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Identification of serum MiRNAs as candidate biomarkers for non-small cell lung cancer diagnosis

BACKGROUND: Lung cancer is one of the most common solid tumors worldwide and the leading cause of cancer-associated death. Non-small cell lung cancer (NSCLC) is accounts for approximately 85% of all the lung cancers and lung squamous carcinoma (SCC) and adenocarcinoma (ADC) are the main subtypes of...

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Autores principales: Zhang, Xintong, Tan, Jinjing, Chen, Yan, Ma, Shang, Bai, Wanqiu, Peng, Yanjing, Shi, Guangli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9756610/
https://www.ncbi.nlm.nih.gov/pubmed/36522766
http://dx.doi.org/10.1186/s12890-022-02267-6
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author Zhang, Xintong
Tan, Jinjing
Chen, Yan
Ma, Shang
Bai, Wanqiu
Peng, Yanjing
Shi, Guangli
author_facet Zhang, Xintong
Tan, Jinjing
Chen, Yan
Ma, Shang
Bai, Wanqiu
Peng, Yanjing
Shi, Guangli
author_sort Zhang, Xintong
collection PubMed
description BACKGROUND: Lung cancer is one of the most common solid tumors worldwide and the leading cause of cancer-associated death. Non-small cell lung cancer (NSCLC) is accounts for approximately 85% of all the lung cancers and lung squamous carcinoma (SCC) and adenocarcinoma (ADC) are the main subtypes of NSCLC. Early diagnose using serum biomarkers could improve the overall survival of patients. In this study, we aimed to identify miRNAs from serum with clinical utility in the diagnosis of NSCLC. METHODS: Ten patients with SCC, ten patients with ADC and five noncancerous individuals were enrolled in the screening cohort. miRNA expression levels in serum were measured by microarray analysis. Candidate miRNAs were validated by real-time quantitative polymerase chain reaction analysis in a validation cohort of 78 NSCLC patients and 44 noncancerous individuals. Receiver operating characteristic curves were used to assess the diagnostic performance of serum miRNAs for NSCLC. Logistic regression was used to evaluate the diagnostic value of the combination of markers. RESULTS: Six candidate miRNAs were differentially expressed between NSCLC patients and noncancerous individuals in the screening set (fold change > 2, p < 0.05). Among them, expression levels of miR-3149 and miR-4769.3p were confirmed to be significantly increased in tumor serum in the validation set. The area under the curve values of miR-3149 and miR-4769.3p in distinguishing NSCLC patients from noncancerous controls were 0.830 and 0.735, respectively. When combined with tumor markers CEA and Cyfra21-1, the joint diagnostic model increased the area under the curve to 0.898. CONCLUSION: Serum miRNAs miR-3149 and miR-4769.3p were up-regulated in NSCLC and may be potential biomarkers for early diagnosis of lung cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-022-02267-6.
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spelling pubmed-97566102022-12-17 Identification of serum MiRNAs as candidate biomarkers for non-small cell lung cancer diagnosis Zhang, Xintong Tan, Jinjing Chen, Yan Ma, Shang Bai, Wanqiu Peng, Yanjing Shi, Guangli BMC Pulm Med Research BACKGROUND: Lung cancer is one of the most common solid tumors worldwide and the leading cause of cancer-associated death. Non-small cell lung cancer (NSCLC) is accounts for approximately 85% of all the lung cancers and lung squamous carcinoma (SCC) and adenocarcinoma (ADC) are the main subtypes of NSCLC. Early diagnose using serum biomarkers could improve the overall survival of patients. In this study, we aimed to identify miRNAs from serum with clinical utility in the diagnosis of NSCLC. METHODS: Ten patients with SCC, ten patients with ADC and five noncancerous individuals were enrolled in the screening cohort. miRNA expression levels in serum were measured by microarray analysis. Candidate miRNAs were validated by real-time quantitative polymerase chain reaction analysis in a validation cohort of 78 NSCLC patients and 44 noncancerous individuals. Receiver operating characteristic curves were used to assess the diagnostic performance of serum miRNAs for NSCLC. Logistic regression was used to evaluate the diagnostic value of the combination of markers. RESULTS: Six candidate miRNAs were differentially expressed between NSCLC patients and noncancerous individuals in the screening set (fold change > 2, p < 0.05). Among them, expression levels of miR-3149 and miR-4769.3p were confirmed to be significantly increased in tumor serum in the validation set. The area under the curve values of miR-3149 and miR-4769.3p in distinguishing NSCLC patients from noncancerous controls were 0.830 and 0.735, respectively. When combined with tumor markers CEA and Cyfra21-1, the joint diagnostic model increased the area under the curve to 0.898. CONCLUSION: Serum miRNAs miR-3149 and miR-4769.3p were up-regulated in NSCLC and may be potential biomarkers for early diagnosis of lung cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-022-02267-6. BioMed Central 2022-12-16 /pmc/articles/PMC9756610/ /pubmed/36522766 http://dx.doi.org/10.1186/s12890-022-02267-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhang, Xintong
Tan, Jinjing
Chen, Yan
Ma, Shang
Bai, Wanqiu
Peng, Yanjing
Shi, Guangli
Identification of serum MiRNAs as candidate biomarkers for non-small cell lung cancer diagnosis
title Identification of serum MiRNAs as candidate biomarkers for non-small cell lung cancer diagnosis
title_full Identification of serum MiRNAs as candidate biomarkers for non-small cell lung cancer diagnosis
title_fullStr Identification of serum MiRNAs as candidate biomarkers for non-small cell lung cancer diagnosis
title_full_unstemmed Identification of serum MiRNAs as candidate biomarkers for non-small cell lung cancer diagnosis
title_short Identification of serum MiRNAs as candidate biomarkers for non-small cell lung cancer diagnosis
title_sort identification of serum mirnas as candidate biomarkers for non-small cell lung cancer diagnosis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9756610/
https://www.ncbi.nlm.nih.gov/pubmed/36522766
http://dx.doi.org/10.1186/s12890-022-02267-6
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