Professor of Medicine
Mayo Clinic College of Medicine
Lisa Boardman is a Professor of Medicine at Mayo Clinic in Rochester, MN where she integrates her clinical practice seeing patients with colorectal neoplasia and hereditary colorectal cancer syndromes with her research program. The translational research performed in our laboratory benefits from a priceless relationship patient participants and our GI neoplasia clinics. For 17 years, Dr. Boardman has recruited patient volunteers who are willing to donate valuable blood and tissue samples for the study of gastrointestinal health and disease. More than 14,000 volunteers have given samples that are preserved for study in the Mayo Biobank for Gastrointestinal Health Research (BGHR). Dr. Boardman’s lab uses samples from the BGHR to define critical molecular features that determine who may be more likely to develop colorectal cancer. A main area of focus in Dr. Boardman’s research program involve telomeres, the end sequences of DNA that form the genetic code that is packaged into chromosomes. Telomeres cap the ends of the chromosomes in ways that promote stability and resist breakdown of the genetic material. However, telomeres tend to shorten with increasing age, and in the majority of cancers. Dr. Boardman compares how human cells maintain telomeres between healthy and cancerous cells. She examines whether cancer develops when telomeres shorten with age, and she probes the molecular machinery of cancers that take control of telomere maintenance mechanisms to divert cells toward malignancy. Another main focus of Dr. Boardman’s program is studying the genetic landscape (including genome, transcriptome and epigenome) of non-malignant colon polyps and those colon polyps that have partially transformed to cancer. This model system aims to evaluate colon neoplasms that remain benign (85%) compared to those that progress to cancer.. Some of those samples were removed endoscopically while others required surgery, some remained benign, and others progressed to cancer. This model system enables a time-lapsed representation of the genetic events that halt cancer from developing from a polyp and those that lead to malignant progression.