Dataset Information

Identification of A Panel of Serum microRNAs as Biomarkers for Early Detection of Lung Adenocarcinoma.

ABSTRACT: Introduction: Since currently no sensitive and specific biomarkers for early detection of lung adenocarcinoma (AD) exist and the majority of AD patients are diagnosed at late stages of disease, the development of effective screening tests for early-stage lung AD is urgently needed. Serum microRNAs (miRNAs) have been documented as novel noninvasive biomarkers in tumor diagnosis; thus, we studied the profile of serum miRNA in AD patients in order to identify the differentially expressed miRNAs as potential biomarkers for early detection of AD. Patients and Methods: Serum samples were collected from 180 AD patients and 180 age- and sex-matched healthy controls. Serum miRNA profiling was performed by low-density array (LDA) using RNA extracted from blood samples of 20 patients and 20 controls. To validate the selected miRNAs, a stem-loop based RT-qPCR assay was used and serum samples from 160 patients and 160 controls were examined. Results: Profiling data showed 11 differentially expressed miRNAs in the serum samples from AD patients compared with the controls. Among them, 6 selected miRNAs in AD patients, including miR-103, miR-146a, miR-151, miR-21, miR-221, miR-222, and miR-223, were validated by RT-qPCR. In particular, the top three, miR-146a, miR-222, and miR-223, were confirmed to be significantly expressed in stage I/II AD patients compared with healthy controls. Conclusion: A panel of miRNAs with miR-146a, miR-222 and miR-223 could be used as potential noninvasive biomarkers for early detection of AD.

SUBMITTER: Lv S

PROVIDER: S-EPMC5264039 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Identification of A Panel of Serum microRNAs as Biomarkers for Early Detection of Lung Adenocarcinoma.

Lv Shaogang S Xue Jian J Wu Chuanyong C Wang Lin L Wu Jing J Xu Shujun S Liang Xiaohui X Lou Jiatao J

Journal of Cancer 20170101 1

<i>Introduction:</i> Since currently no sensitive and specific biomarkers for early detection of lung adenocarcinoma (AD) exist and the majority of AD patients are diagnosed at late stages of disease, the development of effective screening tests for early-stage lung AD is urgently needed. Serum microRNAs (miRNAs) have been documented as novel noninvasive biomarkers in tumor diagnosis; thus, we studied the profile of serum miRNA in AD patients in order to identify the differentially expressed miR ...[more]

PMID: 28123597

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Project description:Lung adenocarcinoma (LUAD) is one of the most common cancers and lethal diseases in the world. Recognition of the undetermined lung nodules at an early stage is useful for a favorable prognosis. However, there is no good method to identify the undetermined lung nodules and predict their clinical outcome. DNA methylation alteration is frequently observed in LUAD and may play important roles in carcinogenesis, diagnosis, and prediction. This study took advantage of publicly available methylation profiling resources and a machine learning method to investigate methylation differences between LUAD and adjacent non-malignant tissue. The prediction panel was first constructed using 338 tissue samples from LUAD patients including 149 non-malignant ones. This model was then validated with data from The Cancer Genome Atlas database and clinic samples. As a result, the methylation status of four CpG loci in homeobox A9 (HOXA9), keratin-associated protein 8-1 (KRTAP8-1), cyclin D1 (CCND1), and tubby-like protein 2 (TULP2) were highlighted as informative markers. A random forest classification model with an accuracy of 94.57% and kappa of 88.96% was obtained. To evaluate this panel for LUAD, the methylation levels of four CpG loci in HOXA9, KRTAP8-1, CCND1, and TULP2 of tumor samples and matched adjacent lung samples from 25 patients with LUAD were tested. In these LUAD patients, the methylation of HOXA9 was significantly upregulated, whereas the methylation of KRTAP8-1, CCND1, and TULP2 were downregulated obviously in tumor samples compared with adjacent tissues. Our study demonstrates that the methylation of HOXA9, KRTAP8-1, CCND1, and TULP2 has great potential for the early recognition of LUAD in the undetermined lung nodules. The findings also exhibit that the application of improved mathematic algorithms can yield accurate and particularly robust and widely applicable marker panels. This approach could greatly facilitate the discovery process of biomarkers in various fields.

Dataset Information

Identification of A Panel of Serum microRNAs as Biomarkers for Early Detection of Lung Adenocarcinoma.

Publications

Identification of A Panel of Serum microRNAs as Biomarkers for Early Detection of Lung Adenocarcinoma.

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