scholarly journals A COMPARATIVE ANALAYSIS OF INTER-SITE GENE EXPRESSION HETEROGENICITY OF NORMAL HUMAN BUCCAL MUCOSA WITH NORMAL GINGIVAL MUCOSA

2021 ◽  
Author(s):  
Rooban Thavarajah ◽  
Kannan Ranganathan

BACKGROUND: Description of heterogeneity of gene expression of various human intraoral sites are not adequate. The aim of this study was to explore the difference of gene expression profiles of whole tissue obtained from apparently normal human gingiva and buccal mucosa (HGM, HBM). MATERIALS AND METHODS: Gene sets fulfilling inclusion and exclusion criteria of HGM and HBM in gene Expression Omnibus(GEO) database were identified, segregated, filtered and analysed using the ExAtlas online web tool using pre-determined cut-off. The differentially expressed genes were studied for epithelial keratinization related, housekeeping(HKG), extracellular matrix related(ECMRG) and epithelial-mesenchymal transition related genes(EMTRGs). RESULTS: In all 40 HBM and 64 HGM formed the study group. In all there were 18012 significantly expressed genes. Of this, 1814 were over-expressed and 1862 under-expressed HBM genes as compared to HGM. One in five of all studied genes significantly differed between HBM and HGM. For the keratinization genes, 1 in 6 differed. One of every 5 HKG-proteomics genes differed between HBM and HGM, while this ratio was 1-in 4 for all ECMRGs and EMTRGs. DISCUSSION: This difference in the gene expression between the HBM and HGM could possibly influence a multitude of biological pathways. This result could explain partly the difference in clinicopathological features of oral lesions occurring in HBM and HGM. The innate genotypic difference between the two intra-oral niches could serve as confounding factor in genotypic studies. Hence studies that compare the HBM and HGM should factor-in these findings while evaluating their results.

2018 ◽  
Vol 178 (3) ◽  
pp. 295-307 ◽  
Author(s):  
Camilla Maria Falch ◽  
Arvind Y M Sundaram ◽  
Kristin Astrid Øystese ◽  
Kjersti Ringvoll Normann ◽  
Tove Lekva ◽  
...  

ObjectiveReliable biomarkers associated with aggressiveness of non-functioning gonadotroph adenomas (GAs) are lacking. As the growth of tumor remnants is highly variable, molecular markers for growth potential prediction are necessary. We hypothesized that fast- and slow-growing GAs present different gene expression profiles and reliable biomarkers for tumor growth potential could be identified, focusing on the specific role of epithelial-mesenchymal transition (EMT).Design and methodsEight GAs selected for RNA sequencing were equally divided into fast- and slow-growing group by the tumor volume doubling time (TVDT) median (27.75 months). Data were analyzed by tophat2, cufflinks and cummeRbund pipeline. 40 genes were selected for RT-qPCR validation in 20 GAs based on significance, fold-change and pathway analyses. The effect of silencingMTDH(metadherin) andEMCN(endomucin) onin vitromigration of human adenoma cells was evaluated.Results350 genes were significantly differentially expressed (282 genes upregulated and 68 downregulated in the fast group,P-adjusted <0.05). Among 40 selected genes, 11 showed associations with TVDT (−0.669<R<−0.46,P < 0.05). These werePCDH18, UNC5D, EMCN, MYO1B, GPM6Aand six EMT-related genes (SPAG9, SKIL, MTDH, HOOK1, CNOT6LandPRKACB).MTDH, but notEMCN, demonstrated involvement in cell migration and association with EMT markers.ConclusionsFast- and slow-growing GAs present different gene expression profiles, and genes related to EMT have higher expression in fast-growing tumors. In addition toMTDH, identified as an important contributor to aggressiveness, the other genes might represent markers for tumor growth potential and possible targets for drug therapy.


2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 301-301
Author(s):  
Chaoyang Li ◽  
Qianglin Liu ◽  
Matt Welborn ◽  
Leshan Wang ◽  
Yuxia Li ◽  
...  

Abstract The amount of intramuscular fat directly influences the meat quality. However, significant differences in the ability to accumulate intramuscular fat are present among different beef cattle breeds. While Wagyu, a cattle breed that originated from Japan, is renowned for abundant intramuscular fat, Brahman cattle generally have very little intramuscular fat accumulation and produce tougher meat. We identified that bovine intramuscular fat is derived from a group of bipotent progenitor cells named fibro/adipogenic progenitors (FAPs) which also give rise to fibroblasts. Thus, the variation in intramuscular fat development between Wagyu and Brahman is likely attributed to the difference in FAPs between these two breeds. In order to understand the gene expression difference between FAPs of the two breeds, single-cell RNA-seq was performed using total single-nucleated cells isolated from the longissimus muscle of young purebred Wagyu, purebred Brahman, and Wagyu-Brahman cross cattle. FAPs constitute the largest single-nucleated cell population in both Wagyu and Brahman skeletal muscle. Multiple subpopulations of FAPs with different gene expression profiles were identified, suggesting that FAP is a heterogeneous population. A unique FAP cluster expressing lower levels of fibrillar collagen and extracellular remodeling enzyme genes but higher levels of select proadipogenic genes was identified exclusively in Wagyu skeletal muscle, which likely contributes to the robust intramuscular adipogenic efficiency of Wagyu FAPs. In conclusion, the difference in the cellular composition and gene expression of FAPs between Wagyu and Brahman cattle likely contribute to their distinct meat quality.


2021 ◽  
pp. 1-6
Author(s):  
Reza Vafaee ◽  
Mostafa Rezaei Tavirani ◽  
Sina Rezaei Tavirani ◽  
Mohammadreza Razzaghi

There are many documents about benefits of exercise on human health. However, evidences indicate to positive effect of exercise on disease prevention, understanding of many aspects of this mechanism need more investigations. Determination of critical genes which effect human health. GSE156249 including 12 gene expression profiles of healthy individual biopsy from vastus lateralis muscle before and after 12-week combined exercise training intervention were extracted from gene expression omnibus (GEO) database. The significant DEGs were included in interactome unit by Cytoscape software and STRING database. The network was analyzed to find the central nodes subnetwork clusters. The nodes of prominent cluster were assessed via gene ontology by using ClueGO. Number of 8 significant DEGs and 100 first neighbors analyzed via network analysis. The network includes 2 clusters and COL3A1, BGN, and LOX were determined as central DEGs. The critical DEGs were involved in cancer prevention process.


2021 ◽  
Author(s):  
Hongpeng Fang ◽  
Zhansen Huang ◽  
Xianzi Zeng ◽  
Jiaming Wan ◽  
Jieying Wu ◽  
...  

Abstract Background As a common malignant cancer of the urinary system, the precise molecular mechanisms of bladder cancer remain to be illuminated. The purpose of this study was to identify core genes with prognostic value as potential oncogenes for the diagnosis, prognosis or novel therapeutic targets of bladder cancer. Methods The gene expression profiles GSE3167 and GSE7476 were available from the Gene Expression Omnibus (GEO) database. Next, PPI network was built to filter the hub gene through the STRING database and Cytoscape software and GEPIA and Kaplan-Meier plotter were implemented. Frequency and type of hub genes and sub groups analysis were performed in cBioportal and ULCAN database. Finally,We used RT-qPCR to confirm our results. Results Totally, 251 DEGs were excavated from two datasets in our study. We only founded high expression of SMC4, TYMS, CCNB1, CKS1B, NUSAP1 and KPNA2 was associated with worse outcomes in bladder cancer patients and no matter from the type of mutation or at the transcriptional level of hub genes, the tumor showed a high form of expression. However, only the expression of SMC4,CCNB1and CKS1B remained changed between the cancer and the normal samples in our results of RT-qPCR. Conclusion In conclusion,These findings indicate that the SMC4,CCNB1 and CKS1B may serve as critical biomarkers in the development and poor prognosis.


2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Fabiana V. Mello ◽  
Marcelo G. P. Land ◽  
Elaine. S. Costa ◽  
Cristina Teodósio ◽  
María-Luz Sanchez ◽  
...  

Virology ◽  
2006 ◽  
Vol 350 (2) ◽  
pp. 418-428 ◽  
Author(s):  
Xiao-Mei Rao ◽  
Xinyu Zheng ◽  
Sabine Waigel ◽  
Wolfgang Zacharias ◽  
Kelly M. McMasters ◽  
...  

2022 ◽  
Vol 2022 ◽  
pp. 1-17
Author(s):  
Md. Rakibul Islam ◽  
Lway Faisal Abdulrazak ◽  
Mohammad Khursheed Alam ◽  
Bikash Kumar Paul ◽  
Kawsar Ahmed ◽  
...  

Background. Medulloblastoma (MB) is the most occurring brain cancer that mostly happens in childhood age. This cancer starts in the cerebellum part of the brain. This study is designed to screen novel and significant biomarkers, which may perform as potential prognostic biomarkers and therapeutic targets in MB. Methods. A total of 103 MB-related samples from three gene expression profiles of GSE22139, GSE37418, and GSE86574 were downloaded from the Gene Expression Omnibus (GEO). Applying the limma package, all three datasets were analyzed, and 1065 mutual DEGs were identified including 408 overexpressed and 657 underexpressed with the minimum cut-off criteria of ∣ log   fold   change ∣ > 1 and P < 0.05 . The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and WikiPathways enrichment analyses were executed to discover the internal functions of the mutual DEGs. The outcomes of enrichment analysis showed that the common DEGs were significantly connected with MB progression and development. The Search Tool for Retrieval of Interacting Genes (STRING) database was used to construct the interaction network, and the network was displayed using the Cytoscape tool and applying connectivity and stress value methods of cytoHubba plugin 35 hub genes were identified from the whole network. Results. Four key clusters were identified using the PEWCC 1.0 method. Additionally, the survival analysis of hub genes was brought out based on clinical information of 612 MB patients. This bioinformatics analysis may help to define the pathogenesis and originate new treatments for MB.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Nina Hauptman ◽  
Emanuela Boštjančič ◽  
Margareta Žlajpah ◽  
Branislava Ranković ◽  
Nina Zidar

Colorectal cancer (CRC) is one of the leading causes of death by cancer worldwide. Bowel cancer screening programs enable us to detect early lesions and improve the prognosis of patients with CRC. However, they also generate a significant number of problematic polyps, e.g., adenomas with epithelial misplacement (pseudoinvasion) which can mimic early adenocarcinoma. Therefore, biomarkers that would enable us to distinguish between adenoma with epithelial misplacement (pseudoinvasion) and adenoma with early adenocarcinomas (true invasion) are needed. We hypothesized that the former are genetically similar to adenoma and the latter to adenocarcinoma and we used bioinformatics approach to search for candidate genes that might be potentially used to distinguish between the two lesions. We used publicly available data from Gene Expression Omnibus database and we analyzed gene expression profiles of 252 samples of normal mucosa, colorectal adenoma, and carcinoma. In total, we analyzed 122 colorectal adenomas, 59 colorectal carcinomas, and 62 normal mucosa samples. We have identified 16 genes with differential expression in carcinoma compared to adenoma:COL12A1,COL1A2,COL3A1, DCN, PLAU, SPARC, SPON2, SPP1,SULF1,FADS1, G0S2, EPHA4, KIAA1324,L1TD1, PCKS1, andC11orf96. In conclusion, ourin silicoanalysis revealed 16 candidate genes with different expression patterns in adenoma compared to carcinoma, which might be used to discriminate between these two lesions.


2021 ◽  
Author(s):  
Tian-Ao Xie ◽  
Hou-He Li ◽  
Zu-En Lin ◽  
Xiao-Ye Lin ◽  
Xin Meng ◽  
...  

Abstract Background: The Corona Virus Disease 2019 (COVID-19) pandemic poses a serious public health threat to the survival and health of people all over the world. We analyzed related mRNA data and gene expression profiles of human cell lines infected with SARS-CoV-2 obtained from GEO (GSE148729), using bioinformatics tools. Differentially expressed genes (DEGs) of human cells infected with SARS-CoV-2 were identified.Method: The GSE148729 datasets were downloaded from the Gene Expression Omnibus (GEO) database. To explore the Biological significance of DEGs, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the DEGs was performed. Protein-protein interaction (PPI) networks of the DEGs were constructed by using the STRING database. The hub genes were selected using the Cytoscape Software, and a t-test was performed to validate the hub genes.Result: A total of 1241 DEGs were screened, including 1049 up-regulated genes and 192 down-regulated genes. Besides, 10 hub genes were obtained from the PPI network, among which the expression level of CXCL2, Etv7, and HIST1H2BG was found to be statistically significant.Conclusion: In conclusion, bioinformatics analysis reveals genes and cellular pathways that are significantly altered in SARS-CoV-2 infected cells. This is conducive to further guide the clinical study of SARS-CoV-2 and provides new perspectives for vaccine development.


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