Cervicovaginal metabolome and tumor characteristics for endometrial cancer detection and risk stratification.

Abstract

Endometrial cancer is highly prevalent and lacking non-invasive diagnostic techniques. Diagnosis depends on histological investigation of biopsy samples. Serum biomarkers for endometrial cancer have lacked sensitivity and specificity. The objective of this study was to investigate the cervicovaginal environment to improve understanding of metabolic reprogramming related to endometrial cancer and identify potential biomarker candidates for non-invasive diagnostic and prognostic tests. Cervicovaginal lavages were collected from 192 participants with endometrial cancer (n=66) and non-malignant conditions (n=108), and global untargeted metabolomics was performed. Using the metabolite data (n=920), we completed a multivariate biomarker discovery analysis. We analyzed grade 1/2 endometrioid carcinoma (n=53) and other endometrial cancer subtypes (n=13) to identify shared and unique metabolic signatures between the subtypes. When compared to non-malignant conditions, downregulation of proline (p<0.0001), tryptophan (p<0.0001), and glutamate (p<0.0001) was found among both endometrial cancer groups, relating to key hallmarks of cancer including immune suppression and redox balance. Upregulation (q<0.05) of sphingolipids, fatty acids, and glycerophospholipids was observed in endometrial cancer in a type-specific manner. Furthermore, cervicovaginal metabolites related to tumor characteristics, including tumor size and myometrial invasion. Our findings provide insights into understanding the endometrial cancer metabolic landscape and improvement into diagnosis. The metabolic dysregulation described in this paper linked specific metabolites and pathophysiological mechanisms including cellular proliferation, energy supply, and invasion of neighbouring tissues. Furthermore, cervicovaginal metabolite levels related to tumor characteristics, which are used for risk stratification. Overall, development of non-invasive diagnostic can improve both the acceptability and accessibility of diagnosis.