期刊
JOURNAL OF MOLECULAR MEDICINE-JMM
卷 90, 期 4, 页码 427-434出版社
SPRINGER
DOI: 10.1007/s00109-011-0829-0
关键词
Saliva; RNA; Salivary diagnostics; Ovarian cancer
资金
- National Research Foundation of Korean government [KRF-2008-314-E00121, 2011-0010286]
- National Research Foundation of Korea [2008-314-E00121, 2011-0010286] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据