood test that can help to diagnose and prognosticate patients with pediatric cancers, so they can be treated as early and precisely as possible.
Mechanistic study of metastatic determinants. Using a proteomic approach, we have identified p27 (CDKN1B) as a crucial metastatic determinant in pediatric osteosarcoma. We have shown that p27 is frequently mislocalized in the cytoplasm of osteosarcoma cases, and the mislocalization increases the metastatic potential of tumor cells. p27 is a well-known tumor suppressor gene that regulates normal cell cycle progression when it is located in the nucleus, but its oncongenic function when located in the cytoplasm is still largely unknown. It may act as a master switch between tumorigenesis and cancer progression. We use a panel of targeted genomic and proteomic methods to dissect the mechanism of the cytoplasmic p27 in the promotion of metastasis in osteosarcoma and other cancers. Our goal is to test if cytoplasmic p27 can be used as a novel therapeutic target to abolish metastasis in cancer.
Cancer bioinformatics. With the explosion of the genomic data and the decreasing cost of the genomic assays, there is a wealth of genomic data available in various public repositories. These resources provide an unprecedented opportunity for data mining to identify common cancer signatures and mechanisms in various cancers. Understanding these common features of different types of cancer will provide an important clue on how to target cancer in general. Our lab is interested in developing bioinformatic methods and tools that can utilize these resources to answer specific biological or clinical questions that will lead to a better understanding of common cancer phenotypes and the development of novel therapeutic targets.
- Flores RJ, Li Y, Yu A, Shen J, Rao PH, Lau SS, Vannucci M, Lau CC and Man TK. A systems biology approach reveals common metastatic pathways in osteosarcoma. BCM Systems Biology, 6:50 (2012). PubMed
- Egler RA, Li Y, Dang TA, Peters TL, Leung E, Huang S, Russell HV, Liu, H., and Man, T.K. An integrated proteomic approach to identifying circulating biomarkers in high risk neuroblastoma and their potential in relapse monitoring. Proteomics: Clinical Applications, 5:532-41 (2011). PubMed
- Daves MH, Hilsenbeck SG, Lau CC and Man TK. Meta-analysis of multiple microarray datasets reveals a common gene signature of metastasis in solid tumors. BMC Med Genomics, 4:56 (2011). PubMed
- Li Y, Flores R, Yu A, Okcu F, Murray J, Chintagumpala M, Hicks J, Lau CC and Man TK. Elevated expression of CXC chemokines in pediatric osteosarcoma patients. Cancer, 117:207-17 (2011). PubMed
- Li Y, Dang TA, Shen J, Perlaky L, Hicks J, Chintagumpala M, Lau CC and Man TK. Plasma proteome predict chemotherapy response in osteosarcoma patients. Oncology Reports, 25:303-14 (2011). PubMed
- Guo B, Villagran A, Vannucci M, Wang J, Man TK, Lau CC and Guerra R. Bayesian estimation of genomic copy number with single nucleotide polymorphis genotyping arrays. BMC Research Notes, 30:3:350 (2010). PubMed
- Cruz-Marcelo A, Guerra R, Vannucci M, Li Y, Lau CC and Man T.K. Comparison of algorithms of pre-processing of SELDI-TOF mass spectrometry data. Bioinformatics, 24:2129-36 (2008). PubMed
For more publications, see listing on PubMed.
Address: Feigin Center-Texas Children's Hospital
Houston, TX 77030
Additional link: Faculty page