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.
Highlights
Lung cancer is the leading cause of cancer-related mortality, with adenocarcinoma the most prevalent among the four major subtypes, though accumulated evidence indicates marked distinctions among adenocarcinomas in terms of genetic and epigenetic alterations[1,2]
The present study was conducted using an overall scheme with two clearly separated stages; construction of a diagnostic classifier based on analysis of a training cohort using ready-made TaqMan Human MicroRNA Arrays containing 768 miRNAs, and validation of the resultant classifier with an independent cohort and a custom-made TaqMan Human MicroRNA array, along with a completely independent set of blood samples from lung adenocarcinoma patients as well as those with other types of cancers (Fig. 1)
We constructed a diagnostic classifier based on the results of miRNA profiling analysis using serum samples from lung adenocarcinoma patients and demonstrated that the presence of lung adenocarcinoma can be detected with only a small amount of serum
Summary
Lung cancer is the leading cause of cancer-related mortality, with adenocarcinoma the most prevalent among the four major subtypes, though accumulated evidence indicates marked distinctions among adenocarcinomas in terms of genetic and epigenetic alterations[1,2]. Following our initial discovery of down-regulation of let-7 6, a number of oncogenic and tumor suppressive miRNAs have been reported to exhibit altered expression in lung cancer tumor tissues[7,8,9,10]. The vast majority of previous reports of miRNA-based serum/plasma biomarkers dealt with non-small cell lung cancer (NSCLC) in only a broad manner. To construct diagnostic classifiers based on a blood-borne miRNA profile with use of an independent validation cohort including other types of cancers[13,14,15,16,17]. We attempted to establish an miRNA profile-based diagnostic method by use of a training cohort of serum samples from lung adenocarcinoma patients. We report here our results showing successful construction and validation of a serum miRNA profile-based classifier for diagnosis of lung adenocarcinoma
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