Cancer Relapse Prediction through Gene Expression Profiling: Personalizing the Treatment of Breast and Colon Cancers
Student: Derek Athy, 2014-2015
Sponsor: Prof. Steven Buechler - Mathematics, Notre Dame, IN
Breast cancer and colon cancer collectively affect hundreds of thousands of people each year in the United States alone, and the route of treatment is often a combination of surgery with chemotherapy, radiation, or medication. A vast number of cancer patients end up receiving chemotherapy; many of which will not benefit additionally from this treatment.
The University of Notre Dame's Dr. Buechler has developed an algorithm for determining the likelihood for relapse of both breast and colon cancers, based on the measurement of expression levels of specific genes from tumor biopsy samples through microarray analysis. Dr. Buechler, along with Dr. Badve of the Indiana University Medical System, have been working to perfect the analysis and scoring system of the algorithm that separates patients into two distinct groups based on the levels of gene expression: those patients designated as having a “good” prognosis who can safely forgo chemotherapy as it is unnecessary, and those patients designated as having a “bad” prognosis who should undergo chemotherapy as it reduces the risk of cancer recurrence and metastasis for this patient subset.
Dr. Buechler and Dr. Badve are working to further validate the use of the specific genes in their microarrays and the algorithm (same in each case) to create a more efficient, effective and specific way of treating these breast and colon cancer patients.