Document Detail


Salivary transcriptomic biomarkers for detection of ovarian cancer: for serous papillary adenocarcinoma.
MedLine Citation:
PMID:  22095100     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
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.
Authors:
Yu-Hsiang Lee; Jae Hoon Kim; Hui Zhou; Bo Wook Kim; David T Wong
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-11-18
Journal Detail:
Title:  Journal of molecular medicine (Berlin, Germany)     Volume:  -     ISSN:  1432-1440     ISO Abbreviation:  -     Publication Date:  2011 Nov 
Date Detail:
Created Date:  2011-11-18     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9504370     Medline TA:  J Mol Med (Berl)     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Graduate Institute of Biomedical Engineering, National Central University, Jhongli City, 32001, Taiwan, Republic of China.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Aldosterone and the Heart: From Basic Research to Clinical Evidence.
Next Document:  Comparative kinome analysis to identify putative colon tumor biomarkers.