Employing bioinformatics analysis to identify hub genes and microRNAs involved in colorectal cancer

2021 ◽  
Vol 38 (9) ◽  
Author(s):  
Johann Ebadfardzadeh ◽  
Mandana Kazemi ◽  
Ali Aghazadeh ◽  
Monireh Rezaei ◽  
Milad Shirvaliloo ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Bioinformatics Analysis ◽  
Hub Genes

Identification of potential hub genes via bioinformatics analysis combined with experimental verification in colorectal cancer

2020 ◽  
Vol 59 (4) ◽  
pp. 425-438 ◽  
Author(s):  
Hongrui Zhou ◽  
Zhe Yang ◽  
Jiaxin Yue ◽  
Yang Chen ◽  
Tianqiao Chen ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Experimental Verification ◽  
Bioinformatics Analysis ◽  
Hub Genes

scholarly journals POS0458 IDENTIFICATION OF HUB GENES AND MOLECULAR PATHWAYS IN PATIENTS WITH RHEUMATOID ARTHRITIS BY BIOINFORMATICS ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 460.1-460
Author(s):  
L. Cheng ◽  
S. X. Zhang ◽  
S. Song ◽  
C. Zheng ◽  
X. Sun ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Signaling Pathway ◽  
Synovial Tissue ◽  
Bioinformatics Analysis ◽  
Metabolic Process ◽  
Shanxi Province ◽  
Molecular Pathways ◽  
Biological Processes ◽  
Hub Genes ◽  
Tissue Samples

Background:Rheumatoid arthritis (RA) is a chronic, inflammatory synovitis based systemic disease of unknown etiology1. The genes and pathways in the inflamed synovium of RA patients are poorly understood.Objectives:This study aims to identify differentially expressed genes (DEGs) associated with the progression of synovitis in RA using bioinformatics analysis and explore its pathogenesis2.Methods:RA expression profile microarray data GSE89408 were acquired from the public gene chip database (GEO), including 152 synovial tissue samples from RA and 28 healthy synovial tissue samples. The DEGs of RA synovial tissues were screened by adopting the R software. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. Protein-protein interaction (PPI) networks were assembled with Cytoscape software.Results:A total of 654 DEGs (268 up-regulated genes and 386 down-regulated genes) were obtained by the differential analysis. The GO enrichment results showed that the up-regulated genes were significantly enriched in the biological processes of myeloid leukocyte activation, cellular response to interferon-gamma and immune response-regulating signaling pathway, and the down-regulated genes were significantly enriched in the biological processes of extracellular matrix, retinoid metabolic process and regulation of lipid metabolic process. The KEGG annotation showed the up-regulated genes mainly participated in the staphylococcus aureus infection, chemokine signaling pathway, lysosome signaling pathway and the down-regulated genes mainly participated in the PPAR signaling pathway, AMPK signaling pathway, ECM-receptor interaction and so on. The 9 hub genes (PTPRC, TLR2, tyrobp, CTSS, CCL2, CCR5, B2M, fcgr1a and PPBP) were obtained based on the String database model by using the Cytoscape software and cytoHubba plugin3.Conclusion:The findings identified the molecular mechanisms and the key hub genes of pathogenesis and progression of RA.References:[1]Xiong Y, Mi BB, Liu MF, et al. Bioinformatics Analysis and Identification of Genes and Molecular Pathways Involved in Synovial Inflammation in Rheumatoid Arthritis. Med Sci Monit 2019;25:2246-56. doi: 10.12659/MSM.915451 [published Online First: 2019/03/28][2]Mun S, Lee J, Park A, et al. Proteomics Approach for the Discovery of Rheumatoid Arthritis Biomarkers Using Mass Spectrometry. Int J Mol Sci 2019;20(18) doi: 10.3390/ijms20184368 [published Online First: 2019/09/08][3]Zhu N, Hou J, Wu Y, et al. Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis. Medicine (Baltimore) 2018;97(22):e10997. doi: 10.1097/MD.0000000000010997 [published Online First: 2018/06/01]Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

scholarly journals LINC00963 affects the development of colorectal cancer via MiR-532-3p/HMGA2 axis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jinjun Ye ◽  
Jidong Liu ◽  
Tao Tang ◽  
Le Xin ◽  
Xing Bao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Growth ◽  
Cell Cycle Progression ◽  
Bioinformatics Analysis ◽  
Scratch Test ◽  
Luciferase Assay ◽  
Migration And Invasion ◽  
Cycle Progression ◽  
Ki67 Expression ◽  
And Function

Abstract Background LINC00963 is high-expressed in various carcinomas, but its expression and function in colorectal cancer (CRC) have not been explored. This study explored the role and mechanism of LINC00963 in CRC. Methods The expression of LINC00963 in CRC and its relationship with prognosis were examined by starBase and survival analysis. The effects of LINC00963, miR-532-3p and HMGA2 on the biological characteristics and EMT-related genes of CRC cells were studied by RT-qPCR, CCK-8, clone formation experiments, flow cytometry, scratch test, Transwell, and Western blot. Xenograft assay and immunohistochemistry were performed to verify the effect of LINC00963 on tumor growth. The correlation among LINC00963, miR-532-3p, and HMGA2 was analyzed by bioinformatics analysis, luciferase assay, and Pearson test. Results LINC00963 was high-expressed in CRC, and this was associated with poor prognosis of CRC. Silencing LINC00963 inhibited the activity, proliferation, migration, and invasion of CRC cells, MMP-3 and MMP-9 expressions, moreover, it also blocked cell cycle progression, and inhibited tumor growth and Ki67 expression. However, overexpression of LINC00963 showed the opposite effects to silencing LINC00963. LINC00963 targeted miR-532-3p to regulate HMGA2 expression. Down-regulation of miR-532-3p promoted cell proliferation, migration and invasion, and expressions of MMP-3 and MMP-9, and knockdown of HMGA2 reversed the effect of miR-532-3p inhibitor. Up-regulation of miR-532-3p inhibited the biological functions of CRC cells, and overexpression of HMGA2 reversed the miR-532-3p mimic effect. Conclusion LINC00963 affects the development of CRC through the miR-532-3p/HMGA2 axis.

scholarly journals Differential Expression of mRNAs in Peripheral Blood Related to Prodrome and Progression of Alzheimer’s Disease

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Weishuang Xue ◽  
Jinwei Li ◽  
Kailei Fu ◽  
Weiyu Teng
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Peripheral Blood ◽  
Bioinformatics Analysis ◽  
Gene Expression Omnibus ◽  
Venn Diagram ◽  
Ppi Network ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Ppi Networks

Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease that affects the quality of life of elderly individuals, while the pathogenesis of AD is still unclear. Based on the bioinformatics analysis of differentially expressed genes (DEGs) in peripheral blood samples, we investigated genes related to mild cognitive impairment (MCI), AD, and late-stage AD that might be used for predicting the conversions. Methods. We obtained the DEGs in MCI, AD, and advanced AD patients from the Gene Expression Omnibus (GEO) database. A Venn diagram was used to identify the intersecting genes. Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) were used to analyze the functions and pathways of the intersecting genes. Protein-protein interaction (PPI) networks were constructed to visualize the network of the proteins coded by the related genes. Hub genes were selected based on the PPI network. Results. Bioinformatics analysis indicated that there were 61 DEGs in both the MCI and AD groups and 27 the same DEGs among the three groups. Using GO and KEGG analyses, we found that these genes were related to the function of mitochondria and ribosome. Hub genes were determined by bioinformatics software based on the PPI network. Conclusions. Mitochondrial and ribosomal dysfunction in peripheral blood may be early signs in AD patients and related to the disease progression. The identified hub genes may provide the possibility for predicting AD progression or be the possible targets for treatments.

scholarly journals High expression of DNA damage-inducible transcript 4 (DDIT4) is associated with advanced pathological features in the patients with colorectal cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fahimeh Fattahi ◽  
Leili Saeednejad Zanjani ◽  
Zohreh Habibi Shams ◽  
Jafar Kiani ◽  
Mitra Mehrazma ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Dna Damage ◽  
Prognostic Significance ◽  
Tissue Microarrays ◽  
Survival Outcomes ◽  
Hub Genes ◽  
Kegg Pathways ◽  
Normal Tissues ◽  
Nuclear Expression ◽  
Pathways Analysis

AbstractDNA damage-inducible transcript 4 (DDIT4) is induced in various cellular stress conditions. This study was conducted to investigate expression and prognostic significance of DDIT4 protein as a biomarker in the patients with colorectal cancer (CRC). PPI network and KEGG pathway analysis were applied to identify hub genes among obtained differentially expressed genes in CRC tissues from three GEO Series. In clinical, expression of DDIT4 as one of hub genes in three subcellular locations was evaluated in 198 CRC tissues using immunohistochemistry method on tissue microarrays. The association between DDIT4 expression and clinicopathological features as well as survival outcomes were analyzed. Results of bioinformatics analysis indicated 14 hub genes enriched in significant pathways according to KEGG pathways analysis among which DDIT4 was selected to evaluate CRC tissues. Overexpression of nuclear DDIT4 protein was found in CRC tissues compared to adjacent normal tissues (P = 0.003). Furthermore, higher nuclear expression of DDIT4 was found to be significantly associated with the reduced tumor differentiation and advanced TNM stages (all, P = 0.009). No significant association was observed between survival outcomes and nuclear expression of DDIT4 in CRC cases. Our findings indicated higher nuclear expression of DDIT4 was significantly associated with more aggressive tumor behavior and more advanced stage of disease in the patients with CRC.

scholarly journals Identification and Verification of Genes Related to Pollen Development and Male Sterility Induced by High Temperature in Thermo-sensitive Genic Male Sterile Wheat Line YanZhan 4110S

2020 ◽  
Author(s):  
Xuetong Yang ◽  
Jiali Ye ◽  
Fuqiang Niu ◽  
Yi Feng ◽  
Xiyue Song
Keyword(s):  
Gene Silencing ◽  
Male Sterility ◽  
Mosaic Virus ◽  
Pollen Development ◽  
Bioinformatics Analysis ◽  
Virus Induced Gene Silencing ◽  
Wheat Line ◽  
Pollen Abortion ◽  
Hub Genes ◽  
Genic Male Sterility

Abstract Background: Environment-sensitive genic male sterility is of vital importance to hybrid vigor in crop production and breeding, therefore, it is meaningful to identify and study the function of the genes related to pollen development and male sterility, which still not fully understanding currently. In this study, Yanzhan 4110S, a new thermo-sensitive genic male sterility (TGMS) wheat line, and its near isogenic line Yanzhan 4110 were carried out cytological features observation, bioinformatics analysis to investgate the abortion state and identified the genes involved in pollen development which have fertility regulation function. Barely stripe mosaic virus-induced gene silencing was used to verify the genes function.Results: Cytological analysis showed pollen abortion event of Yanzhan 4110S occur at the later uninucleate stage (Lun) under higher temperature induction (day/night temperatures of 22 °C/20 °C), when the anthers were collected and assessed for transcriptomic profiling through high-throughput sequencing. We then in-depth analyzed the differentially expressed genes (DEGs) by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, the results showed that the occurrence of Yanzhan 4110S male-sterility most likely related to metabolic pathway, including phenylpropanoid biosynthesis in the biosynthesis of other secondary metabolites, starch and sucrose metabolism in carbohydrate metabolism, carbon fixation in photosynthetic organisms as well as carbon metabolism in energy metabolism. The weighted gene co-expression network analysis in the transcriptome profiles further identified some hub genes, where the key genes involved in those pathways were intersection between the unique DEGs of Yanzhan 4110S in anther and hub genes, totally 228 genes, which were highly related to pollen development including TaMut11 and TaSF3. Moreover, further verification through barely stripe mosaic virus-induced gene silencing elucidated that the silencing of TaMut11 and TaSF3 caused pollen abortion, finally resulting in the declination of fertility. So, the genes TaMut11 and TaSF3 are related to fertility conversion of Yanzhan 4110S.Conclusion: Through comparative transcriptome bioinformatics analysis, the genes TaMut11 and TaSF3 associated with pollen development and male sterility induced by high temperature were identified in Yanzhan 4110S, and verificated by barely stripe mosaic virus-induced gene silencing. These findings provided researching the abortive mechanism in environment-sensitive genic male sterility wheat.

scholarly journals Integrative Identification of Hub Genes Associated With Immune Cells in Atrial Fibrillation Using Weighted Gene Correlation Network Analysis

2021 ◽  
Vol 7 ◽  
Author(s):  
Tao Yan ◽  
Shijie Zhu ◽  
Miao Zhu ◽  
Chunsheng Wang ◽  
Changfa Guo
Keyword(s):  
Atrial Fibrillation ◽  
Network Analysis ◽  
Molecular Mechanism ◽  
Immune Cells ◽  
Bioinformatics Analysis ◽  
Functional Enrichment ◽  
Correlation Network ◽  
Hub Genes ◽  
Qrt Pcr ◽  
Gene Correlation

Background: Atrial fibrillation (AF) is the most common tachyarrhythmia in the clinic, leading to high morbidity and mortality. Although many studies on AF have been conducted, the molecular mechanism of AF has not been fully elucidated. This study was designed to explore the molecular mechanism of AF using integrative bioinformatics analysis and provide new insights into the pathophysiology of AF.Methods: The GSE115574 dataset was downloaded, and Cibersort was applied to estimate the relative expression of 22 kinds of immune cells. Differentially expressed genes (DEGs) were identified through the limma package in R language. Weighted gene correlation network analysis (WGCNA) was performed to cluster DEGs into different modules and explore relationships between modules and immune cell types. Functional enrichment analysis was performed on DEGs in the significant module, and hub genes were identified based on the protein-protein interaction (PPI) network. Hub genes were then verified using quantitative real-time polymerase chain reaction (qRT-PCR).Results: A total of 2,350 DEGs were identified and clustered into eleven modules using WGCNA. The magenta module with 246 genes was identified as the key module associated with M1 macrophages with the highest correlation coefficient. Three hub genes (CTSS, CSF2RB, and NCF2) were identified. The results verified using three other datasets and qRT-PCR demonstrated that the expression levels of these three genes in patients with AF were significantly higher than those in patients with SR, which were consistent with the bioinformatic analysis.Conclusion: Three novel genes identified using comprehensive bioinformatics analysis may play crucial roles in the pathophysiological mechanism in AF, which provide potential therapeutic targets and new insights into the treatment and early detection of AF.

scholarly journals Genomic Expression Profiling of Colorectal Cancer in Silico

2021 ◽  
Author(s):  
Feifei Liu ◽  
Yu Wang ◽  
Wenxue Li ◽  
Diancheng Li ◽  
Yuwei Xin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Survival Analysis ◽  
Mrna Expression ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Analysis Tool ◽  
Hub Genes ◽  
Normal Tissues

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.

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