Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Zhang X

PROVIDER: S-EPMC9756610 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

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

Zhang Xintong X Tan Jinjing J Chen Yan Y Ma Shang S Bai Wanqiu W Peng Yanjing Y Shi Guangli G

BMC pulmonary medicine 20221216 1

<h4>Background</h4>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 NSCL ...[more]

PMID: 36522766

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Project description:BackgroundNon-small cell lung cancer (NSCLC) is the most prevalent malignant tumor of the lung cancer, for which the molecular mechanisms remain unknown. In this study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC by bioinformatics analysis.MethodsFrom the Gene Expression Omnibus database, GSE118370 and GSE10072 microarray datasets were obtained. Identifying the differentially expressed genes (DEGs) between lung adenocarcinoma and normal samples was done. By using bioinformatics tools, a protein-protein interaction (PPI) network was constructed, modules were analyzed, and enrichment analyses were performed. The expression and prognostic values of 14 hub genes were validated by the GEPIA database, and the correlation between hub genes and survival in lung adenocarcinoma was assessed by UALCAN, cBioPortal, String and Cytoscape, and Timer tools.ResultsWe found three genes (PIK3R1, SPP1, and PECAM1) that have a clear correlation with OS in the lung adenocarcinoma patient. It has been found that lung adenocarcinoma exhibits high expression of SPP1 and that this has been associated with poor prognosis, while low expression of PECAM1 and PIK3R1 is associated with poor prognosis (P < 0.05). We also found that the expression of SPP1 was associated with miR-146a-5p, while the high expression of miR-146a-5p was related to good prognosis (P < 0.05). On the contrary, the lower miR-21-5p on upstream of PIK3R1 is associated with a higher surviving rate in cancer patients (P < 0.05). Finally, we found that the immune checkpoint genes CD274(PD-L1) and PDCD1LG2(PD-1) were also related to SPP1 in lung adenocarcinoma.ConclusionsThe results indicated that SPP1 is a cancer promoter (oncogene), while PECAM1 and PIK3R1 are cancer suppressor genes. These genes take part in the regulation of biological activities in lung adenocarcinoma, which provides a basis for improving detection and immunotherapeutic targets for lung adenocarcinoma.

Dataset Information

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

Background

Methods

Results

Conclusion

Publications

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

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