Abstract

Salivary mRNA biomarkers and serum carcinoembryonic antigen (CEA) have been recognized as promising liquid biopsy methods for detection of multiple cancers. However, current tests normally use solitary type of biomarkers, and are limited by unsatisfactory sensitivity and specificity when applied to differentiate cancer patients from healthy controls. In this study, a combined approach of CEA and salivary mRNA biomarkers was evaluated for discriminatory performance of ovarian cancer patients from healthy controls. We designed our study with two phases: a discovery phase to find and evaluate multiple biomarkers, and an independent validation phase to confirm the applicability of the selected biomarkers. In the discovery phase, a total of 140 ovarian cancer patients and 140 healthy controls were recruited. The CEA level in blood as well as five mRNA biomarkers in saliva (i.e. AGPAT1, B2M, BASP1, IER3 and IL1β) were measured, followed by developing a machine-learning model to differentiate ovarian cancer patients and healthy controls. We found a novel panel of biomarkers, which could differentiate ovarian cancer patients from healthy controls with high sensitivity (89.3%) and high specificity (82.9%). Next, we applied this panel of biomarkers in an independent validation study that consisted of 60 ovarian cancer patients and 60 healthy controls. The ovarian cancer patients were successfully differentiated from healthy controls in the validation phase, with sensitivity reaching 85.0% and specificity reaching 88.3%. To our best knowledge, it is the first time that a combined use of CEA and salivary mRNA biomarkers were applied for non-invasive detection of ovarian cancer.

摘要

唾液mRNA生物标志物和血清癌胚抗原（CEA）被公认为是用于检测多种癌症的有希望的液体活检方法。但是，当前的测试通常使用单独类型的生物标志物，并且在将癌症患者与健康对照区分开来时受到灵敏度和特异性不佳的限制。在这项研究中，评估了CEA和唾液mRNA生物标志物的组合方法对卵巢癌患者与健康对照者的区别表现。我们将研究设计为两个阶段：一个发现阶段，用于发现和评估多个生物标记；一个独立的验证阶段，以确认所选生物标记的适用性。在发现阶段，总共招募了140名卵巢癌患者和140名健康对照。测量血液中的CEA水平以及唾液中的五个mRNA生物标志物（即AGPAT1，B2M，BASP1，IER3和IL1β），然后建立机器学习模型以区分卵巢癌患者和健康对照。我们发现了一组新颖的生物标记物，可以高灵敏度（89.3％）和高特异性（82.9％）将卵巢癌患者与健康对照区分开。接下来，我们在由60名卵巢癌患者和60名健康对照组成的独立验证研究中应用了该组生物标志物。在验证阶段，已成功将卵巢癌患者与健康对照区分开来，敏感性达到85.0％，特异性达到88.3％。据我们所知，