A prospective translational study investigating the association of gut microbiome (GM) diversity with pathological complete response (pCR) after neoadjuvant treatment in early stage rectal and esophageal cancers.

TPS819 Background: The gut microbiome (GM) is thought to influence host immunity by modulating multiple immunologic pathways. Studies have suggested that dysbiosis of the GM confers a predisposition to certain malignancies and influences response to immune checkpoint inhibitors. However, little is known about how the GM diversity influences complete pathological response to neoadjuvant therapy in gastrointestinal (GI) tumours. We hypothesize that a more diverse GM constitution at baseline will lead to improved pathological response at the time of definitive surgery. Methods: We designed a cross-institutional multi-center translational study investigating the impact of the GM diversity on the efficacy of neoadjuvant therapy in GI cancers by assessing its association with pathological response. The study population will consist of patients with an early-stage rectal or esophageal cancer due to commence neoadjuvant therapy (including chemotherapy and chemoradiation) and planned for definitive surgery. Patients who received prior chemotherapy/monoclonal antibodies/immune checkpoint inhibitors or radiation will be excluded. The study assessments will include fecal sampling of the GM prior to neoadjuvant therapy, upon completion and again six months post completion of therapy. Fecal samples will be analysed by 16S RNA sequencing. Pathological response will be examined at time of surgery and patients will be classified as responders (complete pathological response) or non-responders. The primary endpoint of the study is to examine the association between the GM diversity and pathological response. 120 patients will be recruited over 18 months. Results: Species richness (Alpha Diversity) will be analysed using the Shannon diversity index and Jaccard similarity index to calculate beta diversity. Classification and clustering analysis will be performed with Principal Component Analysis (PCA) and Random Forest analysis. Comparison of taxa or functions between clinical cohorts will be performed using the two tailed Z test and corrected using the false discovery rate to determine Q-values. The association between GM and complete pathological response will be examined using logistic regression analysis adjusting for potential confounding factors. Adjusted odds ratios (OR) and 95% confidence intervals will be presented. Conclusions: This study will show preliminary insights into the role of GM as a potential biomarker for neoadjuvant therapy efficacy in patients with GI cancers. Recruitment is on-going.