scholarly journals Integrated transcriptome meta-analysis of pancreatic ductal adenocarcinoma and matched adjacent pancreatic tissues

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10141
Author(s):  
Sevcan Atay
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Interaction Analysis ◽  
Meta Analysis ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Prognostic Biomarkers ◽  
Ductal Adenocarcinoma ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Adjacent Tissue

A comprehensive meta-analysis of publicly available gene expression microarray data obtained from human-derived pancreatic ductal adenocarcinoma (PDAC) tissues and their histologically matched adjacent tissue samples was performed to provide diagnostic and prognostic biomarkers, and molecular targets for PDAC. An integrative meta-analysis of four submissions (GSE62452, GSE15471, GSE62165, and GSE56560) containing 105 eligible tumor-adjacent tissue pairs revealed 344 differentially over-expressed and 168 repressed genes in PDAC compared to the adjacent-to-tumor samples. The validation analysis using TCGA combined GTEx data confirmed 98.24% of the identified up-regulated and 73.88% of the down-regulated protein-coding genes in PDAC. Pathway enrichment analysis showed that “ECM-receptor interaction”, “PI3K-Akt signaling pathway”, and “focal adhesion” are the most enriched KEGG pathways in PDAC. Protein-protein interaction analysis identified FN1, TIMP1, and MSLN as the most highly ranked hub genes among the DEGs. Transcription factor enrichment analysis revealed that TCF7, CTNNB1, SMAD3, and JUN are significantly activated in PDAC, while SMAD7 is inhibited. The prognostic significance of the identified and validated differentially expressed genes in PDAC was evaluated via survival analysis of TCGA Pan-Cancer pancreatic ductal adenocarcinoma data. The identified candidate prognostic biomarkers were then validated in four external validation datasets (GSE21501, GSE50827, GSE57495, and GSE71729) to further improve reliability. A total of 28 up-regulated genes were found to be significantly correlated with worse overall survival in patients with PDAC. Twenty-one of the identified prognostic genes (ITGB6, LAMC2, KRT7, SERPINB5, IGF2BP3, IL1RN, MPZL2, SFTA2, MET, LAMA3, ARNTL2, SLC2A1, LAMB3, COL17A1, EPSTI1, IL1RAP, AK4, ANXA2, S100A16, KRT19, and GPRC5A) were also found to be significantly correlated with the pathological stages of the disease. The results of this study provided promising prognostic biomarkers that have the potential to differentiate PDAC from both healthy and adjacent-to-tumor pancreatic tissues. Several novel dysregulated genes merit further study as potentially promising candidates for the development of more effective treatment strategies for PDAC.

scholarly journals Plasma Metabolome Profiling Identifies Metabolic Subtypes of Pancreatic Ductal Adenocarcinoma

Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1821
Author(s):  
Ujjwal Mukund Mahajan ◽  
Ahmed Alnatsha ◽  
Qi Li ◽  
Bettina Oehrle ◽  
Frank-Ulrich Weiss ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Enrichment Analysis ◽  
Response Prediction ◽  
Ductal Adenocarcinoma ◽  
Pathway Enrichment Analysis ◽  
Metabolome Analysis ◽  
Dismal Prognosis ◽  
Chemotherapeutic Response ◽  
Plasma Metabolome ◽  
Metabolome Profiling

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Developing biomarkers for early detection and chemotherapeutic response prediction is crucial to improve the dismal prognosis of PDAC patients. However, molecular cancer signatures based on transcriptome analysis do not reflect intratumoral heterogeneity. To explore a more accurate stratification of PDAC phenotypes in an easily accessible matrix, plasma metabolome analysis using MxP® Global Profiling and MxP® Lipidomics was performed in 361 PDAC patients. We identified three metabolic PDAC subtypes associated with distinct complex lipid patterns. Subtype 1 was associated with reduced ceramide levels and a strong enrichment of triacylglycerols. Subtype 2 demonstrated increased abundance of ceramides, sphingomyelin and other complex sphingolipids, whereas subtype 3 showed decreased levels of sphingolipid metabolites in plasma. Pathway enrichment analysis revealed that sphingolipid-related pathways differ most among subtypes. Weighted correlation network analysis (WGCNA) implied PDAC subtypes differed in their metabolic programs. Interestingly, a reduced expression among related pathway genes in tumor tissue was associated with the lowest survival rate. However, our metabolic PDAC subtypes did not show any correlation to the described molecular PDAC subtypes. Our findings pave the way for further studies investigating sphingolipids metabolisms in PDAC.

scholarly journals Is There a Relationship Between Psoriasis and Hepatitis C?: a Meta-analysis and Bioinformatics Investigation

2021 ◽  
Author(s):  
Yong Liu ◽  
Sheng Nan Cui ◽  
Meng Yao Duan ◽  
Zhi Li Dou ◽  
Yi Zhen Li ◽  
...  
Keyword(s):  
Hepatitis C ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Case Control ◽  
Cochrane Library ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Overlapping Genes ◽  
Cross Sectional ◽  
Pathway Enrichment

Abstract Background: The relationship between psoriasis and hepatitis C was previously controversial, so our purpose is to investigate this connection.Methods: We conducted a systematic review of the case-control, cross-sectional and cohort studies examining the association between psoriasis and hepatitis C in PubMed, EMBASE and Cochrane library databases and investigated the overlapping genes between psoriasis targets and hepatitis C targets using bioinformatics analysis. Based on overlapping genes and hub nodes, we also constructed the protein-protein interaction (PPI) network and module respectively, followed by the pathway enrichment analysis. Results: We included 11 publications that reported a total of 11 studies (8 cross-sectional and 3 case-control). The case–control and cross-sectional studies included 25,047 psoriasis patients and 4,091,631 controls in total. Psoriasis was associated with a significant increase of prevalent hepatitis C (OR 1.72; 95% confidence interval [CI] (1.17-2.52)). A total of 389 significant genes were common to both hepatitis C and psoriasis, which mainly involved IL6, TNF, IL10, ALB, STAT3 and CXCL8. The module and pathway enrichment analyses showed that the common genes had the potential to influence varieties of biological pathways, including the inflammatory response, cytokine activity, cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, which play an important role in the pathogenesis of hepatitis C and psoriasis.Conclusion: Patients with psoriasis display increased prevalence of hepatitis C and the basic related mechanisms between hepatitis C and psoriasis had been preliminarily clarified.

scholarly journals MicroRNA expression profiling in myopia: a meta-analysis and systematic review

2021 ◽  
Author(s):  
Nan Hong ◽  
Bo Jiang ◽  
Lei Gu ◽  
Si-Yi Chen ◽  
Jian-Ping Tong
Keyword(s):  
Expression Profiling ◽  
Protein Modification ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Ocular Tissue ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Vote Counting

Background: Myopia (nearsightedness) is currently the most common human eye disorder worldwide. In the recent years, several studies have addressed the role of microRNAs (miRNAs) in the pathogenesis of myopia. Objectives: The aim of this study was to perform a meta-analysis on the miRNA expression profiling studies in myopia to identify commonly dysregulated miRNAs in myopic tissues. Method: Seven independent studies were included in the meta-analysis. A vote-counting strategy were employed as the meta-analysis method. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Ontology (GO) functional enrichment analysis were performed to identify the pathways most strongly affected by the dysregulated mouse miRNAs. Results: According to the vote-counting method, eighteen miRNAs were reported in at least two studies with the consistent direction, of which 13 miRNAs were commonly up-regulated in myopic samples compared with control samples and five miRNAs were commonly down-regulated. Subgroup analyses divided and compared the differentially expressed miRNAs according to species (human and animal) and ocular tissue types. The KEGG analysis showed that the dysregulated mouse miRNAs were most enriched in extracellular matrix (ECM)-receptor interaction signal pathway. The most enriched GO processes regulated by the dysregulated mouse miRNAs was cellular protein modification process. Conclusions. Our meta-analysis recommends several miRNAs may provide some clues of the potential biomarkers in myopia. Further mechanistic studies are warranted to elucidate the biological role of the dysregulated miRNAs in the development of myopia.

scholarly journals Identification of FEZ2 as a potential oncogene in pancreatic ductal adenocarcinoma

PeerJ ◽  
2022 ◽  
Vol 9 ◽  
pp. e12736
Author(s):  
Chaozhi Yang ◽  
Xuebing Wang ◽  
Chenjie Qiu ◽  
Ziruo Zheng ◽  
Kai Lin ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Progression ◽  
Poor Prognosis ◽  
Malignant Tumors ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Ductal Adenocarcinoma ◽  
Pathway Enrichment Analysis ◽  
Conserved Gene

Pancreatic ductal adenocarcinoma (PDAC) is one of the common malignant tumors with high lethal rate and poor prognosis. Dysregulation of many genes have been reported to be involved in the occurrence and development of PDAC. However, as a highly conserved gene in eukaryotes, the role of Fasciculation and Elongation protein Zeta 2 (FEZ2) in pancreatic cancer progression is not clear. In this study, we identified the oncogenic effect of FEZ2 on PDAC. By mining of The Cancer Genome Atlas (TCGA) database, we found that FEZ2 was upregulated in PDAC tissues and FEZ2 expression was negatively regulated by its methylation. Moreover, high expression and low methylation of FEZ2 correlated with poor prognosis in PDAC patients. Besides, we found that FEZ2 could promote PDAC cells proliferation, migration and 5-FU resistance in vitro. Furthermore, Gene pathway enrichment analysis demonstrated a positive correlation between Wnt signaling activation and FEZ2 expression in PDAC patients. Western blot showed that FEZ2 knockdown significantly suppressed β-catenin expression. Collectively, our finding revealed that FEZ2 functioned as a potential oncogene on PDAC progression and migration, and the expression of FEZ2 had guidance value for the treatment and chemotherapy program of PDAC patients.

scholarly journals Identifying MMP14 and COL12A1 as a potential combination of prognostic biomarkers in pancreatic ductal adenocarcinoma using integrated bioinformatics analysis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10419
Author(s):  
Jingyi Ding ◽  
Yanxi Liu ◽  
Yu Lai
Keyword(s):  
Gene Expression ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Prognostic Biomarkers ◽  
Ductal Adenocarcinoma ◽  
Receptor Interaction ◽  
Analysis Tool ◽  
Ppi Network ◽  
Hub Genes

Background Pancreatic ductal adenocarcinoma (PDAC) is a fatal malignant neoplasm. It is necessary to improve the understanding of the underlying molecular mechanisms and identify the key genes and signaling pathways involved in PDAC. Methods The microarray datasets GSE28735, GSE62165, and GSE91035 were downloaded from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified by integrated bioinformatics analysis, including protein–protein interaction (PPI) network, Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The PPI network was established using the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. GO functional annotation and KEGG pathway analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery. Hub genes were validated via the Gene Expression Profiling Interactive Analysis tool (GEPIA) and the Human Protein Atlas (HPA) website. Results A total of 263 DEGs (167 upregulated and 96 downregulated) were common to the three datasets. We used STRING and Cytoscape software to establish the PPI network and then identified key modules. From the PPI network, 225 nodes and 803 edges were selected. The most significant module, which comprised 11 DEGs, was identified using the Molecular Complex Detection plugin. The top 20 hub genes, which were filtered by the CytoHubba plugin, comprised FN1, COL1A1, COL3A1, BGN, POSTN, FBN1, COL5A2, COL12A1, THBS2, COL6A3, VCAN, CDH11, MMP14, LTBP1, IGFBP5, ALB, CXCL12, FAP, MATN3, and COL8A1. These genes were validated using The Cancer Genome Atlas (TCGA) and Genotype–Tissue Expression (GTEx) databases, and the encoded proteins were subsequently validated using the HPA website. The GO analysis results showed that the most significantly enriched biological process, cellular component, and molecular function terms among the 20 hub genes were cell adhesion, proteinaceous extracellular matrix, and calcium ion binding, respectively. The KEGG pathway analysis showed that the 20 hub genes were mainly enriched in ECM–receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and protein digestion and absorption. These findings indicated that FBN1 and COL8A1 appear to be involved in the progression of PDAC. Moreover, patient survival analysis performed via the GEPIA using TCGA and GTEx databases demonstrated that the expression levels of COL12A1 and MMP14 were correlated with a poor prognosis in PDAC patients (p < 0.05). Conclusions The results demonstrated that upregulation of MMP14 and COL12A1 is associated with poor overall survival, and these might be a combination of prognostic biomarkers in PDAC.

scholarly journals Bioinformatics Analysis of the Regulatory lncRNA-miRNA-mRNA Network in Patients with Neuropathic Pain

2020 ◽  
Author(s):  
Huai-Gen Zhang ◽  
Li Liu ◽  
Zhi-Ping Song ◽  
Da-Ying Zhang
Keyword(s):  
Neuropathic Pain ◽  
Signaling Pathway ◽  
Interaction Analysis ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Biological Information ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interaction ◽  
Potential Therapeutic Application

Abstract Background: Neuropathic pain (NP) is the main form of chronic pain, caused by damage to the nervous system and dysfunction. Methods: Here, we explore the key molecules involved in the development of NP condition via identification of lncRNA-miRNA-mRNA expression pattern of patients with NP. We identified differentially expressed miRNAs, lncRNA and mRNA through a comprehensive analysis strategy. Subsequently, we used bioinformatics approach to perform pathway enrichment analysis on DEGs and protein-protein interaction analysis. Combined with the three datasets, the lncRNA-miRNA-mRNA network was constructed. It will then be used as targets for drug prediction. Results: The results showed that a total of 8,251 DEGs (4,193 upregulated and 4,058 downregulated) were identified from the three microarray datasets, 959 DEmiRs (455 upregulated and 504 downregulated), 2,848 DElncs (1,324 upregulated and 1,524 downregulated). GO analysis showed that DEGs are mainly enriched in blood circulation, regulation of membrane potential and regulation of ion transmembrane transport. KEGG results showed that DEGs are enriched in neuroactive ligand-receptor interaction, PI3K-Akt signaling pathway and MAPK signaling pathway. When the correlation is set to above 0.8, a total of 31 lncRNAs, 36 miRNAs and 24 mRNAs were screened in the lncRNA-miRNA-mRNAs network. The results of drug prediction indicated the targeted drugs mainly include INDOMETHACIN, GLUTAMIC ACID and PIRACETAM. Conclusion: The lncRNA-miRNA-mRNA network has been carried out a comprehensive biological information analysis and predicted the potential therapeutic application of drugs in patients with NP. The corresponding data has a certain reference for studying the pathological mechanism of NP.

A meta-analysis of microRNAs with prognostic significance in pancreatic ductal adenocarcinoma

Pancreatology ◽  
2014 ◽  
Vol 14 (3) ◽  
pp. S84
Author(s):  
Adam E. Frampton ◽  
Jonathan Krell ◽  
Nigel B. Jamieson ◽  
Tamara M.H. Gall ◽  
Leandro Castellano ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Meta Analysis ◽  
Prognostic Significance ◽  
Ductal Adenocarcinoma
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