Blood-borne miRNA profile-based diagnostic classifier for lung adenocarcinoma.
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| Abstract |
Accumulated evidence indicates that various types of miRNA are aberrantly expressed in lung cancer and secreted into the bloodstream. For this study, we constructed a serum diagnostic classifier based on detailed bioinformatics analysis of miRNA profiles from a training cohort of 143 lung adenocarcinoma patients and 49 healthy subjects, resulting in a 20 miRNA-based classifier. Validation performed with an independent cohort of samples from lung adenocarcinoma patients (n = 110), healthy subjects (n = 52), and benign pulmonary disease patients (n = 47) showed a sensitivity of 89.1% and specificity of 94.9%, with an area under the curve value of 0.958. Notably, 90.8% of Stage I lung adenocarcinoma cases were correctly diagnosed. Interestingly, this classifier also detected squamous and large cell lung carcinoma cases at relatively high rates (70.4% and 70.0%, respectively), which appears to be consistent with organ site-dependent miRNA expression in cancer tissues. In contrast, we observed significantly lower rates (0-35%) using samples from 96 cases of cancer in other major organs, with breast cancer the lowest. These findings warrant a future study to realize its clinical application as a part of diagnostic procedures for lung cancers, for which early detection and surgical removal is presently the only hope for eventual cure.
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| Authors | Mei Chee Tai, Kiyoshi Yanagisawa, Masahiro Nakatochi, Naoe Hotta, Yasuyuki Hosono, Koji Kawaguchi, Mariko Naito, Hiroyuki Taniguchi, Kenji Wakai, Kohei Yokoi, Takashi Takahashi |
| Journal | Scientific reports (Sci Rep) Vol. 6 Pg. 31389 (08 10 2016) ISSN: 2045-2322 [Electronic] England |
| PMID | 27507195 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't) |
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