GRB10 and E2F3 as Diagnostic Markers of Osteoarthritis and Their Correlation with Immune Infiltration

Deng, Yajun; Ren, Enhui; Yuan, Wenhua; Zhang, Guang-Zhi; Wu, Zhi-Xi; Xie, Qiqi

doi:10.3390/diagnostics10030171

Cited by 97 publications

(87 citation statements)

References 45 publications

(50 reference statements)

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“…The upregulation of the suppressor of cytokine signaling 3 (SOCS3) gene increases the risk of AMI by potentiating inflammatory responses (16). Moreover, research has shown that immune cell infiltration plays an increasingly significant role in the occurrence and development of various diseases (11,(17)(18)(19). With regards to AMI, mast cells, M2 macrophages, and eosinophils have been demonstrated to affect cardiac function after AMI, providing novel insights into the significance of immune modulation in the infarcted heart (20).…”

Section: Introductionmentioning

confidence: 99%

Predicting Diagnostic Gene Biomarkers Associated With Immune Infiltration in Patients With Acute Myocardial Infarction

Zhao

Xie

Zhang

2020

Front. Cardiovasc. Med.

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The present study was designed to identify potential diagnostic markers for acute myocardial infarction (AMI) and determine the significance of immune cell infiltration in this pathology. Methods: Two publicly available gene expression profiles (GSE66360 and GSE48060 datasets) from human AMI and control samples were downloaded from the GEO database. Differentially expressed genes (DEGs) were screened between 80 AMI and 71 control samples. The LASSO regression model and support vector machine recursive feature elimination (SVM-RFE) analysis were performed to identify candidate biomarkers. The area under the receiver operating characteristic curve (AUC) value was obtained and used to evaluate discriminatory ability. The expression level and diagnostic value of the biomarkers in AMI were further validated in the GSE60993 dataset (17 AMI patients and 7 controls). The compositional patterns of the 22 types of immune cell fraction in AMI were estimated based on the merged cohorts using CIBERSORT. Results: A total of 27 genes were identified. The identified DEGs were mainly involved in carbohydrate binding, Kawasaki disease, atherosclerosis, and arteriosclerotic cardiovascular disease. Gene sets related to atherosclerosis signaling, primary immunodeficiency, IL-17, and TNF signaling pathways were differentially activated in AMI compared with the control. IL1R2, IRAK3, and THBD were identified as diagnostic markers of AMI (AUC = 0.877) and validated in the GSE60993 dataset (AUC = 0.941). Immune cell infiltration analysis revealed that IL1R2, IRAK3, and THBD were correlated with M2 macrophages, neutrophils, monocytes, CD4 + resting memory T cells, activated natural killer (NK) cells, and gamma delta T cells. Conclusion: IL1R2, IRAK3, and THBD can be used as diagnostic markers of AMI, and can provide new insights for future studies on the occurrence and the molecular mechanisms of AMI.

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Section: Introductionmentioning

confidence: 99%

Predicting Diagnostic Gene Biomarkers Associated With Immune Infiltration in Patients With Acute Myocardial Infarction

Zhao

Xie

Zhang

2020

Front. Cardiovasc. Med.

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“…CIBERSORT is a computational tool widely used in the analysis of immune responses of 22 types of immune cells under numerous diseases such as atopic dermatitis [ 11 ], lupus nephritis [ 12 ], ischemia-reperfusion injury in renal transplantation [ 13 ], osteoarthritis [ 14 , 15 ], in fresh, frozen and fixed specimens [ 16 ] based on microarray and RNA-seq data. However, only few researches have utilized the CIBERSORT method to investigate immune cell infiltration characteristics in acne and rosacea.…”

Section: Introductionmentioning

confidence: 99%

Elucidating the immune infiltration in acne and its comparison with rosacea by integrated bioinformatics analysis

et al. 2021

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Background Acne vulgaris and rosacea are common inflammatory complications of the skin, both characterized by abnormal infiltration of immune cells. The two diseases can be differentiated based on characteristic profile of the immune cell infiltrates at the periphery of disease lesions. In addition, dysregulated infiltration of immune cells not only occur in the acne lesions but also in non-lesional areas of patients with the disease, thus characterizing the immune infiltration in these sites can further enhance our understanding on the pathogenesis of acne. Methods Five microarray data-sets (GSE108110, GSE53795, GSE65914, GSE14905 and GSE78097) were downloaded from Gene Expression Omnibus. After removing the batch effects and normalizing the data, we applied the CIBERSORT algorithm combined with signature matrix LM22, to describe 22 types of immune cells’ infiltration in acne less than 48 hour (H) old, in comparation with non-lesional skin of acne patients, healthy skin and rosacea (including erythematotelangiectatic rosacea, papulopustular rosacea and phymatous rosacea) and we compared gene expression of Th1 and Th17-related molecules in acne, rosacea and healthy control. Results Compared with the non-lesional skin of acne patients, healthy individuals and rosacea patients, there is a significant increase in infiltration of neutrophils, monocytes and activated mast cells around the acne lesions, less than 48 H after their development. Contrarily, few naive CD4+ T cells, plasma cells, memory B cells and resting mast cells infiltrate acne sites compared to the aforementioned groups of individuals. Moreover, the infiltration of Regulatory T cells (Tregs) in acne lesions is substantially lower, relative to non-lesional sites of acne patients and skin of healthy individuals. In addition, non-lesional sites of acne patients exhibit lower infiltration of activated memory CD4+ T cells, plasma cells, memory B cells, M0 macrophages, neutrophils, resting mast cells but higher infiltration of Tregs and resting dendritic cells relative to skin of healthy individuals. Intriguingly, we found that among the 3 rosacea subtypes, the immune infiltration profile of papulopustular rosacea is the closest to that of acne lesions. In addition, through gene expression analysis of acne, rosacea and skin tissues of healthy individuals, we found a higher infiltration of Th1 and Th17 cells in acne lesions, relative to non-lesional skin areas of acne patients. Conclusions Our study provides new insights into the inflammatory pathogenesis of acne, and the difference between acne and rosacea, which helps in differentiating the two diseases. Our findings also guide on appropriate target therapy of the immune cell infiltrates in the two disease conditions.

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“…However, our research has some limitations. CIBERSORT analysis is based on limited genetic data, which may deviate from heterogeneous interactions between cells, disease-induced disorders, or phenotypic plasticity (Deng et al, 2020). Second, our sample size is relatively small, so the analysis of the results may not be powerful enough.…”

Section: Discussionmentioning

confidence: 99%

“…CIBER-SORT is a method for quantifying cell type composition from tissue gene expression datasets based on immune cell signatures (Newman et al, 2015). It has been widely used to analyze immune cell infiltration in various diseases such as osteoarthritis (Deng et al, 2020), colorectal cancer (Ye et al, 2019) and atherosclerosis (Xu and Yang, 2020). However, so far, there have been no reports on the use of CIBERSORT to analyze the infiltration of SS immune cells.…”

Section: Introductionmentioning

confidence: 99%

SELL and IFI44 as potential biomarkers of Sjögren’s syndrome and their correlation with immune cell infiltration

Chen

Wang

et al. 2021

Genes Genet. Syst.

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The onset of Sjögren's syndrome (SS) is hidden, early diagnosis is difficult, and the disorder seriously endangers the physical and mental health of affected people. This study aims to identify potential biomarkers of SS and to investigate the characteristics of immune cell infiltration. We used four SS gene expression profile data series from the Gene Expression Omnibus database, and applied bioinformatics analysis and machine learning algorithms to screen two biomarkers, SELL (L-selectin) and IFI44 (interferon-induced protein 44), from 101 differentially expressed genes. The two-gene model comprising SELL and IFI44 showed good diagnostic ability for SS in the training set (AUC = 0.992) and verification set (AUC = 0.917). Analysis of infiltrating immune cells in SS identified naive B cells, resting CD4 memory T cells, activated CD4 memory T cells, gamma delta T cells, M0 macrophages, M1 macrophages, plasma cells, CD8 T cells, activated NK cells and monocytes as candidate participants in the SS process. Furthermore, SELL was associated with M2 macrophages, activated CD4 memory T cells, gamma delta T cells, resting NK cells and plasma cells, while IFI44 was associated with activated mast cells, resting NK cells, resting mast cells and CD8 T cells. This study demonstrates that SELL and IFI44 can serve as good diagnostic markers for SS and may also be new diagnostic and therapeutic targets for SS.

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GRB10 and E2F3 as Diagnostic Markers of Osteoarthritis and Their Correlation with Immune Infiltration

Cited by 97 publications

References 45 publications

Predicting Diagnostic Gene Biomarkers Associated With Immune Infiltration in Patients With Acute Myocardial Infarction

Predicting Diagnostic Gene Biomarkers Associated With Immune Infiltration in Patients With Acute Myocardial Infarction

Elucidating the immune infiltration in acne and its comparison with rosacea by integrated bioinformatics analysis

SELL and IFI44 as potential biomarkers of Sjögren’s syndrome and their correlation with immune cell infiltration

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