Christopher Heaphy

About Christopher Heaphy

Telomeres are repeating sequences of DNA located at the ends of chromosomes that act as a buffer to protect chromosomes from deterioration or abnormal fusions during DNA replication. Telomeres are shortened with every cell division and once too short, chromosomes become unstable and normal cells activate protective cell death mechanisms. These mechanisms are commonly inactivated in cancer cells, allowing for the development of genomic mutations.

Dr. Christopher Heaphy is studying telomere length in prostate biopsy specimens as a diagnostic and prognostic biomarker of prostate cancer. Telomere lengths will be compared in normal prostate cells, prostate cancer cells, and stromal cells (the complex tissue surrounding normal and malignant prostate glands) from prostate needle biopsies from men with and without prostate cancer. They will determine if shorter telomere lengths in various cell types predict the severity of disease.

Finally, telomere lengths will be assessed in tumor specimens from prostate cancer patients who have undergone hormone therapy to determine if they predict therapeutic response, duration, and disease recurrence.

If successful, this project will identify new diagnostic and prognostic biomarkers of prostate cancer outcome and response to hormone therapy.

What this means for patients: It is critical to discover and validate biomarkers that can be used to improve diagnosis, prognosis, and individual risk stratification. Dr. Heaphy will assess the utility of a novel biomarker for predicting prostate cancer aggressiveness and responsiveness to hormone therapy, leading to better selection of treatment for individual patients and new understandings of disease biology.

Award

2014 Bonnie Pfeifer Evans-PCF Young Investigator

Christopher Heaphy, PhD

Johns Hopkins University School of Medicine

Mentors:

Alan Meeker, PhD, Angelo De Marzo, PhD, Elizabeth Platz, PhD

Proposal Title:

The Telomere Biomarker for Individualized Prostate Cancer Risk Stratification and Prognostication