Dataset Information

Regulatory Network Analysis to Reveal Important miRNAs and Genes in Non-Small Cell Lung Cancer.

ABSTRACT: Objective:Lung cancer has high incidence and mortality rate, and non-small cell lung cancer (NSCLC) takes up approximately 85% of lung cancer cases. This study is aimed to reveal miRNAs and genes involved in the mechanisms of NSCLC. Materials and Methods:In this retrospective study, GSE21933 (21 NSCLC samples and 21 normal samples), GSE27262 (25 NSCLC samples and 25 normal samples), GSE43458 (40 NSCLC samples and 30 normal samples) and GSE74706 (18 NSCLC samples and 18 normal samples) were searched from gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) were screened from the four microarray datasets using MetaDE package, and then conducted with functional annotation using DAVID tool. Afterwards, protein-protein interaction (PPI) network and module analyses were carried out using Cytoscape software. Based on miR2Disease and Mirwalk2 databases, microRNAs (miRNAs)-DEG pairs were selected. Finally, Cytoscape software was applied to construct miRNA-DEG regulatory network. Results:Totally, 727 DEGs (382 up-regulated and 345 down-regulated) had the same expression trends in all of the four microarray datasets. In the PPI network, TP53 and FOS could interact with each other and they were among the top 10 nodes. Besides, five network modules were found. After construction of the miRNA-gene network, top 10 miRNAs (such as hsa-miR-16-5p, hsa-let-7b-5p, hsa-miR-15a-5p, hsa-miR-15b-5p, hsa-let-7a-5p and hsa-miR-34a- 5p) and genes (such as HMGA1, BTG2, SOD2 and TP53) were selected. Conclusion:These miRNAs and genes might contribute to the pathogenesis of NSCLC.

SUBMITTER: Zhou X

PROVIDER: S-EPMC6722447 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Regulatory Network Analysis to Reveal Important miRNAs and Genes in Non-Small Cell Lung Cancer.

Zhou Xingni X Zhang Zhenghua Z Liang Xiaohua X

Cell journal 20190729 4

<h4>Objective</h4>Lung cancer has high incidence and mortality rate, and non-small cell lung cancer (NSCLC) takes up approximately 85% of lung cancer cases. This study is aimed to reveal miRNAs and genes involved in the mechanisms of NSCLC.<h4>Materials and methods</h4>In this retrospective study, GSE21933 (21 NSCLC samples and 21 normal samples), GSE27262 (25 NSCLC samples and 25 normal samples), GSE43458 (40 NSCLC samples and 30 normal samples) and GSE74706 (18 NSCLC samples and 18 normal samp ...[more]

PMID: 31376328

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Project description:BackgroundRadioresistance of thoracic radiotherapy is a major bottleneck in the treatment of non-small cell lung cancer (NSCLC). Until now, there have been no effective biomarkers to predict the radiosensitivity.PurposesBased on miRNA profile screened from NSCLC cell lines with different radiosensitivity, this study was conducted to explore the correlation between plasma miRNAs and radiotherapy response in NSCLC patients, and to identify biomarkers of the radiosensitivity in NSCLC.MethodsDifferentially expressed genes were acquired from time-series gene expression profiles of radioresistant H1299 and radiosensitive H460 lung cancer cells (GSE20549). Potential miRNAs were screened from these differentially expressed genes by combining bioinformatics with GO analysis, pathway analysis, and miRNA prediction. A clinical observational study was performed to explore the correlation between candidate miRNAs and radiotherapy response. Stage IIIa-IV NSCLC patients who received two to four cycles of previous chemotherapy and underwent thoracic radiotherapy alone were included. Total RNA was purified from peripheral blood before radiotherapy, and plasma miRNAs were detected by real-time PCR (qRT-PCR). Then, tumor response, progression-free survival (PFS), and overall survival (OS) were acquired. Four miRNAs significantly different between effective and ineffective groups were further analyzed to obtain cutpoints from receiver operating characteristic (ROC) curves and the predictive value of radiosensitivity.ResultsCandidate miRNAs included 14 miRNAs screened from radioresistant genes and five from radiosensitive genes. From Jan., 2013 to Dec., 2014, 54 eligible patients were enrolled with a median follow-up of 15.3 months (range 4.6 to 31.4) by the deadline of Aug. 31, 2015. Totally, there were no case of complete response (CR), 15 of partial response (PR), 35 of stable disease (SD), and 4 of progressive disease (PD). Eight patients had no progression and 19 patients were still alive. The median PFS and OS were 6.6 months (range 2.3 to 29.3) and 15.3 months (range 4.6 to 31.4), respectively. Four miRNAs (hsa-miR-98-5p, hsa-miR-302e, hsa-miR-495-3p, and hsa-miR-613) demonstrated a higher expression in effective group (CR + PR, 15 cases) than in ineffective group (SD + PD, 39 cases). Based on each cutpoint, objective response rate (ORR) was higher in miR-high group than in miR-low group. No miRNA showed correlation with median PFS or OS.ConclusionBioinformatical analysis and clinical verification reveal the correlation between plasma miRNAs and radiosensitivity in NSCLC patients. Plasma miRNAs represent novel biomarkers to predict radiotherapy response clinically.

Project description:The competing endogenous RNA (ceRNA) network is crucial for the development and progression of tumors, including non‑small cell lung cancer (NSCLC). However, what type of ceRNA network regulates NSCLC has not been clarified. The present study aimed to elucidate the long non‑coding RNA (lncRNA)/microRNA (miRNA)/mRNA ceRNA network in NSCLC, particularly for the significance of lncRNAs in NSCLC. NSCLC‑specific differentially expressed lncRNAs, miRNAs and mRNAs in the Cancer Genome Atlas (TCGA) were analyzed and their relationship was analyzed by a ceRNA network. Their potential functions of differentially expressed mRNAs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Furthermore, the expression levels of four selected lncRNAs in TCGA were determined and their associated survival of patients was examined. In addition, the expression profiles of these four lncRNAs in 48 NSCLC specimens and cell lines, their cellular distribution and associated clinical parameters were examined. We successfully constructed a ceRNA network, including 113 lncRNAs, 12 miRNAs and 36 mRNAs differentially expressed between NSCLC and non‑tumor tissues. LINC00525, MED4‑AS1, STEAP2‑AS1 and SYNPR‑AS1 lncRNAs were selected and validated for their association with the survival of NSCLC patients. The expression of these lncRNAs was upregulated in 48 NSCLC tissues and was varying in NSCLC cells. While LINC00525 was mainly expressed in the cytoplasm, MED4‑AS1 was in both the nucleus and cytoplasm of A549 cells. In addition, the expression of LINC00525 was significantly associated with smoking history (P<0.05); MED4‑AS1 was significantly associated with women, poor differentiation and lymph node metastasis (P<0.05); STEAP2‑AS1 was significantly associated with women (P<0.01); and SYNPR‑AS1 was significantly associated with women and adenocarcinoma (P<0.05). These lncRNAs may be valuable biomarkers for prognosis of NSCLC and the ceRNA network may provide new insights in the pathogenesis of NSCLC.

Dataset Information

Regulatory Network Analysis to Reveal Important miRNAs and Genes in Non-Small Cell Lung Cancer.

Publications

Regulatory Network Analysis to Reveal Important miRNAs and Genes in Non-Small Cell Lung Cancer.

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