Autophagy-related genes are potential diagnostic biomarkers for dermatomyositis

Wang, Le; Fang, Dalang; Liu, Yuan

doi:10.21037/atm-22-70

Cited by 8 publications

(6 citation statements)

References 36 publications

(40 reference statements)

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“…Our study showed that DDIT3 and FOS genes were significantly correlated with immune cells, with FOS expression being positively associated with eosinophils and DDIT3 expression being positively associated with immature dendritic cells. It has been reported that FOS may treat dermatomyositis by regulating the infiltration of immune cells ( 38 ). Deng et al.…”

Section: Discussionmentioning

confidence: 99%

Identification of autophagy-related genes in osteoarthritis articular cartilage and their roles in immune infiltration

Qin,

Zhang,

et al. 2023

Front. Immunol.

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BackgroundAutophagy plays a critical role in the progression of osteoarthritis (OA), mainly by regulating inflammatory and immune responses. However, the underlying mechanisms remain unclear. This study aimed to investigate the potential relevance of autophagy-related genes (ARGs) associated with infiltrating immune cells in OA.MethodsGSE114007, GSE169077, and ARGs were obtained from the Gene Expression Omnibus (GEO) database and the Human Autophagy database. R software was used to identify the differentially expressed autophagy-related genes (DEARGs) in OA. Functional enrichment and protein–protein interaction (PPI) analyses were performed to explore the role of DEARGs in OA cartilage, and then Cytoscape was utilized to screen hub ARGs. Single-sample gene set enrichment analysis (ssGSEA) was used to conduct immune infiltration analysis and evaluate the potential correlation of key ARGs and immune cell infiltration. Then, the expression levels of hub ARGs in OA were further verified by the GSE169077 and qRT-PCR. Finally, Western blotting and immunohistochemistry were used to validate the final hub ARGs.ResultsA total of 24 downregulated genes and five upregulated genes were identified, and these genes were enriched in autophagy, mitophagy, and inflammation-related pathways. The intersection results identified nine hub genes, namely, CDKN1A, DDIT3, FOS, VEGFA, RELA, MAP1LC3B, MYC, HSPA5, and HSPA8. GSE169077 and qRT-PCR validation results showed that only four genes, CDKN1A, DDT3, MAP1LC3B, and MYC, were consistent with the bioinformatics analysis results. Western blotting and immunohistochemical (IHC) showed that the expression of these four genes was significantly downregulated in the OA group, which is consistent with the qPCR results. Immune infiltration correlation analysis indicated that DDIT3 was negatively correlated with immature dendritic cells in OA, and FOS was positively correlated with eosinophils.ConclusionCDKN1A, DDIT3, MAP1LC3B, and MYC were identified as ARGs that were closely associated with immune infiltration in OA cartilage. Among them, DDIT3 showed a strong negative correlation with immature dendritic cells. This study found that the interaction between ARGs and immune cell infiltration may play a crucial role in the pathogenesis of OA; however, the specific interaction mechanism needs further research to be clarified. This study provides new insights to further understand the molecular mechanisms of immunity involved in the process of OA by autophagy.

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Section: Discussionmentioning

confidence: 99%

Identification of autophagy-related genes in osteoarthritis articular cartilage and their roles in immune infiltration

Qin,

Zhang,

et al. 2023

Front. Immunol.

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“…ARGs have been shown to be of great value in the diagnosis and/or prognostic evaluation of diseases such as cancer, dilated cardiomyopathy, acute myocardial infarction, diabetic nephropathy, pulmonary hypertension, dermatomyositis, and rheumatoid arthritis ( Du et al, 2020 ; Tong et al, 2021 ; Bai et al, 2022 ; Fan et al, 2022 ; Wang et al, 2022 ; Yang et al, 2022 ; Zhang et al, 2022 ). Therefore, ROC curve and survival analysis were performed on key genes to explore their diagnostic efficacy and prognostic value in sepsis.…”

Section: Discussionmentioning

confidence: 99%

Diagnostic and prognostic value of autophagy-related key genes in sepsis and potential correlation with immune cell signatures

Yang,

Zhou,

et al. 2023

Front. Cell Dev. Biol.

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Background: Autophagy is involved in the pathophysiological process of sepsis. This study was designed to identify autophagy-related key genes in sepsis, analyze their correlation with immune cell signatures, and search for new diagnostic and prognostic biomarkers.Methods: Whole blood RNA datasets GSE65682, GSE134347, and GSE134358 were downloaded and processed. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to identify autophagy-related key genes in sepsis. Then, key genes were analyzed by functional enrichment, protein-protein interaction (PPI), transcription factor (TF)-gene and competing endogenous RNA (ceRNA) network analysis. Subsequently, key genes with diagnostic efficiency and prognostic value were identified by receiver operating characteristic (ROC) curves and survival analysis respectively. The signatures of immune cells were estimated using CIBERSORT algorithm. The correlation between significantly different immune cell signatures and key genes was assessed by correlation analysis. Finally, key genes with both diagnostic and prognostic value were verified by RT-qPCR.Results: 14 autophagy-related key genes were identified and their TF-gene and ceRNA regulatory networks were constructed. Among the key genes, 11 genes (ATIC, BCL2, EEF2, EIF2AK3, HSPA8, IKBKB, NLRC4, PARP1, PRKCQ, SH3GLB1, and WIPI1) had diagnostic efficiency (AUC > 0.90) and 5 genes (CAPN2, IKBKB, PRKCQ, SH3GLB1 and WIPI1) were associated with survival prognosis (p-value < 0.05). IKBKB, PRKCQ, SH3GLB1 and WIPI1 had both diagnostic and prognostic value, and their expression were verified by RT-qPCR. Analysis of immune cell signatures showed that the abundance of neutrophil, monocyte, M0 macrophage, gamma delta T cell, activated mast cell and M1 macrophage subtypes increased in the sepsis group, while the abundance of resting NK cell, resting memory CD4+ T cell, CD8+ T cell, naive B cell and resting dendritic cell subtypes decreased. Most of the key genes correlated with the predicted frequencies of CD8+ T cells, resting memory CD4+ T cells, M1 macrophages and naive B cells.Conclusion: We identified autophagy-related key genes with diagnostic and prognostic value in sepsis and discovered associations between key genes and immune cell signatures. This work may provide new directions for the discovery of promising biomarkers for sepsis.

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“…It can be seen from Figure 5 that the core genes CDKN1A, CDK2, E2F1, CDK1, and PCNA in the top 5 of the degree value are analyzed. Wang et al have confrmed that the above fve genes are closely related to DM, providing a strong basis for the next experiment [7][8][9].…”

Section: Construction Of Ppi Networkmentioning

confidence: 92%

To Investigate the Potential Mechanism of Huanglian Jiangtang Formula Lowering Blood Sugar in View of Network Pharmacology and Molecular Docking Technology

Li¹,

Zhou

Lü

et al. 2023

Evidence-Based Complementary and Alternative Medicine

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Objective. In view of network pharmacology and molecular docking technology, to explore the targets as well as effect mechanism of the Huanglian Jiangtang formula (including Coptis chinensis, Anemarrhena asphodeloides, rhubarb wine, Cortex Moutan, Rehmannia glutinosa, and dried ginger) in the type II diabetes therapy. Methods. TCMSP and Batman database (DB) were used to retrieve the chemical components and action targets of drugs; GeneCards, OMIM, TTD, DrugBank, and other databases were applied to screen the disease targets. We used the UniProt DB to annotate the targets before building the drug-compound-target network with Cytoscape 3.9.1. We also exploited the String DB to construct the protein-protein interaction (PPI) network. In addition, the targets for the treatment of type II diabetes were searched in the DrugBank, OMIM, GeneCards, and TTD database; then, we utilized Venn to intersect the key targets for the therapy of type II diabetes and active ingredient targets to obtain common targets. Furthermore, we exploited the common targets using GO and KEGG enrichment analysis method. The common targets and core components were analyzed by molecular docking using the AutoDock software. Results. A total of 61 effective components of this compound were screened out; drugs and type II diabetes have 278 common targets; the PPI network screened core target proteins such as CDKN1A, CDK2, and E2F1 with the help of molecular docking technology; the three main compounds including quercetin, kaempferol, and gamma-aminobutyric acid were obtained. Besides, the key target proteins had excellent binding properties with the main components. The signal pathways of six compound interventions in type II diabetes were mostly related to cancer, cocaine addiction, aminoacyl-tRNA biosynthesis, glycine, serine, threonine metabolism, platinum drug resistance, and other pathways, according to the KEGG enrichment analysis method. Conclusion. In the treatment of diabetes, the Huanglian Jiangtang formula has sorts of properties especially in the aspects of composition, target, and pathway. Its molecular target and mechanism of action may be related to pathways in cancer, cocaine addiction, aminoacyl-tRNA biosynthesis, glycine, serine, threonine metabolism, platinum drug resistance, and other pathways. This conclusion can provide theoretical support and science for further research.

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Autophagy-related genes are potential diagnostic biomarkers for dermatomyositis

Abstract: Contributions: (I) Conception and design: Y Liu; (II) Administrative support: Y Liu; (III) Provision of study materials or patients: L Wang; (IV) Collection and assembly of data: D Fang; (V) Data analysis and interpretation: D Fang;

Cited by 8 publications

References 36 publications

Identification of autophagy-related genes in osteoarthritis articular cartilage and their roles in immune infiltration

Identification of autophagy-related genes in osteoarthritis articular cartilage and their roles in immune infiltration

Diagnostic and prognostic value of autophagy-related key genes in sepsis and potential correlation with immune cell signatures

To Investigate the Potential Mechanism of Huanglian Jiangtang Formula Lowering Blood Sugar in View of Network Pharmacology and Molecular Docking Technology

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