scholarly journals Bioinformatic analysis identifies potential biomarkers and therapeutic targets of septic-shock-associated acute kidney injury

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Yun Tang ◽  
Xiaobo Yang ◽  
Huaqing Shu ◽  
Yuan Yu ◽  
Shangwen Pan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Septic Shock ◽  
Acute Kidney Injury ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Kidney Injury ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Blood Samples ◽  
Potential Biomarkers

Abstract Background Sepsis and septic shock are life-threatening diseases with high mortality rate in intensive care unit (ICU). Acute kidney injury (AKI) is a common complication of sepsis, and its occurrence is a poor prognostic sign to septic patients. We analyzed co-differentially expressed genes (co-DEGs) to explore relationships between septic shock and AKI and reveal potential biomarkers and therapeutic targets of septic-shock-associated AKI (SSAKI). Methods Two gene expression datasets (GSE30718 and GSE57065) were downloaded from the Gene Expression Omnibus (GEO). The GSE57065 dataset included 28 septic shock patients and 25 healthy volunteers and blood samples were collected within 0.5, 24 and 48 h after shock. Specimens of GSE30718 were collected from 26 patients with AKI and 11 control patents. AKI-DEGs and septic-shock-DEGs were identified using the two datasets. Subsequently, Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs. We also evaluated co-DEGs and corresponding predicted miRNAs involved in septic shock and AKI. Results We identified 62 DEGs in AKI specimens and 888, 870, and 717 DEGs in septic shock blood samples within 0.5, 24 and 48 h, respectively. The hub genes of EGF and OLFM4 may be involved in AKI and QPCT, CKAP4, PRKCQ, PLAC8, PRC1, BCL9L, ATP11B, KLHL2, LDLRAP1, NDUFAF1, IFIT2, CSF1R, HGF, NRN1, GZMB, and STAT4 may be associated with septic shock. Besides, co-DEGs of VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 coupled with corresponding predicted miRNAs, especially miR-29b-3p, miR-152-3p, and miR-223-3p may be regarded as promising targets for the diagnosis and treatment of SSAKI in the future. Conclusions Septic shock and AKI are related and VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 genes are significantly associated with novel biomarkers involved in the occurrence and development of SSAKI.

scholarly journals Evaluation of peptidylarginine deiminase 4 concentration and PADI4 polymorphisms in sepsis-induced acute kidney injury

2019 ◽  
Author(s):  
Nara Aline Costa ◽  
Bertha Furlan Polegato ◽  
Amanda Gomes Pereira ◽  
Rodrigo Velloni da Silva Bastos ◽  
Sérgio Alberto Rupp de Paiva ◽  
...  
Keyword(s):  
Septic Shock ◽  
Acute Kidney Injury ◽  
Renal Replacement Therapy ◽  
Kidney Injury ◽  
Peptidylarginine Deiminase ◽  
Plasma Urea ◽  
Blood Samples ◽  
Icu Stay ◽  
Plasma Urea Concentration ◽  
Its Polymorphism

Abstract Background: The influence of PAD4 concentration and its polymorphisms in SAKI development are poorly evaluated. Thus, the aim of this study is to evaluate the PAD 4 concentration and PADI4 polymorphisms, as predictors of AKI development, need for renal replacement therapy (RRT), and mortality in patients with septic shock. Methods: We included all individuals aged ≥ 18 years, with the diagnosis of septic shock at ICU admission. Blood samples were taken within the first 24 hours of the patient’s admission to determine serum PAD4 concentration and its polymorphism PADI4 (rs11203367) and (rs874881). Patients were followed during their ICU stay and the development of SAKI was evaluated. Among the patients in whom SAKI developed, mortality and need for RRT were also evaluated. Results: 99 patients were included in the analysis. SAKI developed in approximately 51.5% of patients during the ICU stay; of these, 21.5% required RRT and 80% died. There was no difference between PAD4 concentration (p = 0.116) and its polymorphisms rs11203367 (p = 0.910) and rs874881 (p = 0.769) in patients in whom SAKI did or did not develop. However, PAD4 had a positive correlation with plasma urea concentration (r = 0.269 and p = 0.007) and creatinine (r = 0.284 and p = 0.004). The PAD4 concentration and PADI4 polymorphisms were also not associated with RRT and with mortality in patients with SAKI. Conclusion: PAD4 concentration and its polymorphisms were not associated with SAKI development, the need for RRT, or mortality in patients with septic shock. However, PAD4 concentrations were associated with creatinine and urea levels in these patients.

scholarly journals Bioinformatics-Based Identification of lncRNA-miRNA-mRNA Network in Dilated Cardiomyopathy and Drug Prediction

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wei Liu ◽  
Jinqiang Cai ◽  
Mengjie Tang ◽  
QinJing Yang
Keyword(s):  
Gene Expression ◽  
Dilated Cardiomyopathy ◽  
Protein Interactions ◽  
Unknown Etiology ◽  
Pathway Enrichment Analysis ◽  
Blood Samples ◽  
Qrt Pcr ◽  
Cerna Network ◽  
Potential Biomarkers

Background. Dilated cardiomyopathy (DCM) is a cardiovascular disease of unknown etiology with progressive aggravation. More and more studies have shown that long noncoding RNAs (lncRNAs) play an essential role in dilated cardiomyopathy formation and development. The mechanism of action of competitive endogenous RNA (ceRNA) networks formed based on the principle that lncRNAs affect mRNAs’ expression level by competitively binding microRNAs (miRNAs) in dilated cardiomyopathy has rarely been reported. Objective. This study is aimed at constructing a lncRNA-miRNA-mRNA ceRNA network by bioinformatics analysis methods, discovering, and validating potential biomarkers of DCM in the ceRNA network and determining possible therapeutic targets from them for drug prediction. Methods. A lncRNA dataset and a mRNA microarray dataset were downloaded from the Gene Expression Omnibus Database (GEO). Gene expression was compared between blood samples from patients with dilated cardiomyopathy and blood samples from normal subjects to identify differential expression of lncRNAs and mRNAs. The lncRNA-miRNA-mRNA network was constructed using bioinformatics tools, and functional and pathway enrichment analysis and protein-protein interactions were performed. The mRNAs in the network and the proteins they encode are then used as targets for predicting drugs. Besides, the expression of lncRNAs in the ceRNA network was validated by real-time quantitative PCR (qRT-PCR) experiments in vitro. Results. The differentially expressed lncRNA-miRNA-mRNA ceRNA network in dilated cardiomyopathy was successfully established. Two differentially overexpressed key lncRNAs were found from the network: AC093817 and AC091062, and qRT-PCR experiments further validated the overexpression of AC093817 and AC091062. The mRNAs in the network and the proteins encoded by the mRNAs were used for drug prediction to get related drugs. Conclusion. This study supports a possible mechanism and drug development of dilated cardiomyopathy, AC093817 and AC091062 being potential biomarkers of dilated cardiomyopathy.

scholarly journals Bioinformatics Analysis Reveals the Potential Diagnostic Biomarkers for Abdominal Aortic Aneurysm

2021 ◽  
Vol 8 ◽  
Author(s):  
Xinsheng Xie ◽  
En ci Wang ◽  
Dandan Xu ◽  
Xiaolong Shu ◽  
Yu fei Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Inflammatory Responses ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Aortic Aneurysms ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Abdominal Aortic

Objectives: Abdominal aortic aneurysms (AAAs) are associated with high mortality rates. The genes and pathways linked with AAA remain poorly understood. This study aimed to identify key differentially expressed genes (DEGs) linked to the progression of AAA using bioinformatics analysis.Methods: Gene expression profiles of the GSE47472 and GSE57691 datasets were acquired from the Gene Expression Omnibus (GEO) database. These datasets were merged and normalized using the “sva” R package, and DEGs were identified using the limma package in R. The functions of these DEGs were assessed using Cytoscape software. We analyzed the DEGs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Protein–protein interaction networks were assembled using Cytoscape, and crucial genes were identified using the Cytoscape plugin, molecular complex detection. Data from GSE15729 and GSE24342 were also extracted to verify our findings.Results: We found that 120 genes were differentially expressed in AAA. Genes associated with inflammatory responses and nuclear-transcribed mRNA catabolic process were clustered in two gene modules in AAA. The hub genes of the two modules were IL6, RPL21, and RPL7A. The expression levels of IL6 correlated positively with RPL7A and negatively with RPL21. The expression of RPL21 and RPL7A was downregulated, whereas that of IL6 was upregulated in AAA.Conclusions: The expression of RPL21 or RPL7A combined with IL6 has a diagnostic value for AAA. The novel DEGs and pathways identified herein might provide new insights into the underlying molecular mechanisms of AAA.

scholarly journals A Network Pharmacology Study on the Molecular Mechanisms of FDY003 for Breast Cancer Treatment

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Ho-Sung Lee ◽  
In-Hee Lee ◽  
Kyungrae Kang ◽  
Sang-In Park ◽  
Seung-Joon Moon ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Herbal Medicines ◽  
Enrichment Analysis ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Anticancer Efficacy ◽  
Artemisia Capillaris

Herbal medicines have drawn considerable attention with regard to their potential applications in breast cancer (BC) treatment, a frequently diagnosed malignant disease, considering their anticancer efficacy with relatively less adverse effects. However, their mechanisms of systemic action have not been understood comprehensively. Based on network pharmacology approaches, we attempted to unveil the mechanisms of FDY003, an herbal drug comprised of Lonicera japonica Thunberg, Artemisia capillaris Thunberg, and Cordyceps militaris, against BC at a systemic level. We found that FDY003 exhibited pharmacological effects on human BC cells. Subsequently, detailed data regarding the biochemical components contained in FDY003 were obtained from comprehensive herbal medicine-related databases, including TCMSP and CancerHSP. By evaluating their pharmacokinetic properties, 18 chemical compounds in FDY003 were shown to be potentially active constituents interacting with 140 BC-associated therapeutic targets to produce the pharmacological activity. Gene ontology enrichment analysis using g:Profiler indicated that the FDY003 targets were involved in the modulation of cellular processes, involving the cell proliferation, cell cycle process, and cell apoptosis. Based on a KEGG pathway enrichment analysis, we further revealed that a variety of oncogenic pathways that play key roles in the pathology of BC were significantly enriched with the therapeutic targets of FDY003; these included PI3K-Akt, MAPK, focal adhesion, FoxO, TNF, and estrogen signaling pathways. Here, we present a network-perspective of the molecular mechanisms via which herbal drugs treat BC.

scholarly journals Identification and Verification of Core Genes in Colorectal Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Houxi Xu ◽  
Yuzhu Ma ◽  
Jinzhi Zhang ◽  
Jialin Gu ◽  
Xinyue Jing ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Malignant Neoplasm ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Core Genes

Colorectal cancer, a malignant neoplasm that occurs in the colorectal mucosa, is one of the most common types of gastrointestinal cancer. Colorectal cancer has been studied extensively, but the molecular mechanisms of this malignancy have not been characterized. This study identified and verified core genes associated with colorectal cancer using integrated bioinformatics analysis. Three gene expression profiles (GSE15781, GSE110223, and GSE110224) were downloaded from the Gene Expression Omnibus (GEO) databases. A total of 87 common differentially expressed genes (DEGs) among GSE15781, GSE110223, and GSE110224 were identified, including 19 upregulated genes and 68 downregulated genes. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed for common DEGs using clusterProfiler. These common DEGs were significantly involved in cancer-associated functions and signaling pathways. Then, we constructed protein-protein interaction networks of these common DEGs using Cytoscape software, which resulted in the identification of the following 10 core genes: SST, PYY, CXCL1, CXCL8, CXCL3, ZG16, AQP8, CLCA4, MS4A12, and GUCA2A. Analysis using qRT-PCR has shown that SST, CXCL8, and MS4A12 were significant differentially expressed between colorectal cancer tissues and normal colorectal tissues (P<0.05). Gene Expression Profiling Interactive Analysis (GEPIA) overall survival (OS) has shown that low expressions of AQP8, ZG16, CXCL3, and CXCL8 may predict poor survival outcome in colorectal cancer. In conclusion, the core genes identified in this study contributed to the understanding of the molecular mechanisms involved in colorectal cancer development and may be targets for early diagnosis, prevention, and treatment of colorectal cancer.

scholarly journals Evaluation of peptidylarginine deiminase 4 and PADI4 polymorphisms in sepsis-induced acute kidney injury

2020 ◽  
Vol 66 (11) ◽  
pp. 1515-1520
Author(s):  
Nara Aline Costa ◽  
Bertha Furlan Polegato ◽  
Amanda Gomes Pereira ◽  
Sérgio Alberto Rupp de Paiva ◽  
Ana Lúcia Gut ◽  
...  
Keyword(s):  
Septic Shock ◽  
Acute Kidney Injury ◽  
Renal Replacement Therapy ◽  
Replacement Therapy ◽  
Kidney Injury ◽  
Peptidylarginine Deiminase ◽  
Plasma Urea ◽  
Blood Samples ◽  
Peptidylarginine Deiminase 4 ◽  
Plasma Urea Concentration

SUMMARY BACKGROUND: The aim of this study is to evaluate the peptidylarginine deiminase 4 (PAD 4) concentration and PADI4 polymorphisms as predictors of acute kidney injury (AKI) development, the need for renal replacement therapy (RRT), and mortality in patients with septic shock. METHODS: We included all individuals aged ≥ 18 years, with a diagnosis of septic shock at ICU admission. Blood samples were taken within the first 24 hours of the patient's admission to determine serum PAD4 concentration and its PADI4 polymorphism (rs11203367) and (rs874881). Patients were monitored during their ICU stay and the development of SAKI was evaluated. Among the patients in whom SAKI developed, mortality and the need for RRT were also evaluated. RESULTS: There were 99 patients, 51.5% of whom developed SAKI and of these, 21.5% needed RRT and 80% died in the ICU. There was no difference between PAD4 concentration (p = 0.116) and its polymorphisms rs11203367 (p = 0.910) and rs874881 (p = 0.769) in patients in whom SAKI did or did not develop. However, PAD4 had a positive correlation with plasma urea concentration (r = 0.269 and p = 0.007) and creatinine (r = 0.284 and p = 0.004). The PAD4 concentration and PADI4 polymorphisms were also not associated with RRT and with mortality in patients with SAKI. CONCLUSION: PAD4 concentration and its polymorphisms were not associated with SAKI development, the need for RRT, or mortality in patients with septic shock. However, PAD4 concentrations were associated with creatinine and urea levels in these patients.

scholarly journals Identification of Potential Key Genes and Pathways in Enzalutamide-Resistant Prostate Cancer Cell Lines: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) Database

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Long Zheng ◽  
Xiaojie Dou ◽  
Xiaodong Ma ◽  
Wei Qu ◽  
Xiaoshuang Tang
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Cell Lines ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Key Genes ◽  
Geo Database

Enzalutamide (ENZ) has been approved for the treatment of advanced prostate cancer (PCa), but some patients develop ENZ resistance initially or after long-term administration. Although a few key genes have been discovered by previous efforts, the complete mechanisms of ENZ resistance remain unsolved. To further identify more potential key genes and pathways in the development of ENZ resistance, we employed the GSE104935 dataset, including 5 ENZ-resistant (ENZ-R) and 5 ENZ-sensitive (ENZ-S) PCa cell lines, from the Gene Expression Omnibus (GEO) database. Integrated bioinformatics analyses were conducted, such as analysis of differentially expressed genes (DEGs), Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein-protein interaction (PPI) analysis, gene set enrichment analysis (GSEA), and survival analysis. From these, we identified 201 DEGs (93 upregulated and 108 downregulated) and 12 hub genes (AR, ACKR3, GPER1, CCR7, NMU, NDRG1, FKBP5, NKX3-1, GAL, LPAR3, F2RL1, and PTGFR) that are potentially associated with ENZ resistance. One upregulated pathway (hedgehog pathway) and seven downregulated pathways (pathways related to androgen response, p53, estrogen response, TNF-α, TGF-β, complement, and pancreas β cells) were identified as potential key pathways involved in the occurrence of ENZ resistance. Our findings may contribute to further understanding the molecular mechanisms of ENZ resistance and provide some clues for the prevention and treatment of ENZ resistance.

scholarly journals Metabolomics Analysis of the Development of Sepsis and Potential Biomarkers of Sepsis-Induced Acute Kidney Injury

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Feng Ping ◽  
Yingchuan Li ◽  
Yongmei Cao ◽  
Jiawei Shang ◽  
Zhongwei Zhang ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Kidney Diseases ◽  
Early Stage ◽  
Petroselinic Acid ◽  
Univariate Analysis ◽  
Elevated Serum ◽  
Kidney Injury ◽  
Pathway Enrichment Analysis ◽  
Sprague Dawley ◽  
Potential Biomarkers

Sepsis-induced acute kidney injury (SI-AKI) is a serious condition in critically ill patients. Currently, the diagnosis is based on either elevated serum creatinine levels or oliguria, which partially contribute to delayed recognition of AKI. Metabolomics is a potential approach for identifying small molecule biomarkers of kidney diseases. Here, we studied serum metabolomics alterations in rats with sepsis to identify early biomarkers of sepsis and SI-AKI. A rat model of SI-AKI was established by intraperitoneal injection of lipopolysaccharide (LPS). Thirty Sprague-Dawley (SD) rats were randomly divided into the control (CT) group and groups treated for 2 hours (LPS2) and 6 hours (LPS6) with LPS (10 rats per group). Nontargeted metabolomics screening was performed on the serum samples from the control and SI-AKI groups. Combined multivariate and univariate analysis was used for pairwise comparison of all groups to identify significantly altered serum metabolite levels in early-stage AKI in rats with sepsis. Orthogonal partial least squares discriminant analysis (OPLS-DA) showed obvious separation between the CT and LPS2 groups, CT and LPS6 groups, and LPS2 and LPS6 groups. All comparisons of the groups identified a series of differential metabolites according to the threshold defined for potential biomarkers. Intersections and summaries of these differential metabolites were used for pathway enrichment analysis. The results suggested that sepsis can cause an increase in systemic aerobic and anaerobic metabolism, an impairment of the oxygen supply, and uptake and abnormal fatty acid metabolism. Changes in the levels of malic acid, methionine sulfoxide, and petroselinic acid were consistently measured during the progression of sepsis. The development of sepsis was accompanied by the development of AKI, and these metabolic disorders are directly or indirectly related to the development of SI-AKI.

Novel Insight Into the Association Between Obesity and Hepatocellular Carcinoma Occurrence and Recurrence: High-Throughput Microarray Data Set Analysis of Differentially Expressed Genes

2021 ◽  
pp. 1169-1180
Author(s):  
Seyedeh Faezeh Hassani ◽  
Masoud Sayaf ◽  
Seyedeh Sara Danandeh ◽  
Zahra Nourollahzadeh ◽  
Mahshid Shahmohammadi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Differentially Expressed Genes ◽  
Microarray Data ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Data Set ◽  
Potential Biomarkers

PURPOSE This study aims to identify potential biomarkers of hepatocellular carcinoma (HCC) occurrence/recurrence and obesity, along with the molecular mechanisms that involve these biomarkers. METHODS Three microarray data sets, namely GSE18897, GSE25097, and GSE36376 (genetic suppressor elements associated with obesity, tumor, and recurrence, respectively), were downloaded from Gene Expression Omnibus database to be investigated for their expression as differentially expressed genes (DEGs) in HCC and obesity. The functional and pathway enrichment analysis of these DEGs were identified by the Database for Annotation Visualization and Integrated Discovery. The protein-protein interaction network analysis was performed with STRING online tool and Cytoscape software. RESULTS One hundred sixty common DEGs were screened. We found that these genes were associated with certain pathways such as metabolic pathways, terpenoid backbone biosynthesis, and adipocytokine signaling pathway. The involvements of 10 genes, including RPS16, RPS7, CCT3, HNRNPA2B1, EIF4G1, PSMC4, NHP2, EGR1, FDPS, and MCM4, were identified in the subnetwork. HNRNPA2B1 and RPS7 in the GSE18897 data set, RPS16, RPS7, CCT3, HNRNPA2B1, PSMC4, NHP2, FDPS, and MCM4 in the GSE25097 data set, and RPS16, RPS7, CCT3, HNRNPA2B1, EIF4G1, PSMC4, NHP2, FDPS, and MCM4 in the GSE36376 data set exhibited positive fold changes. CONCLUSION These DEGs and pathways could be of diagnostic value as potential biomarkers involved in the pathogenesis of HCC, pertaining to both obesity and HCC occurrence/recurrence.

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