The study of the significance and prognosis of the differential expressed miRNAs and their target genes associated with biological in colorectal cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15088-e15088
Author(s):  
Mingyun Wang ◽  
Mi Yang
Keyword(s):  
Colorectal Cancer ◽  
Target Genes ◽  
Biological Significance ◽  
Differentially Expressed ◽  
Prognostic Indicators ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Prognostic Information ◽  
Chemokine Signaling ◽  
Chemokine Signaling Pathway

e15088 Background: MicroRNAs (miRNAs) have been related to prognostic indicators (such as stage and survival) in colorectal cancer. This study aimed to identify differentially expressed miRNAs and their target genes associated with biological significance and prognosis in colorectal cancer. Methods: The colorectal cancer, colorectal adenoma, and normal samples were obtained from the gene expression profile of GSE71187. A union of differentially expressed genes (DEGs) in the three groups was identified. The significantly different modules with highly interconnected DEGs were identified using weighted correlation network analysis (WGCNA) and were enriched to the KEGG pathway and GO function. Subsequently, the protein-protein interaction (PPI) network for DEGs in the module and the integrated regulatory network of miRNA-DEGs were constructed. In addition, the relationship of target DEGs and prognostic information was analyzed. Results: Three significantly different modules were identified, such as the brown, turquoise, and grey modules. The turquoise module including LTC4S, KLRK1, UNC5C, etc., which was mainly enriched to cell adhesion, cytokine−cytokine receptor interaction, and chemokine signaling pathway, inhibited the development of colorectal cancer. Subsequently, PPI network was constructed with the 678 DEGs in the three modules. Moreover, the miRNA-DEGs network was constructed with the 17 target DEGs (CXCR1, LTC4S, BTK, IGF1, etc.) and 14 miRNA (hsa-miR-335-5p, etc.). Finally, the overexpressed LTC4S was a good prognostic biomarker for colorectal cancer. Conclusions: The hsa-miR-335-5p might have potential prognosis value by targeting LTC4S and CXCR1 in colorectal cancer.

scholarly journals Analysis of Potential Genes and Pathways Involved in the Pathogenesis of Acne by Bioinformatics

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Biao Chen ◽  
Yan Zheng ◽  
Yanhua Liang
Keyword(s):  
Signaling Pathway ◽  
Normal Skin ◽  
Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Cytokine Receptor ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Pathway Enrichment ◽  
Chemokine Signaling ◽  
Chemokine Signaling Pathway

Acne is the eighth most frequent disease worldwide. Inflammatory response runs through all stages of acne. It is complicated and is involved in innate and adaptive immunity. This study aimed to explore the candidate genes and their relative signaling pathways in inflammatory acne using data mining analysis. Microarray data GSE6475 and GSE53795, including 18 acne lesion tissues and 18 matched normal skin tissues, were obtained. Differentially expressed genes (DEGs) were filtered and subjected to functional and pathway enrichment analyses. Protein–protein interaction (PPI) network and module analyses were also performed based on the DEGs. In this work, 154 common DEGs, including 145 upregulated and 9 downregulated, were obtained from two microarray profiles. Gene Ontology and pathway enrichment of DEGs were clustered using significant enrichment analysis. A PPI network containing 110 nodes/DEGs was constructed, and 31 hub genes were obtained. Four modules in the PPI network, which mainly participated in chemokine signaling pathway, cytokine–cytokine receptor interaction, and Fc gamma R-mediated phagocytosis, were extracted. In conclusion, aberrant DEGs and pathways involved in acne pathogenesis were identified using bioinformatic analysis. The DEGs included FPR2, ITGB2, CXCL8, C3AR1, CXCL1, FCER1G, LILRB2, PTPRC, SAA1, CCR2, ICAM1, and FPR1, and the pathways included chemokine signaling pathway, cytokine–cytokine receptor interaction, and Fc gamma R-mediated phagocytosis. This study could serve as a basis for further understanding the pathogenesis and potential therapeutic targets of inflammatory acne.

scholarly journals Identification of Tumor Microenvironment-related Prognostic Genes in Colorectal Cancer based on Bioinformatic Methods

2021 ◽  
Author(s):  
Yi Liu ◽  
Long Cheng ◽  
Chao Li ◽  
Chen Zhang ◽  
Wang Lei ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Ppi Networks ◽  
Chemokine Signaling ◽  
Chemokine Signaling Pathway

Abstract Colorectal cancer (CRC) ranks fourth among the deadliest cancers globally, and the progression is highly affected by the tumor microenvironment (TME). This study explores the relationship between TME and colorectal cancer prognosis and identifies prognostic genes related to the CRC microenvironment. We collected the gene expression data from The Cancer Genome Atlas (TCGA) and calculated the scores of stromal/immune cells and their relations to clinical outcomes in colorectal cancer by the ESTIMATE algorithm. Lower immune scores were significantly related to malignant progression of CRC (stage, p=0.014; metastasis, p=0.001). We screened 292 differentially expressed genes (DEGs) by dividing CRC cases into high and low stromal/immune score groups. Functional enrichment analyses and protein-protein interaction (PPI) networks illustrated that these DEGs were closely involved in immune response, cytokine-cytokine receptor interaction, and chemokine signaling pathway. Six DEGs (FABP4, MEOX2, MMP12, ERMN, TNFAIP6, and CHST11) with prognostic value were identified by survival analysis and validated in an independent cohort (GSE17386). The six DEGs were significantly related to immune cell infiltration levels based on the Tumor Immune Estimation Resource (TIMER). The results might contribute to discovering new diagnostic and prognostic biomarkers and new treatment targets for colorectal cancer.

scholarly journals Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yi Liu ◽  
Long Cheng ◽  
Chao Li ◽  
Chen Zhang ◽  
Lei Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Ppi Networks ◽  
Chemokine Signaling ◽  
Chemokine Signaling Pathway

AbstractColorectal cancer (CRC) ranks fourth among the deadliest cancers globally, and the progression is highly affected by the tumor microenvironment (TME). This study explores the relationship between TME and colorectal cancer prognosis and identifies prognostic genes related to the CRC microenvironment. We collected the gene expression data from The Cancer Genome Atlas (TCGA) and calculated the scores of stromal/immune cells and their relations to clinical outcomes in colorectal cancer by the ESTIMATE algorithm. Lower immune scores were significantly related to the malignant progression of CRC (metastasis, p = 0.001). We screened 292 differentially expressed genes (DEGs) by dividing CRC cases into high and low stromal/immune score groups. Functional enrichment analyses and protein–protein interaction (PPI) networks illustrated that these DEGs were closely involved in immune response, cytokine–cytokine receptor interaction, and chemokine signaling pathway. Six DEGs (FABP4, MEOX2, MMP12, ERMN, TNFAIP6, and CHST11) with prognostic value were identified by survival analysis and validated in two independent cohorts (GSE17538 and GSE161158). The six DEGs were significantly related to immune cell infiltration levels based on the Tumor Immune Estimation Resource (TIMER). The results might contribute to discovering new diagnostic and prognostic biomarkers and new treatment targets for colorectal cancer.

scholarly journals Identification of Potential Biomarkers and Biological Pathways in Juvenile Dermatomyositis Based on miRNA-mRNA Network

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Cheng-Cheng Qiu ◽  
Qi-Sheng Su ◽  
Shang-Yong Zhu ◽  
Ruo-Chuan Liu
Keyword(s):  
Regulatory Network ◽  
Messenger Rna ◽  
Target Genes ◽  
Juvenile Dermatomyositis ◽  
Type I Diabetes ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Type I ◽  
Ppi Network ◽  
Potential Biomarkers

Objective. The aim of this study is to explore the potential pathogenesis of juvenile dermatomyositis by bioinformatics analysis of gene chips, which would screen the hub genes, identify potential biomarkers, and reveal the development mechanism of juvenile dermatomyositis. Material and Methods. We retrieved juvenile dermatomyositis’s original expression microarray data of message RNAs (mRNAs) and microRNAs (miRNAs) from NCBI’s Gene Expression Omnibus database (GEO, http://www.ncbi.nlm.nih.gov/geo/); through the R package of limma in Bioconductor, we can screen the differentially expressed miRNAs and mRNAs, and then we further analyzed the predicted target genes by the methods such as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and miRNA-mRNA regulatory network construction and protein-protein interaction (PPI) network using Cytoscape 3.6.1. Results. Compared with normal juvenile skin tissues, 6 upregulated microRNAs and 5 downregulated microRNAs were identified from 166 downregulated microRNAs and 58 upregulated microRNAs in juvenile dermatomyositis tissues. The enrichment pathways of differentially expressed microRNAs include cell adhesion molecules (CAMs), autoimmune thyroid disease, Type I diabetes mellitus, antigen and presentation, viral myocardium, graft-versus-host disease, and Kaposi sarcoma-associated herpes virus infection. By screening of microRNA-messenger RNA regulatory network and construction of PPI network map, three target miRNAs were identified, namely, miR-193b, miR-199b-5p, and miR-665. Conclusion. We identified mir-193b, mir-199b-5p, and mir-6653 target miRNAs by exploring the miRNA-mRNA regulation network mechanism related to the pathogenesis of juvenile dermatomyositis, which will be of great significance for further study on the pathogenesis and targeted therapy of juvenile dermatomyositis.

scholarly journals Transcriptional modulator ZBED6 affects cell cycle and growth of human colorectal cancer cells

2015 ◽  
Vol 112 (25) ◽  
pp. 7743-7748 ◽  
Author(s):  
Muhammad Akhtar Ali ◽  
Shady Younis ◽  
Ola Wallerman ◽  
Rajesh Gupta ◽  
Leif Andersson ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cell Cycle ◽  
Cell Lines ◽  
Differentially Expressed Genes ◽  
Target Genes ◽  
Egf Receptor ◽  
Differentially Expressed ◽  
Striking Difference ◽  
Human Colorectal Cancer ◽  
Chip Sequencing

The transcription factor ZBED6 (zinc finger, BED-type containing 6) is a repressor of IGF2 whose action impacts development, cell proliferation, and growth in placental mammals. In human colorectal cancers, IGF2 overexpression is mutually exclusive with somatic mutations in PI3K signaling components, providing genetic evidence for a role in the PI3K pathway. To understand the role of ZBED6 in tumorigenesis, we engineered and validated somatic cell ZBED6 knock-outs in the human colorectal cancer cell lines RKO and HCT116. Ablation of ZBED6 affected the cell cycle and led to increased growth rate in RKO cells but reduced growth in HCT116 cells. This striking difference was reflected in the transcriptome analyses, which revealed enrichment of cell-cycle–related processes among differentially expressed genes in both cell lines, but the direction of change often differed between the cell lines. ChIP sequencing analyses displayed enrichment of ZBED6 binding at genes up-regulated in ZBED6-knockout clones, consistent with the view that ZBED6 modulates gene expression primarily by repressing transcription. Ten differentially expressed genes were identified as putative direct gene targets, and their down-regulation by ZBED6 was validated experimentally. Eight of these genes were linked to the Wnt, Hippo, TGF-β, EGF receptor, or PI3K pathways, all involved in colorectal cancer development. The results of this study show that the effect of ZBED6 on tumor development depends on the genetic background and the transcriptional state of its target genes.

scholarly journals Comprehensive Analysis Reveals the Potential Regulatory Mechanism Between Ub–Proteasome System and Cell Cycle in Colorectal Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhiyuan Zhang ◽  
Jingwen Chen ◽  
Wentao Tang ◽  
Qingyang Feng ◽  
Jianmin Xu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cell Cycle ◽  
Regulatory Mechanism ◽  
Differentially Expressed ◽  
Potential Mechanism ◽  
Ppi Network ◽  
Protein Coding ◽  
Protein Protein Interaction ◽  
Differentially Expressed Protein ◽  
Cycle System

The ubiquitin (Ub)–proteasome system (UPS) is an important regulatory component in colorectal cancer (CRC), and the cell cycle is also characterized to play a significant role in CRC. In this present study, we firstly identified UPS-associated differentially expressed genes and all the differentially expressed protein-coding genes in CRC through three differential analyses. UPS-associated genes were also further analyzed via survival analysis. A weighted gene co-expression network analysis (WGCNA) was used to identify the cell cycle-associated genes. We used protein–protein interaction (PPI) network to comprehensively mine the potential mechanism of the UPS–cell cycle regulatory axis. Moreover, we constructed a signature based on UPS-associated genes to predict the overall survival of CRC patients. Our research provides a novel insight view of the UPS and cell cycle system in CRC.

scholarly journals Identification of potential biomarkers with colorectal cancer based on bioinformatics analysis and machine learning

2021 ◽  
Vol 18 (6) ◽  
pp. 8997-9015
Author(s):  
Ahmed Hammad ◽  
◽  
Mohamed Elshaer ◽  
Xiuwen Tang ◽  
◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Machine Learning ◽  
Roc Curve ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Hub Genes ◽  
Survival Analyses ◽  
Potential Biomarkers

<abstract> <p>Colorectal cancer (CRC) is one of the most common malignancies worldwide. Biomarker discovery is critical to improve CRC diagnosis, however, machine learning offers a new platform to study the etiology of CRC for this purpose. Therefore, the current study aimed to perform an integrated bioinformatics and machine learning analyses to explore novel biomarkers for CRC prognosis. In this study, we acquired gene expression microarray data from Gene Expression Omnibus (GEO) database. The microarray expressions GSE103512 dataset was downloaded and integrated. Subsequently, differentially expressed genes (DEGs) were identified and functionally analyzed via Gene Ontology (GO) and Kyoto Enrichment of Genes and Genomes (KEGG). Furthermore, protein protein interaction (PPI) network analysis was conducted using the STRING database and Cytoscape software to identify hub genes; however, the hub genes were subjected to Support Vector Machine (SVM), Receiver operating characteristic curve (ROC) and survival analyses to explore their diagnostic values. Meanwhile, TCGA transcriptomics data in Gene Expression Profiling Interactive Analysis (GEPIA) database and the pathology data presented by in the human protein atlas (HPA) database were used to verify our transcriptomic analyses. A total of 105 DEGs were identified in this study. Functional enrichment analysis showed that these genes were significantly enriched in biological processes related to cancer progression. Thereafter, PPI network explored a total of 10 significant hub genes. The ROC curve was used to predict the potential application of biomarkers in CRC diagnosis, with an area under ROC curve (AUC) of these genes exceeding 0.92 suggesting that this risk classifier can discriminate between CRC patients and normal controls. Moreover, the prognostic values of these hub genes were confirmed by survival analyses using different CRC patient cohorts. Our results demonstrated that these 10 differentially expressed hub genes could be used as potential biomarkers for CRC diagnosis.</p> </abstract>

scholarly journals Bioinformatics Analysis of Key Genes and circRNA-miRNA-mRNA Regulatory Network in Gastric Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Yiting Tian ◽  
Yang Xing ◽  
Zheng Zhang ◽  
Rui Peng ◽  
Luyu Zhang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Extracellular Matrix ◽  
Expression Profiles ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Future Research ◽  
Circular Rnas ◽  
Ppi Network ◽  
Protein Protein Interaction

Gastric cancer (GC) is one of the most common malignancies in the world, with morbidity and mortality ranking second among all cancers. Accumulating evidences indicate that circular RNAs (circRNAs) are closely correlated with tumorigenesis. However, the mechanisms of circRNAs still remain unclear. This study is aimed at determining hub genes and circRNAs and analyzing their potential biological functions in GC. Expression profiles of mRNAs and circRNAs were downloaded from the Gene Expression Omnibus (GEO) data sets of GC and paracancer tissues. Differentially expressed genes (DEGs) and differentially expressed circRNAs (DE-circRNAs) were identified. The target miRNAs of DE-circRNAs and the bidirectional interaction between target miRNAs and DEGs were predicted. Functional analysis was performed, and the protein-protein interaction (PPI) network and the circRNA-miRNA-mRNA network were established. A total of 456 DEGs and 2 DE-circRNAs were identified with 3 mRNA expression profiles and 2 circRNA expression profiles. GO analysis indicated that DEGs were mainly enriched in extracellular matrix and cell adhesion, and KEGG confirmed that DEGs were mainly associated with focal adhesion, the PI3K-Akt signaling pathway, extracellular matrix- (ECM)- receptor interaction, and gastric acid secretion. 15 hub DEGs (BGN, COL1A1, COL1A2, FBN1, FN1, SPARC, SPP1, TIMP1, UBE2C, CCNB1, CD44, CXCL8, COL3A1, COL5A2, and THBS1) were identified from the PPI network. Furthermore, the survival analysis indicate that GC patients with a high expression of the following 9 hub DEGs, namely, BGN, COL1A1, COL1A2, FBN1, FN1, SPARC, SPP1, TIMP1, and UBE2C, had significantly worse overall survival. The circRNA-miRNA-mRNA network was constructed based on 1 circRNA, 15 miRNAs, and 45 DEGs. In addition, the 45 DEGs included 5 hub DEGs. These results suggested that hub DEGs and circRNAs could be implicated in the pathogenesis and development of GC. Our findings provide novel evidence on the circRNA-miRNA-mRNA network and lay the foundation for future research of circRNAs in GC.

scholarly journals Mammary Transcriptome Profile during Peak and Late Lactation Reveals Differentially Expression Genes Related to Inflammation and Immunity in Chinese Holstein

Animals ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 510
Author(s):  
Ziyin Han ◽  
Yongliang Fan ◽  
Zhangping Yang ◽  
Juan J. Loor ◽  
Yi Yang
Keyword(s):  
Mammary Gland ◽  
Signaling Pathway ◽  
Receptor Interaction ◽  
Gene Expressions ◽  
Chinese Holstein ◽  
Chemokine Signaling ◽  
Transcriptomic Sequencing ◽  
Receptor Signaling Pathway ◽  
Differential Expressed Genes ◽  
Chemokine Signaling Pathway

Somatic cell count (SCC) in milk is widely used in the dairy industry, as an indicator of the health of mammary gland. While the SCC of dairy cattle was higher in late lactation than in peak lactation, its association with gene expressions of mammary gland were largely unknown. In this study, a transcriptomic sequencing approach and bioinformatics analysis were used to investigate the differential expressed genes (DEGs) associated with inflammation and immunity between peak and late periods of lactation in Chinese Holstein. A total of 446 DEGs (padj < 0.05 and fold change >2) were identified, 50 of which belonged to seven pathways and five terms related to inflammation and immunity. Our data suggested that the activation of nuclear transcription factor-κB (NF-κB) pathway and Toll-like receptor signaling pathway caused inflammatory response, and the activation of chemokine signaling pathway and cytokine–cytokine receptor interaction signaling pathway caused a protective immune response to ensure dairy cows health during late lactation. Our findings deepen the understanding of the molecular mechanism and physiological functions of mammary inflammation in Chinese Holstein during late lactation.

scholarly journals Network Pharmacology-Based Study on the Mechanism of Gegen Qinlian Decoction against Colorectal Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Qiaowei Fan ◽  
Lin Guo ◽  
Jingming Guan ◽  
Jing Chen ◽  
Yujing Fan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Target Genes ◽  
Enrichment Analysis ◽  
R Package ◽  
Gastrointestinal Diseases ◽  
Gene Expression Omnibus ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Ppi Network

Purpose. Gegen Qinlian decoction (GQD) has been used to treat gastrointestinal diseases, such as diarrhea and ulcerative colitis (UC). A recent study demonstrated that GQD enhanced the effect of PD-1 blockade in colorectal cancer (CRC). This study used network pharmacology analysis to investigate the mechanisms of GQD as a potential therapeutic approach against CRC. Materials and Methods. Bioactive chemical ingredients (BCIs) of GQD were collected from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. CRC-specific genes were obtained using the gene expression profile GSE110224 from the Gene Expression Omnibus (GEO) database. Target genes related to BCIs of GQD were then screened out. The GQD-CRC ingredient-target pharmacology network was constructed and visualized using Cytoscape software. A protein-protein interaction (PPI) network was subsequently constructed and analyzed with BisoGenet and CytoNCA plug-in in Cytoscape. Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis for target genes were then performed using the R package of clusterProfiler. Results. One hundred and eighteen BCIs were determined to be effective on CRC, including quercetin, wogonin, and baicalein. Twenty corresponding target genes were screened out including PTGS2, CCNB1, and SPP1. Among these genes, CCNB1 and SPP1 were identified as crucial to the PPI network. A total of 212 GO terms and 6 KEGG pathways were enriched for target genes. Functional analysis indicated that these targets were closely related to pathophysiological processes and pathways such as biosynthetic and metabolic processes of prostaglandins and prostanoids, cytokine and chemokine activities, and the IL-17, TNF, Toll-like receptor, and nuclear factor-kappa B (NF-κB) signaling pathways. Conclusion. The study elucidated the “multiingredient, multitarget, and multipathway” mechanisms of GQD against CRC from a systemic perspective, indicating GQD to be a candidate therapy for CRC treatment.

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