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Clinical Significance of MicroRNA Expression Profiles and Polymorphisms in Lung Cancer Development and Management.

ABSTRACT: Lung cancers account for a huge percentage of death in industrialized countries, and hence there is an increasing call for the development of novel treatments. These malignancies are caused by a combination of environmental factors, principally cigarette smoking and genetic alterations. MicroRNAs (miRNAs) are a recently discovered class of regulatory noncoding small RNAs with a significance in numerous biological processes. Strong evidence links miRNA impaired expression profiles and pathways to the etiology of several diseases, including neoplasia. This paper focuses on the emerging role of miRNA function in lung cancer development with particular highlighting on the use of miRNA profiles and polymorphisms for the molecular and biological characterization of tumor pulmonary growth and progression. Furthermore, we underline the potential utility of lung cancer-associated miRNAs as clinical biomarkers with a diagnostic, prognostic, and therapeutic significance and give emphasis to the promising novel miRNA-based curative strategies.

SUBMITTER: Megiorni F

PROVIDER: S-EPMC3146996 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Clinical Significance of MicroRNA Expression Profiles and Polymorphisms in Lung Cancer Development and Management.

Megiorni Francesca F Pizzuti Antonio A Frati Luigi L

Pathology research international 20110727

Lung cancers account for a huge percentage of death in industrialized countries, and hence there is an increasing call for the development of novel treatments. These malignancies are caused by a combination of environmental factors, principally cigarette smoking and genetic alterations. MicroRNAs (miRNAs) are a recently discovered class of regulatory noncoding small RNAs with a significance in numerous biological processes. Strong evidence links miRNA impaired expression profiles and pathways to ...[more]

PMID: 21811665

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Project description:BackgroundGastric cancer (GC) is one of the common gastrointestinal malignancy worldwide and exhibits a poor prognosis. Increasing studies have indicated that microRNAs play critical roles in the cancer progression and have shown great potential as useful biomarkers. The search for potential diagnostic and prognostic biomarkers of gastric cancer (GC) with integrated bioinformatics analyses has been undertaken in previous studies.MethodsIn this study, the robust rank aggregation (RRA) method was used to perform an integrated analysis of differentially expressed miRNAs (DEMs) from five microarray datasets in the Gene Expression Omnibus (GEO) database to find robust biomarkers for GC. Ultimately, seven miRNAs were filtered from fourteen primary miRNAs using the validation set of The Cancer Genome Atlas (TCGA) database. Based on these results, diagnostic and survival analyses were performed, and logistic regression and Cox regression were used to determine the clinicopathological characteristics of the DEM expression and overall survival.ResultsNine eligible miRNA datasets related to GC were selected from the GEO database for integrated analysis in this study. Diagnostic analysis implied that these miRNAs could be regarded as promising candidate diagnostic biomarkers in GC tissues, but whether the results of the tissue analysis are consistent with those of peripheral blood analysis requires further validation. The logistic regression indicated that the ectopic expression of these DEMs was relevant to the histological type, anatomical region, and pathological grade of GC. However, the survival and Cox regression analyses suggested that the poor prognosis of GC patients was not strongly dependent on the ectopic expression of the seven miRNAs, but rather, a poor prognosis was associated with age, metastasis, and histological grade.ConclusionsBased on the results presented in this study it can be concluded that these miRNAs (miR-455-3p, miR-135b-5p, let-7a-3p, miR-195-5p, miR-204-5p, miR-149-5p, and miR-143-3p) might be potential biomarkers for the early diagnosis of GC patients, but this finding should be regarded with caution. A large-scale, prospective, and multicenter cohort study should be performed.

Project description:The association of lung cancer with changes in microRNAs in plasma shown in multiple studies suggests a utility for circulating microRNA biomarkers in non-invasive detection of the disease. We examined if presence of lung cancer is reflected in whole blood microRNA expression as well, possibly because of a systemic response. Locked nucleic acid microarrays were used to quantify the global expression of microRNAs in whole blood of 22 patients with lung adenocarcinoma and 23 controls, ten of whom had a radiographically detected non-cancerous lung nodule and the other 13 were at high risk for developing lung cancer because of a smoking history of >20 pack-years. Cases and controls differed significantly for age with a mean difference of 10.7 years, but not for gender, race, smoking history, blood hemoglobin, platelet count, or white blood cell count. Of 1282 quantified human microRNAs, 395 (31%) were identified as expressed in the study's subjects, with 96 (24%) differentially expressed between cases and controls. Classification analyses of microRNA expression data were performed using linear kernel support vector machines (SVM) and top-scoring pairs (TSP) methods, and classifiers to identify presence of lung adenocarcinoma were internally cross-validated. In leave-one-out cross-validation, the TSP classifiers had sensitivity and specificity of 91% and 100%, respectively. The values with SVM were both 91%. In a Monte Carlo cross-validation, average sensitivity and specificity values were 86% and 97%, respectively, with TSP, and 88% and 89%, respectively, with SVM. MicroRNAs miR-190b, miR-630, miR-942, and miR-1284 were the most frequent constituents of the classifiers generated during the analyses. These results suggest that whole blood microRNA expression profiles can be used to distinguish lung cancer cases from clinically relevant controls. Further studies are needed to validate this observation, including in non-adenocarcinomatous lung cancers, and to clarify upon the confounding effect of age.

Dataset Information

Clinical Significance of MicroRNA Expression Profiles and Polymorphisms in Lung Cancer Development and Management.

Publications

Clinical Significance of MicroRNA Expression Profiles and Polymorphisms in Lung Cancer Development and Management.

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