Dataset Information

Blood-borne miRNA profile-based diagnostic classifier for lung adenocarcinoma.

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.

SUBMITTER: Tai MC

PROVIDER: S-EPMC4979017 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Blood-borne miRNA profile-based diagnostic classifier for lung adenocarcinoma.

Tai Mei Chee MC Yanagisawa Kiyoshi K Nakatochi Masahiro M Hotta Naoe N Hosono Yasuyuki Y Kawaguchi Koji K Naito Mariko M Taniguchi Hiroyuki H Wakai Kenji K Yokoi Kohei K Takahashi Takashi T

Scientific reports 20160810

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 subject ...[more]

PMID: 27507195

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Project description:Background: Chemotherapy is one of the most common therapies used in the treatment of colorectal cancer (CRC), but chemoresistance inevitably occurs. It is challenging to obtain an immediate and accurate diagnosis of chemoresistance. The potential of circulating exosomal miRNAs as oxaliplatin-based chemoresistant biomarkers in CRC patients was investigated in this study. Methods: Plasma exosomal miRNAs in sensitive and resistant patients were analyzed by miRNA microarray analysis, followed by verification with a quantitative reverse-transcription polymerase chain reaction (RT-qPCR) assay in two independent cohorts. The diagnostic accuracy was determined by ROC curve analysis. Logistic regression analysis and Spearman's rank correlation test were also performed. Finally, bioinformatics was used to preliminarily explore the potential molecular mechanism of the selected miRNAs in chemoresistance. Results: miRNA microarray analysis identified four upregulated miRNAs and 20 downregulated miRNAs in chemoresistant patients compared to chemosensitive patients. Twelve markedly dysregulated miRNAs were selected for further investigation, of which six (miR-100, miR-92a, miR-16, miR-30e, miR-144-5p, and let-7i) were verified to be significantly and consistently dysregulated (>1.5-fold, P < 0.05). The combination of the six miRNAs had the highest AUC (0.825, 95% CI, 0.753-0.897). The expression level of these 6 miRNAs was not correlated with tumor location, stage, or chemotherapy program. Only miR-100 was significantly upregulated in low histological grade. GO analysis and KEGG pathway analysis showed that miRNAs were related to RNA polymerase II transcription and enriched in the PI3K-AKT signaling pathway, AMPK signaling pathway, and FoxO signaling pathway. Conclusions: We identified a panel of plasma exosomal miRNAs, containing miR-100, miR-92a, miR-16, miR-30e, miR-144-5p, and let-7i, that could significantly distinguish chemoresistant patients from chemosensitive patients. The detection of circulating exosomal miRNAs may serve as an effective way to monitor CRC patient responses to chemotherapy. Targeting these miRNAs may also be a promising strategy for CRC treatment.

Dataset Information

Blood-borne miRNA profile-based diagnostic classifier for lung adenocarcinoma.

Publications

Blood-borne miRNA profile-based diagnostic classifier for lung adenocarcinoma.

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