A. Greenbaum2, S. Ness4, T. Bocklage3, J. Lee1, A. Rajput2 1University Of New Mexico HSC,Epidemiology, Biostatistics And Preventative Medicine/Internal Medicine,Albuquerque, NM, USA 2University Of New Mexico HSC,Surgery,Albuquerque, NM, USA 3University Of New Mexico HSC,Pathology,Albuquerque, NM, USA 4University Of New Mexico HSC,Internal Medicine,Albuquerque, NM, USA
Introduction: Neoadjuvant chemoradiation is the standard of care for locally advanced adenocarcinoma of the rectum. It is currently unknown which patients will respond to therapy. We aimed to determine if Mutant-Allele Tumor Heterogeneity (MATH) scores, a novel bioinformatics tool, can predict response to neoadjuvant treatment in locally advanced rectal tumors.
Methods: We performed high read-depth (“deep”) sequencing of >400 cancer-relevant genes on a group of 13 patients with locally advanced rectal adenocarcinoma. Normal and tumor DNA were extracted from formalin-fixed, paraffin-embedded tissues. DNA samples were analyzed using the Ion Ampliseq Comprehensive Cancer Panel™ assay. Sequencing was performed on the Ion Proton Next-Generation Sequencing™ instrument. Mutant allele frequencies were determined and a calculated MATH score was used to quantify tumor heterogeneity. Response to chemo therapy was determine by primary resection pathology report.
Results: A total of 13 patients with locally advanced rectal cancer (T3/4 or N1/2) were analyzed. The boxplot in Figure 1 shows the range of calculated MATH scores by neoadjuvant therapy response category. Four patients were noted to have complete response, 7 had minimal/moderate and 2 demonstrated poor response. Tumor heterogeneity (as shown in MATH scores) was found to be significantly different amongst the 3 response groups (p=0.026), with higher MATH scores correlating with poorer response to treatment.
Conclusion: The novel approach of applying the shape of a whole bioinformatics data set to analyze tumor heterogeneity may provide a useful biomarker for locally advanced rectal cancer. MATH scores may allow a means of predicting response to neoadjuvant chemoradiation therapy.
