Immunohistochemical observation of local inflammatory cell infiltration in the host-tissue reaction site of human hydatid cysts

2018 ◽  
Vol 93 (3) ◽  
pp. 277-285 ◽  
Author(s):  
R. Jafari ◽  
B. Sanei ◽  
A. Baradaran ◽  
M. Kolahdouzan ◽  
B. Bagherpour ◽  
...  
Keyword(s):  
T Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Tissue Reaction ◽  
Distinct Pattern ◽  
Host Tissue ◽  
Cell Infiltration ◽  
Reaction Site ◽  
Hydatid Cysts ◽  
Ki 67

AbstractThe aim of this study was to evaluate the pattern of local immune cell infiltration in human cystic echinococcosis (CE) by identifying the subtypes of immune cells using immunohistochemistry (IHC). Fifty surgically removed hydatid cyst samples and surrounding tissues were collected from patients referred to Al-Zahra Hospital, Isfahan, Iran. IHC was performed on the surrounding host tissue of hydatid cysts using anti-human CD3, CD19, CD8, CD4, CD68, CD56, Ki-67 and Foxp3 (forkhead box P3) antibodies. The results were then compared to hepatocellular carcinoma and chronic hepatitis. In the host-tissue reaction site of liver hydatid cysts, a distinct pattern of local immune cell response, which outwardly consisted of a pack of the fibrous elements, a layer of palisading macrophages, an eosinophil-containing layer and a layer of accumulated lymphocytes, was observed. However, in some cases there were no positive cells for CD56+ natural killer cells and Foxp3+ regulatory T cells. The CD3+ T cells were the predominant inflammatory cells in all groups, followed by CD19+ B cells. It can be concluded that different immune cells are involved in the local response to human hydatid cysts.

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.

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 Identification of the Key Serum Biomarkers to Diagnose and Predict Metastasis of Osteosarcoma Based on the Analysis of Immune Cell Infiltration Characteristics

2021 ◽  
Author(s):  
Zhihao Chen ◽  
Liubing Li ◽  
Ziyuan Li ◽  
Xi Wang ◽  
Mingxiao Han ◽  
...  
Keyword(s):  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Serum Biomarkers ◽  
Differentially Expressed ◽  
Cell Infiltration ◽  
Diagnostic Model ◽  
Immune Cell Infiltration ◽  
Differentially Expressed Mirnas

Abstract Background: The potential functions of circular RNAs (circRNAs) and micro RNAs (miRNAs) in osteosarcoma (OS) have not been fully elucidated. Especially, the behavior and mechanism of immune responses in OS development and progression have not been fully demonstrated. It was reported that circRNAs and miRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of many cancers. This study aimed to identify novel key serum biomarkers to diagnose and predict metastasis of OS based on the analysis of immune cell infiltration characteristics.Methods: The differentially-expressed circRNAs (DEcircRNAs), differentially-expressed miRNAs (DEmiRNAs),and differentially-expressed mRNAs (DEmRNAs) of human OS were investigated based on the microarray data downloaded from Gene Expression Omnibus (GEO) datasets. Then, we analyzed immune characteristics pattern of tumor-infiltrating immune cells in OS. On this basis, we identified statistically-significant transcription factors and performed pathway enrichment analysis. Subsequently, we constructed protein-protein interaction (PPI) and competitive endogenous RNA (ceRNA) networks. Moreover, the biological characteristic of targets in ceRNA networks was proposed. Finally, the expression and diagnostic capability of these potential biomarkers from ceRNA network were confirmed by RT-qPCR in patients’ serum.Results: Seven differentially-expressed circRNAs (DEcircRNAs), 166 differentially-expressed miRNAs (DEmiRNAs) and 175 differentially-expressed mRNAs (DEmRNAs) were identified in total. The highest level of infiltration in OS patients were M0 macrophages, M2 macrophages and CD8+ T cells. Further, M0 macrophages and CD8+ T cells were showed the largest negative correlation coefficients. These significant immune characteristics pattern of tumor-infiltrating immune cells were revealed by the principal component analysis in OS. Moreover, we found 185 statistically-significant transcription factors in which the main significant molecules show the potential in immunotherapy of OS. Hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A from ceRNA networks associated with immune cell infiltration were confirmed as the potential novel biomarkers for OS diagnosis, of which FAM98A could distinguish and predict metastasis. Most importantly, a novel diagnostic model consisting of the four promising biomarkers (hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A) was highlighted with 0.928 AUC value.Conclusions: In summary, the potenial serum biomarkers to diagnose and predict metastasis of OS based on the analysis of immune cell infiltration characteristics were found, and a novel diagnostic model consisting of four promising serum biomarkers was proposed firstly. These results provided a new perspective for the immunotherapy of OS.

scholarly journals Immune cell landscape analysis reveals prognostic immune cells and its potential mechanism in squamous cell lung carcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9996
Author(s):  
Yongyong Wang ◽  
Jianji Guo
Keyword(s):  
T Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Smoking History ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Squamous Cell Lung Carcinoma ◽  
Cell Lung Carcinoma ◽  
Tfh Cells ◽  
Memory Cd4 T Cells

Background Squamous cell lung carcinoma (LUSC) was closely associated with smoking which was known to have a distant immunosuppression effect. In this study, we aimed to explore the relationship between immune cells and clinical outcomes of LUSC patients with smoking history. Methods The immune cell infiltration and RNA expression profiles of LUSC patients were collected from The Cancer Genome Atlas (TCGA). Then, the correlation between immune cell infiltration and clinical characteristics was explored. According to the level of immune cell infiltration, LUSC patients with smoking history were divided into high or low group to screen the differentially expressed lncRNAs and mRNAs. The prediction of target genes was performed by miRanda. Finally, the prognostic value of a certain signature was confirmed in an independent dataset. Results Higher abundance of tumor-infiltrating T follicular helper (Tfh) cells together with a lower abundance of resting memory CD4 T cells had been found in LUSC current reformed smokers for ≤15 years and current smoking patients. Moreover, Tfh cell infiltration was not only associated with better overall survival (OS) but also varied from different degrees of TNM stage. Low expression of lncRNA PWRN1 and its potential regulating genes DMRTB1, PIRT, APOBEC1, and ZPBP2 were associated with better OS. Combining PWRN1 and four regulating genes as a signature, patients with higher-level expression of the signature had shorter survival time in not only the TCGA but also in the GEO dataset. Conclusions It was found that Tfh cells presented higher infiltration in LUSC current reformed smokers for ≤15 years and current smokers, while resting memory CD4 T cells had lower infiltration. The signature consisting of PWRN1 as well as its predicted targeted mRNAs was dysregulated in different levels of Tfh cell infiltration and might indicate patients’ OS.

scholarly journals Assessing immune infiltration and the tumor microenvironment for the diagnosis and prognosis of sarcoma

2020 ◽  
Author(s):  
Naiqiang Zhu ◽  
Jingyi Hou
Keyword(s):  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Blue Module

Abstract Background: Sarcomas, cancers originating from mesenchymal cells, are comprehensive tumors with poor prognoses, yet their tumorigenic mechanisms are largely unknown. In this study, we characterize infiltrating immune cells and analyze immune scores to identify the molecular mechanism of immunologic response to sarcomas.Method: The “CIBERSORT” algorithm was used to calculate the amount of L22 immune cell infiltration in sarcomas. Then, the “ESTIMATE” algorithm was used to assess the “Estimate,” “Immune,” and “Stromal” scores. Weighted gene co-expression network analysis (WGCNA) was utilized to identify the significant module related to the immune therapeutic target. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the “clusterProfiler” package in R for annotation and visualization. Results: Macrophages were the most common immune cells infiltrating sarcomas. The number of CD8 T cells was negatively associated with that of M0 and M2 macrophages, and positively associated with M macrophages in sarcomas samples. The clinical parameters (disease type, gender) significantly increased with higher Estimate, Immune, and Stromal scores, and with a better prognosis. The blue module was significantly associated with CD8 T cells. Functional enrichment analysis showed that the blue module was mainly involved in chemokine signaling and the PI3K-Akt signaling pathway. CD48, P2RY10 and RASAL3 were identified and validated at the protein level.Conclusion: Based on the immune cell infiltration and immune microenvironment, three key genes were identified, thus presenting novel molecular mechanisms of sarcoma metastasis.

scholarly journals Assessing immune infiltration and the tumor microenvironment for the diagnosis and prognosis of sarcoma

2020 ◽  
Author(s):  
Naiqiang Zhu ◽  
Jingyi Hou
Keyword(s):  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Blue Module

Abstract Background: Sarcomas, cancers originating from mesenchymal cells, are comprehensive tumors with poor prognoses, yet their tumorigenic mechanisms are largely unknown. In this study, we characterize infiltrating immune cells and analyze immune scores to identify the molecular mechanism of immunologic response to sarcomas.Method: The “CIBERSORT” algorithm was used to calculate the amount of L22 immune cell infiltration in sarcomas. Then, the “ESTIMATE” algorithm was used to assess the “Estimate,” “Immune,” and “Stromal” scores. Weighted gene co-expression network analysis (WGCNA) was utilized to identify the significant module related to the immune therapeutic target. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the “clusterProfiler” package in R for annotation and visualization. Results: Macrophages were the most common immune cells infiltrating sarcomas. The number of CD8 T cells was negatively associated with that of M0 and M2 macrophages, and positively associated with M macrophages in sarcomas samples. The clinical parameters (disease type, gender) significantly increased with higher Estimate, Immune, and Stromal scores, and with a better prognosis. The blue module was significantly associated with CD8 T cells. Functional enrichment analysis showed that the blue module was mainly involved in chemokine signaling and the PI3K-Akt signaling pathway. CD48, P2RY10 and RASAL3 were identified and validated at the protein level.Conclusion: Based on the immune cell infiltration and immune microenvironment, three key genes were identified, thus presenting novel molecular mechanisms of sarcoma metastasis.

scholarly journals Activation of MAPK/ERK signalling in Merlin-null Schwann cells leads to increased and sustained immune cell infiltration in the peripheral nervous system

2021 ◽  
Vol 23 (Supplement_4) ◽  
pp. iv8-iv8
Author(s):  
Evyn Woodhouse ◽  
Liyam Laraba ◽  
Charlotte Lespade ◽  
Marie Srotyr ◽  
Alison C Lloyd ◽  
...  
Keyword(s):  
T Cells ◽  
Schwann Cells ◽  
Immune Cells ◽  
Peripheral Nerves ◽  
Dorsal Root ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Erk Pathway ◽  
Raf Kinase

Abstract Aims Previous work has shown that increased numbers of macrophages are associated with more rapid schwannoma tumour growth and we are interested in signals that control entry of macrophages and other immune cells into these tumours. Activation of the Raf-kinase domain and the Raf/MEK/ERK pathway within Schwann cells has been observed to induce an inflammatory response in peripheral nerves in the absence of injury. Activation of an inducible Raf-kinase transgene in Schwann cells allows modelling of acute demyelination of peripheral nerves without nerve injury. This Raf-oestrogen receptor fusion protein (Raf-TR) is activated by the oestrogen analogue Tamoxifen and so allows targeted, controlled activation of the Raf/MEK/ERK pathway within the Schwann cells. Here, in order to understand drivers of tumour formation, we assess the effect of MAPK activation in Merlin-null Schwann cells upon immune cell infiltration within the PNS. Method RafTR-P0CRE-NF2fl/fl mice of 4-6 weeks age were injected daily (IP) with 2mg of 4-hydroxy-tamoxifen or vehicle (corn oil) control for 5 consecutive days. RafTR was activated on either a Merlin (NF2) wild-type (NF2 fl/fl, P0-CRE-) or NF2 null (NF2 fl/fl, P0-CRE+) background and effects on immune cell infiltration studied in each condition. Immunofluorescence was performed in the dorsal root ganglia (DRGs) and sciatic nerves of mice to identify various immune cell infiltrates at various timepoints. These will include neutrophils, mast cells, T-Cells and macrophages using the cell markers Csf3r, C-kit, CD3 and IBA1 respectively. Results At 21 days post treatment, a significantly increased infiltration of macrophages within the sciatic nerve and dorsal root ganglia was observed in mice treated with Tamoxifen when compared to vehicle controls. Loss of NF2 led to a massive increase in the number of macrophages recruited to peripheral nerves in tamoxifen-treated mice compared to Cre- mice and Cre+ treated with vehicle alone. Further assessment of other immune cell infiltration including neutrophils, mast cells and T cells are ongoing. Conclusion Raf/MEK/ERK signalling, in the absence of tumour suppressor Merlin, significantly increases the infiltration of inflammatory cells such as macrophages into peripheral nerves even in the absence of injury. As this effect is enhanced in NF2 null mice, this suggests that Merlin plays an important role in inhibiting the inflammatory response in peripheral nerves. It also suggests that Merlin could be involved in maintaining the blood nerve barrier (BNB), as in its absence the greater influx of immune cells into the nerves and DRGs suggests a more complete loss of BNB function than just activation of the Raf/MEK/ERK cascade alone.

scholarly journals Assessing immune infiltration and the tumor microenvironment for the diagnosis and prognosis of sarcoma

2020 ◽  
Author(s):  
Naiqiang Zhu ◽  
Jingyi Hou
Keyword(s):  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Blue Module

Abstract Background Sarcomas, cancers originating from mesenchymal cells, are comprehensive tumors with poor prognoses, yet their tumorigenic mechanisms are largely unknown. In this study, we aimed to characterize infiltrating immune cells and genes associated with the immunologic response to sarcomas. Method The “CIBERSORT” algorithm was used to calculate the amount of L22 immune cell infiltration in sarcomas. Then, the “ESTIMATE” algorithm was used to assess the “Estimate,” “Immune,” and “Stromal” scores. Weighted gene co-expression network analysis (WGCNA) was utilized to identify the significant module related to the immune therapeutic target. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Gens and Genomes (KEGG) analysis were applied using the “clusterProfiler” package in R for annotation and visualization. Results Macrophages were the most common immune cells infiltrating sarcomas. The number of CD8 T cells was negatively associated with that of M0 and M2 macrophages, and positively associated with M macrophages in sarcomas samples. The clinical parameters (disease type, gender) significantly increased with higher Estimate, Immune, and Stromal scores, and with a better prognosis. The blue module was significantly associated with CD8 T cells. Functional enrichment analysis showed that the blue module was mainly involved in chemokine signaling and the PI3K-Akt signaling pathway. CD48, P2RY10 and RASAL3 were identified and validated at the protein level. Conclusion Based on the immune cell infiltration and immune microenvironment, three key genes were identified, which suggest novel molecular mechanisms of sarcoma metastasis.

scholarly journals The Immune Cell Landscape in Renal Allografts

2021 ◽  
Vol 30 ◽  
pp. 096368972199545
Author(s):  
Jun Lu ◽  
Yi Zhang ◽  
Jingjing Sun ◽  
Shulin Huang ◽  
Weizhen Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Cell Infiltration ◽  
M1 Macrophages ◽  
Deconvolution Analysis ◽  
Renal Allografts ◽  
Antibody Mediated Rejection

Immune cell infiltration plays an important role in the pathophysiology of kidney grafts, but the composition of immune cells is ill-defined. Here, we aimed at evaluating the levels and composition of infiltrating immune cells in kidney grafts. We used CIBERSORT, an established algorithm, to estimate the proportions of 22 immune cell types based on gene expression profiles. We found that non-rejecting kidney grafts were characteristic with high rates of M2 macrophages and resting mast cells. The proportion of M1 macrophages and activated NK cells were increased in antibody-mediated rejection (ABMR). In T cell-mediated rejection (TCMR), a significant increase in CD8 T cell and γδT cell infiltration was observed. CD8 positive T cells were dramatically increased in mixed-ABMR/TCMR. Then, the function of ABMR and TCMR prognostic molecular biomarkers were identified. Finally, we described the gene expression of molecular markers for ABMR diagnosis was elevated and related to the ratio of monocytes and M1 macrophages in ABMR biopsies, while the expression of TCMR diagnosis markers was increased too and positively correlated with γδT cells and activated CD4 memory T cells in TCMR biopsies. Our data suggest that CIBERSORT’s deconvolution analysis of gene expression data provides valuable information on the composition of immune cells in renal allografts.

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.

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