George Vasmatzis, Ph.D., is a senior associate consultant in the Division of Experimental Pathology in the Department of Laboratory Medicine and Pathology; an assistant professor of laboratory medicine and pathology in the College of Medicine, Mayo Clinic; and a member of the Mayo Clinic Cancer Center. Dr. Vasmatzis has a Ph.D. in biomedical engineering and has experience in diverse disciplines, including bioinformatics, molecular biology and computational biology.
His research program consists of bioinformatics specialists, molecular biologists, epidemiologists and pathologists. They combine computational and experimental techniques to facilitate the 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. Clinical and pathological findings such as stage, tumor type, tumor differentiation and certain biomarkers provide some prognostic information, but in many instances it's impossible to predict survival even among patients with identical clinical and pathological characteristics.
The determination of tumor aggressiveness is critical in the development of treatment strategies, particularly in patients who may benefit from early adjuvant therapies because they're at a high risk for progression and death from cancer. In the future, this will become even more important as novel and effective tumor vaccines and other immunotherapies are developed.
The approach of Dr. Vasmatzis and his colleagues is to study cancer behavior by detecting differences in gene expression between cells of different histologic type by examining mRNA quantities, 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.
Dr. Vasmatzis' research interests include:
- Gene discovery
- Discovery of new biomarkers for the 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
Significance to patient care
In many cases, clinical tests that exist today are not sensitive or specific enough to enable doctors to make confident disease diagnoses. For example, a test may be able to identify that a given disease is present, but it can't determine if it's a mild or severe case. Other times, a test may not be entirely reliable.
As a result, doctors must take a "one size fits all" approach to patient care. New tests that use specific and sensitive biomarkers, such as those being developed by Dr. Vasmatzis and his colleagues, will lead to more individualized patient care and reduce overtreatment, undertreatment and incorrect treatment.
- Member, NCI Cancer Diagnostic and Therapeutic Agents Enabled by Nanotechnology (SBIR [U43/U44]) Special Emphasis Panel
- Member, NCI Centers of Cancer Nanotechnology Excellence Special Emphasis Panel
Review Panel Member, Integrative Cancer Biology Program
- Member, NCI Cellular and Tissue Biology P01 Special Emphasis Review Panel
- Member, NCI Discovery, Development and Diagnosis P01 Special Emphasis Panel
- Participant, EDRN GU Collaborative Group and Steering Committee Meeting
- Member, National Biospecimen Network Informatics Task Force