Pathway Protein-protein Interaction Research Articles

STEM-08. ANGIOGENESIS IN PEDIATRIC CHOROID PLEXUS PAPILLOMAS

Abstract BACKGROUND Choroid plexus papillomas (CPP) are rare brain tumors that tend to occur in very young children. Although most of them are curative with surgical resection, a subset of them has propensity for tumor recurrence, progression, and metastasis. Moreover, surgery can be technically difficult due to their deep locations and high vascularity. In-depth mechanisms of their biology remain poorly understood. Separately, the process of angiogenesis has been implicated in several cancers. To date, there has been no previous study focused on CPP and angiogenesis. This study aims to explore and ascertain the existence of angiogenesis in CPP. METHODS This is a study approved by the hospital ethics review board. Cerebrospinal fluid (CSF) and CPP tumor samples are collected at the time of surgery. A multiplex immunoassay panel is used to measure cytokine concentrations in the CSF samples. Identified cytokines of interest are input into online platforms to assess for protein-protein interaction pathways. Concurrently, patient-derived primary cell cultures and their supernatants are derived from CPP samples. A targeted proteome blot array and HUVEC tubule formation assays are used to validate clinical and in silico findings. RESULT CSF profiling showed higher expression of MCP-1, MMP-1, IL-2, TNF-ɑ, TRAIL and CD40-L in CPP patient samples versus non-tumor controls. Next, in silico assessment via STRING and BioGRID platforms report that these cytokines are associated with endothelial cell regulation. This is clinically relevant as we are aware that the endothelium has important functions in the regulation of angiogenesis. Using an angiogenesis-focused approach, CPP-derived cell lines and supernatants showed congruently higher expression of MCP-1, MMP-1 and TNF-ɑ. Next, tubule formation was observed in HUVEC cultures where conditioned CPP cell culture media was added. CONCLUSIONS Based on our preliminary findings, this proof-of-concept study demonstrates potential to explore the role of angiogenesis in CPP for better disease understanding.

Multi-target mechanism of polyherbal extract to treat diabetic foot ulcer based on network pharmacology and molecular docking

Introduction: Diabetic foot ulcer (DFU) potentially leads to loss of function, infections, hospitalization, lower-extremity amputation, and even death. The potential therapeutic efficacy of a polyherbal candidate named TIP-Heal was identified for treating DFU. TIP-Heal, which stands for Tinospora crispa, Isotoma longiflora, and Piper betle L var nigra, consists of extracts from these three herbs in a ratio of 2:1:1. The Indonesian population commonly uses these herbs due to their wound-healing properties. It is our interest to analyse the mechanism of the polyherbal extract using network pharmacology and molecular docking. Methods: This study uses network pharmacology and molecular docking methods to analyze the multi-target mechanism of active compounds in TIP-Heal extract for DFU treatment. The proteins targeted by the bioactive chemical present in TIP-Heal and DFU were identified within a particular dataset with the keyword "homo sapiens." The identified target proteins were assessed using gene ontology (GO) analysis, the Kyoto Encyclopaedia of Gene and Genomes (KEGG) pathways, protein-protein interactions (PPIs), and molecular docking. Results: The critical proteins obtained were AKT serine/threonine kinase 1 (AKT1), caspase-3 (CASP3), epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase Src (SRC) and matrix metalloproteinase-9 (MMP-9). Several compounds, namely PubChem (Compound Identifier=CID: 5319898), 3-epiursolic acid, palmitic acid, and alpha-linolenic acid showed great potential as viable candidates to facilitate the healing process of DFU. Conclusion: The findings of this study indicate that the TIP-Heal extract has the potential to be used as a natural herbal treatment for DFUs with the involvement of AKT1, CASP3, EFGR, and SRC proteins.

The Interaction and Effect of a Small MitoBlock Library as Inhibitor of ALR Protein-Protein Interaction Pathway.

MIA40 and ALR of the MIA pathway mediate the import of protein precursors that form disulfides into the mitochondrial intermembrane space. This import pathway is suggested to be a linear pathway in which MIA40 first binds to the precursor via a disulfide linkage and oxidizes it. Subsequently, ALR re-oxidizes MIA40 and then ALR transfers electrons to terminal electron acceptors. However, the precise mechanism by which ALR and MIA40 coordinate translocation is unknown. With a collection of small molecule modulators (MB-5 to MB-9 and MB-13) that inhibit ALR activity, we characterized the import mechanism in mitochondria. NMR studies show that most of the compounds bind to a similar region in ALR. Mechanistic studies with small molecules demonstrate that treatment with compound MB-6 locks the precursor in a state bound to MIA40, blocking re-oxidation of MIA40 by ALR. Thus, small molecules that target a similar region in ALR alter the dynamics of the MIA import pathway differently, resulting in a set of probes that are useful for studying the catalysis of the redox-regulated import pathway in model systems.

Interplay of machine learning and bioinformatics approaches to identify genetic biomarkers that affect survival of patients with glioblastoma

Glioblastoma, also known as grade IV astrocytoma, is an aggressive and quickly developing brain tumor whose median survival period is believed to be between 12 and 18 months. Patients with glioblastoma are at high risk of developing comorbidities like leukemia, atherosclerosis, autism, sudden cardiac death, and pancreatic neoplasms. Identification of influential biomarker genes is crucial to diagnose and design therapeutic targets for cancer. To do this, we considered The Cancer Genome Atlas (TCGA) dataset to identify the significant genes of glioblastoma. Therefore, we pre-processed the dataset and applied the Kruskal-Wallis test and Bonferroni correction methods to select significant biomarker genes. A total of 26 significant dysregulated genes have been identified from 16261 genes, of which 19 are up-regulated and 7 are down-regulated genes. We performed analysis of functional and ontological pathways, protein-protein interactions (PPI), and protein-drug interactions (PDI) to predict the functions of these influential genes. Comorbidities validation was performed using gold benchmark databases. Furthermore, the Cox proportional hazard model and the product-limit (PL) estimator were used to examine the influence of clinical and genetic variables that play an important role in the survival of glioblastoma patients. This study provides the basis of identifying cancer-influencing genes and understanding the impact of glioblastoma on the progression of comorbidities.

The role of lncFABP4 in modulating adipogenic differentiation in buffalo intramuscular preadipocytes.

Intramuscular fat (IMF) is a crucial determinant of meat quality and is influenced by various regulatory factors. Despite the growing recognition of the important role of long noncoding RNAs (lncRNAs) in IMF deposition, the mechanisms underlying buffalo IMF deposition remain poorly understood. In this study, we identified and characterized a lncRNA, lncFABP4, which is transcribed from the antisense strand of fatty acid-binding protein 4 (FABP4). lncFABP4 inhibited cell proliferation in buffalo intramuscular preadipocytes. Moreover, lncFABP4 significantly increased intramuscular preadipocyte differentiation, as indicated by an increase in the expression of the adipogenic markers peroxisome proliferator-activated receptor gamma (PPARG), CCAAT enhancer binding protein alpha (C/EBPα), and FABP4. Mechanistically, lncFABP4 was found to have the potential to regulate downstream gene expression by participating in protein-protein interaction pathways. These findings contribute to further understanding of the intricate mechanisms through which lncRNAs modulate intramuscular adipogenesis in buffaloes.

4D-DIA quantitative proteomics revealed the core mechanism of diabetic retinopathy after berberine treatment

ObjectiveTo reveal the core mechanism of berberine (BBR) in the treatment of diabetic retinopathy (DR), by using Four-dimensional independent data acquisition (4D-DIA) proteomics combined bioinformatics analysis with experimental validation. Methods: DR injury model was established by injecting streptozotocin intraperitoneally. At 8 weeks after BBR administration, optical coherence tomography (OTC) photos and Hematoxylin-eosin staining from retina in each group were performed, then the retina was collected for 4D-DIA quantitative proteomics detection. Moreover, difference protein analysis, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI) network, as well as molecular docking was performed, respectively. In the part of experiment, Western blot (WB) and immunofluorescent staining was used to confirm the change and distribution of carbonic anhydrase 1 (CA1), one of the most important molecules from quantitative PCR detection. Lastly, RNA knockdown was used to determine the crucial role of CA1 in retinal pigment epithelial cells (RPEs) administrated with berberine. ResultsOCT detection showed that the outer nucleus, inner layer and outer accessory layer of RPEs were thinned in DR group, compared with in sham one, while they were thickened after berberine administration, when compared with in DR group. 10 proteins were screened out by using proteomic analysis and Venny cross plot, in which, denn domain containing 1A (DENND1A) and UTP6 small subunit processome component (UTP6) was down-regulated, while ATPase copper transporting alpha (ATP7A), periplakin (PPL), osteoglycin (OGN), nse1 Homolog (NSMCE1), membrane metalloendopeptidase (MME), lim domain only 4 (LMO4), CA1 and fibronectin 1 (FN1) was up-regulated in DR group, and the BBR treatment can effectively reverse their expressions. PPI results showed that 10 proteins shared interactions with each other, but only ATP7A, FN1 and OGN exhibited directly associated with each other. Moreover, we enlarged the linked relation up to 15 genes in network, based on 10 proteins found from proteomics detection, so as to perform deep GO and KEGG analysis. As a result, the most important biological process is involving rRNA processing; the most important cell component is small subunit processor; the most important molecular function is Phospholipid binding; the KEGG pathway was Ribosome biogenesis in eukaryotes. Moreover, molecular docking showed that LMO4, ATP7A, PPL, NSMCE1, MME, CA1 could form a stable molecular binding pattern with BBR. Of these, the mRNA expression of CA1, PPL and ATP7A and the protein level of CA1 was increased in DR, and decreased in BBR group. Lastly, CA1 RNA knockdown confirmed the crucial role of CA1 in RPE administered with BBR. ConclusionThe present findings confirmed the role of BBR in DR treatment and explained associated molecular network mechanism, in which, CA1 could be considered as a crucial candidate in the protection of RPEs with berberine treatment.

Identification of Potential Biomarkers in Stomach Adenocarcinoma using Machine Learning Approaches

Background: Stomach adenocarcinoma (STAD) is a common cancer with poor clinical outcomes globally. Due to a lack of early diagnostic markers of disease, the majority of patients are diagnosed at an advanced stage. Objective: The aim of the present study is to provide some new insights into the available biomarkers for patients with STAD using bioinformatics. Methods: RNA-Sequencing and other relevant data of patients with STAD from The Cancer Genome Atlas (TCGA) database were evaluated to identify differentially expressed genes (DEGs). Then, Machine Learning algorithms were undertaken to predict biomarkers. Additionally, Kaplan–Meier analysis was used to detect prognostic biomarkers. Furthermore, the Gene Ontology and Reactome pathways, protein-protein interactions (PPI), multiple sequence alignment, phylogenetic mapping, and correlation between clinical parameters were evaluated. Results: The results showed 61 DEGs, and the key dysregulated genes associated with STAD are MTHFD1L (Methylenetetrahydrofolate dehydrogenase 1-like), ZWILCH (Zwilch Kinetochore Protein), RCC2 (Regulator of chromosome condensation 2), DPT (Dermatopontin), GCOM1 (GRINL1A complex locus 1), and CLEC3B (C-Type Lectin Domain Family 3 Member B). Moreover, the survival analysis reported ASPA (Aspartoacylase) as a prognostic marker. Conclusion: Our study provides a proof of concept of the potential value of ASPA as a prognostic factor in STAD, requiring further functional investigations to explore the value of emerging markers.

Exploring Prognostic Biomarkers of Acute Myeloid Leukemia to Determine Its Most Effective Drugs from the FDA-Approved List through Molecular Docking and Dynamic Simulation.

Acute myeloid leukemia (AML) is a blood cancer caused by the abnormal proliferation and differentiation of hematopoietic stem cells in the bone marrow. The actual genetic markers and molecular mechanisms of AML prognosis are unclear till today. This study used bioinformatics approaches for identifying hub genes and pathways associated with AML development to uncover potential molecular mechanisms. The expression profiles of RNA-Seq datasets, GSE68925 and GSE183817, were retrieved from the Gene Expression Omnibus (GEO) database. These two datasets were analyzed by GREIN to obtain differentially expressed genes (DEGs), which were used for performing the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI), and survival analysis. The molecular docking and dynamic simulation were performed to identify the most effective drug/s for AML from the drug list approved by the Food and Drug Administration (FDA). By integrating the two datasets, 238 DEGs were identified as likely to be affected by AML progression. GO enrichment analyses exhibited that the upregulated genes were mainly associated with inflammatory response (BP) and extracellular region (CC). The downregulated DEGs were involved in the T-cell receptor signalling pathway (BP), an integral component of the lumenal side of the endoplasmic reticulum membrane (CC) and peptide antigen binding (MF). The pathway enrichment analysis showed that the upregulated DEGs were mainly associated with the T-cell receptor signalling pathway. Among the top 15 hub genes, the expression levels of ALDH1A1 and CFD were associated with the prognosis of AML. Four FDA-approved drugs were selected, and a top-ranked drug was identified for each biomarker through molecular docking studies. The top-ranked drugs were further confirmed by molecular dynamic simulation that revealed their binding stability and confirmed their stable performance. Therefore, the drug compounds, enasidenib and gilteritinib, can be recommended as the most effective drugs against the ALDH1A1 and CFD proteins, respectively.

Identification of common pathway and hub genes in the degeneration of both annulus fibrosus and nucleus pulposus in intervertebral disc.

This study aimed to identify the common pathways and hub genes related to oxidative stress (OS) and autophagy of both annulus fibrosus (AF) and nucleus pulposus (NP) in intervertebral disc degeneration (IDD) based on the data obtained from the Gene Expression Omnibus (GEO) database. The Gene expression data for human intervertebral discs was obtained from the GEO database, including the AF and NP of both non-degenerated disc and degenerated disc. The differentially expressed genes (DEGs) were identified using the limma package in R language. DEGs related to OS and autophagy were obtained using Gene Ontology (GO) database. Analyses of the GO, signaling pathways, protein-protein interaction (PPI) networks, and hub genes were performed using AnnotationDbi package, DAVID, GSEA, STRING database, and Cytoscape software, respectively. Finally, the online tool of NetworkAnalyst and the Drug Signatures database (DSigDB) were used to screen for transcriptional factors and potential drugs of the hub genes. There were 908 genes associated with OS and autophagy found. A total of 52 DEGs were identified, included five upregulated and 47 downregulated genes. These DEGs were mainly involved in mTOR signaling pathway and the NOD-like receptor signaling pathway. The top 10 hub genes were CAT, GAPDH, PRDX1, PRDX4, TLR4, GPX7, GPX8, MSRA, RPTOR, GABARAPL1. Besides, FOXC1, PPARG, RUNX2, JUN, and YY1 were identified as the key regulatory factors of hub genes. L-cysteine, oleanolic acid, and berberine were potential therapeutic agents for the treatment of IDD. Common hub genes, signaling pathways, transcription factors, and potential drugs associated with OS and autophagy were identified, which provides significant basis for further mechanism research and drug screening of IDD.

Systematic pan-cancer analysis identifies RALA as a tumor targeting immune therapeutic and prognostic marker.

RALA is a member of the small GTPase Ras superfamily and has been shown to play a role in promoting cell proliferation and migration in most tumors, and increase the resistance of anticancer drugs such as imatinib and cisplatin. Although many literatures have studied the cancer-promoting mechanism of RALA, there is a lack of relevant pan-cancer analysis. This study systematically analyzed the differential expression and mutation of RALA in pan-cancer, including different tissues and cancer cell lines, and studied the prognosis and immune infiltration associated with RALA in various cancers. Next, based on the genes co-expressed with RALA in pan-cancer, we selected 241 genes with high correlation for enrichment analysis. In terms of pan-cancer, we also analyzed the protein-protein interaction pathway of RALA and the application of small molecule drug Guanosine-5'-Diphosphate. We screened hepatocellular cancer (HCC) to further study RALA. The results indicated that RALA was highly expressed in most cancers. RALA was significantly correlated with the infiltration of B cells and macrophages, as well as the expression of immune checkpoint molecules such as CD274, CTLA4, HAVCR2 and LAG3, suggesting that RALA can be used as a kind of new pan-cancer immune marker. The main functions of 241 genes are mitosis and protein localization to nucleosome, which are related to cell cycle. For HCC, the results displayed that RALA was positively correlated with common intracellular signaling pathways such as angiogenesis and apoptosis. In summary, RALA was closely related to the clinical prognosis and immune infiltration of various tumors, and RALA was expected to become a broad-spectrum molecular immune therapeutic target and prognostic marker for pan-cancer.

Comprehensive bioinformatics analysis reveals common potential mechanisms, progression markers, and immune cells of coronary virus disease 2019 and atrial fibrillation

Atrial fibrillation (AF) is the most common arrhythmia in coronary virus disease 2019 (COVID-19) patients, especially in severe patients. A history of AF can exacerbate COVID-19 symptoms. COVID-19 Patients with new-onset AF have prolonged hospital stays and increased death risk. However, the mechanisms and targets of the interaction between COVID-19 and AF have not been elucidated. We used a series of bioinformatics analyses to understand biological pathways, protein-protein interaction (PPI) networks, gene regulatory networks (GRNs), and protein-chemical interactions between COVID-19 and AF and constructed an AF-related gene signature to assess COVID-19 severity and prognosis. We found folate and one-carbon metabolism, calcium regulation, and TFG-β signaling pathway as potential mechanisms linking COVID-19 and AF, which may be involved in alterations in neutrophil metabolism, inflammation, and endothelial cell function. We identified hug genes and found that NF-κb, hsa-miR-1-3p, hsa-miR-124-3p, valproic acid, and quercetin may be key regulatory molecules. We constructed a 3-gene signature consisting of ARG1, GIMAP7, and RFX2 models for the assessment of COVID-19 severity and prognosis, and found that they are associated with neutrophils, T cells, and hematopoietic stem cells, respectively. Our study reveals a dysregulation of metabolism, inflammation, and immunity between COVID-19 and AF, and identified several therapeutic targets and progression markers. We hope that the results will reveal important insights into the complex interactions between COVID-19 and AF that will drive novel drug development and help in severity assessment.

Ageing-Associated Transcriptomic Alterations in Peri-Implantitis Pathology: A Bioinformatic Study.

Background Ageing is associated with increased incidence of peri-implantitis but the roles of ageing-associated biological mechanisms in the occurrence of peri-implantitis are not known. This study is aimed at performing integrative bioinformatic analysis of publically available datasets to uncover molecular mechanisms related to ageing and peri-implantitis. Methods Gene expression datasets related to ageing and peri-implantitis (PI) were sought, and differentially expressed genes (DEGs) were analysed. Ageing-related genes were also identified from the “Aging Atlas” database. Using intersection analysis, an age-related-PI gene set was identified. Functional enrichment analysis for enriched GO biological process and KEGG pathways, protein-protein interaction (PPI) network analysis, correlation analysis, and immune cell infiltration analysis to determine high-abundance immune cells were performed. Least absolute shrinkage and selection operator (LASSO) logistic regression identified key age-related-PI genes. Transcription factor-gene and drug-gene interactions and enriched KEGG pathways for the key age-related-PI genes were determined. Results A total of 52 genes were identified as age-related-PI genes and found enriched in several inflammation-associated processes including myeloid leukocyte activation, acute inflammatory response, mononuclear cell differentiation, B cell activation, NF-kappa B signalling, IL-17 signalling, and TNF signalling. LYN, CDKN2A, MAPT, BTK, and PRKCB were hub genes in the PPI network. Immune cell infiltration analysis showed activated dendritic cells, central memory CD4 T cells, immature dendritic cells, and plasmacytoid dendritic cells were highly abundant in PI and ageing. 7 key age-related PI genes including ALOX5AP, EAF2, FAM46C, GZMK, MAPT, RGS1, and SOSTDC1 were identified using LASSO with high predictive values and found to be enriched in multiple neurodegeneration-associated pathways, MAPK signalling, and Fc epsilon RI signalling. MAPT and ALOX5AP were associated with multiple drugs and transcription factors and interacted with other age-related genes to regulate multiple biological pathways. Conclusion A suite of bioinformatics analysis identified a 7-signature gene set highly relevant to cooccurrence of ageing and peri-implantitis and highlighted the role of neurodegeneration, autoimmune, and inflammation related pathways. MAPT and ALOX5AP were identified as key candidate target genes for clinical translation.

Atractylenolide-1 Targets FLT3 to Regulate PI3K/AKT/HIF1-α Pathway to Inhibit Osteogenic Differentiation of Human Valve Interstitial Cells.

Atractylenolide-1 (AT-1), a natural active ingredient extracted from Atractylodes macrocephala, was reported to have good anti-fibrotic and anti-inflammatory effects. Osteogenic changes induced by the inflammation of valve interstitial cells (VICs) play a role in the development of calcified aortic valve disease (CAVD). This study aimed to investigate the anti-osteogenic effects of AT-1 in human VICs. Human VICs were exposed to osteogenic induction medium (OM) containing AT-1 to analyze cell viability, as well as protein and osteogenic gene expression. Anti-calcification tests were also performed. mRNA transcriptome sequencing was performed to identify differential genes and pathways regulated by AT-1. Western blotting was used to verify the enrichment pathway, protein-protein interaction (PPI) analysis was conducted to identify drug targets. Finally, molecular docking and inhibitors are used to verify the drug targets. Treatment of VICs with 20 μM AT-1 resulted in no significant cytotoxicity. The addition of AT-1 to OM prevented the accumulation of calcified nodules, and decreases in the level of (Alkaline Phosphatase) ALP and RUNX2 gene and protein expression were observed. Atractylenolide-1 can target FLT3 protein and inhibit the phosphorylation of FLT3, thereby blocking PI3K/AKT pathway activation, reducing the production of Hypoxia inducible factor(HIF)1-α, and inhibiting the osteogenic differentiation of VICs. These results suggest AT-1 as a potential drug for treating calcified aortic valve disease.

Transcriptome Profiling Unveils a Critical Role of IL-17 Signaling-Mediated Inflammation in Radiation-Induced Esophageal Injury in Rats.

Elucidation of the molecular mechanisms involving the initiation and progression of radiation-induced esophageal injury (RIEI) is important for prevention and treatment. Despite ongoing advances, the underlying mechanisms controlling RIEI remain largely unknown. In the present study, RNA-seq was performed to characterize mRNA profiles of the irradiated rat esophagus exposed to 0, 25, or 35 Gy irradiation. Bioinformatics analyses including dose-dependent differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Gene and Genome (KEGG) pathway, protein-protein interaction (PPI) network, and immune infiltration were performed. 134 DEGs were screened out with a dose-dependent manner (35 Gy > 25 Gy > control, or 35 Gy < 25 Gy < control). GO and KEGG analyses showed that the most significant mechanism was IL-17 signaling-mediated inflammatory response. 5 hub genes, Ccl11, Cxcl3, Il17a, S100a8, and S100a9, were identified through the intersection of the DEGs involved in inflammatory response, IL-17 pathway, and PPI network. Additionally, immune infiltration analysis showed the activation of macrophages, monocytes, T cells, NKT cells, and neutrophils, among which macrophages, monocytes, and neutrophils might be the main sources of S100a8 and S100a9. Thus, these findings further our understanding on the molecular biology of RIEI and may help develop more effective therapeutic strategies.

Erythropoiesis signature and ubiquitin-mediated proteolysis are enriched in systematic juvenile idiopathic arthritis.

Systemic Juvenile Idiopathic Arthritis (sJIA) is a distinctive subtype of Juvenile Idiopathic Arthritis (JIA). The pathogenesis of sJIA is still unclear with the limited treatment options. Although previous bioinformatics analyses have identified some genetic factors underlying sJIA, these studies were mostly single centre with a small sample size and the results were often inconsistent. Herein, we combined two data sets of GSE20307 and GSE21521 and select the matrix of patients diagnosed as sJIA in it for further analysis. The GSE20307 and GSE21521 matrixes downloaded from the Gene Expression Omnibus (GEO) were analysed using online tools GEO2R, Venny, Metascape, STRING and Cytoscape to identify differentially expressed genes (DEGs), enrichment pathways, protein-protein interaction (PPI), main module and hub genes between sJIA individuals and healthy controls. A total of 289 overlapping genes (consisting of 41 downregulated genes and 248 upregulated genes) were identified. Hub genes were primarily related to erythropoiesis. And the KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis of overlapping DEGs were mainly involved in malaria and non-small cell lung cancer. Besides, DEGs in main module were involved in ubiquitin-mediated proteolysis. Our study suggests that the erythropoiesis signature indeed exists in sJIA similar to previous reports. And ubiquitin-mediated proteolysis is important in sJIA.

Enlightening the molecular mechanisms of type 2 diabetes with a novel pathway clustering and pathway subnetwork approach.

Type 2 diabetes mellitus (T2D) constitutes 90% of the diabetes cases, and it is a complex multifactorial disease. In the last decade, genome-wide association studies (GWASs) for T2D successfully pinpointed the genetic variants (typically single nucleotide polymorphisms, SNPs) that associate with disease risk. In order to diminish the burden of multiple testing in GWAS, researchers attempted to evaluate the collective effects of interesting variants. In this regard, pathway-based analyses of GWAS became popular to discover novel multigenic functional associations. Still, to reveal the unaccounted 85 to 90% of T2D variation, which lies hidden in GWAS datasets, new post-GWAS strategies need to be developed. In this respect, here we reanalyze three metaanalysis data of GWAS in T2D, using the methodology that we have developed to identify disease-associated pathways by combining nominally significant evidence of genetic association with the known biochemical pathways, protein-protein interaction (PPI) networks, and the functional information of selected SNPs. In this research effort, to enlighten the molecular mechanisms underlying T2D development and progress, we integrated different in silico approaches that proceed in top-down manner and bottom-up manner, and presented a comprehensive analysis at protein subnetwork, pathway, and pathway subnetwork levels. Using the mutual information based on the shared genes, the identified protein subnetworks and the affected pathways of each dataset were compared. While most of the identified pathways recapitulate the pathophysiology of T2D, our results show that incorporating SNP functional properties, PPI networks into GWAS can dissect leading molecular pathways, and it could offer improvement over traditional enrichment strategies.

The potential mechanism of PPP2R3A in myocardial cells and its interacting proteins.

PPP2R3A plays a key role in the cardiac pathological and physiological processes, yet little is known about how the protein involved in normal myocardium formation and the protein-protein interaction pathways involved. To address this issue, we investigated the role of PPP2R3A in cardiac myocytes and identify PPP2R3A specific protein interaction partners to accelerate the developmental process of the mechanistic studies. PPP2R3A-silenced primary myocardial cell of neonatal rats and H9c2 cells were established by infecting shRNA lentiviral particles. RT-PCR and Western blot were used to determine the expression of PPP2R3A and silencing efficiency. The cell viability was analyzed by CCK-8 kit, then the cell cycles and apoptosis assays were detected by flow cytometry. Novel protein-protein interactions of PPP2R3A were detected by Yeast Two-Hybrid assays using a high-quality human primary cardiomyocyte cDNA library. PPP2R3A-silencing rat primary cardiomyocytes and H9c2 cells were established successfully, and the expression of PPP2R3A was downregulated significantly as confirmed by RT-PCR and Western blot. PPP2R3A silencing can inhibit the myocardial cell proliferation, arrest the cell cycle in the S phase and promote the cardiomyocytes apoptosis. 19 potential candidates like COL1A2, GIPC1and BCL6 specifically interact with PPP2R3A, and COL1A2 was the highest screening frequency, covering 12.5% of the 24 clones. These partners are highly enriched in signaling pathways associated with a variety of cellular processes. A series of studies have discovered that PPP2R3A was closely associated with heart failure and arrhythmia. Our data further confirmed PPP2R3A plays an important role in the cardiomyocytes and PPP2R3A in the regulation of cardiac events via its interaction partners. Therefore, it is a potential therapeutic target for the disease.

Abstract 10944: A Network Analysis to Identify Pathophysiological Pathways Associated with Systolic Function Recovery After Myocardial Infarction

Introduction: Identification of factors involved in early stages of left ventricular systolic function recovery after acute myocardial infarction (AMI) can provide a basis for novel therapies. We aimed to characterize proteomic biomarkers and underlying mechanistic pathways associated with improvement of left ventricular systolic function. Hypothesis: Proteomic biomarkers and protein-protein interaction pathways differ between patients with and without systolic function recovery after AMI. Methods: Patients with ejection fraction (EF) &lt;40% at hospital discharge were selected from a prospective registry of AMI patients (n=819). We used matched case-control design. Cases were patients with EF&lt;40% at hospital discharge, but EF&gt;50% at the follow-up visit 3-6 months after discharge (EF recovery group). Controls were patients with EF&lt;40% both at hospital discharge and follow-up visit. Controls were matched for age, gender, and discharge EF. Blood samples were drawn within 24h since hospital admission. We used proximity extension assays (Olink, Uppsala) to measure plasma biomarkers and protein-protein interaction network to identify pathophysiological pathways distinguishing cases and controls. Results: In total, 41 cases and 41 controls (mean age 59±10 years, 73% males) were included. At baseline, study groups did not differ in the main clinical variables. Of the 362 biomarkers tested, and after adjustment for age, gender and baseline EF, 44 proteins were differentially expressed, of which 2 (interleukin 6 and stem cell factor) showed association with EF recovery after false discovery rate correction. In the Reactome pathway analysis, Interleukin-6 family signaling was the most significant pathway associated with systolic function recovery. Conclusions: We identified the Interleukin-6 family signaling pathway with IL-6 and leukemia inhibitory factor (LIF) as potential early factors supporting recovery of systolic function after AMI.

Characterization of Dynamic Regulatory Gene and Protein Networks in Wheat Roots Upon Perceiving Water Deficit Through Comparative Transcriptomics Survey.

A well-developed root system benefits host plants by optimizing water absorption and nutrient uptake and thereby increases plant productivity. In this study we have characterized the root transcriptome using RNA-seq and subsequential functional analysis in a set of drought tolerant and susceptible genotypes. The goal of the study was to elucidate and characterize water deficit-responsive genes in wheat landraces that had been through long-term field and biochemical screening for drought tolerance. The results confirm genotype differences in water-deficit tolerance in line with earlier results from field trials. The transcriptomics survey highlighted a total of 14,187 differentially expressed genes (DEGs) that responded to water deficit. The characterization of these genes shows that all chromosomes contribute to water-deficit tolerance, but to different degrees, and the B genome showed higher involvement than the A and D genomes. The DEGs were mainly mapped to flavonoid, phenylpropanoid, and diterpenoid biosynthesis pathways, as well as glutathione metabolism and hormone signaling. Furthermore, extracellular region, apoplast, cell periphery, and external encapsulating structure were the main water deficit-responsive cellular components in roots. A total of 1,377 DEGs were also predicted to function as transcription factors (TFs) from different families regulating downstream cascades. TFs from the AP2/ERF-ERF, MYB-related, B3, WRKY, Tify, and NAC families were the main genotype-specific regulatory factors. To further characterize the dynamic biosynthetic pathways, protein-protein interaction (PPI) networks were constructed using significant KEGG proteins and putative TFs. In PPIs, enzymes from the CYP450, TaABA8OH2, PAL, and GST families play important roles in water-deficit tolerance in connection with MYB13-1, MADS-box, and NAC transcription factors.

Identification of prognostic immune-related gene signature associated with tumor microenvironment of colorectal cancer

BackgroundThe tumor microenvironment (TME) has significantly correlation with tumor occurrence and prognosis. Our study aimed to identify the prognostic immune-related genes (IRGs)in the tumor microenvironment of colorectal cancer (CRC).MethodsTranscriptome and clinical data of CRC cases were downloaded from TCGA and GEO databases. Stromal score, immune score, and tumor purity were calculated by the ESTIMATE algorithm. Based on the scores, we divided CRC patients from the TCGA database into low and high groups, and the differentially expressed genes (DEGs) were identified. Immune-related genes (IRGs) were selected by venn plots. To explore underlying pathways, protein-protein interaction (PPI) networks and functional enrichment analysis were used. After utilizing LASSO Cox regression analysis, we finally established a multi-IRGs signature for predicting the prognosis of CRC patients. A nomogram consists of the thirteen-IRGs signature and clinical parameters was developed to predict the overall survival (OS). We investigated the association between prognostic validated IRGs and immune infiltrates by TIMER database.ResultsGene expression profiles and clinical information of 1635 CRC patients were collected from the TCGA and GEO databases. Higher stromal score, immune score and lower tumor purity were observed positive correlation with tumor stage and poor OS. Based on stromal score, immune score and tumor purity, 1517 DEGs, 1296 DEGs, and 1892 DEGs were identified respectively. The 948 IRGs were screened by venn plots. A thirteen-IRGs signature was constructed for predicting survival of CRC patients. Nomogram with a C-index of 0.769 (95%CI, 0.717–0.821) was developed to predict survival of CRC patients by integrating clinical parameters and thirteen-IRGs signature. The AUC for 1-, 3-, and 5-year OS were 0.789, 0.783 and 0.790, respectively. Results from TIMER database revealed that CD1B, GPX3 and IDO1 were significantly related with immune infiltrates.ConclusionsIn this study, we established a novel thirteen immune-related genes signature that may serve as a validated prognostic predictor for CRC patients, thus will be conducive to individualized treatment decisions.