Dataset Information

Identification of novel immune-related targets mediating disease progression in acute pancreatitis.

ABSTRACT:

Introduction

Acute pancreatitis (AP) is an inflammatory disease with very poor outcomes. However, the order of induction and coordinated interactions of systemic inflammatory response syndrome (SIRS) and compensatory anti-inflammatory response syndrome (CARS) and the potential mechanisms in AP are still unclear.

Methods

An integrative analysis was performed based on transcripts of blood from patients with different severity levels of AP (GSE194331), as well as impaired lung (GSE151572), liver (GSE151927) and pancreas (GSE65146) samples from an AP experimental model to identify inflammatory signals and immune response-associated susceptibility genes. An AP animal model was established in wild-type (WT) mice and Tlr2-deficient mice by repeated intraperitoneal injection of cerulein. Serum lipase and amylase, pancreas impairment and neutrophil infiltration were evaluated to assess the effects of Tlr2 in vivo.

Results

The numbers of anti-inflammatory response-related cells, such as M2 macrophages (P = 3.2 × 10^-3), were increased with worsening AP progression, while the numbers of pro-inflammatory response-related cells, such as neutrophils (P = 3.0 × 10^-8), also increased. Then, 10 immune-related AP susceptibility genes (SOSC3, ITGAM, CAMP, FPR1, IL1R1, TLR2, S100A8/9, HK3 and MMP9) were identified. Finally, compared with WT mice, Tlr2-deficient mice exhibited not only significantly reduced serum lipase and amylase levels after cerulein induction but also alleviated pancreatic inflammation and neutrophil accumulation.

Discussion

In summary, we discovered SIRS and CARS were stimulated in parallel, not activated consecutively. In addition, among the novel susceptibility genes, TLR2might be a novel therapeutic target that mediates dysregulation of inflammatory responses during AP progression.

SUBMITTER: Liu Q

PROVIDER: S-EPMC9795030 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of novel immune-related targets mediating disease progression in acute pancreatitis.

Liu Qiang Q Li Lingyun L Xu Dongchao D Zhu Jianpeng J Huang Zhicheng Z Yang Jianfeng J Cheng Sile S Gu Ye Y Zheng Liyun L Zhang Xiaofeng X Shen Hongzhang H

Frontiers in cellular and infection microbiology 20221214

<h4>Introduction</h4>Acute pancreatitis (AP) is an inflammatory disease with very poor outcomes. However, the order of induction and coordinated interactions of systemic inflammatory response syndrome (SIRS) and compensatory anti-inflammatory response syndrome (CARS) and the potential mechanisms in AP are still unclear.<h4>Methods</h4>An integrative analysis was performed based on transcripts of blood from patients with different severity levels of AP (GSE194331), as well as impaired lung (GSE15 ...[more]

PMID: 36590588

Similar Datasets

Project description:BackgroundCuproptosis is a novel type of mediated cell death strongly associated with the progression of several cancers and has been implicated as a potential therapeutic target. However, the role of cuproptosis in cholangiocarcinoma for prognostic prediction, subgroup classification, and therapeutic strategies remains largely unknown.MethodsA systematic analysis was conducted among 146 cuproptosis-related genes and clinical information based on independent mRNA and protein datasets to elucidate the potential mechanisms and prognostic prediction value of cuproptosis-related genes. A 10-cuproptosis-related gene prediction model was constructed, and its effects on cholangiocarcinoma prognosis were significantly connected to poor patient survival. Additionally, the expression patterns of our model included genes that were validated with several cholangiocarcinoma cancer cell lines and a normal biliary epithelial cell line.ResultsFirst, a 10-cuproptosis-related gene signature (ADAM9, ADAM17, ALB, AQP1, CDK1, MT2A, PAM, SOD3, STEAP3, and TMPRSS6) displayed excellent predictive performance for the overall survival of cholangiocarcinoma. The low-cuproptosis group had a significantly better prognosis than the high-cuproptosis group with transcriptome and protein cohorts. Second, compared with the high-risk and low-risk groups, the 2 groups displayed distinct tumor microenvironments, reduced proportions of endothelial cells, and increased levels of cancer-associated fibroblasts based on CIBERSORTx and EPIC analyses. Third, patients' sensitivities to chemotherapeutic drugs and immune checkpoints revealed distinctive differences between the 2 groups. Finally, in replicating the expression patterns of the 10 genes, these results were validated with quantitative real-time polymerase chain reaction results validating the abnormal expression pattern of the target genes in cholangiocarcinoma.ConclusionsCollectively, we established and verified an effective prognostic model that could separate cholangiocarcinoma patients into 2 heterogeneous cuproptosis subtypes based on the molecular or protein characteristics of 10 cuproptosis-related genes. These findings may provide potential benefits for unveiling molecular characteristics and defining subgroups could improve the early diagnosis and individualized treatment of cholangiocarcinoma patients.

Project description:Acute pancreatitis (AP) is a painful and potentially life-threatening disorder with the potential for therapeutic interventions. Biomarkers that characterize cases by severity and pathogenic mechanisms involved are not yet available but needed for the implementation of rational therapies. Here, we used shotgun proteomics to obtain information from plasma samples about local and systemic pathologies taking place during cases of alcoholic AP. Plasma was obtained at Kaunas University of Medicine Hospital (Lithuania) from 12 AP patients of alcohol related etiology (median age of 40) within 24 h of presentation, and 12 age-matched, healthy controls. Patients entered into the study had moderately severe AP with the following characteristics: mean blood lactate dehydrogenase level of 1127 mg/dl; median APACHEII score of 5.5 and mean IMRIE score of 3.5. For proteomic analysis, less-abundant proteins in plasma samples were enriched using Top 12 abundant protein depletion columns. Further processing was performed by a modified filter-assisted sample preparation combined with tandem mass tag labeling for quantitation. Samples were analyzed using an Orbitrap Elite mass spectrometer for high resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS). Our analysis revealed 31 proteins that exhibited significant 1.5-fold or higher increases in the AP compared to control patients, and six that were significantly decreased. Gene ontology analysis indicated a strong correlation with exosomal origin in the elevated proteins, with 29/31 (93.5%) associated with this extracellularly-secreted compartment. Elevated proteins included established and proposed biomarkers of AP including C-reactive protein, LPS-binding protein, intercellular adhesion molecule-1, and von Willebrand factor, as well as several novel potential biomarkers. These results provide the methodology for proteomic analysis of plasma samples to discover novel biomarkers that characterize pancreatitis cases by pathogenic mechanism as well as disease activity at an early stage that is highly informative for routine clinical practice and clinical trials.

Project description:BackgroundCoronary artery disease (CAD) is a complex illness with unknown pathophysiology. Peripheral biomarkers are a non-invasive method required to track the onset and progression of CAD and have unbeatable benefits in terms of early identification, prognostic assessment, and categorization of the diagnosis. This study aimed to identify and validate the diagnostic and therapeutic potential of differentially expressed immune-related genes (DE-IRGs) in CAD, which will aid in improving our knowledge on the etiology of CAD and in forming genetic predictions.MethodsFirst, we searched coronary heart disease in the Gene Expression Omnibus (GEO) database and identified GSE20680 (CAD = 87, Normal = 52) as the trial set and GSE20681 (CAD = 99, Normal = 99) as the validation set. Functional enrichment analysis using protein-protein interactions (PPIs), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) was carried out on the identified differentially expressed genes. Optimal feature genes (OFGs) were generated using the support vector machine recursive feature elimination algorithm and the least absolute shrinkage and selection operator (LASSO) algorithm. Furthermore, immune infiltration in CAD patients and healthy controls was compared using CIBERSORT, and the relationship between immune cells and OFGs was examined. In addition, we constructed potential targeted drugs for this model through the Drug-Gene Interaction database (DGIdb) database. Finally, we verify the expression of S100A8-dominated OFGs in the GSE20681 dataset to confirm the universality of our study.ResultsWe identified the ten best OFGs for CAD from the DE-IRGs. Functional enrichment analysis showed that these marker genes are crucial for receptor-ligand activity, signaling receptor activator activity, and positive control of the response to stimuli from the outside world. Additionally, CIBERSORT revealed that S100A8 could be connected to alterations in the immune microenvironment in CAD patients. Furthermore, with the help of DGIdb and Cytoscape, a total of 64 medicines that target five marker genes were subsequently discovered. Finally, we verified the expression of the OFGs genes in the GSE20681 dataset between CAD patients and normal patients and found that there was also a significant difference in the expression of S100A8.ConclusionWe created a 10-gene immune-related prognostic model for CAD and confirmed its validity. The model can identify potential biomarkers for CAD prediction and more accurately gauge the progression of the disease.

Dataset Information

Identification of novel immune-related targets mediating disease progression in acute pancreatitis.

Introduction

Methods

Results

Discussion

Publications

Identification of novel immune-related targets mediating disease progression in acute pancreatitis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets