377.10 - Differential Extracellular Matrix Proteomic Signatures in Malignant and Benign Polyps from Appalachian Region Colon Cancer Patients
Tuesday, April 5, 2022
10:45 AM – 11:00 AM
Room: 118 A - Pennsylvania Convention Center
Alexander Sougiannis (Medical University of South Carolina), Stephen Zambrzycki (Medical University of South Carolina), Gavin Cauley (Medical University of South Carolina), Derek Allison (University of Kentucky College of Medicine), Eun Lee (University of Kentucky College of Medicine), Ramon Sun (University of Kentucky College of Medicine), Peggi Angel (Medical University of South Carolina)
Presenting Author Medical University of South Carolina
Emerging evidence suggests that extracellular matrix behavior may influence the prognosis and response to treatment of colorectal cancer (CRC). The differences in collagen structure were investigated as a predictive model of tumor stage and population differences in the American Appalachian population. Tissue microarrays (TMAs) comprising of matched benign and malignant tissue from 45 patients were constructed into 86 samples to evaluate extracellular matrix structure. 5 specific peaks were discovered to differ between benign and malignant polyps (plt;0.05). Receiver operating characteristic (ROC) curve analysis indicated high sensitivity and specificity of these peaks to predict polyp malignancy. A total of 17 peptide features showed high predictive power between malignant early-stage (Stage I+II) and late-stage (Stage III+IV) polyps (Area: gt;0.7, 95% CI: 0.7014-0.7696, p=1.000x10-15). Analysis of late-stage malignant polyps showed the same 17 peptide features were significantly increased in patients from the Appalachian region of the United States vs Non-Appalachian residents. Interestingly, there was a significant predictive power to detect morbidly obese patients compared to normal BMI (Area: gt;0.7, 95% CI: 0.7068-0.7840, p=1.000x10-15) and overweight BMI (Area: gt;0.7, 95% CI: 0.6588-0.7439, p=2.800x10-14). This present study highlights the potential for utilizing TMA as a method for detecting with high predictive power the changes in extracellular matrix behavior related to colorectal cancer disease burden. We believe this method can be used to assess overall tumor prognosis and further detect between population differences which might improve diagnostic and prognostic outcomes in certain at-risk populations.
