scholarly journals SDF4 Is a Prognostic Factor for 28-Days Mortality in Patients With Sepsis via Negatively Regulating ER Stress

2021 ◽  
Vol 12 ◽  
Author(s):  
Tingting Zhu ◽  
Qun Su ◽  
Cuili Wang ◽  
Lingling Shen ◽  
Hongjun Chen ◽  
...  
Keyword(s):  
Er Stress ◽  
Cecal Ligation ◽  
Clinical Signs ◽  
Gene Expression Omnibus ◽  
Hub Gene ◽  
Specificity And Sensitivity ◽  
Downstream Effects ◽  
Outcome Information ◽  
Stromal Cell Derived Factor ◽  
Geo Database

Sepsis is a heterogeneous syndrome induced by infection and results in high mortality. Even though more than 100 biomarkers for sepsis prognosis were evaluated, prediction of patient outcomes in sepsis continues to be driven by clinical signs because of unsatisfactory specificity and sensitivity of these biomarkers. This study aimed to elucidate the key candidate genes involved in sepsis response and explore their downstream effects based on weighted gene co-expression network analysis (WGCNA). The dataset GSE63042 with sepsis outcome information was obtained from the Gene Expression Omnibus (GEO) database and then consensus WGCNA was conducted. We identified the hub gene SDF4 (stromal cell derived factor 4) from the M6 module, which was significantly associated with mortality. Subsequently, two datasets (GSE54514 and E-MTAB-4421) and cohort validation (n=89) were performed. Logistic regression analysis was used to build a prediction model and the combined score resulting in a satisfactory prognosis value (area under the ROC curve=0.908). The model was subsequently tested by another sepsis cohort (n=70, ROC= 0.925). We next demonstrated that endoplasmic reticulum (ER) stress tended to be more severe in patients PBMCs with negative outcomes compared to those with positive outcomes and SDF4 was related to this phenomenon. In addition, our results indicated that adenovirus-mediated Sdf4 overexpression attenuated ER stress in cecal ligation and puncture (CLP) mice lung. In summary, our study indicates that incorporation of SDF4 can improve clinical parameters predictive value for the prognosis of sepsis, and decreased expression levels of SDF4 contributes to excessive ER stress, which is associated with worsened outcomes, whereas overexpression of SDF4 attenuated such activation.

Title: Weighted Gene Co-Expression Network Analysis Identifies Five Hub Genes Associated with Metastasis in Synovial Sarcoma

2021 ◽  
Vol 24 ◽  
Author(s):  
Hongzeng Wu ◽  
Benzheng Zhang ◽  
Jiazheng Zhao ◽  
Yi Zhao ◽  
Xiaowei Ma ◽  
...  
Keyword(s):  
Synovial Sarcoma ◽  
Tumor Metastasis ◽  
Gene Expression Omnibus ◽  
Survival Ratio ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Metastatic Lesions ◽  
Ppi Networks ◽  
Malignant Soft Tissue ◽  
Geo Database

Background: Synovial sarcoma (SS) refers to a malignant soft tissue sarcoma (STS) which often occurs in children and adults and has a poor prognosis in elderly patients. Patients with local lesions can be treated with extensive surgical resection combined with adjuvant or radiotherapy, whereas about half of the cases have recurrent diseases and metastatic lesions, and five-year survival ratio is assessed within the range of 27% - 55% only. Method: We downloaded a set of expression profile data (GSE40021) related to SS metastasis based on the Gene Expression Omnibus (GEO) database, and selected distinctly represented genes (DEGs) related to tumor metastasis. WGCNA was used to emphasize the DEGs related to tumor metastasis and obtain co-expression modules. Then, the module most related to SS metastasis was screened out. The genes enriched in this module were analyzed by Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway improvement analysis. Cytoscape software was used for constructing protein-protein interaction (PPI) networks, and hub genes were screened in Oncomine analysis. Result: We selected 514 DEGs, consisting of 210 up-regulated genes and 304 down-regulated genes. Through WGCAN, we got seven co-expression modules and the module most related to SS metastasis was the turquoise module, which contained 66 genes. Finally, we screened out five hub genes (HJURP, NCAPG, TPX2, CENPA, NDC80) through CytoHubba and Oncomine analysis. Conclusion: In this study, we screened five hub genes that may help in clinical diagnosis and serve as the latent purpose of SS treatment.

scholarly journals Characterization of Differentially Expressed miRNAs by CXCL12/SDF-1 in Human Bone Marrow Stromal Cells

2021 ◽  
Vol 12 (1) ◽  
pp. 132-143
Author(s):  
Matthew L. Potter ◽  
Kathryn Smith ◽  
Sagar Vyavahare ◽  
Sandeep Kumar ◽  
Sudharsan Periyasamy-Thandavan ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Fracture Healing ◽  
Osteogenic Differentiation ◽  
Stromal Cell ◽  
Target Genes ◽  
Fatty Acid Biosynthesis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Mirna Regulation ◽  
Stromal Cell Derived Factor

Abstract Stromal cell-derived factor 1 (SDF-1) is known to influence bone marrow stromal cell (BMSC) migration, osteogenic differentiation, and fracture healing. We hypothesize that SDF-1 mediates some of its effects on BMSCs through epigenetic regulation, specifically via microRNAs (miRNAs). MiRNAs are small non-coding RNAs that target specific mRNA and prevent their translation. We performed global miRNA analysis and determined several miRNAs were differentially expressed in response to SDF-1 treatment. Gene Expression Omnibus (GEO) dataset analysis showed that these miRNAs play an important role in osteogenic differentiation and fracture healing. KEGG and GO analysis indicated that SDF-1 dependent miRNAs changes affect multiple cellular pathways, including fatty acid biosynthesis, thyroid hormone signaling, and mucin-type O-glycan biosynthesis pathways. Furthermore, bioinformatics analysis showed several miRNAs target genes related to stem cell migration and differentiation. This study's findings indicated that SDF-1 induces some of its effects on BMSCs function through miRNA regulation.

scholarly journals Comparative Bioinformatics Characteristic of Bladder Cancer Stage 2 from Stage 4 Expression Profile: A Network-Based Study

2018 ◽  
Vol 7 ◽  
pp. e1279
Author(s):  
Mona Zamanian Azodi ◽  
Mostafa Rezaei-Tavirani ◽  
Mohammad Rostami-Nejad ◽  
Majid Rezaei-Tavirani
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Gene Expression Omnibus ◽  
Expression Data ◽  
Molecular Feature ◽  
Online Tool ◽  
Therapeutic Protocol ◽  
Stage 4 ◽  
Differential Network ◽  
Geo Database

Background: Bladder cancer (BC) has remained as one of the most challenging issues in medicine. The aim of this study was to investigate the differential network analysis of stages 2 and 4 of BC to better understand the molecular pathology of these states. Materials and Methods: We chose gene expression data of GSE52519 from Gene Expression Omnibus (GEO) database analyzed by the GEO2R online tool. Cytoscape version 3.6.1 and its algorithms are the methods applied for the network construction and investigation of differentially expressed genes (DEG) in these states. Result: Our result revealed that the analysis DEGs provides useful information about a common molecular feature of stages 2 and 4 of BC. Conclusion: Consequently, the network finding revealed that more investigation about stage 2 is required to achieve an effective therapeutic protocol to block the transition from stage 2 to stage 4.[GMJ.2018;7:e1279] 

scholarly journals Identification of hub genes and their clinical value for predicting the development of prostate cancer from benign prostate hyperplasia by bioinformatic analysis

2021 ◽  
Author(s):  
Xi Chen ◽  
Junjie Ma ◽  
Chengdang Xu ◽  
Licheng Wang ◽  
Yicong Yao ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Survival Data ◽  
Benign Prostate Hyperplasia ◽  
Disease Free Survival ◽  
Ppi Network ◽  
Hub Genes ◽  
Prostate Hyperplasia ◽  
Hub Gene ◽  
Benign Prostate ◽  
Geo Database

Abstract BackgroundProstate cancer (PCa) and benign prostate hyperplasia (BPH) are commonly encountered diseases in elderly males. The two diseases have some commonalities: both are growth depend on hormone and respond to antiandrogen therapy. Some studies have shown that genetic factors are responsible for the occurrences of both diseases. There may be a correlation between BPH and PCa. MethodsThe GEO database can help determine the differentially expressed genes (DEGs) between BPH and PCa. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were utilized to find pathways in which the DEGs were enriched. The STRING database can provide a protein–protein interaction (PPI) network, and Cytoscape software can find hub genes in PPI network. GEPIA can be used to analyze expression and survival data for hub genes. R software was used to progress regression analysis, decision curve analysis and built nomograph. UALCAN and The Human Protein Atlas was utilized to test the results. Finally, we made clinical and cell experiments to verify the results.ResultsSixty DEGs, consisting of 15 up-regulated and 45 down-regulated genes, were found based on the GEO database. Using Cytoscape, we found 7 hub gene in the PPI network. The hub gene expression was tested on TCGA database. Except CXCR4, all hub genes expressed differently between tumor and normal samples. Meanwhile, all hub genes exclude CXCR4 has diagnostic value in predicting PCa and their mutations are risk factors leading to PCa. The expression of CSRP1, MYL9 and SNAI2 changed in different tumor stage. CSRP1 and MYH11 could affect the disease-free survival (DFS). The same results reflected in different database. In addition, we also chose three hub gene, MYC, MYL9, and SNAI2, to validate their functions in clinical specimens and cells.ConclusionThese identified hub genes can help us to understand the process and mechanism by which BPH develops into PCa and provide achievable targets for predicting which BPH patients may later develop PCa.

scholarly journals Transcriptome Analysis of the Thymus in Short-Term Calorie-Restricted Mice Using RNA-seq

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Zehra Omeroğlu Ulu ◽  
Salih Ulu ◽  
Soner Dogan ◽  
Bilge Guvenc Tuna ◽  
Nehir Ozdemir Ozgenturk
Keyword(s):  
Calorie Restriction ◽  
Critical Role ◽  
Gene Expression Omnibus ◽  
Cdna Libraries ◽  
Rna Seq ◽  
Illumina Hiseq ◽  
Ncbi Gene Expression Omnibus ◽  
Important Player ◽  
Feeding Regimes ◽  
Geo Database

Calorie restriction (CR), which is a factor that expands lifespan and an important player in immune response, is an effective protective method against cancer development. Thymus, which plays a critical role in the development of the immune system, reacts to nutrition deficiency quickly. RNA-seq-based transcriptome sequencing was performed to thymus tissues of MMTV-TGF-α mice subjected to ad libitum (AL), chronic calorie restriction (CCR), and intermittent calorie restriction (ICR) diets in this study. Three cDNA libraries were sequenced using Illumina HiSeq™ 4000 to produce 100 base pair-end reads. On average, 105 million clean reads were mapped and in total 6091 significantly differentially expressed genes (DEGs) were identified (p<0.05). These DEGs were clustered into Gene Ontology (GO) categories. The expression pattern revealed by RNA-seq was validated by quantitative real-time PCR (qPCR) analysis of four important genes, which are leptin, ghrelin, Igf1, and adinopectin. RNA-seq data has been deposited in NCBI Gene Expression Omnibus (GEO) database (GSE95371). We report the use of RNA sequencing to find DEGs that are affected by different feeding regimes in the thymus.

scholarly journals mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell Biomarkers

Genes ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 257 ◽  
Author(s):  
Yitong Zhang ◽  
Joseph Ta-Chien Tseng ◽  
I-Chia Lien ◽  
Fenglan Li ◽  
Wei Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cell ◽  
Lung Adenocarcinoma ◽  
Tumor Necrosis Factor Receptor ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Clinical Stages ◽  
Key Genes ◽  
Geo Database

Cancer stem cells (CSCs), characterized by self-renewal and unlimited proliferation, lead to therapeutic resistance in lung cancer. In this study, we aimed to investigate the expressions of stem cell-related genes in lung adenocarcinoma (LUAD). The stemness index based on mRNA expression (mRNAsi) was utilized to analyze LUAD cases in the Cancer Genome Atlas (TCGA). First, mRNAsi was analyzed with differential expressions, survival analysis, clinical stages, and gender in LUADs. Then, the weighted gene co-expression network analysis was performed to discover modules of stemness and key genes. The interplay among the key genes was explored at the transcription and protein levels. The enrichment analysis was performed to annotate the function and pathways of the key genes. The expression levels of key genes were validated in a pan-cancer scale. The pathological stage associated gene expression level and survival probability were also validated. The Gene Expression Omnibus (GEO) database was additionally used for validation. The mRNAsi was significantly upregulated in cancer cases. In general, the mRNAsi score increases according to clinical stages and differs in gender significantly. Lower mRNAsi groups had a better overall survival in major LUADs, within five years. The distinguished modules and key genes were selected according to the correlations to the mRNAsi. Thirteen key genes (CCNB1, BUB1, BUB1B, CDC20, PLK1, TTK, CDC45, ESPL1, CCNA2, MCM6, ORC1, MCM2, and CHEK1) were enriched from the cell cycle Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, relating to cell proliferation Gene Ontology (GO) terms, as well. Eight of the thirteen genes have been reported to be associated with the CSC characteristics. However, all of them have been previously ignored in LUADs. Their expression increased according to the pathological stages of LUAD, and these genes were clearly upregulated in pan-cancers. In the GEO database, only the tumor necrosis factor receptor associated factor-interacting protein (TRAIP) from the blue module was matched with the stemness microarray data. These key genes were found to have strong correlations as a whole, and could be used as therapeutic targets in the treatment of LUAD, by inhibiting the stemness features.

Direct blood PCR detection of Babesia bigemina and its effect on haematological and biochemical profile in crossbred cattle of eastern Haryana

2017 ◽  
Author(s):  
Anita Ganguly ◽  
R. S. Bisla ◽  
Indrajit Ganguly ◽  
Harpreet Singh ◽  
Vandna Bhanot ◽  
...  
Keyword(s):  
Clinical Signs ◽  
Pcr Detection ◽  
Biochemical Profile ◽  
Crossbred Cattle ◽  
Babesia Bigemina ◽  
Direct Pcr ◽  
Blood Samples ◽  
Crossbred Cows ◽  
Specificity And Sensitivity ◽  
Healthy Control

The present study aimed to diagnose Babesia bigemina in naturally infected crossbred cows and to determine its effect on haemato-biochemical profile of host animals. Blood samples from lactating crossbred cows (n=30) between 3-6 years of age and showing clinical signs of babesiosis were collected, with or without anticoagulant, and analyzed for the protozoa by direct smear, direct blood PCR detection of the apical membrane antigen 1 (AMA-1) gene specific amplicon of B. bigemina and estimation of haematological and biochemical parameters. Healthy crossbred cows (n=10), examined free from haemoprotozoan infections were included as control. Blood Direct PCR revealed a 448-bp amplified fragment. Out of 150 random blood samples screened, (27/150) 18% were positive under light microscope, whereas direct blood PCR revealed (39/150) 26% samples positive for B. bigemina. The result shows higher specificity and sensitivity of PCR test over blood smear examination. The infected group showed significantly (p less than 0.001) decreased levels of TEC (3.04±0.19), Hb (4.78±0.27) and PCV (14.53 ±0.87) than healthy control animals. However, differences in the red blood cell indices (MCV, MCH and MCHC) were non-significant (p>0.05) between the groups indicating normocytic hypochromic anaemia in affected crossbred cattle. Serum samples of infected cows showed significantly (p less than 0.01) higher values of ALT (78.83±8.95), AST (146.13±7.62), BUN (27.09±1.02), creatinine (1.93±0.1) and TBIL (1.42±0.06) than that of healthy control. A significant decrease (p less than 0.01) of TSP (6.12±0.13) and albumin (2.39±0.09) was also recorded in the infected cows compare to healthy control. The standardized blood direct PCR method of the present investigation may be useful for rapid and reliable diagnosis of B. bigemina in conjunction with microscopic examination. Moreover, marked changes in haematological and serum biochemical profile observed in B. bigemina infected crossbred cows may be useful in understanding disease pathogenesis and undertaking necessary corrective measures..

scholarly journals Gene Differential Expression and Interaction Networks Illustrate the Biomarkers and Molecular Mechanisms of Atherosclerotic Cerebral Infarction

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Benzhuo Zhang ◽  
Wei Huang ◽  
Mingquan Yi ◽  
Chunxu Xing
Keyword(s):  
Network Analysis ◽  
Cerebral Infarction ◽  
Antigen Processing ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Neutrophil Activation ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Geo Database

Atherosclerotic cerebral infarction (ACI) seriously threatens the health of the senile patients, and the strategies are urgent for the diagnosis and treatment of ACI. This study investigated the mRNA profiling of the patients with ischemic stroke and atherosclerosis via excavating the datasets in the GEO database and attempted to reveal the biomarkers and molecular mechanism of ACI. In this study, GES16561 and GES100927 were obtained from Gene Expression Omnibus (GEO) database, and the related differentially expressed genes (DEGs) were analyzed with R language. Furthermore, the DEGs were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Besides, the protein-protein interaction (PPI) network of DEGs was analyzed by STRING database and Cytoscape. The results showed that 133 downregulated DEGs and 234 upregulated DEGs were found in GES16561, 25 downregulated DEGs and 104 upregulated DEGs were found in GSE100927, and 6 common genes were found in GES16561 and GES100927. GO enrichment analysis showed that the functional models of the common genes were involved in neutrophil activation, neutrophil degranulation, neutrophil activation, and immune response. KEGG enrichment analysis showed that the DEGs in both GSE100927 and GSE16561 were connected with the pathways including Cell adhesion molecules (CAMs), Cytokine-cytokine receptor interaction, Phagosome, Antigen processing and presentation, and Staphylococcus aureus infection. The PPI network analysis showed that 9 common DEGs were found in GSE100927 and GSE16561, and a cluster with 6 nodes and 12 edges was also identified by PPI network analysis. In conclusion, this study suggested that FCGR3A and MAPK pathways were connected with ACI.

scholarly journals Novel markers to detect HER2 amplification in Breast cancer

2021 ◽  
Author(s):  
Shikha Mudgal ◽  
Arnav Kalra ◽  
Shalinee Rao ◽  
Bina Ravi ◽  
Nilotpal Chowdhury
Keyword(s):  
Breast Cancer ◽  
In Situ Hybridization ◽  
Predictive Biomarker ◽  
Gene Expression Omnibus ◽  
Surrogate Markers ◽  
Her2 Expression ◽  
Her2 Amplification ◽  
Reflex Testing ◽  
Geo Database

Overexpression of HER2 in breast cancer is an important prognostic and predictive biomarker, assessed using immunohistochemistry (IHC) and in situ hybridization (ISH). More than 20% of tumours are graded equivocal on IHC and is send for reflex testing via ISH. In situ hybridization (ISH) is an expensive assay and is not available widely in resource limiting areas. Therefore, we propose that genes found significantly co-expressed with HER2 in breast cancer can be used as surrogate markers for HER2 in breast cancer which can detect HER2 positivity on IHC itself. This hypothesis is based on analysis of publicly available datasets from the Gene Expression Omnibus (GEO) database. The genes found most significantly correlated with HER2 expression were PGAP3 (r = 0.85), GRB7 (r = 0.82), STARD3 (r = 0.78), CDK12 (r= 0.68), PSMD3 (r= 0.67) and GSDMB (r = 0.63). We hypothesize that these identified surrogate markers for HER2 amplification which can be detected on IHC can detect HER2 amplification status in HER2 equivocal tumors based on IHC staining alone and will reduce the number of HER2 2+ (equivocal) category tumours.

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