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Circulating microRNA expression levels can serve as diagnostic/prognostic biomarkers in several types of malignant tumors; however, to our knowledge, there have been reports describing their value in cervical squamous cell carcinoma (SCC). In this study, we used hybridization arrays to compare the microRNA expression profiles in cervical squamous cell carcinomas (SCC) samples among patients with lymph node metastasis (LNM) or without LNM; 89 microRNAs were found to fit our inclusion criteria. Using quantitative PCR (qPCR), we examined the expression levels of these microRNAs in cervical cancer tissue, as well as in serum from patients and healthy women. We compared the expression levels between patients with LNM (n=40) and those without LNM (n=40) and healthy controls (n=20). Using regression analysis, we generated a comprehensive set of marker microRNAs and drew the fitted binormal receiver operating characteristic (ROC) curves to access the predictive value. We identified 6 serum microRNAs that can predict LNM in cervical SCC patients; these microRNAs were miR-1246, miR-20a, miR-2392, miR-3147, miR-3162-5p and miR-4484. The area under the curve (AUC) of the comprehensive set of serum microRNAs predicting LNM was 0.932 (sensitivity, 0.856; specificity, 0.850). The predictive value of the serum microRNAs was inferior to that in tissue (AUC 0.992; sensitivity, 0.967; specificity, 0.950; P=0.018). We compared the LNM predictive value of serum microRNAs and SCC antigen (SCC-Ag) by drawing fitted binormal ROC curves However, serum microRNA analysis is by far superior to serum SCC‑Ag analysis (AUC 0.713; sensitivity, 0.612; specificity, 0.700; P<0.0001). Serum microRNAs are a good predictor of LNM with clinical value in early-stage cervical SCC.
Pubmed ID: 23799609
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Welcome to Michael Eisens lab in the Howard Hughes Medical Institute (HHMI) at University of California at Berkeley (UCB) and the Lawrence Berkeley National Lab (LBNL). We are part of the Department of Molecular and Cell Biology of UCB and the Genomics Division of LBNL, and the. We are located in Stanley Hall on the Berkeley campus.Our lab applies computational and experimental genomic approaches to study how genome sequences specify organismal form and function. We are particularly interested in the regulation of gene expression, and focus on how the information that specifies when and where genes are expressed is encoded in genome sequences, the role that regulated gene expression plays in animal development and the response of microbes to their environments, and how variation in and evolution of gene expression contributes to phenotypic variation and the remarkable diversity of life on Earth. This site contains a more detailed description of our research projects, an introduction to members of the lab, reprints of all of our publications, free downloadable and web-based software. Sponsor. Experimental work described here was supported by a Howard Hughes Medical Institute Investigator award to MBE and by National Institutes of Health (NIH) grant GM704403 to MBE and MDB. Computational analyses were supported in by NIH grant HG002779 to MBE. Work at Lawrence Berkeley National Laboratory was conducted under Department of Energy contract DE-AC02-05CH11231. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
View all literature mentionsSoftware to graphically browse results of clustering and other analyses from Cluster.
View all literature mentionsSoftware R package. Methods for Cluster analysis. Performs variety of types of cluster analysis and other types of processing on large microarray datasets.
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