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 ◽  
...  

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.

2021 ◽  
Author(s):  
Meng Wang ◽  
Ruijie Zhang ◽  
Qiongfeng Guan ◽  
Yindan Yao ◽  
Liyuan Han

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.


2021 ◽  
Author(s):  
Zhihao Chen ◽  
Liubing Li ◽  
Ziyuan Li ◽  
Xi Wang ◽  
Mingxiao Han ◽  
...  

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.


PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9996
Author(s):  
Yongyong Wang ◽  
Jianji Guo

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.


2020 ◽  
Author(s):  
Naiqiang Zhu ◽  
Jingyi Hou

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.


2020 ◽  
Author(s):  
Naiqiang Zhu ◽  
Jingyi Hou

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.


2020 ◽  
Author(s):  
Naiqiang Zhu ◽  
Jingyi Hou

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.


Diagnostics ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 171 ◽  
Author(s):  
Ya-Jun Deng ◽  
En-Hui Ren ◽  
Wen-Hua Yuan ◽  
Guang-Zhi Zhang ◽  
Zuo-Long Wu ◽  
...  

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.


2020 ◽  
Author(s):  
Naiqiang Zhu ◽  
Jingyi Hou

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.


2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Naiqiang Zhu ◽  
Jingyi Hou

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.


2020 ◽  
Author(s):  
Zeyu Yang ◽  
Tianjing Du ◽  
Qiao Xiong ◽  
Weiwei Zhang ◽  
Chao Wang ◽  
...  

Abstract Background The role of immune cell infiltration in tumor biology and the potential of immunotherapy for the treatment of several cancers have been proven. However, the immunogenomic landscape and immune cell infiltration need to be comprehensively analyzed in bladder cancer (BC). This study aimed to explore the immune-related genes (IRGs) in BC to create a prognostic risk assessment model and gain some insights into the molecular underpinnings of BC. Methods Based on the datasets retrieved from The Cancer Genome Atlas (TCGA) database, we identified survival-associated IRGs via univariate Cox analysis. Then, we created an immune-related gene-based prognostic factor (IRGPF) and validated it by multivariable Cox analysis. We displayed the profiles of 22 types of immune cells by using CIBERSORT and explored the relationship between IRGs and immune cell infiltration. Results Altogether, 58 differentially expressed IRGs were found to be associated with the prognosis of patients with BC. We constructed a prognostic assessment model as an IRGPF with IRGs (THBS1, CXCL9, CXCL11, FABP6, BIRC5, and PPY). Profiles of the infiltrating immune cells confirmed their significance based on clinical factors and individual differences. The IRGPF was related to immune cell infiltration, and the key gene was identified as THBS1. Conclusions Our findings confirmed that IRGs could act as independent prognostic factors and immune-driver factors. Patients with high levels of activated memory CD4 T cells but low levels of resting memory CD4 T cells had a better prognosis. This study indicates the possibility of developing new immunotherapeutic strategies and individualized treatment based on this approach.


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