Abstract
Recent associations between vaginal microbiota and gynecological cancer have led to high-throughput sequencing datasets identifying diagnostic biomarkers for Endometrial Cancer (EC). However, lack of bioinformatics standards results in inconsistent independent studies with poor reproducibility, making them clinically inapplicable. This study leverages publicly available amplicon sequence data to address the reproducibility of EC microbiome studies. We implemented bioinformatics pipelines from five studies to reproduce and measure the replicability of published results across cohorts using metrics such as alpha diversity, beta diversity and differentially expressed taxa. We further evaluated separability between benign and cancer patients at different taxonomic levels (phylum, class, order, family, and genus) within and across datasets using boosted tree classifiers and Area Under the Curve (AUC) as the performance metric. While we reproduced the general trend of observing higher microbial diversity in EC compared to healthy controls, we found irregularities in two cohorts. Using beta diversity distance metrics, we identified that histology alone explains less than 3% of the variance in all cohorts. Three microbiome differential abundance methods were used in the five studies. While they all agree on a decrease in the Lactobacillus genus in EC patients, there is no consensus on other taxa associated with EC. We also found that separability between benign and cancerous conditions is highest at the class level, having an AUC score of 0.86. In subsequent steps, we will perform an integrative analysis to identify an EC vaginal microbiome predictive signature that is preserved across all five cohorts, benefiting screening programs.
Citation Format: Dollina D. Dodani, Aline Talhouk. Assessing the reproducibility crisis in vaginal microbiome studies for clinical applications in endometrial cancer [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr A023.