Positions
- Associate Professor
-
Pediatrics-Oncology
ÌÇÐÄÊÓÆµ of Medicine
Houston, TX, US
- Member
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Dan L Duncan Comprehensive Cancer Center
ÌÇÐÄÊÓÆµ of Medicine
Houston, Texas, United States
Education
- Postdoctoral Training at Washington University
- 01/2001 - St. Louis, MO, United States
- PhD from University Of Texas Medical School At Houston
- 01/1997 - Houston, Texas, United States
- BSc from Hong Kong Baptist College
- 01/1986 - Hong Kong, Hong Kong
Professional Interests
- Research Interests
Professional Statement
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.
Websites
Link to VIICTR
Selected Publications
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Flores RJ, Li Y, Yu A, Shen J, Rao PH, Lau SS, Vannucci M, Lau CC, Man TK. " " BMC Syst Biol. 2012 ; 6 : 50.
Pubmed PMID: . -
Egler RA, Li Y, Dang TA, Peters TL, Leung E, Huang S, Russell HV, Liu H, Man TK. " " Proteomics Clin Appl. 2011 Oct ; 5 (41527) : 532-41.
Pubmed PMID: . -
Li Y, Flores R, Yu A, Okcu MF, Murray J, Chintagumpala M, Hicks J, Lau CC, Man TK. " " Cancer. 2011 Jan 1; 117 (1) : 207-17.
Pubmed PMID: . -
Li Y, Dang TA, Shen J, Hicks J, Chintagumpala M, Lau CC, Man TK. " " Oncol. Rep.. 2011 Feb ; 25 (2) : 303-14.
Pubmed PMID: .
Projects
- Identification of blood-based biomarkers for ostesosarcoma
- CPRIT
- Examination of the prognostic significance of p27 in osteosarcoma
Memberships
- Children's Oncology Group
- Associate Member
- American Assoication for Cancer Research
- Member
Funding
-
Harnessing P27 for Prognostication of Pediatric Osteosarcoma
#1R01HD074553 - (01/01/2013 - 12/31/2015)
- Grant funding from NIH/NICHD
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Targeted Therapies for Metastatic Osteosarcoma
#RP140022-P2 - (08/01/2010 - 02/29/2016)
- Grant funding from Cancer Prevention and Research Institute of Texas
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Targeting the CXCL10-CXCR3 axis in metastatic osteosarcoma
- $1,200,000.00 (08/31/2020 - 08/30/2024)
- Grant funding from Cancer Prevention and Research Institute of Texas
Skills
- Bioinformatics
- Cancer Research
- Genomics and Proteomics
Languages
Chinese (Cantonese)
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