scholarly journals The Role of NLRP3 in The Prognosis and Immune Infiltrates of Skin Cutaneous Melanoma (SKCM)

2020 ◽  
Author(s):  
Shaobo Wu ◽  
Qijuan Zang ◽  
Bingling Dai
Keyword(s):  
T Cells ◽  
Logistic Regression ◽  
Cutaneous Melanoma ◽  
Survival Rates ◽  
Gene Set Enrichment Analysis ◽  
Receptor Protein ◽  
Data Set ◽  
Immune Infiltration ◽  
The Impact ◽  
Nlrp3 Expression

Abstract BackgroundSkin cutaneous melanoma is one of most aggressive type of cancers worldwide, Therefore, the identification of SKCM biomarkers is of great importance. NLRP3 Inflammasome Complex Nodelike Receptor protein 3 (NLRP3) is one of the most characteristic inflammasomes belonging to the NLR protein family. This is the first time to use TCGA data to study NLRP3 expression in SKCM patients and its prognostic value, potential biological function, and impact on the immune system. MethodsThe expression of NLRP3 in SKCM was analyzed by GEPIA. We assessed the impact of NLRP3 on SKCM patient survival through the survival module. Then download the SKCM data set from TCGA. Logistic regression was used to analyze the correlation between clinical data and NLRP3 expression. Univariate survival rate and multivariate Cox analysis were used to compare several clinical features and survival rates. We also used CIBERSORT to investigate the association between NLRP3 and cancer immune infiltration. We used TIMER to investigate NLRP3 expression and collection of immune infiltration levels in SKCM, as well as cumulative survival in SKCM. Gene set enrichment analysis (GSEA) was performed using the TCGA dataset. In addition, data from the HPA was used to validate the results.ResultsUnivariate Logistic regression analysis showed that increased NLRP3 expression was significantly correlated with age, stage and tumor status. Specifically, NLRP3 expression level has significant positive correlations with infiltrating levels of B cell, CD4+ T cells, CD8+ T cells, Macrophages, Neutrophils and DCs in SKCM. GSEA revealed that NLRP3 is closely correlated with pathways in cancer. HPA showed that in tumor tissues, NLRP3 has higher levels of expression compared to normal tissues.ConclusionThe discovery of NLRP3 as a new biomarker of SKCM helps to elucidate how changes in the immune environment promote the occurrence of cutaneous melanoma. Further analysis suggested that NLRP3 might be a predictor of SKCM prognosis.

NLRP3 is a Novel Prognostic Biomarker and Correlates With Immune Infiltrates in Lung Adenocarcinoma and Skin Cutaneous Melanoma

2021 ◽  
Author(s):  
Chenxi Yuan ◽  
Qingwei Wang ◽  
Xueting Dai ◽  
Yipeng Song ◽  
Jinming Yu
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Lung Adenocarcinoma ◽  
Immune Cells ◽  
Cutaneous Melanoma ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Potential Biomarker ◽  
The Impact ◽  
Nlrp3 Expression

Abstract Background: Lung adenocarcinoma (LUAD) and skin cutaneous melanoma (SKCM) are common tumors around the world. However, the prognosis in advanced patients is poor. Because NLRP3 was not extensively studied in cancers, so that we aimed to identify the impact of NLRP3 on LUAD and SKCM through bioinformatics analyses. Methods: TCGA and TIMER database were utilized in this study. We compared the expression of NLRP3 in different cancers and evaluated its influence on survival of LUAD and SKCM patients. The correlations between clinical information and NLRP3 expression were analyzed using logistic regression. Clinicopathologic characteristics associated with overall survival in were analyzed by Cox regression. In addition, we explored the correlation between NLRP3 and immune infiltrates. GSEA and co-expressed gene with NLRP3 were also done in this study. Results: NLRP3 expressed disparately in tumor tissues and normal tissues. Cox regression analysis indicated that up-regulated NLRP3 was an independent prognostic factor for good prognosis in LUAD and SKCM. Logistic regression analysis showed increased NLRP3 expression was significantly correlated with favorable clinicopathologic parameters such as no lymph node invasion and no distant metastasis. Specifically, a positive correlation between increased NLRP3 expression and immune infiltrating level of various immune cells was observed. Conclusion: Together with all these findings, increased NLRP3 expression correlates with favorable prognosis and increased proportion of immune cells in LUAD and SKCM. These conclusions indicate that NLRP3 can serve as a potential biomarker for evaluating prognosis and immune infiltration level.

scholarly journals Aberrant expression of USF2 in refractory rheumatoid arthritis and its regulation of proinflammatory cytokines in Th17 cells

2020 ◽  
Vol 117 (48) ◽  
pp. 30639-30648
Author(s):  
Dan Hu ◽  
Emily C. Tjon ◽  
Karin M. Andersson ◽  
Gabriela M. Molica ◽  
Minh C. Pham ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
T Cells ◽  
Transcription Factor ◽  
Proinflammatory Cytokines ◽  
Th17 Cells ◽  
Gene Set Enrichment Analysis ◽  
Aberrant Expression ◽  
Signature Genes ◽  
The Impact

IL-17–producing Th17 cells are implicated in the pathogenesis of rheumatoid arthritis (RA) and TNF-α, a proinflammatory cytokine in the rheumatoid joint, facilitates Th17 differentiation. Anti-TNF therapy ameliorates disease in many patients with rheumatoid arthritis (RA). However, a significant proportion of patients do not respond to this therapy. The impact of anti-TNF therapy on Th17 responses in RA is not well understood. We conducted high-throughput gene expression analysis of Th17-enriched CCR6+CXCR3−CD45RA−CD4+T (CCR6+T) cells isolated from anti-TNF–treated RA patients classified as responders or nonresponders to therapy. CCR6+T cells from responders and nonresponders had distinct gene expression profiles. Proinflammatory signaling was elevated in the CCR6+T cells of nonresponders, and pathogenic Th17 signature genes were up-regulated in these cells. Gene set enrichment analysis on these signature genes identified transcription factor USF2 as their upstream regulator, which was also increased in nonresponders. Importantly, short hairpin RNA targetingUSF2in pathogenic Th17 cells led to reduced expression of proinflammatory cytokines IL-17A, IFN-γ, IL-22, and granulocyte-macrophage colony-stimulating factor (GM-CSF) as well as transcription factor T-bet. Together, our results revealed inadequate suppression of Th17 responses by anti-TNF in nonresponders, and direct targeting of the USF2-signaling pathway may be a potential therapeutic approach in the anti-TNF refractory RA.

scholarly journals An Immune Signature Robustly Predicts Clinical Deterioration for Hepatitis C Virus-Related Early-Stage Cirrhosis Patients

2021 ◽  
Vol 8 ◽  
Author(s):  
Cheng Guo ◽  
Chenglai Dong ◽  
Junjie Zhang ◽  
Rui Wang ◽  
Zhe Wang ◽  
...  
Keyword(s):  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Early Stage ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Calibration Plot ◽  
Prognostic Signature ◽  
Data Set ◽  
Immune Infiltration ◽  
Immune Related Genes

Hepatitis C virus (HCV)-related cirrhosis leads to a heavy global burden of disease. Clinical risk stratification in HCV-related compensated cirrhosis remains a major challenge. Here, we aim to develop a signature comprised of immune-related genes to identify patients at high risk of progression and systematically analyze immune infiltration in HCV-related early-stage cirrhosis patients. Bioinformatics analysis was applied to identify immune-related genes and construct a prognostic signature in microarray data set. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted with the “clusterProfiler” R package. Besides, the single sample gene set enrichment analysis (ssGSEA) was used to quantify immune-related risk term abundance. The nomogram and calibrate were set up via the integration of the risk score and clinicopathological characteristics to assess the effectiveness of the prognostic signature. Finally, three genes were identified and were adopted to build an immune-related prognostic signature for HCV-related cirrhosis patients. The signature was proved to be an independent risk element for HCV-related cirrhosis patients. In addition, according to the time-dependent receiver operating characteristic (ROC) curves, nomogram, and calibration plot, the prognostic model could precisely forecast the survival rate at the first, fifth, and tenth year. Notably, functional enrichment analyses indicated that cytokine activity, chemokine activity, leukocyte migration and chemotaxis, chemokine signaling pathway and viral protein interaction with cytokine and cytokine receptor were involved in HCV-related cirrhosis progression. Moreover, ssGSEA analyses revealed fierce immune-inflammatory response mechanisms in HCV progress. Generally, our work developed a robust prognostic signature that can accurately predict the overall survival, Child-Pugh class progression, hepatic decompensation, and hepatocellular carcinoma (HCC) for HCV-related early-stage cirrhosis patients. Functional enrichment and further immune infiltration analyses systematically elucidated potential immune response mechanisms.

scholarly journals APOC1 is a Potential Prognostic Biomarker and Correlated With Immune Infiltration in ESCC

2020 ◽  
Author(s):  
Jia-yi XIE ◽  
Ming Liu ◽  
Yaxin Luo ◽  
Zhen Wang ◽  
Zhenghong Lu ◽  
...  
Keyword(s):  
T Cells ◽  
Transcription Factors ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Killer Cell ◽  
Gene Set Enrichment Analysis ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract PurposeEsophageal cancer (EC) is the sixth leading cause of cancer death worldwide. Esophageal squamous cell carcinoma (ESCC) is a predominant subtype of EC. Identifying diagnostic biomarkers for ESCC is necessary for cancer practice. Increasing evidence illustrates that apolipoprotein C-1 (APOC1) participates in the carcinogenesis. However, the biological function of APOC1 in ESCC remains unclear. Patients and methodsWe investigated the expression level of APOC1 using TIMER2.0 and GEO databases, the prognostic value of APOC1 in ESCC using Kaplan-Meier plotter and TCGA databases. We used LinkedOmics to identify co-expressed genes with APOC1 and perform GO and KEGG pathway analysis. The target networks of kinases, miRNAs and transcription factors were predicted by gene set enrichment analysis (GSEA). The correlations between APOC1 and immune infiltration were calculated using TIMER2.0 and CIBERSORT databases. We further performed the prognostic analysis based on APOC1 expression levels in related immune cells subgroups via Kaplan-Meier plotter database. ResultsAPOC1 was found overexpressed in tumor tissues in multiple ESCC cohorts and high APOC1 expression was related to a dismal prognosis. Multivariate analysis confirmed that APOC1 overexpression was an independent indicator of poor OS. Functional network analysis indicated that APOC1 might regulate the natural killer cell mediated cytotoxicity, phagosome, AMPK and hippo signaling through pathways involving some cancer-related kinases, miRNA and transcription factors. Immune infiltration analysis showed that APOC1 was significantly positively correlated with M0 macrophages cells, M1 macrophages cells and activated NK cells, negatively correlated with regulatory T cells, CD8 T cells, neutrophils and monocytes. High APOC1 expression had a poor prognosis in server immune cells subgroups in ESCC, including decreased CD8+ T cells subgroups. ConclusionThese findings suggest that increased expression of APOC1 is related to poor prognosis and immune infiltration in ESCC. APOC1 holds promise for serving as a valuable diagnostic and prognostic marker in ESCC.

Prognostic Significance of Nuclear Receptor Coactivator-3 Overexpression in Primary Cutaneous Melanoma

2006 ◽  
Vol 24 (28) ◽  
pp. 4565-4569 ◽  
Author(s):  
Javier Rangel ◽  
Sima Torabian ◽  
Ladan Shaikh ◽  
Mehdi Nosrati ◽  
Frederick L. Baehner ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Nuclear Receptor ◽  
Cutaneous Melanoma ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Primary Cutaneous Melanoma ◽  
Nuclear Receptor Coactivator ◽  
Kaplan Meier ◽  
The Impact

Purpose To assess the prognostic significance of nuclear receptor coactivator-3 (NCOA3) overexpression in primary cutaneous melanoma. Patients and Methods NCOA3 expression was assessed using immunohistochemical analysis of a melanoma tissue microarray (TMA) containing primary melanomas from 343 patients with defined histology and follow-up. The impact of the presence or absence of various prognostic factors on relapse-free survival (RFS) and disease-specific survival (DSS) of melanoma patients was assessed using Cox regression and Kaplan-Meier analysis. The impact of presence or absence of various factors on sentinel lymph node (SLN) metastasis was assessed using logistic regression analysis. Results Increasing degree of NCOA3 expression was significantly predictive of SLN metastasis (P = .013) and the mean number of SLN metastases (P = .031). Kaplan-Meier analysis demonstrated a significant association between NCOA3 overexpression and reduced RFS (P = .021) and DSS (P = .030). Logistic regression analysis revealed increasing degree of NCOA3 expression to be an independent predictor of SLN status (P = .017). Multivariate Cox regression analysis showed the independent impact of NCOA3 expression on RFS (P = .0095) and DSS (P = .021). NCOA3 was the most powerful factor predicting DSS, outperforming tumor thickness and ulceration. Conclusion These results identify NCOA3 as a novel, independent marker of melanoma outcome, with a significant impact on SLN metastasis, RFS, and DSS.

Resource-based view of innovation activity in SMEs: an empirical analysis based on the global competitiveness project

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lívia Lukovszki ◽  
András Rideg ◽  
Norbert Sipos
Keyword(s):  
Logistic Regression ◽  
Literature Review ◽  
Empirical Analysis ◽  
Binary Logistic Regression ◽  
Point Of View ◽  
Innovation Activity ◽  
Data Set ◽  
Content Type ◽  
Resources And Capabilities ◽  
The Impact

Purpose The purpose of this study is to identify the corporate functions that contribute most to the innovation success of SMEs with limited resources. After a systematic literature review, the authors used a unique primary data set of 784 SMEs from eight countries. Descriptive statistics and binary logistic regression were used to show the data set peculiarities. The logistic regression targeted the presence of innovative products and services in sales by 11 dummy variables and 4 principal factors describing SMEs’ different resources and capabilities. Design/methodology/approach The authors developed a resource-based product innovation model that is synthesising the impact of the company resources and capabilities and of the innovation activity of the company on the actual innovation performance. The authors carry out an empirical analysis of the characteristic features of innovation activity in an international sample of SMEs. Findings The results show that two corporate functions play a crucial role in the effectiveness of innovation for SMEs as follows: management and research and development (R&D). In addition, although of lesser importance, the effect of the marketing function also appears significant. The binary logistic regression had 84.2% of explanatory power. Originality/value From a scientific point of view, the SME-focussed, complex and synthesising RBV model of innovation construction and literature review can be used as a reference point for future researches. From a practical point of view, the analysis is useful for those SMEs, which want to gain a competitive advantage through innovation. Indeed, the results show that in the case of SMEs, a company wishing to innovate must invest in three corporate functions for innovation to be effective as follows: management, R&D and marketing.

scholarly journals Identification of Key Immune-Related Genes, Molecular Pathways and Immune Infiltration as Diagnostic and Therapeutic Candidate Targets for RA: an integrated bioinformatics-based analysis

2021 ◽  
Author(s):  
Sheng Fang ◽  
Xiao Fang ◽  
Xin Xu ◽  
Lin Zhong ◽  
An-quan Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Mast Cells ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Systemic Autoimmune Disease ◽  
Molecular Pathways ◽  
Hub Genes ◽  
Immune Infiltration

Abstract Relevance Rheumatoid arthritis (RA) is a systemic autoimmune disease with an aggressive, chronic synovial inflammation as the main pathological change. However, the specific etiology, pathogenesis, and related biomarkers in diagnosis and treatment are still not fully elucidated. This study attempts to provide new perspectives and insights into RA at the genetic, molecular, and cellular levels through the tenet of personalized medicine. Methods Gene expression profiles of four individual knee synovial tissues were downloaded from a comprehensive gene expression database, R language was used to screen for significantly differentially expressed genes (DEGs), Gene Ontology Enrichment Analysis, Kyoto Gene Encyclopedia, and Gene Set Enrichment Analysis were performed to analyze the biological functions and signaling pathways of these DEGs, STRING online database was used to establish protein-protein interaction networks, Cytoscape software to obtain ten hub genes, Goplot to get six inflammatory immune-related hub genes, and CIBERSORT algorithm to impute immune infiltration. Results Molecular pathways that play important roles in RA were obtained: Toll-like receptors, AMPK, MAPK, TNF, FoxO, TGF-beta, PI3K and NF-κB pathways, Ten hub genes: Ccr1, Ccr2, Ccr5, Ccr7, Cxcl5, Cxcl6, Cxcl13, Ccl13, Adcy2, and Pnoc. among which Adcy2 and Pnoc have not been reported in RA studies, suggesting that they may be worthy targets for further study. It was also found that among the synoviocytes in RA, the proportions of plasma cells, CD8 T cells, follicular helper T cells, monocytes, γ delta T cells, and M0 macrophages were higher, while the proportions of CD4 memory resting T cells, regulatory T cells (Tregs), activated NK cells, resting dendritic cells, M1 macrophages, eosinophils, activated mast cells, resting mast cells were lower in proportion, and each cell played an important role in RA. Conclusions This study may help understand the key genes, molecular pathways, the role of inflammatory immune infiltrating cells in RA’s pathogenesis and provide new targets and ideas for the diagnosis and personalized treatment of RA.

scholarly journals Pan-Cancer Analysis of Radiotherapy Benefits and Immune Infiltration in Multiple Human Cancers

Cancers ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 957
Author(s):  
Pengbo Wen ◽  
Yang Gao ◽  
Bin Chen ◽  
Xiaojing Qi ◽  
Guanshuo Hu ◽  
...  
Keyword(s):  
T Cells ◽  
Immune Cell ◽  
Treatment Options ◽  
Tumor Treatment ◽  
Immune Infiltration ◽  
Memory Cd4 T Cells ◽  
The Impact ◽  
Pan Cancer ◽  
Insight Into ◽  
Shed Light

Response to radiotherapy (RT) in cancers varies widely among patients. Therefore, it is very important to predict who will benefit from RT before clinical treatment. Consideration of the immune tumor microenvironment (TME) could provide novel insight into tumor treatment options. In this study, we investigated the link between immune infiltration status and clinical RT outcome in order to identify certain leukocyte subsets that could potentially influence the clinical RT benefit across cancers. By integrally analyzing the TCGA data across seven cancers, we identified complex associations between immune infiltration and patients RT outcomes. Besides, immune cells showed large differences in their populations in various cancers, and the most abundant cells were resting memory CD4 T cells. Additionally, the proportion of activated CD4 memory T cells and activated mast cells, albeit at low number, were closely related to RT overall survival in multiple cancers. Furthermore, a prognostic model for RT outcomes was established with good performance based on the immune infiltration status. Summarized, immune infiltration was found to be of significant clinical relevance to RT outcomes. These findings may help to shed light on the impact of tumor-associated immune cell infiltration on cancer RT outcomes, and identify biomarkers and therapeutic targets.

scholarly journals An Integrative Pan-Cancer Analysis Revealing LCN2 as an Oncogenic Immune Protein in Tumor Microenvironment

2020 ◽  
Vol 10 ◽  
Author(s):  
Wen-Xiu Xu ◽  
Jian Zhang ◽  
Yu-Ting Hua ◽  
Su-Jin Yang ◽  
Dan-Dan Wang ◽  
...  
Keyword(s):  
T Cells ◽  
Cytochrome P450 ◽  
Interaction Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Sterile Inflammation ◽  
Lipocalin 2 ◽  
Immune Infiltration ◽  
Pan Cancer

BackgroundLipocalin 2 (LCN2), an innate immune protein, plays a pivotal role in promoting sterile inflammation by regulating immune responses. However, the role of LCN2 in diverse cancers remains poorly defined. This research aimed to investigate the correlation between LCN2 expression and immunity and visualize its prognostic landscape in pan-cancer.MethodsRaw data in regard to LCN2 expression in cancer patients were acquired from TCGA and GTEx databases. Besides, we investigated the genomic alterations, expression pattern, and survival analysis of LCN2 in pan-cancer across numerous databases, including cBioPortal and GEPIA database. The correlation between LCN2 expression and tumor immune infiltration was explored via TIMER, and we utilized CIBERSORT and ESTIMATE computational methods to assess the proportion of tumor-infiltrating immune cells (TIICs) and the amount of stromal and immune components from TCGA database. Protein–Protein Interaction analysis was performed in GeneMANIA database, and gene functional enrichment was performed by Gene Set Enrichment Analysis (GSEA).ResultsOn balance, tumor tissue had a higher LCN2 expression level compared with that in normal tissue. Elevated expression of LCN2 was related to poor clinical regimen with OS and RFS. There were significant positive correlations between LCN2 expression and TIICs, including CD8+ T cells, CD4+ T cells, B cells, neutrophils, macrophages, and dendritic cells. Moreover, markers of TIICs exhibited different LCN2-related immune infiltration patterns. GSEA analysis showed that the expression of LCN2 was related to retinol metabolism, drug metabolism cytochrome P450 and metabolism of xenobiotics by cytochrome P450.ConclusionsThese findings suggested that LCN2 might serve as a biomarker for immune infiltration and poor prognosis in cancers, shedding new light on therapeutics of cancers.

scholarly journals The impact of Internet use on mental wellbeing and health behaviours among persons with disability

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
K Szulc ◽  
M Duplaga
Keyword(s):  
Logistic Regression ◽  
Digital Divide ◽  
Internet Use ◽  
Health Behaviours ◽  
The Internet ◽  
Suicidal Thoughts ◽  
Data Set ◽  
Persons With Disabilities ◽  
Internet Users ◽  
The Impact

Abstract Background Disability is frequently related to the digital divide. However, the Internet may be also an opportunity for many people with disabilities, especially for those who suffer from difficulties in involving in social activities. For some of them, it is also a tool for undertaking professional tasks. The aim of the study was the assessment of the impact of the Internet on selected aspects of psychological wellbeing and undertaking health behaviours in persons with disabilities. Methods From the data set of the biannual Social Diagnosis survey, data of respondents confirming the status of disability were extracted. They were used for the development of multivariate logistic regression models for self-assessment of life, the prevalence of suicidal thoughts, feeling lonely, the use of psychological support and health behaviours. The impact of Internet usage was adjusted for sociodemographic variables. Weights provided by the study team were used in the analysis. Results The responses from 3231 respondents were used in the analysis. There were 33.1% of Internet users in the study group. Respondents with a mild disability made 25.3%, with moderate 39.4%, with severe 24.2%, and without an established degree of disability 11.1%. Logistic regression modelling revealed that Internet users more frequently assessed their lives as happy (odds ratio, 95% confidence interval (OR, 95%CI): 1.40, 1.13-1.75) and undertook some form of physical activity (2.32, 1.84-2.91). They also less frequently excessively consumed alcohol (0.51, 0.33-0.80). No relation was found for experiencing loneliness (0.89, 0.71-1.12), suicidal thoughts (0.998, 0.77-1.29), receiving psychological care (0.84, 0.62-1.14) and smoking (0.83, 0.66-1.04). Conclusions Although persons with disabilities suffer from digital divide, Internet use may exert a beneficial impact on their wellbeing and favour more beneficial health behaviours. Key messages Internet access and use among persons with disabilities may be an opportunity for improved wellbeing. Persons with disabilities who are Internet users assess their lives as more happy and demonstrate more favourable health behaviours.

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