BATF2 and PDK4 As Diagnostic Molecular Markers of Sarcoidosis and Their Relationship With Immune Infiltration

2021 ◽  
Author(s):  
Xiaoyan Li ◽  
Jing Zhou ◽  
Jie He
Keyword(s):  
Immune Cells ◽  
Immune Cell ◽  
External Validation ◽  
Pulmonary Sarcoidosis ◽  
Gene Expression Omnibus ◽  
Diagnostic Markers ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Immune Disorder ◽  
Qpcr Method

Abstract Background: Sarcoidosis (SA) is an immune disorder disease featured with granulomas formation. The work purposed to uncover potential markers for sarcoidosis (SA) diagnosis and explore how immune cell infiltration contributes to the pathogenesis of SA.Methods: Sarcoidosis GSE83456 samples and GSE42834 from Gene Expression Omnibus (GEO) were analyzed as the training and external validation sets, respectively. R statistical software was employed to uncover the differentially expressed genes (DEGs) of GSE83456. SVM algorithms and LASSO logistic regression were applied for screening and verification of the diagnostic markers for key module genes. The infiltration of immune cells in sarcoidosis patients’ blood samples was assessed by CIBERSORT. The expression of serum BATF2 and PDK4 was detected by RT-qPCR method, and the value of BATF2 and PDK4 mRNA expression in the diagnosis of pulmonary sarcoidosis was analyzed.Results: In total, 580 DEGs were identified from the key module. PDK4 (AUC=0.942) and BATF4 (AUC=0.980) were revealed as diagnostic markers of sarcoidosis. We found that monocytes, T cells regulatory (Tregs), mast cells, macrophages，NK cells, and dendritic cells may contribute to sarcoidosis development. In addition, PDK4 and BATF4 were closely associated with these immune cells. BATF2 and PDK4 were highly expressed in pulmonary sarcoidosis. BATF2 and PDK4 combined to predict the area under the ROC curve of pulmonary sarcoidosis was 0.922.Conclusions: PDK4 and BATF4 could be used as diagnostic markers of sarcoidosis, and immune cell infiltration severs an important role in sarcoidosis.

scholarly journals Five Genes as Diagnostic Markers of Ischemic Stroke and Their Correlation with Immune Infiltration

2021 ◽  
Author(s):  
Meng Wang ◽  
Ruijie Zhang ◽  
Qiongfeng Guan ◽  
Yindan Yao ◽  
Liyuan Han
Keyword(s):  
T Cells ◽  
Dendritic Cells ◽  
Ischemic Stroke ◽  
Immune Cells ◽  
Immune Cell ◽  
Diagnostic Markers ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Γδt Cells ◽  
Negatively Associated

Abstract Background: This study aimed to identify potential diagnostic markers of ischemic stroke (IS) and discuss the function of immune cell infiltration during the pathological process. Methods: We used IS datasets from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified, and functional correlation analysis was performed. We then screened and verified the diagnostic markers of IS. We evaluated the infiltration of immune cells in infarcts using CIBERSORT and analyzed the correlation between diagnostic markers and infiltrating immune cells. Results: A total of 366 DEGs were screened in this study. Genes encoding CTSG, F13A1, PABPC1, ECHDC2, BIRC2 and infiltrating monocytes, M0 macrophages, activated dendritic cells, and neutrophils (area under the curve [AUC] = 0.945) were identified as diagnostic markers of IS. Immune cell infiltration analysis suggested that memory B cells, regulatory T cells, M0 macrophages, CD8 + T cells, γδT cells, activated natural killer cells, monocytes, activated mast cells, and neutrophils were involved in the IS process. Analysis of correlations between expressed genes and infiltrating immune cells found that CTSG was positively associated with M0 macrophages, F13A1 was positively associated with monocytes, PABPC1 was positively associated with activated dendritic cells, eosinophils were negatively associated with neutrophils, ECHDC2 was negatively associated with monocytes, and BIRC2 was positively associated with eosinophils. Conclusion: five genes and four types of immune cells were identified as diagnostic markers of IS, and immune cell infiltration may play an important role in the progression of IS.

scholarly journals An immune cell infiltration-related gene signature predicts prognosis for bladder cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hualin Chen ◽  
Yang Pan ◽  
Xiaoxiang Jin ◽  
Gang Chen
Keyword(s):  
Bladder Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
External Validation ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Prognostic Indicators ◽  
Immune Cell Infiltration ◽  
Related Gene

AbstractTo explore novel therapeutic targets, develop a gene signature and construct a prognostic nomogram of bladder cancer (BCa). Transcriptome data and clinical traits of BCa were downloaded from UCSC Xena database and Gene Expression Omnibus (GEO) database. We then used the method of Single sample Gene Set Enrichment analysis (ssGSEA) to calculate the infiltration abundances of 24 immune cells in eligible BCa samples. By weighted correlation network analysis (WGCNA), we identified turquoise module with strong and significant association with the infiltration abundance of immune cells which were associated with overall survival of BCa patients. Subsequently, we developed an immune cell infiltration-related gene signature based on the module genes (MGs) and immune-related genes (IRGs) from the Immunology Database and Analysis Portal (ImmPort). Then, we tested the prognostic power and performance of the signature in both discovery and external validation datasets. A nomogram integrated with signature and clinical features were ultimately constructed and tested. Five prognostic immune cell infiltration-related module genes (PIRMGs), namely FPR1, CIITA, KLRC1, TNFRSF6B, and WFIKKN1, were identified and used for gene signature development. And the signature showed independent and stable prognosis predictive power. Ultimately, a nomogram consisting of signature, age and tumor stage was constructed, and it showed good and stable predictive ability on prognosis. Our prognostic signature and nomogram provided prognostic indicators and potential immunotherapeutic targets for BCa. Further researches are needed to verify the clinical effectiveness of this nomogram and these biomarkers.

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

Diagnostics ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 171 ◽  
Author(s):  
Ya-Jun Deng ◽  
En-Hui Ren ◽  
Wen-Hua Yuan ◽  
Guang-Zhi Zhang ◽  
Zuo-Long Wu ◽  
...  
Keyword(s):  
T Cells ◽  
Mast Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Diagnostic Markers ◽  
Cell Infiltration ◽  
Recursive Feature Elimination ◽  
Support Vector ◽  
Resting Cells ◽  
Immune Cell Infiltration

This study aimed to find potential diagnostic markers for osteoarthritis (OA) and analyze the role of immune cells infiltration in this pathology. We used OA datasets from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and perform functional correlation analysis. Then least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination algorithms were used to screen and verify the diagnostic markers of OA. Finally, CIBERSORT was used to evaluate the infiltration of immune cells in OA tissues, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. A total of 458 DEGs were screened in this study. GRB10 and E2F3 (AUC = 0.962) were identified as diagnostic markers of OA. Immune cell infiltration analysis found that resting mast cells, T regulatory cells, CD4 memory resting T cells, activated NK cells, and eosinophils may be involved in the OA process. In addition, GRB10 was correlated with NK resting cells, naive CD4 + T cells, and M1 macrophages, while E2F3 was correlated with resting mast cells. In conclusion, GRB10 and E2F3 can be used as diagnostic markers of osteoarthritis, and immune cell infiltration plays an important role in the occurrence and progression of OA.

scholarly journals Identification of immune-based prostate cancer subtypes using mRNA expression

2020 ◽  
Author(s):  
Jukun Song ◽  
Song He ◽  
Wei Wang ◽  
Jiaming Su ◽  
Dongbo Yuan ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Immune Response ◽  
Immune Cells ◽  
Immune Cell ◽  
Molecular Classification ◽  
Cell Types ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Cell Subpopulation ◽  
Immune Cell Infiltration

Abstract Background Immune infiltration of Prostate cancer (PCa) was highly related to clinical outcomes. However, previous works failed to elucidate the diversity of different immune cell types that make up the function of the immune response system. The aim of the study was to uncover the composition of TIICs in PCa utilizing the CIBERSORT algorithm and further reveal the molecular characteristics of PCa subtypes. Method In the present work, we employed the CIBERSORT method to evaluate the relative proportions of immune cell profiling in PCa and adjacent samples, normal samples. We analyzed the correlation between immune cell infiltration and clinical information. The tumor-infiltrating immune cells of the TCGA PCa cohort were analyzed for the first time. The fractions of 22 immune cell types were imputed to determine the correlation between each immune cell subpopulation and clinical feature. Three types of molecular classification were identified via R-package of “CancerSubtypes”. The functional enrichment was analyzed in each subtype. The submap and TIDE algorithm were used to predict the clinical response to immune checkpoint blockade, and GDSC was employed to screen chemotherapeutic targets for the potential treatment of PCa. Results In current work, we utilized the CIBERSORT algorithm to assess the relative proportions of immune cell profiling in PCa and adjacent samples, normal samples. We investigated the correlation between immune cell infiltration and clinical data. The tumor-infiltrating immune cells in the TCGA PCa cohort were analyzed. The 22 immune cells were also calculated to determine the correlation between each immune cell subpopulation and survival and response to chemotherapy. Three types of molecular classification were identified. Each subtype has specific molecular and clinical characteristics. Meanwhile, Cluster I is defined as advanced PCa, and is more likely to respond to immunotherapy. Conclusions Our results demonstrated that differences in immune response may be important drivers of PCa progression and response to treatment. The deconvolution algorithm of gene expression microarray data by CIBERSOFT provides useful information about the immune cell composition of PCa patients. In addition, we have found a subtype of immunopositive PCa subtype and will help to explore the reasons for the poor effect of PCa on immunotherapy, and it is expected that immunotherapy will be used to guide the individualized management and treatment of PCa patients.

scholarly journals Correlation Between 18F-FDG Uptake and Immune Cell Infiltration in Metastatic Brain Lesions

2021 ◽  
Vol 11 ◽  
Author(s):  
Young-Sil An ◽  
Se-Hyuk Kim ◽  
Tae Hoon Roh ◽  
So Hyun Park ◽  
Tae-Gyu Kim ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
Standardized Uptake Value ◽  
Brain Lesions ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Ki 67 ◽  
Glucose Transporter 1 ◽  
Fdg Uptake

BackgroundThe purpose of this study was to investigate the correlation between 18F-fluorodeoxyglucose (FDG) uptake and infiltrating immune cells in metastatic brain lesions.MethodsThis retrospective study included 34 patients with metastatic brain lesions who underwent brain 18F-FDG positron emission tomography (PET)/computed tomography (CT) followed by surgery. 18F-FDG uptake ratio was calculated by dividing the standardized uptake value (SUV) of the metastatic brain lesion by the contralateral normal white matter uptake value. We investigated the clinicopathological characteristics of the patients and analyzed the correlation between 18F-FDG uptake and infiltration of various immune cells. In addition, we evaluated immune-expression levels of glucose transporter 1 (GLUT1), hexokinase 2 (HK2), and Ki-67 in metastatic brain lesions.ResultsThe degree of 18F-FDG uptake of metastatic brain lesions was not significantly correlated with clinical parameters. There was no significant relationship between the 18F-FDG uptake and degree of immune cell infiltration in brain metastasis. Furthermore, other markers, such as GLUT1, HK2, and Ki-67, were not correlated with degree of 18F-FDG uptake. In metastatic brain lesions that originated from breast cancer, a higher degree of 18F-FDG uptake was observed in those with high expression of CD68.ConclusionsIn metastatic brain lesions, the degree of 18F-FDG uptake was not significantly associated with infiltration of immune cells. The 18F-FDG uptake of metastatic brain lesions from breast cancer, however, might be associated with macrophage activity.

Prognostic and predictive value of tumor-infiltrating immune cells in Japanese patients with stage II/III gastric cancer.

2014 ◽  
Vol 32 (3_suppl) ◽  
pp. 46-46
Author(s):  
Sophie Earle ◽  
Toru Aoyama ◽  
Alexander I. Wright ◽  
Darren Treanor ◽  
Yohei Miyagi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Adjuvant Chemotherapy ◽  
Immune Cells ◽  
Prognostic Markers ◽  
Immune Cell ◽  
Japanese Patients ◽  
Stage Ii ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Treatment Interaction

46 Background: Since the ACTS-GC trial, Japanese patients with stage II/III gastric cancer (GC) receive adjuvant S1 chemotherapy. However, selection of patients (pts) by TNM stage does not predict benefit from adjuvant S1 with certainty. Thus, there is an urgent clinical need to identify predictive biomarkers. Increasing evidence suggests tumor immune cell infiltration may be related to GC pts prognosis. We tested the hypothesis that extent and type of immune cell infiltration in GC is related to benefit from adjuvant chemotherapy. Methods: Tissue microarrays from 252 GC resections (109 pts treated by surgery alone (S), 143 pts treated by surgery and adjuvant S1 chemotherapy (SC)) from the Kanagawa Cancer Center Hospital (Yokohama, Japan) were investigated by immunohistochemistry for common leucocytes antigen (CD45), neutrophils (CD66b), macrophages (CD68 and CD163), T-cell subtypes (CD45R0, CD8, CD3), B-cells (CD20) and Treg cells (FOXP3). Staining was quantified as percentage immunoreactivity/area by automated image analysis. Relationship with overall survival was analyzed. A Cox regression model was used to identify independent prognostic markers and treatment interaction effect. Results: The hazard ratio of S1 was 0.694 in this GC cohort which is similar to the results of the ACTS-GC trial. CD45 and CD45R0 were independent prognostic markers in the S group only (CD45 p=0.032, CD45R0 p=0.003). A treatment interaction effect was seen for CD45, CD45R0, and CD68 (p value for test of interaction: CD45 p=0.062, CD45R0 p=0.082, CD68 p=0.057). Survival in the SC group was significantly poorer compared to the S group for CD45>56% or CD68>7% (p<0.05). Conclusions: This is the first study to investigate the relationship between tumor immune cell infiltration at time of surgery and benefit from adjuvant chemotherapy. Our results indicate that GC patients with high intratumoral levels of CD68, CD45, or CD45R0 positive immune cells might not benefit from adjuvant S1 chemotherapy. These findings require validation in a second independent dataset before conducting a prospective study stratifying patients with stage II/III GC based upon extent of CD45, CD45R0, or CD68 immune cell infiltration for adjuvant treatment.

scholarly journals The prognostic value of a tumor microenvironment-based immune cell infiltration score model in colon cancer

2021 ◽  
Author(s):  
Xiaofen Pan ◽  
Xingkui Tang ◽  
Minling Liu ◽  
Xijun Luo ◽  
Mengyuan Zhu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Signaling Pathway ◽  
Immune Cells ◽  
Evaluation System ◽  
Prognostic Value ◽  
Immune Cell ◽  
Wnt Signaling Pathway ◽  
Mapk Signaling ◽  
Cell Infiltration ◽  
Immune Cell Infiltration

Abstract BackgroundTumor microenvironment consists of tumor cells, immune cells and other matric components. Tumor infiltration immune cells are associated with prognosis. But all the current prognosis evaluation system dose not take tumor immune cells other matrix component into consideration. In the current study, we aimed to construct a prognosis predictive model based on tumor microenvironment.MethodCIBERSORT and ESTIMATE algorithms were used to reveal the immune cell infiltration landscape of colon cancer. Patients were classified into three clusters by ConsensusClusterPlus algorithm. Immune cell infiltration (ICI) scores of each patient were determine by principal-component analysis. Patients were divided to high and low ICI score groups. Survival, gene expression and somatic mutation of the two groups were compared.ResultsPatients with no lymph node invasion, no metastasis, T1-2 disease and stage I-II had higher ICI scores. Calcium signaling pathway, leukocyte transendothelial migration pathway, MAPK signaling pathway, TGF β pathway, and WNT signaling pathway were enriched in high ICI score group. Immune-checkpoint genes and immune-activity associated genes were significantly decreased in high ICI score. Patients in high ICI score group had better survival than low ICI score group. Prognostic value of ICI score was independent of TMB.ConclusionICI score might serve as an independent prognostic biomarker in colon cancer.

scholarly journals SERPINE1 associated with remodeling of the tumor microenvironment in colon cancer progression: a novel therapeutic target

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shaokun Wang ◽  
Li Pang ◽  
Zuolong Liu ◽  
Xiangwei Meng
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
The Relationship

Abstract Background The change of immune cell infiltration essentially influences the process of colorectal cancer development. The infiltration of immune cells can be regulated by a variety of genes. Thus, modeling the immune microenvironment of colorectal cancer by analyzing the genes involved can be more conducive to the in-depth understanding of carcinogenesis and the progression thereof. Methods In this study, the number of stromal and immune cells in malignant tumor tissues were first estimated by using expression data (ESTIMATE) and cell-type identification with relative subsets of known RNA transcripts (CIBERSORT) to calculate the proportion of infiltrating immune cell and stromal components of colon cancer samples from the Cancer Genome Atlas database. Then the relationship between the TMN Classification and prognosis of malignant tumors was evaluated. Results By investigating differentially expressed genes using COX regression and protein-protein interaction network (PPI), the candidate hub gene serine protease inhibitor family E member 1 (SERPINE1) was found to be associated with immune cell infiltration. Gene Set Enrichment Analysis (GSEA) further projected the potential pathways with elevated SERPINE1 expression to carcinogenesis and immunity. CIBERSORT was subsequently utilized to investigate the relationship between the expression differences of SERPINE1 and immune cell infiltration and to identify eight immune cells associated with SERPINE1 expression. Conclusion We found that SERPINE1 plays a role in the remodeling of the colon cancer microenvironment and the infiltration of immune cells.

scholarly journals The Downregulation of PTGS2 Mediated by ncRNAs is Tightly Correlated with Systemic Sclerosis-Interstitial Lung Disease

2022 ◽  
Vol 12 ◽  
Author(s):  
Zhixiao Xu ◽  
Chengshui Chen
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Immune Cell ◽  
Gene Expression Omnibus ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Hub Genes ◽  
Cd20 Expression ◽  
Key Genes

Background: Interstitial lung disease in systemic sclerosis (SSc-ILD) is one of the most severe complications of systemic sclerosis (SSc) and is the main cause of mortality. In this study, we aimed to explore the key genes in SSc-ILD and analyze the relationship between key genes and immune cell infiltration as well as the key genes relevant to the hallmarks of cancer.Methods: Weighted gene co-expression network analysis (WGCNA) algorithm was implemented to explore hub genes in SSc-ILD samples from the Gene Expression Omnibus (GEO) database. Logistic regression analysis was performed to screen and verify the key gene related to SSc-ILD. CIBERSORT algorithms were utilized to analyze immune cell infiltration. Moreover, the correlation between the key genes and genes relevant to cancer was also evaluated. Furthermore, non-coding RNAs (ncRNAs) linking to PTGS2 were also explored.Results: In this study, we first performed WGCNA analysis for three GEO databases to find the potential hub genes in SSc-ILD. Subsequently, we determined PTGS2 was the key gene in SSC-ILD. Furthermore, in CIBERSORT analyses, PTGS2 were tightly correlated with immune cells such as regulatory T cells (Tregs) and was negatively correlated with CD20 expression. Moreover, PTGS2 was associated with tumor growth. Then, MALAT1, NEAT1, NORAD, XIST identified might be the most potential upstream lncRNAs, and LIMS1 and RANBP2 might be the two most potential upstream circRNAs.Conclusion: Collectively, our findings elucidated that ncRNAs-mediated downregulation of PTGS2, as a key gene in SSc-ILD, was positively related to the occurrence of SSc-ILD and abnormal immunocyte infiltration. It could be a promising factor for SSc-ILD progression to malignancy.

scholarly journals Prevention of lipopolysaccharide-induced CD11b+ immune cell infiltration in the kidney: role of AT2 receptors

2019 ◽  
Vol 39 (5) ◽  
Author(s):  
Sanket Patel ◽  
Isha Dhande ◽  
Elizabeth Alana Gray ◽  
Quaisar Ali ◽  
Tahir Hussain
Keyword(s):  
Immune Cells ◽  
Immune Cell ◽  
Interleukin 10 ◽  
Conditioned Media ◽  
Cell Infiltration ◽  
Low Grade ◽  
Immune Cell Infiltration ◽  
Anti Inflammatory

AbstractImmune cell infiltration plays a central role in mediating endotoxemic acute kidney injury (AKI). Recently, we have reported the anti-inflammatory and reno-protective role of angiotensin-II type-2 receptor (AT2R) activation under chronic low-grade inflammatory condition in the obese Zucker rat model. However, the role of AT2R activation in preventing lipopolysaccharide (LPS)-induced early infiltration of immune cells, inflammation and AKI is not known. Mice were treated with AT2R agonist C21 (0.3 mg/kg), with and without AT2R antagonist PD123319 (5 mg/kg) prior to or concurrently with LPS (5 mg/kg) challenge. Prior-treatment with C21, but not concurrent treatment, significantly prevented the LPS-induced renal infiltration of CD11b+ immune cells, increase in the levels of circulating and/or renal chemotactic cytokines, particularly interleukin-6 (IL-6) and monocyte chemoattractant protein-1 (MCP-1) and markers of renal dysfunction (blood urea nitrogen and albuminuria), while preserving anti-inflammatory interleukin-10 (IL-10) production. Moreover, C21 treatment in the absence of LPS increased renal and circulating IL-10 levels. To investigate the role of IL-10 in a cross-talk between epithelial cells and monocytes, we performed in vitro conditioned media (CM) studies in human kidney proximal tubular epithelial (HK-2) cells and macrophages (differentiated human monocytes, THP-1 cells). These studies revealed that the conditioned-media derived from the C21-treated HK-2 cells reduced LPS-induced THP-1 tumor necrosis factor-α (TNF-α) production via IL-10 originating from HK-2 cells. Our findings suggest that prior activation of AT2R is prophylactic in preventing LPS-induced renal immune cell infiltration and dysfunction, possibly via IL-10 pathway.

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