scholarly journals Integrated bioinformatics analysis reveals ASPM and CENPF with prognostic value in lung cancer

2019 ◽  
Author(s):  
jinghang li ◽  
Jing Zhang ◽  
Lin Huang ◽  
Min Jin ◽  
Sheng Zhao
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Cell Cycle ◽  
Mirna Gene ◽  
Genetic Alterations ◽  
Potential Candidate ◽  
Kaplan Meier ◽  
Β Receptor ◽  
Regulation Of Cell Cycle ◽  
And Function

Abstract Lung cancer (LC) is the most frequent type of cancer in the world. But the mechanism of LC is still largely unknown. In this study, we analyzed three lung cancer gene expression microarray of different pathologic types to explore the potential candidate genes in LC by Integrated bioinformatical methods. 459 overlapped differentially expressed genes (DEGs) were explored in three GEO gene expression profile from different pathologic types of lung cancer and function annotation were analyzed. Biological process of the DEGs was enriched in regulation of vasculature development and angiogenesis. The significant molecular function of the DEGs was TGF-β receptor activity. The most significant Reactome pathway of DEGs was cell cycle and extracellular matrix organization pathway. The PPI network of the DEGs was constructed and 23 candidate hub genes were established in the network. Kaplan-Meier survival analysis show 21 genes were confirmed to associated with the prognosis of LC. The genetic alterations analysis of these genes by using cBioPortal shown ASPM has the highest genetic alteration rate of 9% in main pathological types of 3191 LC patients, and CENPF has the second highest alteration rate of 6%. ASPM and CENPF also have a significant co-occurrence relationship in LC, and they both participate in the regulation of cell cycle. In the TF -miRNA-gene network of 21 genes shown CENPF have the most significant value in the network and the most relevant TF are NFYA, E2F1 and MYC. In conclusion, this study explored several key genes about LC and analyzed potential TF of those genes, provides possible therapeutic targets and biomarker for further clinical application.

scholarly journals Integrated bioinformatics analysis reveals ASPM and CENPF with prognostic value in lung cancer

2019 ◽  
Author(s):  
jinghang li ◽  
Jing Zhang ◽  
Lin Huang ◽  
Sheng Zhao
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Cell Cycle ◽  
Expression Profiles ◽  
Mirna Gene ◽  
Gene Expression Profiles ◽  
Genetic Alterations ◽  
Potential Candidate ◽  
Expression Microarrays ◽  
Regulation Of Cell Cycle

Abstract Lung cancer (LC) is the most frequent type of cancer in the world. But the mechanism of LC is still largely unknown. In this study, we analyzed three lung cancer gene expression microarrays of different pathologic types to explore the potential candidate genes in LC by Integrated bioinformatical methods. 459 overlapped differentially expressed genes (DEGs) were explored in three GEO gene expression profiles of different pathologic types of lung cancer and function annotation of DEGs were performed. The main biological process of DEGs was regulation of vasculature development and angiogenesis. The most significant molecular function of DEGs was TGF-β receptor activity. The most significant Reactome pathway of DEGs was cell cycle and extracellular matrix organization pathway. The PPI network of the DEGs was constructed and 23 candidate hub genes were identified in the network . Kaplan-Meier survival analysis show 21 genes were associated with the prognosis of LC. The genetic alterations analysis of these genes by using cBioPortal shown ASPM has the highest genetic alteration rate of 9% in main pathological types of 3191 LC patients , CENPF has the second highest alteration rate of 6% in LC patients. ASPM and CENPF also identified have a significant co-occurrence relationship in LC, and the GO analysis shown they both participate in the regulation of cell cycle. In the TF -miRNA-gene network of 21 genes shown CENPF have the most significant value in the network and the most relevant TF are NFYA, E2F1 and MYC.In conclusion, this study explored several key genes about LC and analyzed potential TF of those genes, provides possible therapeutic targets and biomarker for further clinical application.

scholarly journals Identification of Hub Genes as Biomarkers Correlated with the Proliferation and Prognosis in Lung Cancer: A Weighted Gene Co-Expression Network Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xuting Xu ◽  
Limin Xu ◽  
Huilian Huang ◽  
Jing Li ◽  
Shunli Dong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Cell Cycle ◽  
Network Analysis ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter ◽  
Advanced Tumors ◽  
Blue Module

Lung cancer is one of the most malignant tumors in the world. Early diagnosis and treatment of lung cancer are vitally important to reduce the mortality of lung cancer patients. In the present study, we attempt to identify the candidate biomarkers for lung cancer by weighted gene co-expression network analysis (WGCNA). Gene expression profile of GSE30219 was downloaded from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) were analyzed by the limma package, and the co-expression modules of genes were built by WGCNA. UALCAN was used to analyze the relative expression of normal group and tumor subgroups based on tumor individual cancer stages. Survival analysis for the hub genes was performed by Kaplan–Meier plotter analysis with the TCGA database. A total of 2176 genes (745 upregulated and 1431 downregulated genes) were obtained from the GSE30219 database. Seven gene co-expression modules were conducted by WGCNA and the blue module might be inferred as the most crucial module in the pathogenesis of lung cancer. In the pathway enrichment analysis of KEGG, the candidate genes were enriched in the “DNA replication,” “Cell cycle,” and “P53 signaling pathway” pathways. Among these, the cell cycle pathway was the most significant pathway in the blue module with four hub genes CCNB1, CCNE2, MCM7, and PCNA which were selected in our study. Kaplan–Meier plotter analysis indicated that the high expressions of four hub genes were correlated with a worse overall survival (OS) and advanced tumors. qRT-PCR showed that mRNA expression levels of MCM7 (p=0.038) and CCNE2 (0.003) were significantly higher in patients with the TNM stage. In summary, the high expression of the MCM7 and CCNE2 were significantly related with advanced tumors and worse OS in lung cancer. Thus, the MCM7 and CCNE2 genes can be good indicators for cellular proliferation and prognosis in lung cancer.

scholarly journals FERMT3 mediates cigarette smoke-induced epithelial–mesenchymal transition through Wnt/β-catenin signaling

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xiaoshan Su ◽  
Junjie Chen ◽  
Xiaoping Lin ◽  
Xiaoyang Chen ◽  
Zhixing Zhu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Cell Cycle ◽  
Cell Migration ◽  
Cigarette Smoke ◽  
Epithelial Mesenchymal Transition ◽  
Control Group ◽  
Data Set ◽  
Mesenchymal Transition

Abstract Background Cigarette smoking is a major risk factor for chronic obstructive pulmonary disease (COPD) and lung cancer. Epithelial–mesenchymal transition (EMT) is an essential pathophysiological process in COPD and plays an important role in airway remodeling, fibrosis, and malignant transformation of COPD. Previous studies have indicated FERMT3 is downregulated and plays a tumor-suppressive role in lung cancer. However, the role of FERMT3 in COPD, including EMT, has not yet been investigated. Methods The present study aimed to explore the potential role of FERMT3 in COPD and its underlying molecular mechanisms. Three GEO datasets were utilized to analyse FERMT3 gene expression profiles in COPD. We then established EMT animal models and cell models through cigarette smoke (CS) or cigarette smoke extract (CSE) exposure to detect the expression of FERMT3 and EMT markers. RT-PCR, western blot, immunohistochemical, cell migration, and cell cycle were employed to investigate the potential regulatory effect of FERMT3 in CSE-induced EMT. Results Based on Gene Expression Omnibus (GEO) data set analysis, FERMT3 expression in bronchoalveolar lavage fluid was lower in COPD smokers than in non-smokers or smokers. Moreover, FERMT3 expression was significantly down-regulated in lung tissues of COPD GOLD 4 patients compared with the control group. Cigarette smoke exposure reduced the FERMT3 expression and induces EMT both in vivo and in vitro. The results showed that overexpression of FERMT3 could inhibit EMT induced by CSE in A549 cells. Furthermore, the CSE-induced cell migration and cell cycle progression were reversed by FERMT3 overexpression. Mechanistically, our study showed that overexpression of FERMT3 inhibited CSE-induced EMT through the Wnt/β-catenin signaling. Conclusions In summary, these data suggest FERMT3 regulates cigarette smoke-induced epithelial–mesenchymal transition through Wnt/β-catenin signaling. These findings indicated that FERMT3 was correlated with the development of COPD and may serve as a potential target for both COPD and lung cancer.

Aberrant Expression Of miRNA and mRNA Of Cell Cycle and Adhesion-Related Genes In Bone Marrow Stroma Cells Derived From Patients With Multiple Myeloma

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3149-3149 ◽  
Author(s):  
Rimma Berenstein ◽  
Blau Igor Wolfgang ◽  
Axel Nogai ◽  
Marlies Wächter ◽  
Antonio Pezzutto ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Multiple Myeloma ◽  
Bone Marrow ◽  
Genetic Alterations ◽  
Bone Marrow Stroma ◽  
Aberrant Expression ◽  
Healthy Donors ◽  
Marrow Stroma ◽  
Bone Marrow Stroma Cells

Abstract Multiple myeloma (MM) is a B-cell malignancy characterized by accumulation of malignant plasma cells (PC) within the bone marrow. The bone marrow microenvironment such as bone marrow stroma cells (BMSC) supports MM disease progression, resistance to chemotherapy, protects the tumor cells against apoptosis and causes osteolytic bone disease and angiogenesis. The aim of this study was to identify constitutive genetic alterations in BMSC derived from patients with MM (MM-BMSC) in comparison to BMSC from healthy donors. For BMSC selection, mononuclear cells were isolated from fresh bone marrow aspirates and were further expanded in cell culture. We studied 25 MM patients and 5 healthy donors. Senescence status was determined in passage 1 of cell cultures. MM-BSMC displayed a considerably higher percentage of senescence cells (p<0,05). We investigated the expression of cell cycle and adhesion-associated genes (CCNE1, CCND1, CDKN1B, VCAM, ICAM, IKK-alpha) in BMSC (passage 4) using SYBR-Green Real-Time PCR and relative quantification by linear regression. A downregulation of CCNE1 (p=0,05), CDKN1B (p=0,29), and an upregulation of CCND1 (p=0,05), VCAM-1 (p=0,33), ICAM-1 (p=0,33), and IKK-alpha (p=0,05) was demonstrated. Furthermore, the expression profile of miRNAs, targeting the analyzed mRNA genes or correlating with senescence, was studied (miR-16, miR-221, miR-126, miR-223, miR-485-5p and miR-519d). For miRNA detection treatment with Poly(A)-Polymerase and cDNA-Synthesis with a Poly(T)VN-Adaptor primer were carried out following an amplification with an universal reverse primer corresponding to the adaptor sequence and a miRNA-specific primer. miR-16, miR-223, miR-485-5p and miR-519d were significantly upregulated, (p=0,02; p=0,004; p=0,02; and p=0,002, respectively), whereas miR-221 and miR-126 showed no considerable differences to BMSC obtained from healthy donors. Next we investigated incubation of immunmodulatory drug Lenalidomid in BMSC cultures. Cells were treated with 10 µM Lenalidomid over 72 hours and expression was normalized to a 0,01 % DMSO control. Significant difference in gene expression were visible for ICAM-1 (p=0,01). For CDKN1B (p=0,16) and VCAM-1 (p=0,12) we demonstrated changes in gene expression. Our results indicate aberrant expression of cell cycle and adhesion-related genes, such as CCNE1, CCND1 and CDKN1B VCAM-1, ICAM-1 and IKK-alpha in MM-BMSC as compared with healthy donors. Furthermore, we found significant upregulation of miR-16, miR-223, miR-485-5p and miR-519d. Further investigation are needed to determine molecular mechanisms in MM-BMSC and PC interaction that lead to constitutive changes in BMSC characteristics and gene expression patterns. Disclosures: No relevant conflicts of interest to declare.

scholarly journals DDA1, a novel oncogene, promotes lung cancer progression through regulation of cell cycle

2017 ◽  
Vol 21 (8) ◽  
pp. 1532-1544 ◽  
Author(s):  
Lin Cheng ◽  
Qianmei Yang ◽  
Can Li ◽  
Lei Dai ◽  
Yang Yang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cell Cycle ◽  
Cancer Progression ◽  
Regulation Of Cell Cycle

scholarly journals PLEK2 and SCN7A: novel biomarkers of non-small cell lung cancer

2020 ◽  
Author(s):  
Yongchang Liu ◽  
Xi Li ◽  
Ruimin Chang ◽  
Yufan Chen ◽  
Yang Gao
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Cell Adhesion ◽  
Small Cell Lung Cancer ◽  
Focal Adhesion ◽  
Cell Lung Cancer ◽  
Gene Expression Omnibus ◽  
Small Cell ◽  
Small Cell Lung ◽  
Kaplan Meier

Abstract Objective Lung cancer is the leading cause of cancer-related death globally, and non-small cell lung cancer (NSCLC) is the most common type of lung cancer. However, the diagnosis and prognosis of NSCLC remain dim. Our team has focused on identifying differentially expressed genes (DEGs) between NSCLC tissues and adjacent tissues, which may be useful as effective diagnostic markers that can better explain the progression of NSCLC. Methods The Gene Expression Omnibus (GEO) database was used to screen the Gene Expression Omnibus series, which records the information of a large number of patients with primary NSCLC (n > 50). Then, the DEGs were validated using Student’s t -test. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using DAVID. The prognosis information was analyzed separately using data obtained from three databases, Human Protein Atlas, Kaplan–Meier Plotter, and SurvExpress. Results A series of 180 DEGs (33 upregulated and 147 downregulated genes), mainly involving genes associated with extracellular exosomes, focal adhesion, and cell adhesion, were identified via GO analysis. Subsequently, KEGG analysis demonstrated that focal adhesion, cell adhesion molecules, and PPAR signaling pathway were the most enriched pathways. Then, we paid particular attention to pleckstrin 2 (PLEK2) and sodium voltage-gated channel alpha subunit 7 (SCN7A), as they have not been investigated as cancer-related genes previously. Kaplan–Meier survival analysis illustrated that PLEK2 and SCN7A levels were significantly correlated with the prognosis of NSCLC. Conclusions Our research found that, as potential biomarkers, both PLEK2 and SCN7A are related to the development and prognosis of NSCLC. They may be used in disease screening and prognosis. The clinical significance of these two genes deserves further investigation.

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