Cervicovaginal Metabolome and Tumor Characteristics for Endometrial Cancer Detection and Risk Stratification.

PURPOSE: Endometrial cancer is highly prevalent and lacking noninvasive 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 the understanding of metabolic reprogramming related to endometrial cancer and identify potential biomarker candidates for noninvasive diagnostic and prognostic tests. EXPERIMENTAL DESIGN: 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. RESULTS: 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. CONCLUSIONS: Our findings provide insights into understanding the endometrial cancer metabolic landscape and improvement in diagnosis. The metabolic dysregulation described in this article linked specific metabolites and pathophysiological mechanisms including cellular proliferation, energy supply, and invasion of neighboring tissues. Furthermore, cervicovaginal metabolite levels related to tumor characteristics, which are used for risk stratification. Overall, development of noninvasive diagnostics can improve both the acceptability and accessibility of diagnosis.

Protein biomarkers in cervicovaginal lavages for detection of endometrial cancer.

BACKGROUND: Rates of endometrial cancer (EC) are increasing. For a definitive diagnosis, women undergo various time-consuming and painful medical procedures, such as endometrial biopsy with or without hysteroscopy, and dilation and curettage, which may create a barrier to early detection and treatment, particularly for women with inadequate healthcare access. Thus, there is a need to develop robust EC diagnostics based on non- or minimally-invasive sampling. The objective of this study was to quantify a broad range of immuno-oncology proteins in cervicovaginal lavage (CVL) samples and investigate these proteins as predictive diagnostic biomarkers for EC. METHODS: One hundred ninety-two women undergoing hysterectomy for benign or malignant indications were enrolled in this cross-sectional study. Classification of women to four disease groups: benign conditions (n = 108), endometrial hyperplasia (n = 18), low-grade endometrioid carcinoma (n = 53) and other EC subtypes (n = 13) was based on histopathology of biopsy samples collected after the surgery. CVL samples were collected in the operating room during the standard-of-care hysterectomy procedure. Concentrations of 72 proteins in CVL samples were evaluated using multiplex immunoassays. Global protein profiles were assessed using principal component and hierarchical clustering analyses. The relationships between protein levels and disease groups and disease severity were determined using Spearman correlation, univariate and multivariate receiver operating characteristics, and logistic regression analyses. RESULTS: Women with EC and benign conditions exhibited distinctive cervicovaginal protein profiles. Several proteins in CVL samples (e.g., an immune checkpoint protein, TIM-3, growth factors, VEGF, TGF-α, and an anti-inflammatory cytokine, IL-10) discriminated EC from benign conditions, particularly, when tested in combinations with CA19-9, CA125, eotaxin, G-CSF, IL-6, MCP-1, MDC, MCP-3 and TRAIL (sensitivity of 86.1% and specificity of 87.9%). Furthermore, specific biomarkers (e.g., TIM-3, VEGF, TGF-α, TRAIL, MCP-3, IL-15, PD-L2, SCF) associated with histopathological tumor characteristics, including histological type and grade, tumor size, presence and depth of myometrial invasion or mismatch repair protein status, implying their potential utility for disease prognosis or monitoring therapies. CONCLUSIONS: This proof-of-principle study demonstrated that cervicovaginal sampling coupled with multiplex immunoassay technology can offer a minimally to non-invasive method for EC detection.