scholarly journals KRT8 and KRT19, associated with EMT, are hypomethylated and overexpressed in lung adenocarcinoma and link to unfavorable prognosis

2020 ◽  
Vol 40 (7) ◽  
Author(s):  
Wenlong Wang ◽  
Junhong He ◽  
Hongda Lu ◽  
Qingzhi Kong ◽  
Shengyou Lin
Keyword(s):  
Lung Adenocarcinoma ◽  
Epithelial To Mesenchymal Transition ◽  
Methylation Status ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Cxcl12 Expression ◽  
Mesenchymal Transition ◽  
Gene Set ◽  
Protein Protein Interaction ◽  
Ppi Networks

Abstract Background: Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer. To date, the prognosis of patients with LUAD remains dismal. Methods: Three datasets were downloaded from the GEO database. Differentially expressed genes (DEGs) were obtained. FunRich was used to perform pathway enrichment analysis. Protein–protein interaction (PPI) networks were established and hub genes were obtained by Cytoscape software. GEPIA was utilized to conduct correlation and survival analysis. Upstream miRNAs of DEGs were predicted via miRNet database, and methylation status of promoters of DEGs was determined through UALCAN database. Results: A total of 375 DEGs, including 105 and 270 up-regulated and down-regulated genes in LUAD, were commonly appeared in three datasets. These DEGs were significantly enriched in mesenchymal-to-epithelial transition (MET) and epithelial-to-mesenchymal transition (EMT). About 8 up-regulated and 5 down-regulated DEGs were commonly appeared in EMT/MET-related gene set and the top 50 hub gene set. Among the 13 genes, increased expression of KRT8 and KRT19 indicated unfavorable prognosis whereas high expression of DCN and CXCL12 suggested favorable prognosis in LUAD. Correlation analysis showed that KRT8 (DCN) expression was linked to KRT19 (CXCL12) expression. Further analysis displayed that KRT8 and KRT19 could jointly forecast poor prognosis in LUAD. About 42 and 2 potential miRNAs were predicted to target KRT8 and KRT19, respectively. Moreover, methylation level analysis demonstrated that KRT8 and KRT19 were significantly hypomethylated in LUAD compared with normal controls. Conclusions: All these findings suggest that KRT8 and KRT19 are hypomethylated and overexpressed in LUAD and associated with unfavorable prognosis.

scholarly journals IKBIP is a novel EMT-related biomarker and predicts poor survival in glioma

2021 ◽  
Vol 12 (1) ◽  
pp. 009-019
Author(s):  
Ying Yang ◽  
Jin Wang ◽  
Shihai Xu ◽  
Wen Lv ◽  
Fei Shi ◽  
...  
Keyword(s):  
Epithelial To Mesenchymal Transition ◽  
Molecular Subtype ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Transcriptional Level ◽  
Who Grade ◽  
Interacting Protein ◽  
Mesenchymal Transition ◽  
Gene Set ◽  
Substrate Adhesion

Abstract Background In cancer, kappa B-interacting protein (IKBIP) has rarely been reported. This study aimed at investigating its expression pattern and biological function in brain glioma at the transcriptional level. Methods We selected 301 glioma patients with microarray data from CGGA database and 697 glioma patients with RNAseq data from TCGA database. Transcriptional data and clinical data of 998 samples were analyzed. Statistical analysis and figure generating were performed with R language. Results We found that IKBIP expression showed positive correlation with WHO grade of glioma. IKBIP was increased in isocitrate dehydrogenase (IDH) wild type and mesenchymal molecular subtype of glioma. Gene ontology analysis demonstrated that IKBIP was profoundly associated with extracellular matrix organization, cell–substrate adhesion and response to wounding in both pan-glioma and glioblastoma. Subsequent gene set enrichment analysis revealed that IKBIP was particularly correlated with epithelial-to-mesenchymal transition (EMT). To further elucidate the relationship between IKBIP and EMT, we performed gene set variation analysis to screen the EMT-related signaling pathways and found that IKBIP expression was significantly associated with PI3K/AKT, hypoxia and TGF-β pathway. Moreover, IKBIP expression was found to be synergistic with key biomarkers of EMT, especially with N-cadherin, vimentin, snail, slug and TWIST1. Finally, higher IKBIP indicated significantly shorter survival for glioma patients. Conclusions IKBIP was associated with more aggressive phenotypes of gliomas. Furthermore, IKBIP was significantly involved in EMT and could serve as an independent prognosticator in glioma.

scholarly journals Identification of Key Genes and miRNAs in Osteosarcoma Patients with Chemoresistance by Bioinformatics Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Binbin Xie ◽  
Yiran Li ◽  
Rongjie Zhao ◽  
Yuzi Xu ◽  
Yuhui Wu ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Regulation Of Transcription ◽  
Functional Annotations ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Search Tool ◽  
Poor Outcomes

Chemoresistance is a significant factor associated with poor outcomes of osteosarcoma patients. The present study aims to identify Chemoresistance-regulated gene signatures and microRNAs (miRNAs) in Gene Expression Omnibus (GEO) database. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) included positive regulation of transcription, DNA-templated, tryptophan metabolism, and the like. Then differentially expressed genes (DEGs) were uploaded to Search Tool for the Retrieval of Interacting Genes (STRING) to construct protein-protein interaction (PPI) networks, and 9 hub genes were screened, such as fucosyltransferase 3 (Lewis blood group) (FUT3) whose expression in chemoresistant samples was high, but with a better prognosis in osteosarcoma patients. Furthermore, the connection between DEGs and differentially expressed miRNAs (DEMs) was explored. GEO2R was utilized to screen out DEGs and DEMs. A total of 668 DEGs and 5 DEMs were extracted from GSE7437 and GSE30934 differentiating samples of poor and good chemotherapy reaction patients. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used to perform GO and KEGG pathway enrichment analysis to identify potential pathways and functional annotations linked with osteosarcoma chemoresistance. The present study may provide a deeper understanding about regulatory genes of osteosarcoma chemoresistance and identify potential therapeutic targets for osteosarcoma.

scholarly journals PPARG Drives Molecular Networks as an Inhibitor for the Pathologic Development and Progression of Lung Adenocarcinoma

PPAR Research ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Min Zhao ◽  
Xiaoyang Li ◽  
Yunxiang Zhang ◽  
Hongming Zhu ◽  
Zhaoqing Han ◽  
...  
Keyword(s):  
Tumor Cell ◽  
Lung Adenocarcinoma ◽  
Large Scale ◽  
Enrichment Analysis ◽  
Molecular Networks ◽  
Pathway Enrichment Analysis ◽  
Molecular Pathways ◽  
Functional Connection ◽  
Regulatory Pathways ◽  
Protein Protein Interaction

Previous studies showed that low PPARG expression was associated with poor prognosis of lung adenocarcinoma (LA) with limited mechanisms identified. We first conducted a large-scale literature-based data mining to identify potential molecular pathways where PPARG could exert influence on the pathological development of LA. Then a mega-analysis using 13 independent LA expression datasets and a Pathway Enrichment Analysis (PEA) was conducted to study the gene expression levels and the functionalities of PPARG and the PPARG-driven triggers within the molecular pathways. Finally, a protein-protein interaction (PPI) network was established to reveal the functional connection between PPARG and its driven molecules. We identified 25 PPARG-driven molecule triggers forming multiple LA-regulatory pathways. Mega-analysis using 13 LA datasets supported these pathways and confirmed the downregulation of PPARG in the case of LA (p=1.07e−05). Results from the PEA and PPI analysis suggested that PPARG might inhibit the development of LA through the regulation of tumor cell proliferation and transmission-related molecules, including an LA tumor cell suppressor MIR145. Our results suggested that increased expression of PPARG could drive multiple molecular triggers against the pathologic development and prognosis of LA, indicating PPARG as a valuable therapeutic target for LA treatment.

scholarly journals Temporal Identification of Dysregulated Genes and Pathways in Clear Cell Renal Cell Carcinoma Based on Systematic Tracking of Disrupted Modules

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Shao-Mei Wang ◽  
Ze-Qiang Sun ◽  
Hong-Yun Li ◽  
Jin Wang ◽  
Qing-Yong Liu
Keyword(s):  
Pearson Correlation ◽  
Enrichment Analysis ◽  
Glutathione Metabolism ◽  
Pathway Enrichment Analysis ◽  
Cell Renal Cell Carcinoma ◽  
Bipartite Matching ◽  
Pathway Enrichment ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Metabolism Of Xenobiotics

Objective. The objective of this work is to identify dysregulated genes and pathways of ccRCC temporally according to systematic tracking of the dysregulated modules of reweighted Protein-Protein Interaction (PPI) networks.Methods. Firstly, normal and ccRCC PPI network were inferred and reweighted based on Pearson correlation coefficient (PCC). Then, we identified altered modules using maximum weight bipartite matching and ranked them in nonincreasing order. Finally, gene compositions of altered modules were analyzed, and pathways enrichment analyses of genes in altered modules were carried out based on Expression Analysis Systematic Explored (EASE) test.Results. We obtained 136, 576, 693, and 531 disrupted modules of ccRCC stages I, II, III, and IV, respectively. Gene composition analyses of altered modules revealed that there were 56 common genes (such asMAPK1,CCNA2, andGSTM3) existing in the four stages. Besides pathway enrichment analysis identified 5 common pathways (glutathione metabolism, cell cycle, alanine, aspartate, and glutamate metabolism, arginine and proline metabolism, and metabolism of xenobiotics by cytochrome P450) across stages I, II, III, and IV.Conclusions. We successfully identified dysregulated genes and pathways of ccRCC in different stages, and these might be potential biological markers and processes for treatment and etiology mechanism in ccRCC.

scholarly journals Caveolin-1, a Key Mediator Across Multiple Pathways in Glioblastoma and an Independent Negative Biomarker of Patient Survival

2021 ◽  
Vol 11 ◽  
Author(s):  
Chiara Moriconi ◽  
Prospero Civita ◽  
Catia Neto ◽  
Geoffrey J. Pilkington ◽  
Mark Gumbleton
Keyword(s):  
Drug Targets ◽  
Poor Prognosis ◽  
Epithelial To Mesenchymal Transition ◽  
Enrichment Analysis ◽  
Migration And Invasion ◽  
Pathway Enrichment Analysis ◽  
Significant Independent Predictor ◽  
Genomic Databases ◽  
Mesenchymal Transition ◽  
Caveolin 1

Glioblastoma (GB) remains an aggressive malignancy with an extremely poor prognosis. Discovering new candidate drug targets for GB remains an unmet medical need. Caveolin-1 (Cav-1) has been shown to act variously as both a tumour suppressor and tumour promoter in many cancers. The implications of Cav-1 expression in GB remains poorly understood. Using clinical and genomic databases we examined the relationship between tumour Cav-1 gene expression (including its spatial distribution) and clinical pathological parameters of the GB tumour and survival probability in a TCGA cohort (n=155) and CGGA cohort (n=220) of GB patients. High expression of Cav-1 represented a significant independent predictor of shortened survival (HR = 2.985, 5.1 vs 14.9 months) with a greater statistically significant impact in female patients and in the Proneural and Mesenchymal GB subtypes. High Cav-1 expression correlated with other factors associated with poor prognosis: IDH w/t status, high histological tumour grade and low KPS score. A total of 4879 differentially expressed genes (DEGs) in the GB tumour were found to correlate with Cav-1 expression (either positively or negatively). Pathway enrichment analysis highlighted an over-representation of these DEGs to certain biological pathways. Focusing on those that lie within a framework of epithelial to mesenchymal transition and tumour cell migration and invasion we identified 27 of these DEGs. We then examined the prognostic value of Cav-1 when used in combination with any of these 27 genes and identified a subset of combinations (with Cav-1) indicative of co-operative synergistic mechanisms of action. Overall, the work has confirmed Cav-1 can serve as an independent prognostic marker in GB, but also augment prognosis when used in combination with a panel of biomarkers or clinicopathologic parameters. Moreover, Cav-1 appears to be linked to many signalling entities within the GB tumour and as such this work begins to substantiate Cav-1 or its associated signalling partners as candidate target for GB new drug discovery.

scholarly journals Screening and identification of MSX1 for predicting progestin resistance in endometrial cancer

2020 ◽  
Author(s):  
linlin yang ◽  
Yunxia Cui ◽  
Ting Huang ◽  
Xiao Sun ◽  
Yudong Wang
Keyword(s):  
Overall Survival ◽  
Endometrial Cancer ◽  
Methylation Status ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Genomic Alteration ◽  
Hub Genes ◽  
Gene Set ◽  
Protein Protein Interaction ◽  
Screening And Identification

Abstract Background Progestin resistance is a critical obstacle for endometrial conservative therapy. Therefore, the studies to acquire a more comprehensive understanding of the mechanisms are very important. However, the pivotal roles of essential molecules are still unexplored.Methods We downloaded GSE121367 from the GEO database. The “limma” R language package was applied to identify differentially expressed genes (DEGs). We conducted Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) analysis. Protein–protein interaction was constructed by STRING and visualized in Cytoscape. The tumor immune microenvironment was explored by TISIDB database. Methylation validation and overall survival analysis was conducted by TCGA database. In addition, the upstream modulators of hub genes were predicted by miRTarBase and Network Analyst database.Results A total of 3282 DEGs were identified and they were mostly enriched in cell adhesion pathway. We screened out ten hub genes including CDH1, JAG1, PTGES, EPCAM, CNTNAP2, TBX1, MSX1, KRT19, OAS1 and DAB2 among different groups, whose genomic alteration rates were low based on the current endometrial carcinoma sample sets. Has-miR-335-5p, has-miR-124-3p, MAZ and TFDP1 were the most prominent upstream regulators. The methylation status of CDH1, JAG1, EPCAM and MSX1 were decreased, corresponding to their high protein expression, which also predicted better overall survival. The homeobox protein of MSX1 showed significantly tissue specificity and better prognostic value.Conclusions Our study identified the gene of MSX1 promised to be the specific indicator. This would shed new light on the underlying biological mechanism to overcome progestin resistance of endometrial cancer.

scholarly journals Analysis of differential gene expression between right-sided and left-sided colon cancer by bioinformatics analysis

2020 ◽  
Author(s):  
Qiangwei Chi ◽  
Shizuan Chen ◽  
Shaotang Li
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Bioinformatics Analysis ◽  
Disease Free Survival ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Ppi Networks

Abstract Background Colon cancer is a common tumor of the digestive tract worldwide. Recent researches have revealed that colon cancer exhibits distinct differences in clinical and biological characteristics depending on the location of the tumor. However, the underlying genetic and molecular mechanism of the differences between right-sided colon cancer (RCC) and left-sided colon cancer (LCC) are not fully understood. This study aimed to identify molecular potential biomarkers and therapeutic targets for precise treatment of right-sided and left-sided colon cancer using bioinformatics analysis. Methods The gene microarray profile, named GSE44076, from the Gene Expression Omnibus (GEO) public database was downloaded and processed to then select differentially expressed genes (DEGs) on the base of two sample groups of RCC and LCC. Also, gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein–protein interaction (PPI) network construction, module analysis, validation of hub genes, and survival analysis. Results Finally, we obtained 2259 DEGs between RCC and LCC, 1300 of which were upregulated in RCC and 945 of which were upregulated in LCC. The results of GO and KEGG analysis of the DEGs indicated that the biological functions of DEGs in RCC and LCC were significantly different. CTLA4, IL10, IL2RB, IFNG, NCAM1, EGFR, MYC, SRC, CUL3, and NCBP2 were identified from the PPI networks as the hub genes of RCC and LCC. Among the hub genes, the log-rank tests for overall survival (OS) and disease free survival (DFS) were applied. Moreover, all hub genes, except CUL3, had differential expression levels of miRNA between tumor group and normal group. Conclusion These hub genes and pathways identified based on bioinformatics analysis might conduce to explain the differences between RCC and LCC, and most of the hub genes were specific to the malignant tissues. Notably, these hub genes, especially the genes associated with immunotherapy such as CTLA4, might be potential specific targets or prognostic markers for precise treatment of colon cancer.

KCNN4 promotes the progression of lung adenocarcinoma by activating the AKT and ERK signaling pathways

2021 ◽  
pp. 1-15
Author(s):  
Ping Xu ◽  
Xiao Mo ◽  
Ruixue Xia ◽  
Long Jiang ◽  
Chengfei Zhang ◽  
...  
Keyword(s):  
Potassium Channels ◽  
Lung Adenocarcinoma ◽  
Potassium Channel ◽  
Signaling Pathways ◽  
Epithelial To Mesenchymal Transition ◽  
Tumor Biology ◽  
Erk Signaling ◽  
Mesenchymal Transition

BACKGROUND: Potassium channels, encoded by more than seventy genes, are cell excitability transmembrane proteins and become evident to play essential roles in tumor biology. OBJECTIVE: The deregulation of potassium channel genes has been related to cancer development and patient prognosis. The objective of this study is to understand the role of potassium channels in lung cancer. METHODS: We examined all potassium channel genes and identified that KCNN4 is the most significantly overexpressed one in lung adenocarcinoma. The role and mechanism of KCNN4 in lung adenocarcinoma were further investigated by in vitro cell and molecular assay and in vivo mouse xenograft models. RESULTS: We revealed that the silencing of KCNN4 significantly inhibits cell proliferation, migration, invasion, and tumorigenicity of lung adenocarcinoma. Further studies showed that knockdown of KCNN4 promotes cell apoptosis, induces cell cycle arrested in the S phase, and is associated with the epithelial to mesenchymal transition (EMT) process. Most importantly, we demonstrated that KCNN4 regulates the progression of lung adenocarcinoma through P13K/AKT and MEK/ERK signaling pathways. The use of inhibitors that targeted AKT and ERK also significantly inhibit the proliferation and metastasis of lung adenocarcinoma cells. CONCLUSIONS: This study investigated the function and mechanism of KCNN4 in lung adenocarcinoma. On this basis, this means that KCNN4 can be used as a tumor marker for lung adenocarcinoma and is expected to become an important target for a potential drug.

scholarly journals Decoding the molecular mechanism of parthenocarpy in Musa spp. through protein–protein interaction network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Suthanthiram Backiyarani ◽  
Rajendran Sasikala ◽  
Simeon Sharmiladevi ◽  
Subbaraya Uma
Keyword(s):  
Candidate Genes ◽  
Protein Interaction ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Auxin Signaling ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
The Difference

AbstractBanana, one of the most important staple fruit among global consumers is highly sterile owing to natural parthenocarpy. Identification of genetic factors responsible for parthenocarpy would facilitate the conventional breeders to improve the seeded accessions. We have constructed Protein–protein interaction (PPI) network through mining differentially expressed genes and the genes used for transgenic studies with respect to parthenocarpy. Based on the topological and pathway enrichment analysis of proteins in PPI network, 12 candidate genes were shortlisted. By further validating these candidate genes in seeded and seedless accession of Musa spp. we put forward MaAGL8, MaMADS16, MaGH3.8, MaMADS29, MaRGA1, MaEXPA1, MaGID1C, MaHK2 and MaBAM1 as possible target genes in the study of natural parthenocarpy. In contrary, expression profile of MaACLB-2 and MaZEP is anticipated to highlight the difference in artificially induced and natural parthenocarpy. By exploring the PPI of validated genes from the network, we postulated a putative pathway that bring insights into the significance of cytokinin mediated CLAVATA(CLV)–WUSHEL(WUS) signaling pathway in addition to gibberellin mediated auxin signaling in parthenocarpy. Our analysis is the first attempt to identify candidate genes and to hypothesize a putative mechanism that bridges the gaps in understanding natural parthenocarpy through PPI network.

scholarly journals Epigenetics of Most Aggressive Solid Tumors: Pathways, Targets and Treatments

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3209
Author(s):  
Javier Martinez-Useros ◽  
Mario Martin-Galan ◽  
Maria Florez-Cespedes ◽  
Jesus Garcia-Foncillas
Keyword(s):  
Epithelial To Mesenchymal Transition ◽  
Smoking Habit ◽  
Methylation Status ◽  
Advanced Ovarian Cancer ◽  
Epigenetic Modifications ◽  
Ductal Adenocarcinoma ◽  
Epigenetic Therapy ◽  
Mesenchymal Transition ◽  
Aggressive Tumors ◽  
Influence Gene Expression

Highly aggressive tumors are characterized by a highly invasive phenotype, and they display chemoresistance. Furthermore, some of the tumors lack expression of biomarkers for target therapies. This is the case of small-cell lung cancer, triple-negative breast cancer, pancreatic ductal adenocarcinoma, glioblastoma, metastatic melanoma, and advanced ovarian cancer. Unfortunately, these patients show a low survival rate and most of the available drugs are ineffective. In this context, epigenetic modifications have emerged to provide the causes and potential treatments for such types of tumors. Methylation and hydroxymethylation of DNA, and histone modifications, are the most common targets of epigenetic therapy, to influence gene expression without altering the DNA sequence. These modifications could impact both oncogenes and tumor suppressor factors, which influence several molecular pathways such as epithelial-to-mesenchymal transition, WNT/β–catenin, PI3K–mTOR, MAPK, or mismatch repair machinery. However, epigenetic changes are inducible and reversible events that could be influenced by some environmental conditions, such as UV exposure, smoking habit, or diet. Changes in DNA methylation status and/or histone modification, such as acetylation, methylation or phosphorylation, among others, are the most important targets for epigenetic cancer therapy. Therefore, the present review aims to compile the basic information of epigenetic modifications, pathways and factors, and provide a rationale for the research and treatment of highly aggressive tumors with epigenetic drugs.

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