Identification of Potential Tumor-educated Platelets RNA Biomarkers for Pan Cancer Detection and Staging

2020 ◽  
Author(s):  
Xinxin Ge ◽  
Liuxia Yuan ◽  
Ying Hu ◽  
Bin Cheng ◽  
Khan Muhammad Shoaib ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Enrichment Analysis ◽  
Diagnostic Value ◽  
Metabolic Process ◽  
Pathway Enrichment Analysis ◽  
High Morbidity ◽  
Healthy Controls ◽  
Roc Curve Analysis ◽  
Pathway Enrichment ◽  
Pan Cancer

Abstract Cancer is a disturbing disease with high morbidity and mortality. Although medical technology has been developed rapidly, diagnosis of cancer is still complicated, difficult, as well as expensive. Furthermore, cancers are mostly diagnosed at an advanced stage. Platelets mRNA profiles are altered after educated by tumors. Thereby, tumor-educated platelets (TEPs) mRNA profiles have the potentially diagnostic value for cancers currently. We downloaded and analyzed the next-generation sequencing datasets, GSE68086 and GSE89843, by integrated bioinformatics. A total of 43 biomarker genes were selected for further pathway enrichment analysis and correlation analysis, as well as diagnostic analysis. Gene ontology (GO) analysis showed these 43 TEPs mRNAs were mostly involved in protein binding, extracellular matrix and cellular protein metabolic process. Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis revealed that genes were mainly enriched in metabolic process. Eventually, after taking these 43 genes into spearman correlation analysis and receiving operating characteristic (ROC) curve analysis, we identified: 1) TEPs RSL24D1 mRNA was negatively related to early pan cancer as compared to healthy controls, and potential for early pan cancer diagnosis with a sensitivity of 71.8%, and a specificity of 64.3%; 2) HPSE, IFI27, LGALS3BP, CRYM, HBD, COL6A3, LAMB2, and IFITM3 showed an upward trend in the expression from early to more advanced pan cancer stages. The sensitivity of the diagnostic value for pan cancer of these genes was 60.9%, 59.1%, 56.5%, 57.8%, 54.3%, 55.2%, 55.2%, 60.9%, and a specificity of 94.5%, 90.9%, 87.3%, 89.1%, 72.7%, 85.5%, 89.1%, 94.5% respectively; 3) ARL2, FCGR2A, and KLHDC8B were positively associated with advanced, metastatic pan cancer as compared to healthy controls and could be diagnostic indicators for advanced pan cancer with a sensitivity of 59.2%, 61.8%, 59.7%, and a specificity of 80%, 89.1%, 83.6%, respectively. In summary, our findings identified that the 12-gene TEP liquid-biopsy biomarkers will not only facilitate early diagnosis of pan cancer, but also be beneficial to pan cancer staging.

scholarly journals Identification of Urine Metabolic Biomarkers for Vogt-Koyanagi-Harada Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Rui Chang ◽  
Ying Zhu ◽  
Jing Xu ◽  
Lin Chen ◽  
Guannan Su ◽  
...  
Keyword(s):  
High Performance ◽  
Area Under The Curve ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Healthy Controls ◽  
Roc Curve Analysis ◽  
Multivariate Statistical ◽  
Flight Mass Spectrometry ◽  
Laboratory Biomarkers ◽  
Vkh Disease

The diagnosis of Vogt-Koyanagi-Harada (VKH) disease is mainly based on a complex clinical manifestation while it lacks objective laboratory biomarkers. To explore the potential molecular biomarkers for diagnosis and disease activity in VKH, we performed an untargeted urine metabolomics analysis by ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS). Through univariate and multivariate statistical analysis, we found 9 differential metabolites when comparing VKH patients with healthy controls, and 26 differential metabolites were identified when comparing active VKH patients with inactive VKH patients. Pathway enrichment analysis showed that glycine, serine and threonine metabolism, and arginine and proline metabolism were significantly altered in VKH versus healthy controls. Lysine degradation and biotin metabolism pathways were significantly altered in active VKH versus inactive VKH. Furthermore, the receiver operating characteristic (ROC) curve analysis revealed that the combination of acetylglycine and gamma-glutamylalanine could differentiate VKH from healthy controls with an area under the curve (AUC) of 0.808. A combination of ureidopropionic acid and 5′-phosphoribosyl-5-amino-4-imidazolecarboxamide (AICAR) had an excellent AUC of 0.958 for distinguishing active VKH from inactive VKH. In summary, this study identified abnormal metabolites in urine of patients with VKH disease. Further studies are needed to confirm whether these metabolites are specific for this disease.

scholarly journals Identification of Potential Autophagy-Related Genes in Steroid-Induced Osteonecrosis of the Femoral Head

2021 ◽  
Author(s):  
XueZhen LIANG ◽  
Di LUO ◽  
Yan-Rong CHEN ◽  
Jia-Cheng LI ◽  
Bo-Zhao YAN ◽  
...  
Keyword(s):  
Femoral Head ◽  
Correlation Analysis ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
R Software ◽  
Pathway Enrichment

Abstract Purpose: Steroid-induced osteonecrosis of the femoral head (SONFH) was a refractory orthopedic hip joint disease in the young and middle-aged people. Previous experimental studies had shown that autophagy might be involved in the pathological process of SONFH, but the pathogenesis of autophagy in SONFH remained unclear. We aim to identify and validate the key potential autophagy-related genes of SONFH to further illustrate the mechanism of autophagy in SONFH through bioinformatics analysis. Methods: The mRNA expression profile dataset GSE123568 was download from Gene Expression Omnibus (GEO) database, including 10 non-SONFH (following steroid administration) samples and 30 SONFH samples. The autophagy-related genes were obtained from the Human Autophagy Database (HADb). The autophagy-related genes of SONFH were screened by intersecting GSE123568 dataset with autophagy genes. The differentially expressed autophagy-related genes of SONFH were identified by R software. Besides, the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted for the differentially expressed autophagy-related genes of SONFH by R software. Then, the correlation analysis between the expression levels of differentially expressed autophagy-related genes of SONFH was confirmed by R software. Moreover, the protein–protein interaction (PPI) network were analyzed by the Search Tool for the Retrieval of Interacting Genes (STRING), and the significant gene cluster modules were identified by the MCODE Cytoscape plugin, and hub genes of differentially expressed autophagy-related genes of SONFH were screened by the CytoHubba Cytoscape plugin. Finally, the expression levels of hub genes of differentially expressed autophagy-related genes of SONFH was validated in hip articular cartilage specimens from necrosis femur head (NFH) by GSE74089 dataset. Results: A total of 34 differentially expressed autophagy-related genes were identified between the peripheral blood of SONFH samples and non-SONFH Samples based on the defined criteria, including 25 up-regulated genes and 9 down-regulated genes. The GO and KEGG pathway enrichment analysis revealed that these 34 differentially expressed autophagy-related genes of SONFH were concentrated in death domain receptors, FOXO signaling pathway and apoptosis. The correlation analysis revealed a significant correlation among the 34 differentially expressed autophagy-related genes of SONFH. The PPI results demonstrated that the 34 differentially expressed autophagy-related genes interacted with each other. There were 10 hub genes identified by the MCC algorithms of Cytohubba. The results of GSE74089 dataset showed TNFSF10, PTEN and CFLAR were significantly upregulated while BCL2L1 were significantly downregulated in the hip cartilage specimens, which were consistent with the GSE123568 dataset. Conclusions: There were 34 potential autophagy-related genes of SONFH identified using bioinformatics analysis. TNFSF10, PTEN, CFLAR and BCL2L1 might serve as potential drug targets and biomarkers by regulating autophagy. These results would expand new insights into the autophagy-related understanding of SONFH and might be useful in the diagnosis and prognosis of SONFH.

scholarly journals A Unique Monocyte Transcriptome Discriminates Sickle Cell Disease from Other Hereditary Hemolytic Anemias and Shows the Particular Importance of Lipid and Interferon Signaling

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 980-980
Author(s):  
Annelies J. Van Vuren ◽  
Stephanie van Straaten ◽  
Michal Mokry ◽  
Richard van Wijk ◽  
Eduard J. van Beers
Keyword(s):  
Research Funding ◽  
Enrichment Analysis ◽  
The Other ◽  
Pathway Enrichment Analysis ◽  
Type I ◽  
Healthy Controls ◽  
Cell Disease ◽  
Immune Signaling ◽  
Tlr4 Signaling ◽  
Pathway Enrichment

Introduction Sickle cell disease (SCD) is a hereditary hemolytic disease characterized by a complex pathophysiology including inflammation and oxidative stress. Intravascular hemolysis leads to release of heme, an erythrocyte-derived Danger Associated Molecular Pattern (e-DAMP) that augments Toll Like Receptor 4 (TLR4) signaling. TLR4 signaling is important in development of acute and chronic complications in SCD. We investigated gene expression profiles of TLR4+ cells (by positive selection of its co-receptor CD14) of patients with SCD and other hemolytic anemias to identify differential regulated pathophysiological pathways. Methods Analyses were performed in 60 adults with hereditary hemolytic anemia and 10 healthy controls included in the ZEbRA cohort (UMC Utrecht, [NL5189]). Patients treated with systemic anti-inflammatory drugs were excluded (n=1). Deferasirox (DFX)-treated SCD patients were analyzed separately as DFX ameliorated pro-inflammatory effects of heme. CD14+ cells were isolated using anti-CD14 microbeads. RNA sequencing was performed on a Nextseq500 platform (Illumina) using a single-end 75bp high-output run. Differentially expressed genes (DEGs) were identified using DESeq2 v1.24.0 in R. To correct for presence of reticulocytes and lymphocytes, data were corrected for expression of 4 hemoglobin (HBA1, HBB, HBG1, HBG2) and 4 T cell specific genes (CD3E, CD3D, CD3G, CD247). A list was constructed from all genes differentially expressed (adj. p<0.01; absolute log2fold change >1) in both the comparisons of SCD without DFX versus other hemolytic anemias and of SCD without DFX versus healthy controls. Pathway enrichment analysis (ReactomePA v1.28.0 in R) was performed with preselected DEGs (adj. p<0.1; absolute log2fold change >0.5). P-values were adjusted with the Benjamini-Hochberg procedure. Results Demographics and hematological values are provided in Table 1. Principal component analysis based on RNA sequencing data separated SCD patients without DFX from hemolytic anemia patients, healthy controls and SCD patients with DFX (Figure 1). Analysis of DEGs discriminating SCD patients from both patients with other hemolytic anemias and healthy controls rendered 29 genes (Figure 2). Heme oxygenase-1 (HMOX1) was one of these genes (versus healthy controls adj. p=5.6E-13; versus other hemolytic anemias adj. p=3.3E-15) and this is in line with the hypothesis that intravascular free heme is an important effector of gene regulation in monocytes. This sets SCD apart from the other studied hemolytic anemias. The other 28 genes included, PPARG, GUCY1A1, KLF5 and CXCR3 signaling (CXCL9 and CXCL11) which are associated with vascular remodeling and development of pulmonary hypertension. The list of 29 DEGs highlights interesting differences in gene expression of two processes related to immune signaling: CXCR3 signaling by CXCL9 and CXCL11, and lipid metabolism (STARD4, DLC1, SQLE, ME1). Pathway enrichment analysis showed enrichment of genes involved in IFN signaling (type I and II) in SCD versus healthy controls (adj. p=4.4E-16). And, in line with the list of 29 genes, enrichment of genes concerning chemokine signaling in SCD versus both healthy controls and other hemolytic anemias (respectively adj. p=0.06 and adj. p=0.01) and cholesterol biosynthesis in SCD versus other hemolytic anemias (adj. p=0.09). Conclusion Our data shows the unique inflammatory profile of SCD monocytes as opposed to other hemolytic anemias. Moreover, it suggests that lipid metabolism and IFN signaling are important differentiating immune signaling pathways. It is known that alterations in plasma lipid levels in SCD relate to hemolytic severity and vasculopathy. Our data suggests an important role for lipid biology in SCD monocytes. We hypothesize on an important contribution of cholesterol accumulation in enhancement of TLR4 signaling, as lipid rafts accelerated Nf-kB activation in macrophages. (Lee et al., Nat. Commun. 2017; Koseki et al., J. Lip. Res. 2007) The importance of type I and II IFN signaling in SCD suggests widespread involvement of the immune system. IFNg-inducible cytokines CXCL9 and CXCL11 are associated with Th1 polarization and activation. In summary, the data support the unique role of monocyte immune signaling in SCD. Furthermore, we identified pathways that seem to be relevant for immune regulation and thereby for development of disease complications. Disclosures van Wijk: Agios Pharmaceuticals: Consultancy, Research Funding; RR Mechatronics: Research Funding. van Beers:Agios Pharmaceuticals, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; RR Mechatronics: Research Funding; Novartis: Consultancy, Research Funding.

scholarly journals Serum metabolomic alterations in Beagle dogs experimentally infected with Toxocara canis

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Wen-Bin Zheng ◽  
Yang Zou ◽  
Hany M. Elsheikha ◽  
Guo-Hua Liu ◽  
Min-Hua Hu ◽  
...  
Keyword(s):  
Roc Curve ◽  
Unsaturated Fatty Acids ◽  
Enrichment Analysis ◽  
Toxocara Canis ◽  
Diagnostic Value ◽  
Pathway Enrichment Analysis ◽  
Biosynthesis Pathway ◽  
Roc Curve Analysis ◽  
Hormone Biosynthesis ◽  
Globally Distributed

Abstract Background Toxocara canis, a globally distributed roundworm, can cause debilitating disease in dogs and humans; however, little is known about the metabolomic response of the hosts to T. canis infection. There is an increasing need to understand the metabolic mechanisms underlying the pathogenesis of T. canis infection in dogs. Here, we examined the metabolomic changes in Beagle dogsʼ serum following T. canis infection using LC-MS/MS. Results The metabolic profiles of Beagle dogsʼ serum were determined at 12 h, 24 h, 10 d and 36 d after oral infection with 300 infectious T. canis eggs by LC-MS/MS. We tested whether the T. canis-associated differentially abundant metabolites could distinguish the serum of infected dogs from controls, as measured by the area under the receiver operating characteristic (ROC) curve (AUC). The differentially expressed metabolites were further evaluated by principal components analysis and pathway enrichment analysis. A total of 5756 and 5299 ions were detected in ESI+ and ESI− mode, respectively. ROC curve analysis revealed nine and five metabolite markers, at 12 hpi and 24 hpi to 36 dpi, respectively, with potential diagnostic value for toxocariasis. The levels of taurocholate, estradiol, prostaglandins and leukotriene were significantly changed. Primary bile acid biosynthesis pathway, steroid hormone biosynthesis pathway and biosynthesis of unsaturated fatty acids pathway were significantly altered by T. canis infection. Conclusions These findings show that T. canis infection can induce several changes in the dog serum metabolome and that the metabolic signature associated with T. canis infection in dogs has potential for toxocariasis diagnosis.

Abnormal Platelet miRNA Profile Associated with Endometriosis

2020 ◽  
Vol 12 (7) ◽  
pp. 863-873
Author(s):  
Miaomiao Du ◽  
Jiabao Wu ◽  
Yali Zhu ◽  
Di Mao ◽  
Zhihong Liu ◽  
...  
Keyword(s):  
Target Gene ◽  
High Throughput Sequencing ◽  
Blood Platelets ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Healthy Controls ◽  
Pathway Enrichment ◽  
Cyclin Protein ◽  
Dual Pathway

Endometriosis (EM) is a condition characterized by the growth of functional endometrium in areas other than the uterus. In this study, microRNAs (miRNAs) were extracted from peripheral blood platelets from patients diagnosed with EM and from healthy controls for high-throughput sequencing; differential expression of miR-542-3p and miR-618 was identified via database comparisons. Dual pathway enrichment analysis revealed that both miRNAs may target the cyclin protein, G1/S-specific cyclin-D2 (CCND2). CCND2 was verified as a target gene of both miR-542-3p and miR-618 via experiments carried out in vivo. Taken together, these results reveal that CCND2 may serve as a functional biomarker for the diagnosis of EM.

A Method of Pathway Enrichment Analysis Based Gene Expression Variability

2013 ◽  
Vol 40 (12) ◽  
pp. 1256
Author(s):  
XiaoDong JIA ◽  
XiuJie CHEN ◽  
Xin WU ◽  
JianKai XU ◽  
FuJian TAN ◽  
...  
Keyword(s):  
Gene Expression ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Expression Variability ◽  
Pathway Enrichment

Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

2019 ◽  
Vol 22 (6) ◽  
pp. 411-420 ◽  
Author(s):  
Xian-Jun Wu ◽  
Xin-Bin Zhou ◽  
Chen Chen ◽  
Wei Mao
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Diseases ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Pathway Enrichment ◽  
Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

scholarly journals Signature RNAS and related regulatory roles in type 1 diabetes mellitus based on competing endogenous RNA regulatory network analysis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qinghong Shi ◽  
Hanxin Yao
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Network Analysis ◽  
Type 1 Diabetes Mellitus ◽  
Regulatory Network ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Competing Endogenous Rna ◽  
Pathway Enrichment

Abstract Background Our study aimed to investigate signature RNAs and their potential roles in type 1 diabetes mellitus (T1DM) using a competing endogenous RNA regulatory network analysis. Methods Expression profiles of GSE55100, deposited from peripheral blood mononuclear cells of 12 T1DM patients and 10 normal controls, were downloaded from the Gene Expression Omnibus to uncover differentially expressed long non-coding RNAs (lncRNAs), mRNAs, and microRNAs (miRNAs). The ceRNA regulatory network was constructed, then functional and pathway enrichment analysis was conducted. AT1DM-related ceRNA regulatory network was established based on the Human microRNA Disease Database to carry out pathway enrichment analysis. Meanwhile, the T1DM-related pathways were retrieved from the Comparative Toxicogenomics Database (CTD). Results In total, 847 mRNAs, 41 lncRNAs, and 38 miRNAs were significantly differentially expressed. The ceRNA regulatory network consisted of 12 lncRNAs, 10 miRNAs, and 24 mRNAs. Two miRNAs (hsa-miR-181a and hsa-miR-1275) were screened as T1DM-related miRNAs to build the T1DM-related ceRNA regulatory network, in which genes were considerably enriched in seven pathways. Moreover, three overlapping pathways, including the phosphatidylinositol signaling system (involving PIP4K2A, INPP4A, PIP4K2C, and CALM1); dopaminergic synapse (involving CALM1 and PPP2R5C); and the insulin signaling pathway (involving CBLB and CALM1) were revealed by comparing with T1DM-related pathways in the CTD, which involved four lncRNAs (LINC01278, TRG-AS1, MIAT, and GAS5-AS1). Conclusion The identified signature RNAs may serve as important regulators in the pathogenesis of T1DM.

Identification of novel cardiovascular disease associated metabolites using untargeted metabolomics

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Shams Tabrez ◽  
Mohammed Razeeth Shait Mohammed ◽  
Nasimudeen R. Jabir ◽  
Mohammad Imran Khan
Keyword(s):  
Cardiovascular Disease ◽  
Metabolic Pathways ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Healthy Individuals ◽  
Great Opportunity ◽  
Pathway Enrichment ◽  
Pathophysiological Role ◽  
The World ◽  
Metabolomic Approach

Abstract Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality around the world. Early diagnosis of CVD could provide the opportunity for sensible management and better clinical outcome along with the prevention of further progression of the disease. In the current study, we used an untargeted metabolomic approach to identify possible metabolite(s) that associate well with the CVD and could serve either as therapeutic target or disease-associated metabolite. We identified 26 rationally adjusted unique metabolites that were differentially present in the serum of CVD patients compared with healthy individuals, among them 15 were found to be statistically significant. Out of these metabolites, we identified some novel metabolites like UDP-l-rhamnose and N1-acetylspermidine that have not been reported to be linked with CVD directly. Further, we also found that some metabolites like ethanolamide, solanidine, dimethylarginine, N-acetyl-l-tyrosine, can act as a discriminator of CVD. Metabolites integrating pathway enrichment analysis showed enrichment of various important metabolic pathways like histidine metabolism, methyl histidine metabolism, carnitine synthesis, along with arginine and proline metabolism in CVD patients. Our study provides a great opportunity to understand the pathophysiological role and impact of the identified unique metabolites and can be extrapolated as specific CVD specific metabolites.

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