Graduate Institute of Biomedical Engineering, National Central University, Jhongli City, Taiwan, Republic of China.
J Mol Med (Berl). 2012 Apr;90(4):427-34. doi: 10.1007/s00109-011-0829-0. Epub 2011 Nov 18.
Ovarian cancer is the most lethal gynecological cancer due to lack of clear symptom and reliable screening biomarker in the early stage. The capability to detect the initiation of malignancy with a sensitive and effective approach is one of the most desirable goals for ovarian cancer therapy. In this study, we spearheaded noninvasive detection of ovarian cancer by salivary transcriptomic biomarkers, and evaluated the clinical utilities of discovered biomarkers using a clinical case-control study. To find salivary mRNA biomarkers, salivary transcriptomes in 11 ovarian cancer patients and 11 matched controls were profiled by Affymetrix HG-U133-Plus-2.0 array. The biomarker candidates selected from the microarray results were then subjected to clinical validation by RT-qPCR using an independent sample cohort including 21 ovarian cancer patients and 35 healthy controls. Seven downregulated mRNA biomarkers were validated. The logistic regression model revealed the combination of five validated biomarkers (AGPAT1, B2M, BASP2, IER3, and IL1B) can significantly discriminate ovarian cancer patients (n = 21) from the healthy controls (n = 35), yielding a receiver operating characteristic plot, area under the curve value of 0.909 with 85.7% sensitivity and 91.4% specificity. In summary, we have demonstrated that the RNA signatures in saliva could serve as biomarkers for detection of ovarian cancer with high sensitivity and specificity. This emerging approach with high-throughput, noninvasive, and effective advantages provides a feasible means for detection of systemic cancer, and opens a new avenue for early disease detection.
卵巢癌是最致命的妇科癌症，因为在早期缺乏明确的症状和可靠的筛查生物标志物。用一种敏感而有效的方法来检测恶性肿瘤的发生是卵巢癌治疗最理想的目标之一。在这项研究中，我们通过唾液转录组生物标志物率先实现了卵巢癌的非侵入性检测，并通过临床病例对照研究评估了所发现生物标志物的临床应用价值。为了找到唾液 mRNA 生物标志物，我们用 Affymetrix HG-U133-Plus-2.0 阵列对 11 名卵巢癌患者和 11 名匹配对照者的唾液转录组进行了分析。从微阵列结果中选择的生物标志物候选物随后通过 RT-qPCR 用包括 21 名卵巢癌患者和 35 名健康对照者的独立样本队列进行了临床验证。七种下调的 mRNA 生物标志物得到了验证。逻辑回归模型显示，五种验证生物标志物（AGPAT1、B2M、BASP2、IER3 和 IL1B）的组合可以显著区分卵巢癌患者（n=21）和健康对照者（n=35），ROC 图的曲线下面积值为 0.909，灵敏度为 85.7%，特异性为 91.4%。总之，我们已经证明唾液中的 RNA 特征可以作为卵巢癌检测的高灵敏度和特异性生物标志物。这种具有高通量、非侵入性和有效性优势的新兴方法为系统性癌症的检测提供了可行的手段，并为早期疾病检测开辟了新途径。
