scholarly journals Identification of hub genes associated with esophageal cancer progression using bioinformatics analysis

2020 ◽  
Vol 20 (5) ◽  
pp. 1-1
Author(s):  
Jiangfen Li ◽  
Yufang Xie ◽  
Xueli Wang ◽  
Chenhao Jiang ◽  
Xin Yuan ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Cancer Progression ◽  
Bioinformatics Analysis ◽  
Hub Genes

HMMR Functions as a Prognostic Biomarker in Uterine Carcinosarcoma Identified by Comprehensive Bioinformatics Analysis

2020 ◽  
Author(s):  
Hui Sun ◽  
Li Ma ◽  
Jie Chen
Keyword(s):  
Cancer Progression ◽  
Poor Prognosis ◽  
Bioinformatics Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Normal Tissues ◽  
Potential Biomarker

Abstract BackgroundUterine carcinosarcoma (UCS) is a rare aggressive tumor with a high metastasis rate and poor prognosis. Bioinformatics analysis has been widely applied to screen and analyze genes in linkage to various types of cancer progression. This study aims to explore the molecular mechanism of UCS. MethodsFirst, transcriptional different expression data between UCS and normal samples were got from the GEPIA database. Subsequently, differentially expressed genes were analyzed through the Metascape with Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the STRING website and Cytoscape software were applied to construct the protein-protein interaction network. Finally, the top 30 genes obtained through the MCC algorithm were selected as hub genes, which was finally validated in TIMER, and UALCAN databases. ResultsA total of 1894 DEGs (579 up-regulated and 1315 down-regulated) were identified, GO and KEGG functional enrichment analysis were performed for the DEGs. The PPI network was constructed based on DEGs, and four clusters were excavated for further analysis and the top 30 genes were identified as hub genes. Our data showed that the expression of HMMR is significantly higher in UCS tissues compared to the paired normal tissues (p<0.05) and the elevated expression of HMMR is related to poor prognosis in patients with UCS (p= 0.0031). TPX2, AURKA, BRCA1 and BARD1 are essential for the function of HMMR. TPX2 and AURKA were found to be significantly higher in UCS compared to the normal tissue (p<0.05), and there was a statistically significant positive correlation between the expression of HMMR and AURKA, TPX2, BRCA1, BARD1 in UCS (p=1.08e-07, p=1.62e-05, p=2.02e-3, p=6.54e-6). ConclusionsOur study suggested that HMMR may be a potential biomarker for predicting the prognosis of UCS patients.

scholarly journals Fibroblast activation protein targeted near infrared photoimmunotherapy (NIR PIT) overcomes therapeutic resistance in human esophageal cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ryoichi Katsube ◽  
Kazuhiro Noma ◽  
Toshiaki Ohara ◽  
Noriyuki Nishiwaki ◽  
Teruki Kobayashi ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Cancer Cells ◽  
Cancer Progression ◽  
Near Infrared ◽  
Fibroblast Activation Protein ◽  
Therapeutic Resistance ◽  
Fibroblast Activation ◽  
Human Esophageal Cancer

AbstractCancer-associated fibroblasts (CAFs) have an important role in the tumor microenvironment. CAFs have the multifunctionality which strongly support cancer progression and the acquisition of therapeutic resistance by cancer cells. Near-infrared photoimmunotherapy (NIR-PIT) is a novel cancer treatment that uses a highly selective monoclonal antibody (mAb)-photosensitizer conjugate. We developed fibroblast activation protein (FAP)-targeted NIR-PIT, in which IR700 was conjugated to a FAP-specific antibody to target CAFs (CAFs-targeted NIR-PIT: CAFs-PIT). Thus, we hypothesized that the control of CAFs could overcome the resistance to conventional chemotherapy in esophageal cancer (EC). In this study, we evaluated whether EC cell acquisition of stronger malignant characteristics and refractoriness to chemoradiotherapy are mediated by CAFs. Next, we assessed whether the resistance could be rescued by eliminating CAF stimulation by CAFs-PIT in vitro and in vivo. Cancer cells acquired chemoradiotherapy resistance via CAF stimulation in vitro and 5-fluorouracil (FU) resistance in CAF-coinoculated tumor models in vivo. CAF stimulation promoted the migration/invasion of cancer cells and a stem-like phenotype in vitro, which were rescued by elimination of CAF stimulation. CAFs-PIT had a highly selective effect on CAFs in vitro. Finally, CAF elimination by CAFs-PIT in vivo demonstrated that the combination of 5-FU and NIR-PIT succeeded in producing 70.9% tumor reduction, while 5-FU alone achieved only 13.3% reduction, suggesting the recovery of 5-FU sensitivity in CAF-rich tumors. In conclusion, CAFs-PIT could overcome therapeutic resistance via CAF elimination. The combined use of novel targeted CAFs-PIT with conventional anticancer treatments can be expected to provide a more effective and sensible treatment strategy.

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 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 Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Wei Gu ◽  
Ying Sun ◽  
Xiong Zheng ◽  
Jin Ma ◽  
Xiao-Ying Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Microarray Analysis ◽  
Cancer Progression ◽  
Pathway Analysis ◽  
Bioinformatics Analysis ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Circular Rnas ◽  
Target Mrnas

Gastric cancer is one of the common malignant tumors worldwide. Increasing studies have indicated that circular RNAs (circRNAs) play critical roles in the cancer progression and have shown great potential as useful markers and therapeutic targets. However, the precise mechanism and functions of most circRNAs are still unknown in gastric cancer. In the present study, we performed a microarray analysis to detect circRNA expression changes between tumor samples and adjacent nontumor samples. The miRNA expression profiles were obtained from the National Center of Biotechnology Information Gene Expression Omnibus (GEO). The differentially expressed circRNAs and miRNAs were identified through fold change filtering. The interactions between circRNAs and miRNAs were predicted by Arraystar’s home-made miRNA target prediction software. After circRNA-related miRNAs and dysregulated miRNAs were intersected, 23 miRNAs were selected. The target mRNAs of miRNAs were predicted by TarBase v7.0. Gene ontology (GO) enrichment analysis and pathway analysis were performed using standard enrichment computational methods for the target mRNAs. The results of pathway analysis showed that p53 signaling pathway and hippo signal pathway were significantly enriched and CCND2 was a cross-talk gene associated with them. Finally, a circRNA-miRNA-mRNA regulation network was constructed based on the gene expression profiles and bioinformatics analysis results to identify hub genes and hsa_circRNA_101504 played a central role in the network.

scholarly journals NETO2 promotes esophageal cancer progression by inducing proliferation and metastasis via PI3K/AKT and ERK pathway

2021 ◽  
Vol 17 (1) ◽  
pp. 259-270
Author(s):  
Jia-cheng Xu ◽  
Tian-yin Chen ◽  
Le-tai Liao ◽  
Tao Chen ◽  
Quan-lin Li ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Cancer Progression ◽  
Erk Pathway ◽  
Proliferation And Metastasis

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.

Sign in / Sign up

Export Citation Format

Share Document