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Early detection of lung adenocarcinoma in sputum by a panel of microRNA markers

✍ Scribed by Lei Yu; Nevins W. Todd; Lingxiao Xing; Ying Xie; Howard Zhang; Zhenqiu Liu; HongBin Fang; Jian Zhang; Ruth L. Katz; Feng Jiang

Publisher
John Wiley and Sons
Year
2010
Tongue
French
Weight
312 KB
Volume
127
Category
Article
ISSN
0020-7136

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✦ Synopsis

Abstract

Adenocarcinoma is the most common type of lung cancer, the leading cause of cancer deaths in the world. Early detection is the key to improve the survival of lung adenocarcinoma patients. We have previously shown that microRNAs (miRNAs) were stably present in sputum and could be applied to diagnosis of lung cancer. The aim of our study was to develop a panel of miRNAs that can be used as highly sensitive and specific sputum markers for early detection of lung adenocarcinoma. Our study contained 3 phases: (i) marker discovery using miRNA profiling on paired normal and tumor lung tissues from 20 patients with lung adenocarcinoma; (ii) marker optimization by real‐time reverse transcription‐quantitative polymerase chain reaction on sputum of a case–control cohort consisting of 36 cancer patients and 36 health individuals and (iii) validation on an independent set of 64 lung cancer patients and 58 cancer‐free subjects. From the surgical tissues, 7 miRNAs with significantly altered expression were identified, of which “4” were overexpressed and “3” were underexpressed in all 20 tumors. On the sputum samples of the case–control cohort, 4 (miR‐21, miR‐486, miR‐375 and miR‐200b) of the 7 miRNAs were selected, which in combination produced the best prediction in distinguishing lung adenocarcinoma patients from normal subjects with 80.6% sensitivity and 91.7% specificity. Validation of the marker panel in the independent populations confirmed the sensitivity and specificity that provided a significant improvement over any single one alone. The sputum markers demonstrated the potential of translation to laboratory settings for improving the early detection of lung adenocarcinoma.

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