Purpose: 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. 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 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.

中文翻译：

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用于子宫内膜癌检测和风险分层的宫颈阴道代谢组和肿瘤特征

目的：子宫内膜癌非常普遍，且缺乏非侵入性诊断技术。诊断取决于活检样本的组织学研究。子宫内膜癌的血清生物标志物缺乏敏感性和特异性。本研究的目的是调查宫颈阴道环境，以提高对与子宫内膜癌相关的代谢重编程的理解，并确定用于非侵入性诊断和预后测试的潜在生物标志物候选物。实验设计：从 192 名患有子宫内膜癌 (n=66) 和非恶性疾病 (n=108) 的参与者中收集宫颈阴道灌洗液，并进行整体非靶向代谢组学研究。使用代谢物数据 (n=920)，我们完成了多变量生物标志物发现分析。结果：我们分析了 1/2 级子宫内膜样癌 (n=53) 和其他子宫内膜癌亚型 (n=13)，以确定亚型之间共享和独特的代谢特征。与非恶性疾病相比，两个子宫内膜癌组中都发现脯氨酸 (p<0.0001)、色氨酸 (p<0.0001) 和谷氨酸 (p<0.0001) 下调，这与癌症的关键标志包括免疫抑制和氧化还原有关平衡。在子宫内膜癌中以类型特异性方式观察到鞘脂、脂肪酸和甘油磷脂的上调(q＜0.05)。此外，宫颈阴道代谢物与肿瘤特征相关，包括肿瘤大小和子宫肌层浸润。结论：我们的研究结果为了解子宫内膜癌代谢格局和改进诊断提供了见解。本文描述的代谢失调将特定的代谢物和病理生理机制（包括细胞增殖、能量供应和邻近组织的侵袭）联系起来。此外，宫颈阴道代谢物水平与肿瘤特征相关，可用于风险分层。总体而言，非侵入性诊断的发展可以提高诊断的可接受性和可及性。