Guoan Chen

Guoan Chen, MD, PhD

Associate Research Scientist, Thoracic Surgery


Guoan Chen, M.D., Ph.D, is a faculty member in the Section of Thoracic Surgery at the University of Michigan. Dr. Chen received his medical degree from Xi'an Jiaotong University in Xi'an, China in 1986 and finished his M.S. program in Pulmonary Medicine in Xi'an Jiaotong University. In 1999, he received his Ph.D. in oncology from Chinese Academy of Medical Sciences, Peking Union Medical College. In 2000, he joined Professor David G. Beer's Tumor Biology Laboratory as a research fellow and completed his post-doctoral training in tumor molecular biology at the University of Michigan and was promoted to the faculty as research investigator at the University of Michigan Medical School in 2004.

Dr. Chen's research interests are focused within the field of lung cancer. He utilize genomics, proteomics, epitomic profiling of the humoral immune response, gene fusion analysis and bioinformatics to identify transcriptional profiles, protein profiles and autoantibody profiles related to patient survival and for the early diagnosis in lung cancer. He utilizes many modern and state of the art molecular technologies and approaches, including microarray, SNP array, Luminex bead-based approach and Solexa genome sequencing in our research. Current projects are: (1) identification of survival related 91 genes based on microarray analyses of over 600 primary tumors and verification them using qRT-PCR in an independent set of 101 lung adenocarcinoma samples. (2) identification of survival related DNA copy number changes based on SNP arrays and verification them using SNP arrays or qPCR in an independent set of lung adenocarcinomas. (3) identification and verification of diagnosis, prognosis or recurrence related MicroRNA and DNA methylation in lung cancer. Other ongoing projects involve screening for new fusion genes in lung cancer using Solexa sequencing, analysis of embryonic stem cell like or cancer stem cell signatures in lung cancer and identification of prediction markers for guiding cancer therapy.

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