Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA)

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies consisting essentially of adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Although the diagnosis and treatment of ADC and SCC have been greatly improved in recent decades, there is still an urgent need to identify accurate transcriptome profile associated with the histological subtypes of NSCLC. The present study aims to identify the key dysregulated pathways and genes involved in the development of lung ADC and SCC and to relate them with the clinical traits. The transcriptional changes between tumour and normal lung tissues were investigated by RNA-seq. Gene ontology (GO), canonical pathways analysis with the prediction of upstream regulators, and weighted gene co-expression network analysis (WGCNA) to identify co-expressed modules and hub genes were used to explore the biological functions of the identified dysregulated genes. It was indicated that specific gene signatures differed significantly between ADC and SCC related to the distinct pathways. Of identified modules, four and two modules were the most related to clinical features in ADC and SCC, respectively. CTLA4, MZB1, NIP7, and BUB1B in ADC, as well as GNG11 and CCNB2 in SCC, are novel top hub genes in modules associated with tumour size, SUVmax, and recurrence-free survival. Our research provides a more effective understanding of the importance of biological pathways and the relationships between major genes in NSCLC in the perspective of searching for new molecular targets.

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Monastrol Targeted KIF11 Showed Potential Treatment Effective of Small Cell Lung Cancer

10.21203/rs.2.17513/v1 ◽

2019 ◽

Author(s):

Xinhui Wang ◽

Shanshan Jiang ◽

Baolin Zhou ◽

Zhantao Liu ◽

Ziling Liu

Keyword(s):

Lung Cancer ◽

Network Analysis ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Small Cell ◽

Normal Lung ◽

Small Cell Lung ◽

Hub Genes ◽

Vitro Assay

Abstract Objective: This study is to identify Small Cell Lung Cancer (SCLC) driver genes, annotate enrichment functions and key pathways, and also verify Monastrol therapeutic effect. Methods: The gene expression profiles of GSE40275 and GSE43346 was analyzed to identify the DEGs (Differentially Expressed Genes) between SCLC and the normal tissue. GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis and PPI (Protein-protein interaction) network analysis were conducted to find out the enrichment functions, pathways and hub genes. Moreover, in vitro, MTT assay, colony-forming assay, and the scratch assay were performed to verify the effect of Monastrol. Results: There were common 129 up-regulated and 176 down-regulated DEGs between SCLC samples and normal lung samples. KIF11, NDC80 and PBK were identified as hub genes after PPI network analysis. The q-PCR results showed that genes KIF11, NDC80 and PBK consistently expressed higher in cancer cells than normal cell lines. And in vitro assay showed that Monastrol inhibited SCLC cellular viability, proliferation and migration (P < 0.01). Conclusion: KIF11, NDC80 and PBK were aberrantly expressed and could be potentially applied as diagnostic biomarkers, therapeutic targets and prognostic biomarkers. Monastrol was a promising drug in treatment of SCLC patients. Key words: bioinformatics; lung science; SCLC; Monastrol.

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Identification of Gene Biomarkers for Distinguishing Small-Cell Lung Cancer from Non-Small-Cell Lung Cancer Using a Network-Based Approach

BioMed Research International ◽

10.1155/2015/685303 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8 ◽

Cited By ~ 7

Author(s):

Fei Long ◽

Jia-Hang Su ◽

Bin Liang ◽

Li-Li Su ◽

Shu-Juan Jiang

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Expression Patterns ◽

Small Cell ◽

Normal Lung ◽

Specific Gene ◽

Small Cell Lung ◽

Cancer Subtypes ◽

Gene Modules

Lung cancer consists of two main subtypes: small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) that are classified according to their physiological phenotypes. In this study, we have developed a network-based approach to identify molecular biomarkers that can distinguish SCLC from NSCLC. By identifying positive and negative coexpression gene pairs in normal lung tissues, SCLC, or NSCLC samples and using functional association information from the STRING network, we first construct a lung cancer-specific gene association network. From the network, we obtain gene modules in which genes are highly functionally associated with each other and are either positively or negatively coexpressed in the three conditions. Then, we identify gene modules that not only are differentially expressed between cancer and normal samples, but also show distinctive expression patterns between SCLC and NSCLC. Finally, we select genes inside those modules with discriminating coexpression patterns between the two lung cancer subtypes and predict them as candidate biomarkers that are of diagnostic use.

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A mRNA-miRNA-lncRNA regulatory network related to potential pathogenesis and prognostic markers of Non- small cell lung cancer

10.21203/rs.3.rs-318131/v1 ◽

2021 ◽

Author(s):

Fei Wang ◽

Chong Yuan ◽

Yanfang Yang ◽

Bo Liu ◽

Hezhen Wu

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Malignant Tumors ◽

Small Cell ◽

Normal Lung ◽

Small Cell Lung ◽

Hub Genes ◽

Incidence And Mortality ◽

Nsclc Patients

Abstract Non-small cell lung cancer (NSCLC) is one of the most malignant tumors with the fastest increasing incidence and mortality rate, but the etiology of NSCLC is still not clear. Most of lncRNAs have some structural similarities with mRNAs, suggesting that miRNAs negatively regulate the expression of lncRNAs to affect the occurrence and development of tumor. Therefore, system bioinformatics was used to explore the potential biomarkers and possible pathogenesis of NSCLC in this study. Firstly, all the clinical information and transcriptome data were downloaded from GEO and TCGA databases. R language was used to analyze the differentially expressed genes (DEGs) in NSCLC and normal lung tissues. Then, 50 overlapped DEGs were obtained via Venn database, including 10 down-regulated mRNAs and 40 down-regulated mRNAs. Secondly, the top 20 DEGs were selected for KEGG pathway and GO enrichment analysis. After screening 4 HUB genes related to the survival and prognosis of NSCLC patients, their prognosis models were established. Meanwhile, HUB genes related miRNAs and lncRNAs were screened. Finally, a mRNA-miRNA-lncRNA network related to the survival and prognosis of NSCLC patients was established, including 4 up-regulated mRNAs, 3 up-regulated miRNAs, 10 down-regulated miRNAs, 6 up-regulated lncRNAs and 19 down-regulated lncRNAs. Subject terms: Non-small cell lung cancer, mRNA-miRNA-lncRNA, pathogenesis, prognostic biomarkers.

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Identification of potential target genes and crucial pathways in small cell lung cancer based on bioinformatic strategy and human samples

PLoS ONE ◽

10.1371/journal.pone.0242194 ◽

2020 ◽

Vol 15 (11) ◽

pp. e0242194

Author(s):

Xiuwen Chen ◽

Li Wang ◽

Xiaomin Su ◽

Sen-yuan Luo ◽

Xianbin Tang ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Molecular Mechanisms ◽

Target Genes ◽

Small Cell ◽

Normal Lung ◽

Small Cell Lung ◽

Hub Genes ◽

Human Samples

Small cell lung cancer (SCLC) is a carcinoma of the lungs with strong invasion, poor prognosis and resistant to multiple chemotherapeutic drugs. It has posed severe challenges for the effective treatment of lung cancer. Therefore, searching for genes related to the development and prognosis of SCLC and uncovering their underlying molecular mechanisms are urgent problems to be resolved. This study is aimed at exploring the potential pathogenic and prognostic crucial genes and key pathways of SCLC via bioinformatic analysis of public datasets. Firstly, 117 SCLC samples and 51 normal lung samples were collected and analyzed from three gene expression datasets. Then, 102 up-regulated and 106 down-regulated differentially expressed genes (DEGs) were observed. And then, functional annotation and pathway enrichment analyzes of DEGs was performed utilizing the FunRich. The protein-protein interaction (PPI) network of the DEGs was constructed through the STRING website, visualized by Cytoscape. Finally, the expression levels of eight hub genes were confirmed in Oncomine database and human samples from SCLC patients. It showed that CDC20, BUB1, TOP2A, RRM2, CCNA2, UBE2C, MAD2L1, and BUB1B were upregulated in SCLC tissues compared to paired adjacent non-cancerous tissues. These suggested that eight hub genes might be viewed as new biomarkers for prognosis of SCLC or to guide individualized medication for the therapy of SCLC.

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The Key microRNAs Regulated the Development of Non-small Cell Lung Cancer by Targeting TGF-β-induced epithelial–mesenchymal Transition

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207322666190410151945 ◽

2019 ◽

Vol 22 (4) ◽

pp. 238-244 ◽

Cited By ~ 2

Author(s):

Gang Chen ◽

Bo Ye

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lines ◽

Cell Lung Cancer ◽

Small Cell ◽

Nsclc Cell ◽

Normal Lung ◽

Migration And Invasion ◽

Small Cell Lung ◽

Mesenchymal Transition

Purpose: Epithelial-to-Mesenchymal Transition (EMT) was reported to play a key role in the development of Non-Small Cell Lung Cancer (NSCLC). The process of EMT is regulated by the changes of miRNAs expression. However, it is still unknown which miRNA changed the most in the process of canceration and whether these changes played a role in tumor development. Methods: A total of 36 SCLC patients treated in our hospital between 11th, 2015 and 10th, 2017 were enrolled. The samples of cancer tissues and paracancer tissues of patients were collected and analyzed. Then, the miRNAs in normal lung cells and NSCLC cells were also analyzed. In the presence of TGF-β, we transfected the miRNA mimics or inhibitor into NSCLC cells to investigate the role of the significantly altered miRNAs in cell migration and invasion and in the process of EMT. Results: MiR-330-3p was significantly up-regulated in NSCLC cell lines and tissues and miRNA- 205 was significantly down-regulated in NSCLC cell lines and NSCLC tissues. Transfected miRNA-205 mimics or miRMA-330-3p inhibitor inhibited the migration and invasion of NCIH1975 cell and restrained TGF-β-induced EMT in NSCLC cells. Conclusion: miRNA-330-3p and miRNA-205 changed the most in the process of canceration in NSCLC. Furthermore, miR-330-3p promoted cell invasion and metastasis in NSCLC probably by promoting EMT and miR-205 could restrain NSCLC likely by suppressing EMT.

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Kinesin superfamily protein 21B acts as an oncogene in non-small cell lung cancer

10.21203/rs.3.rs-20245/v2 ◽

2020 ◽

Author(s):

Zhi-Gang Sun ◽

Feng Pan ◽

Jing-Bo Shao ◽

Qian-Qian Yan ◽

Lu Lu ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Nude Mice ◽

Cell Lung Cancer ◽

A549 Cells ◽

Small Cell ◽

Normal Lung ◽

Migration And Invasion ◽

Small Cell Lung ◽

Kinesin Superfamily

Abstract Background: Kinesin superfamily proteins (KIFs) serve as microtubule-dependent molecular motors, and are involved in the progression of many malignant tumors. In this study, we aimed to investigate the expression pattern and precise role of kinesin family member 21B (KIF21B) in non-small cell lung cancer (NSCLC). Methods: KIF21B expression in 72 cases of NSCLC tissues was measured by immunohistochemical staining (IHC). We used shRNA-KIF21B interference to silence KIF21B in NSCLC H1299 and A549 cells and normal lung epithelial bronchus BEAS-2B cells. The biological roles of KIF21B in the growth and metastasis abilities of NSCLC cells were measured by Cell Counting Kit-8 (CCK8), colony formation and Hoechst 33342/PI, wound-healing, and Transwell assays, respectively. Expression of apoptosis-related proteins was determined using western blot. The effect of KIF21B on tumor growth in vivo was examined using nude mice model. Results: KIF21B was up-regulated in NSCLC tissues, and correlated with pathological lymph node and pTNM stage, its high expression was predicted a poor prognosis of patients with NSCLC. Silencing of KIF21B mediated by lentivirus-delivered shRNA significantly inhibited the proliferation ability of H1299 and A549 cells. KIF21B knockdown increased apoptosis in H1299 and A549 cells, down-regulated the expression of Bcl-2 and up-regulated the expression of Bax and active Caspase 3. Moreover, KIF21B knockdown decreased the level of phosphorylated form of Akt (p-Akt) and Cyclin D1 expression in H1299 and A549 cells. In addition, silencing of KIF21B impeded the migration and invasion of H1299 and A549 cells. Further, silencing of KIF 21B dramatically inhibited xenograft growth in BALB/c nude mice. However, silencing of KIF21B did not affect the proliferation, migration and invasion of BEAS-2B cells.Conclusions: These results reveal that KIF21B is up-regulated in NSCLC and acts as an oncogene in the growth and metastasis of NSCLC, which may function as a potential therapeutic target and a prognostic biomarker for NSCLC.

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Promoter Methylation of Selected Genes in Non-Small-Cell Lung Cancer Patients and Cell Lines

International Journal of Molecular Sciences ◽

10.3390/ijms21134595 ◽

2020 ◽

Vol 21 (13) ◽

pp. 4595

Author(s):

Victoria Sarne ◽

Samuel Huter ◽

Sandrina Braunmueller ◽

Lisa Rakob ◽

Nico Jacobi ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lines ◽

Cell Lung Cancer ◽

Promoter Methylation ◽

Small Cell ◽

Marker Genes ◽

Specific Gene ◽

Small Cell Lung ◽

The Impact

Specific gene promoter DNA methylation is becoming a powerful epigenetic biomarker in cancer diagnostics. Five genes (CDH1, CDKN2Ap16, RASSF1A, TERT, and WT1) were selected based on their frequently published potential as epigenetic markers. Diagnostic promoter methylation assays were generated based on bisulfite-converted DNA pyrosequencing. The methylation patterns of 144 non-small-cell lung cancer (NSCLC) and 7 healthy control formalin-fixed paraffin-embedded (FFPE) samples were analyzed to evaluate the applicability of the putative diagnostic markers. Statistically significant changes in methylation levels are shown for TERT and WT1. Furthermore, 12 NSCLC and two benign lung cell lines were characterized for promoter methylation. The in vitro tests involved a comparison of promoter methylation in 2D and 3D cultures, as well as therapeutic tests investigating the impact of CDH1/CDKN2Ap16/RASSF1A/TERT/WT1 promoter methylation on sensitivity to tyrosine kinase inhibitor (TKI) and DNA methyl-transferase inhibitor (DNMTI) treatments. We conclude that the selected markers have potential and putative impacts as diagnostic or even predictive marker genes, although a closer examination of the resulting protein expression and pathway regulation is needed.

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