scholarly journals Diagnostic MicroRNA Biomarker Discovery for Non-Small-Cell Lung Cancer Adenocarcinoma by Integrative Bioinformatics Analysis

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Yang Shao ◽  
Bin Liang ◽  
Fei Long ◽  
Shu-Juan Jiang
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Target Genes ◽  
Biomarker Discovery ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Small Cell ◽  
Functional Enrichment ◽  
Small Cell Lung

Lung cancer is the leading cause of cancer death and its incidence is ranked high in men and women worldwide. Non-small-cell lung cancer (NSCLC) adenocarcinoma is one of the most frequent histological subtypes of lung cancer. The aberration profile and the molecular mechanism driving its progression are the key for precision therapy of lung cancer, while the screening of biomarkers is essential to the precision early diagnosis and treatment of the cancer. In this work, we applied a bioinformatics method to analyze the dysregulated interaction network of microRNA-mRNA in NSCLC, based on both the gene expression data and the microRNA-gene regulation network. Considering the properties of the substructure and their biological functions, we identified the putative diagnostic biomarker microRNAs, some of which have been reported on the PubMed citations while the rest, that is, miR-204-5p, miR-567, miR-454-3p, miR-338-3p, and miR-139-5p, were predicted as the putative novel microRNA biomarker for the diagnosis of NSCLC adenocarcinoma. They were further validated by functional enrichment analysis of their target genes. These findings deserve further experimental validations for future clinical application.

scholarly journals Bioinformatics analysis reveals 6 key biomarkers associated with non-small-cell lung cancer

2019 ◽  
Vol 48 (3) ◽  
pp. 030006051988763 ◽  
Author(s):  
Bai Dai ◽  
Li-qing Ren ◽  
Xiao-yu Han ◽  
Dong-jun Liu
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Small Cell ◽  
Ppi Network ◽  
Small Cell Lung ◽  
Hub Genes ◽  
Detection And Diagnosis

Objective Non-small-cell lung cancer (NSCLC) accounts for >85% of lung cancers, and its incidence is increasing. We explored expression differences between NSCLC and normal cells and predicted potential target sites for detection and diagnosis of NSCLC. Methods Three microarray datasets from the Gene Expression Omnibus database were analyzed using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were conducted. Then, the String database, Cytoscape, and MCODE plug-in were used to construct a protein–protein interaction (PPI) network and screen hub genes. Overall and disease-free survival of hub genes were analyzed using Kaplan-Meier curves, and the relationship between expression patterns of target genes and tumor grades were analyzed and validated. Gene set enrichment analysis and receiver operating characteristic curves were used to verify enrichment pathways and diagnostic performance of hub genes. Results In total, 293 differentially expressed genes were identified and mainly enriched in cell cycle, ECM–receptor interaction, and malaria. In the PPI network, 36 hub genes were identified, of which 6 were found to play significant roles in carcinogenesis of NSCLC: CDC20, ECT2, KIF20A, MKI67, TPX2, and TYMS. Conclusion The identified target genes can be used as biomarkers for the detection and diagnosis of NSCLC.

scholarly journals Circ_MDM2_000139, Circ_ATF2_001418, Circ_CDC25C_002079, and Circ_BIRC6_001271 Are Involved in the Functions of XAV939 in Non-Small Cell Lung Cancer

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Haixiang Yu ◽  
Lei Xu ◽  
Zhengjia Liu ◽  
Bo Guo ◽  
Zhifeng Han ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Regulatory Network ◽  
Family Members ◽  
Enrichment Analysis ◽  
Small Cell ◽  
Small Cell Lung ◽  
Expression Levels ◽  
Relative Expression

Background. The small molecule inhibitor XAV939 could inhibit the proliferation and promote the apoptosis of non-small cell lung cancer (NSCLC) cells. This study was conducted to identify the key circular RNAs (circRNAs) and microRNAs (miRNAs) in XAV939-treated NSCLC cells. Methods. After grouping, the NCL-H1299 cells in the treatment group were treated by 10 μM XAV939 for 12 h. RNA-sequencing was performed, and then the differentially expressed circRNAs (DE-circRNAs) were analyzed by the edgeR package. Using the clusterprofiler package, enrichment analysis for the hosting genes of the DE-circRNAs was performed. Using Cytoscape software, the miRNA-circRNA regulatory network was built for the disease-associated miRNAs and the DE-circRNAs. The DE-circRNAs that could translate into proteins were predicted using circBank database and IRESfinder tool. Finally, the transcription factor (TF)-circRNA regulatory network was built by Cytoscape software. In addition, A549 and HCC-827 cell treatment with XAV939 were used to verify the relative expression levels of key DE-circRNAs. Results. There were 106 DE-circRNAs (including 61 upregulated circRNAs and 45 downregulated circRNAs) between treatment and control groups. Enrichment analysis for the hosting genes of the DE-circRNAs showed that ATF2 was enriched in the TNF signaling pathway. Disease association analysis indicated that 8 circRNAs (including circ_MDM2_000139, circ_ATF2_001418, circ_CDC25C_002079, and circ_BIRC6_001271) were correlated with NSCLC. In the miRNA-circRNA regulatory network, let-7 family members⟶circ_MDM2_000139, miR-16-5p/miR-134-5p⟶circ_ATF2_001418, miR-133b⟶circ_BIRC6_001271, and miR-221-3p/miR-222-3p⟶circ_CDC25C_002079 regulatory pairs were involved. A total of 47 DE-circRNAs could translate into proteins. Additionally, circ_MDM2_000139 was targeted by the TF POLR2A. The verification test showed that the relative expression levels of circ_MDM2_000139, circ_CDC25C_002079, circ_ATF2_001418, and circ_DICER1_000834 in A549 and HCC-827 cell treatment with XAV939 were downregulated comparing with the control. Conclusions. Let-7 family members and POLR2A targeting circ_MDM2_000139, miR-16-5p/miR-134-5p targeting circ_ATF2_001418, miR-133b targeting circ_BIRC6_001271, and miR-221-3p/miR-222-3p targeting circ_CDC25C_002079 might be related to the mechanism in the treatment of NSCLC by XAV939.

scholarly journals A Comparative Study of Mouse Hepatic and Intestinal Gene Expression Profiles under PPARαKnockout by Gene Set Enrichment Analysis

PPAR Research ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Kan He ◽  
Qishan Wang ◽  
Yumei Yang ◽  
Minghui Wang ◽  
Yuchun Pan
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Enrichment Analysis ◽  
Small Cell ◽  
Gene Set Enrichment Analysis ◽  
Small Cell Lung ◽  
Gene Set Enrichment ◽  
Tissue Specific

Gene expression profiling of PPARαhas been used in several studies, but fewer studies went further to identify the tissue-specific pathways or genes involved in PPARαactivation in genome-wide. Here, we employed and applied gene set enrichment analysis to two microarray datasets both PPARαrelated respectively in mouse liver and intestine. We suggested that the regulatory mechanism of PPARαactivation by WY14643 in mouse small intestine is more complicated than in liver due to more involved pathways. Several pathways were cancer-related such as pancreatic cancer and small cell lung cancer, which indicated that PPARαmay have an important role in prevention of cancer development. 12 PPARαdependent pathways and 4 PPARαindependent pathways were identified highly common in both liver and intestine of mice. Most of them were metabolism related, such as fatty acid metabolism, tryptophan metabolism, pyruvate metabolism with regard to PPARαregulation but gluconeogenesis and propanoate metabolism independent of PPARαregulation. Keratan sulfate biosynthesis, the pathway of regulation of actin cytoskeleton, the pathways associated with prostate cancer and small cell lung cancer were not identified as hepatic PPARαindependent but as WY14643 dependent ones in intestinal study. We also provided some novel hepatic tissue-specific marker genes.

scholarly journals Frontiers of MicroRNA Signature in Non-small Cell Lung Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Xinping Zhu ◽  
Masahisa Kudo ◽  
Xiangjie Huang ◽  
Hehuan Sui ◽  
Haishan Tian ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Target Genes ◽  
Late Onset ◽  
Relative Survival ◽  
Small Cell ◽  
Diagnostic Tools ◽  
Screening Methods ◽  
Small Cell Lung

Lung cancer is the leading cause of cancer-related deaths worldwide and non-small cell lung cancer (NSCLC) accounts for more than 80% of all lung cancer cases. Recent advancements in diagnostic tools, surgical treatments, chemotherapies, and molecular targeted therapies that improved the therapeutic efficacy in NSCLC. However, the 5-years relative survival rate of NSCLC is only about 20% due to the inadequate screening methods and late onset of clinical symptoms. Dysregulation of microRNAs (miRNAs) was frequently observed in NSCLC and closely associated with NSCLC development, progression, and metastasis through regulating their target genes. In this review, we provide an updated overview of aberrant miRNA signature in NSCLC, and discuss the possibility of miRNAs becoming a diagnostic and therapeutic tool. We also discuss the possible causes of dysregulated miRNAs in NSCLC.

scholarly journals Targeted Therapy for Non-Small Cell Lung Cancer

2020 ◽  
Vol 95 (2) ◽  
pp. 78-88
Author(s):  
Jung Sun Kim ◽  
Eun Joo Kang
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Survival Benefit ◽  
Target Genes ◽  
Gene Mutations ◽  
Therapeutic Agents ◽  
Small Cell ◽  
Small Cell Lung ◽  
Gene Alterations

Treatment of progressive non-small cell lung cancer (NSCLC) has advanced remarkably, due in part to the development of targeted therapies. Several gene alterations, including EGFR, ALK, ROS1, and BRAF, play important roles in carcinogenesis. Therefore, many targeted agents focusing these gene alterations have been developed and proving their therapeutic efficacies in many clinical trials. Now we should test these gene mutations and should apply treatments individually and properly to ensure the maximal survival benefit of each patient. In this review, we summarize the target genes and respective therapeutic agents in NSCLC.

scholarly journals Circulating Microvesicles and Exosomes in Small Cell Lung Cancer by Quantitative Proteomics

2021 ◽  
Author(s):  
Shona Pedersen ◽  
Katrine Papendick Jensen ◽  
Bent Honoré ◽  
Søren Risom Kristensen ◽  
Camilla Holm Pedersen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Early Detection ◽  
Small Cell Lung Cancer ◽  
Extracellular Vesicles ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Factor H ◽  
Functional Enrichment ◽  
Healthy Controls ◽  
Small Cell Lung

Abstract Background: Early detection of small cell lung cancer (SCLC) crucially demands highly reliable markers. Growing evidence suggests that extracellular vesicles carry tumor cell-specific cargo suitable as protein markers in cancer. Quantitative proteomic profiling of circulating microvesicles and exosomes can be a high-throughput platform for discovery of novel molecular insights and putative markers. Hence, this study aimed to investigate proteome dynamics of plasma-derived microvesicles and exosomes in newly diagnosed SCLC patients to improve early detection.Methods: Plasma-derived microvesicles and exosomes from 24 healthy controls and 24 SCLC patients were isolated from plasma by either high-speed- or ultracentrifugation. Proteins derived from these extracellular vesicles were quantified using label-free mass spectrometry and statistical analysis was carried out aiming at identifying significantly altered protein expressions between SCLC patients and healthy controls. Furthermore, significantly expressed proteins were subjected to functional enrichment analysis to identify biological pathways implicated in SCLC pathogenesis.Results: Based on fold change (FC) ≥ 2 or ≤ 0.5 and AUC ≥ 0.70 (p < 0.05), we identified 10 common and 16 and 17 unique proteins for microvesicles and exosomes, respectively. Among these proteins, we found dysregulation of coagulation factor XIII A (Log2 FC = −1.1, p = 0.0003, AUC = 0.82, 95% CI: 0.69-0.96) and complement factor H-related protein 4 (Log2 FC = 1.2, p = 0.0005, AUC = 0.82, 95% CI; 0.67-0.97) in SCLC patients compared to heatlhy individuals. Our data may indicate a novel tumor-suppressing role of blood coagulation and involvement of complement activation in SCLC pathogenesis.Conclusions: In comparing SCLC patients and healthy individuals, several differentially expressed proteins were identified. This is the first study showing that circulating extracellular vesicles may encompass specific proteins with potential diagnostic attributes for SCLC, thereby opening new opportunities as novel non-invasive markers.

scholarly journals Bioinformatics prediction of differential miRNAs in non-small cell lung cancer

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254854
Author(s):  
Kui Xiao ◽  
Shenggang Liu ◽  
Yijia Xiao ◽  
Yang Wang ◽  
Zhiruo Zhu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cell Cycle ◽  
Survival Analysis ◽  
Drug Metabolism ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Roc Analysis ◽  
Enrichment Analysis ◽  
Small Cell ◽  
Small Cell Lung

Background Non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancers. The drug resistance of NSCLC has clinically increased. This study aimed to screen miRNAs associated with NSCLC using bioinformatics analysis. We hope that the screened miRNA can provide a research direction for the subsequent treatment of NSCLC. Methods We screened out the common miRNAs after compared the NSCLC-related genes in the TCGA database and GEO database. Selected miRNA was performed ROC analysis, survival analysis, and enrichment analysis (GO term and KEGG pathway). Results A total of 21 miRNAs were screened in the two databases. And they were all highly expressed in normal and low in cancerous tissues. Hsa-mir-30a was selected by ROC analysis and survival analysis. Enrichment analysis showed that the function of hsa-mir-30a is mainly related to cell cycle regulation and drug metabolism. Conclusion Our study found that hsa-mir-30a was differentially expressed in NSCLC, and it mainly affected NSCLC by regulating the cell cycle and drug metabolism.

scholarly journals CLPTM1L induces estrogen receptor β signaling-mediated radioresistance in non-small cell lung cancer cells

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Hang Li ◽  
Jun Che ◽  
Mian Jiang ◽  
Ming Cui ◽  
Guoxing Feng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Estrogen Receptor ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Target Genes ◽  
Small Cell ◽  
Small Cell Lung

Abstract Introduction Radioresistance is a major challenge in lung cancer radiotherapy, and new radiosensitizers are urgently needed. Estrogen receptor β (ERβ) is involved in the progression of non-small cell lung cancer (NSCLC), however, the role of ERβ in the response to radiotherapy in lung cancer remains elusive. In the present study, we investigated the mechanism underlying ERβ-mediated transcriptional activation and radioresistance of NSCLC cells. Methods Quantitative real-time PCR, western blot and immunohistochemistry were used to detect the expression of CLPTM1L, ERβ and other target genes. The mechanism of CLPTM1L in modulation of radiosensitivity was investigated by chromatin immunoprecipitation assay, luciferase reporter gene assay, immunofluorescence staining, confocal microscopy, coimmunoprecipitation and GST pull-down assays. The functional role of CLPTM1L was detected by function assays in vitro and in vivo. Results CLPTM1L expression was negatively correlated with the radiosensitivity of NSCLC cell lines, and irradiation upregulated CLPTM1L in radioresistant (A549) but not in radiosensitive (H460) NSCLC cells. Meanwhile, IR induced the translocation of CLPTM1L from the cytoplasm into the nucleus in NSCLC cells. Moreover, CLPTM1L induced radioresistance in NSCLC cells. iTRAQ-based analysis and cDNA microarray identified irradiation-related genes commonly targeted by CLPTM1L and ERβ, and CLPTM1L upregulated ERβ-induced genes CDC25A, c-Jun, and BCL2. Mechanistically, CLPTM1L coactivated ERβ by directly interacting with ERβ through the LXXLL NR (nuclear receptor)-binding motif. Functionally, ERβ silencing was sufficient to block CLPTM1L-enhanced radioresistance of NSCLC cells in vitro. CLPTM1L shRNA treatment in combination with irradiation significantly inhibited cancer cell growth in NSCLC xenograft tumors in vivo. Conclusions The present results indicate that CLPTM1L acts as a critical coactivator of ERβ to promote the transcription of its target genes and induce radioresistance of NSCLC cells, suggesting a new target for radiosensitization in NSCLC therapy.

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