Positions

Associate Professor
Pediatrics-Oncology
Baylor College of Medicine
Houston, TX, US
Member
Dan L Duncan Comprehensive Cancer Center
Baylor College of Medicine
Houston, Texas, United States

Education

Advanced Training from Washington University
Ph.D. from University Of Texas Medical School At Houston
B.S. from Hong Kong Baptist College

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.

Selected Publications

Memberships

Children's Oncology Group
American Assoication for Cancer Research

Projects

Identification of blood-based biomarkers for ostesosarcoma
Examination of the prognostic significance of p27 in osteosarcoma

Funding

Harnessing P27 for Prognostication of Pediatric Osteosarcoma
- #1R01HD074553
Grant funding from NIH/NICHD
Targeted Therapies for Metastatic Osteosarcoma
- #RP140022-P2
Grant funding from Cancer Prevention and Research Institute of Texas

Skills

Bioinformatics
Cancer Research
Genomics and Proteomics