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1 Department of Pathology, University of Pittsburgh Medical Center; 2 Department of Pharmacology, University of Pittsburgh School of Medicine; 3 University of Pittsburgh Cancer Institute, Hillman Cancer Center; and 4 Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
Requests for reprints: Simion Chiosea, Department of Pathology, University of Pittsburgh Medical Center Presbyterian, C920, 200 Lothrop Street, Pittsburgh, PA 15213. Phone: 412-958-5459; Fax: 412-624-0614; E-mail: chioseasi{at}upmc.edu.
Differential microRNA (miR) expression is described in non–small cell lung carcinoma. miR biogenesis requires a set of proteins collectively referred to as the miR machinery. In the proposed multistep carcinogenesis model, peripheral adenocarcinoma of the lung develops from noninvasive precursor lesions known as atypical adenomatous hyperplasia (AAH) and bronchioloalveolar carcinoma (BAC). The gene array analysis of BAC and adenocarcinoma showed a transient up-regulation of Dicer (a key effector protein for small interfering RNA and miR function) and PACT along with down-regulation of most genes encoding miR machinery proteins. Immunohistochemically, Dicer was up-regulated in AAH and BAC and down-regulated in areas of invasion and in advanced adenocarcinoma. A fraction of adenocarcinomas lose Dicer as a result of deletions at the Dicer locus. Expanded immunohistochemical and Western blot analysis showed higher Dicer level in squamous cell carcinoma (SCC) of the lung when compared with adenocarcinoma. Other proteins of the RNA-induced silencing complex (RISC; SND1, PACT, and FXR1) were also present at higher levels in a SCC cell line when compared with an adenocarcinoma cell line. In conclusion, the stoichiometry of miR machinery and RISC depends on histologic subtype of lung carcinoma, varies along the AAH-BAC-adenocarcinoma sequence, and might explain the observed abnormal miR profile in lung cancer. The status of the endogenous miR machinery in various histologic subtypes and stages of lung cancer may help to predict the toxicity of and susceptibility to future RNA interference–based therapy. [Cancer Res 2007;67(5):2345–50]
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