Marc Greenblatt received his M.D. from Jefferson Medical College in Philadelphia. He completed his residency training in Internal Medicine from 1983-1986, and his fellowship training in Hematology/Oncology from 1988-1991, both at the University of New Mexico Hospitals. From 1991 to 1995 he was a Postdoctoral Biotechnology Training Fellow at the National Cancer Institute with Curtis Harris, M.D., in the Laboratory of Human Carcinogenesis. Dr. Greenblatt joined the faculty at the UVM College of Medicine in 1995. His areas of concentration are Cancer Genetics (through VCC's Familial Cancer Program) and Gastrointestinal Cancer. He has served as the president of the Collaborative Group of the Americas for Inherited Colorectal Cancer (CGA-ICC), on the councils of the CGA-ICC and the Human Genome Variation Society, and as a communicating editor for the journal Human Mutation.

Dr. Greenblatt's research interests are in interpreting genetic variants in cancer susceptibility genes using multiple lines of evidence (epidemiology, statistics, tumor pathology, evolution, structure, and function). This project has evolved from early work curating the p53 mutation database and analyzing it for clues to carcinogenesis and mechanisms of mutation (Greenblatt 2001, 1996, 1994, Hollstein 1994, Walker 1999), and has now expanded to studies of CDKN2A (p16) and other genes (Greenblatt 2003, Raevaara 2005, Ollila 2006). Dr. Greenblatt directs a project involving computational and laboratory analysis of CDKN2a variation, function, structure, and association with cancer (Familial Melanoma and others).

Missense substitutions may or may not result in a functionally altered protein. Interpreting the biological significance of missense amino acid (AA) substitutions in cancer-related genes is critical in a variety of contexts. Clinical cancer geneticists often must decide whether a previously unknown allelic variant causes disease. In carcinogenesis research, functional predictions are important in evaluating allelic variants of potential cancer-related genes. Genomic research has identifed single nucleotide polymorphisms (SNPs) at a rate of greater than 1/1000 in the human genome, including the coding sequences of many genes. Differentiation between neutral and pathogenic variants is essential in the study of complex genetic traits. Dr. Greenblatt's studies are integrating computational and functional data to help in interpreting genetic variants.

The objectives of Dr. Greenblatt's laboratory research are to develop and test a model for classifying variants in CDKN2A and other genes as pathogenic or neutral by integrating multiple data types. Specific aims of his current project are: 1) To classify as pathogenic or neutral all CDKN2A variants found in the human germline using multiple lines of evidence, and 2) To improve bioinformatics tools for disseminating data to interpret coding region genetic variants.   CDKN2A is used as a prototype for study because 1) germline mutations play a role in Familial Melanoma; 2) somatic mutations are found in multiple cancers, and a significant database of somatic mutations exists; 3) allelic variants occur whose functional consequences are unknown; 4) reliable functional assays exist; and 5) a crystal structure is known, so data for mutational spectrum, evolution, structure, and function can be correlated. These studies should be generalizable to the interpretation of mutations in other cancer-related genes and to other SNPs found throughout the genome.