Dr. George Vasmatzis is a Senior Associate Consultant in the Experimental Pathology division, in the Department of Laboratory Medicine and Pathology and a member of the Mayo Clinic Cancer Center. He is also an Assistant Professor in the Department of Laboratory Medicine at the Mayo Medical School. He has a Ph.D. in Biomedical Engineering and has acquired experience in diverse disciplines, including Bioinformatics, Molecular Biology, and Computational Biology.

Dr. Vasmatzis research program consists of bioinformatics specialists, molecular biologists, epidemiologists, and pathologists. They combine computational and experimental techniques to facilitate discovery of genes that can be used as diagnostic markers, prognostic markers, or targets for therapy of different cancers.

It is often difficult to predict the behavior of cancer, and an individual patient's response to cancer treatment. The clinical and pathologic findings such as stage, tumor type, tumor differentiation and certain biomarkers provide some prognostic information, but in many instances, it is impossible to predict survival even among patients with identical clinical and pathologic characteristics. The determination of tumor aggressiveness is critical in the development of treatment strategies, particularly in patients at high risk for progression and death from cancer who may benefit from early adjuvant therapies. In the future, this will become even more important as novel and effective tumor vaccines and other immunotherapies are developed. Our approach to study cancer behavior is by detecting differences in gene expression between cells of different histologic type via examining mRNA quantities by sequencing cDNA libraries or performing microarray experiments followed by electronic profiling. The study requires multiple steps, such as, bioinformatic and biostatistical analysis, as well as verification with molecular biology techniques.

His research interests include:

Gene Discovery. Discovery of new biomarkers for diagnosis of prostate, kidney, and lung cancer. Developing Bioinformatics methods to analyze gene expression profiles in different cancers. Validating differential gene expression using experimental techniques. Assay development: Developing clinical assays for early detection and prognosis of cancer. Protein Engineering and Modeling. Using antibody engineering techniques to improve anti-cancer drugs (immunotoxins). Stabilization of protein structure. Modeling of cancer-targeting antibodies. Design of mutations to decrease drug toxicity. Improving the affinity of antibodies by Phage display. Structure prediction of GalR by homologous extension.