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Erschienen in: Journal of Cancer Research and Clinical Oncology 10/2017

24.05.2017 | Original Article – Cancer Research

Analysis of primary-miRNA-3662 and its mature form may improve detection of the lung adenocarcinoma

verfasst von: Tomasz Powrózek, Radosław Mlak, Marcin Dziedzic, Teresa Małecka-Massalska, Dariusz Sagan

Erschienen in: Journal of Cancer Research and Clinical Oncology | Ausgabe 10/2017

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Abstract

Introduction

Because of the alarming data concerning lung cancer morbidity and mortality, investigation of new molecular markers allowing early cancer detection is desirable. In the present study, we investigated the potential role of miRNA-3662 precursor (pri-miRNA-3662) as potential novel diagnostic marker of lung adenocarcinoma (AC).

Materials and methods

Expression of miRNA-3662 and pri-miRNA-3662 was analyzed in 56 fresh-frozen tissues of non-small cell lung cancer and corresponding adjacent non-cancerous tissues using (NCT) qRT-PCR. Using receiver operating curves (ROC) analysis, the diagnostic accuracy of both studied markers for AC detection was assessed.

Results

miRNA-3662 and its precursor were significantly overexpressed in AC compared to squamous-cell carcinoma (SCC) and NCT. Combined analysis of pri-miRNA-3662 and mature miRNA-3662 allowed to distinguish AC tissue from SCC with sensitivity of 96% and specificity of 85.7% (AUC = 0.963), and SCC from non-cancerous tissue with 92% sensitivity and 92% specificity (AUC = 0.979).

Conclusions

miRNA-3662 and its precursor are potentially involved in AC development. pri-miRNA seem to be novel interesting group of potential cancer biomarkers, because they demonstrate high diagnostic accuracy for tumor detection.
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Metadaten
Titel
Analysis of primary-miRNA-3662 and its mature form may improve detection of the lung adenocarcinoma
verfasst von
Tomasz Powrózek
Radosław Mlak
Marcin Dziedzic
Teresa Małecka-Massalska
Dariusz Sagan
Publikationsdatum
24.05.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Journal of Cancer Research and Clinical Oncology / Ausgabe 10/2017
Print ISSN: 0171-5216
Elektronische ISSN: 1432-1335
DOI
https://doi.org/10.1007/s00432-017-2444-0

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