scholarly journals Development of an Immune-Related Gene Signature for Prognosis in Melanoma

2021 ◽  
Vol 10 ◽  
Author(s):  
Jia-An Zhang ◽  
Xu-Yue Zhou ◽  
Dan Huang ◽  
Chao Luan ◽  
Heng Gu ◽  
...  
Keyword(s):  
T Cells ◽  
Immune Cell ◽  
Treatment Method ◽  
Gene Signature ◽  
Cell Infiltration ◽  
Venn Diagram ◽  
Immune Cell Infiltration ◽  
Tumor Purity ◽  
New Treatment ◽  
Immune Related Genes

Melanoma remains a potentially deadly malignant tumor. The incidence of melanoma continues to rise. Immunotherapy has become a new treatment method and is widely used in a variety of tumors. Original melanoma data were downloaded from TCGA. ssGSEA was performed to classify them. GSVA software and the "hclust" package were used to analyze the data. The ESTIMATE algorithm screened DEGs. The edgeR package and Venn diagram identified valid immune-related genes. Univariate, LASSO and multivariate analyses were used to explore the hub genes. The "rms" package established the nomogram and calibrated the curve. Immune infiltration data were obtained from the TIMER database. Compared with that of samples in the high immune cell infiltration cluster, we found that the tumor purity of samples in the low immune cell infiltration cluster was higher. The immune score, ESTIMATE score and stromal score in the low immune cell infiltration cluster were lower. In the high immune cell infiltration cluster, the immune components were more abundant, while the tumor purity was lower. The expression levels of TIGIT, PDCD1, LAG3, HAVCR2, CTLA4 and the HLA family were also higher in the high immune cell infiltration cluster. Survival analysis showed that patients in the high immune cell infiltration cluster had shorter OS than patients in the low immune cell infiltration cluster. IGHV1-18, CXCL11, LTF, and HLA-DQB1 were identified as immune cell infiltration-related DEGs. The prognosis of melanoma was significantly negatively correlated with the infiltration of CD4+ T cells, CD8+ T cells, dendritic cells, neutrophils and macrophages. In this study, we identified immune-related melanoma core genes and relevant immune cell subtypes, which may be used in targeted therapy and immunotherapy of melanoma.

scholarly journals Identification and Verification of Immune-Related Gene Prognostic Signature Based on ssGSEA for Osteosarcoma

2020 ◽  
Vol 10 ◽  
Author(s):  
Bo Xiao ◽  
Liyan Liu ◽  
Aoyu Li ◽  
Cheng Xiang ◽  
Pingxiao Wang ◽  
...  
Keyword(s):  
Immune Cell ◽  
Cox Regression ◽  
Gene Signature ◽  
Cell Infiltration ◽  
Significant Prognostic Factor ◽  
Immune Cell Infiltration ◽  
Related Gene ◽  
Prognostic Signature ◽  
Immune Related Gene ◽  
Immune Related Genes

Osteosarcoma is the most common malignant bone tumor in children and adolescence. Multiple immune-related genes have been reported in different cancers. The aim is to identify an immune-related gene signature for the prospective evaluation of prognosis for osteosarcoma patients. In this study, we evaluated the infiltration of immune cells in 101 osteosarcoma patients downloaded from TARGET using the ssGSEA to the RNA-sequencing of these patients, thus, high immune cell infiltration cluster, middle immune cell infiltration cluster and low immune cell infiltration cluster were generated. On the foundation of high immune cell infiltration cluster vs. low immune cell infiltration cluster and normal vs. osteosarcoma, we found 108 common differentially expressed genes which were sequentially submitted to univariate Cox and LASSO regression analysis. Furthermore, GSEA indicated some pathways with notable enrichment in the high- and low-immune cell infiltration cluster that may be helpful in understanding the potential mechanisms. Finally, we identified seven immune-related genes as prognostic signature for osteosarcoma. Kaplan-Meier analysis, ROC curve, univariate and multivariate Cox regression further confirmed that the seven immune-related genes signature was an innovative and significant prognostic factor independent of clinical features. These results of this study offer a means to predict the prognosis and survival of osteosarcoma patients with uncovered seven-gene signature as potential biomarkers.

scholarly journals SFTPA1 is a potential prognostic biomarker correlated with immune cell infiltration and response to immunotherapy in lung adenocarcinoma

2021 ◽  
Author(s):  
Lu Yuan ◽  
Xixi Wu ◽  
Longshan Zhang ◽  
Mi Yang ◽  
Xiaoqing Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
T Cells ◽  
Lung Adenocarcinoma ◽  
Expression Profile ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Regulatory Pathways ◽  
Chronic Lung Diseases ◽  
Potential Biomarker

AbstractPulmonary surfactant protein A1 (SFTPA1) is a member of the C-type lectin subfamily that plays a critical role in maintaining lung tissue homeostasis and the innate immune response. SFTPA1 disruption can cause several acute or chronic lung diseases, including lung cancer. However, little research has been performed to associate SFTPA1 with immune cell infiltration and the response to immunotherapy in lung cancer. The findings of our study describe the SFTPA1 expression profile in multiple databases and was validated in BALB/c mice, human tumor tissues, and paired normal tissues using an immunohistochemistry assay. High SFTPA1 mRNA expression was associated with a favorable prognosis through a survival analysis in lung adenocarcinoma (LUAD) samples from TCGA. Further GeneOntology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses showed that SFTPA1 was involved in the toll-like receptor signaling pathway. An immune infiltration analysis clarified that high SFTPA1 expression was associated with an increased number of M1 macrophages, CD8+ T cells, memory activated CD4+ T cells, regulatory T cells, as well as a reduced number of M2 macrophages. Our clinical data suggest that SFTPA1 may serve as a biomarker for predicting a favorable response to immunotherapy for patients with LUAD. Collectively, our study extends the expression profile and potential regulatory pathways of SFTPA1 and may provide a potential biomarker for establishing novel preventive and therapeutic strategies for lung adenocarcinoma.

scholarly journals Enhanced CD4+ and CD8+ T cell infiltrate within convex hull defined pancreatic islet borders as autoimmune diabetes progresses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alexander J. Dwyer ◽  
Jacob M. Ritz ◽  
Jason S. Mitchell ◽  
Tijana Martinov ◽  
Mohannad Alkhatib ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Convex Hull ◽  
Pancreatic Islets ◽  
Immune Cell ◽  
Nod Mice ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Analytical Strategy ◽  
Islet Mass

AbstractThe notion that T cell insulitis increases as type 1 diabetes (T1D) develops is unsurprising, however, the quantitative analysis of CD4+ and CD8+ T cells within the islet mass is complex and limited with standard approaches. Optical microscopy is an important and widely used method to evaluate immune cell infiltration into pancreatic islets of Langerhans for the study of disease progression or therapeutic efficacy in murine T1D. However, the accuracy of this approach is often limited by subjective and potentially biased qualitative assessment of immune cell subsets. In addition, attempts at quantitative measurements require significant time for manual analysis and often involve sophisticated and expensive imaging software. In this study, we developed and illustrate here a streamlined analytical strategy for the rapid, automated and unbiased investigation of islet area and immune cell infiltration within (insulitis) and around (peri-insulitis) pancreatic islets. To this end, we demonstrate swift and accurate detection of islet borders by modeling cross-sectional islet areas with convex polygons (convex hulls) surrounding islet-associated insulin-producing β cell and glucagon-producing α cell fluorescent signals. To accomplish this, we used a macro produced with the freeware software ImageJ equipped with the Fiji Is Just ImageJ (FIJI) image processing package. Our image analysis procedure allows for direct quantification and statistical determination of islet area and infiltration in a reproducible manner, with location-specific data that more accurately reflect islet areas as insulitis proceeds throughout T1D. Using this approach, we quantified the islet area infiltrated with CD4+ and CD8+ T cells allowing statistical comparison between different age groups of non-obese diabetic (NOD) mice progressing towards T1D. We found significantly more CD4+ and CD8+ T cells infiltrating the convex hull-defined islet mass of 13-week-old non-diabetic and 17-week-old diabetic NOD mice compared to 4-week-old NOD mice. We also determined a significant and measurable loss of islet mass in mice that developed T1D. This approach will be helpful for the location-dependent quantitative calculation of islet mass and cellular infiltration during T1D pathogenesis and can be combined with other markers of inflammation or activation in future studies.

scholarly journals A novel pyroptosis-associated gene signature for immune status and prognosis of cutaneous melanoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12304
Author(s):  
Zhengyuan Wu ◽  
Leilei Chen ◽  
Chaojie Jin ◽  
Jing Xu ◽  
Xingqun Zhang ◽  
...  
Keyword(s):  
Cutaneous Melanoma ◽  
Immune Status ◽  
Immune Cell ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Tumor Cell Death ◽  
Prognostic Gene ◽  
Prognostic Gene Signature

Background Cutaneous melanoma (CM) is a life-threatening destructive malignancy. Pyroptosis significantly correlates with programmed tumor cell death and its microenvironment through active host-tumor crosstalk. However, the prognostic value of pyroptosis-associated gene signatures in CM remains unclear. Methods Gene profiles and clinical data of patients with CM were downloaded from The Cancer Genome Atlas (TCGA) to identify differentially expressed genes associated with pyroptosis and overall survival (OS). We constructed a prognostic gene signature using LASSO analysis, then applied immune cell infiltration scores and Kaplan-Meier, Cox, and pathway enrichment analyses to determine the roles of the gene signature in CM. A validation cohort was collected from the Gene Expression Omnibus (GEO) database. Results Four pyroptosis-associated genes were identified and incorporated into a prognostic gene signature. Integrated bioinformatics findings showed that the signature correlated with patient survival and was associated with tumor growth and metastasis. The results of Gene Set Enrichment Analysis of a risk signature indicated that several enriched pathways are associated with cancer and immunity. The risk signature for immune status significantly correlated with tumor stem cells, the immune microenvironment, immune cell infiltration and immune subtypes. The expression of four pyroptosis genes significantly correlated with the OS of patients with CM and was related to the sensitivity of cancer cells to several antitumor drugs. A signature comprising four genes associated with pyroptosis offers a novel approach to the prognosis and survival of patients with CM and will facilitate the development of individualized therapy.

Identification and Validation of Immune-Related Genes and Immune Cell Infiltration in Preeclampsia

2021 ◽  
Author(s):  
Rongxin Chen ◽  
Qing Han ◽  
Huale Zhang ◽  
Jianying Yan
Keyword(s):  
Immune Cell ◽  
Risk Model ◽  
Differentially Expressed ◽  
Cell Infiltration ◽  
Receptor Interaction ◽  
Immune Cell Infiltration ◽  
Multisystem Disease ◽  
Predicting Model ◽  
Immune Related Genes ◽  
Maternal Fetal Interface

Abstract Background Preeclampsia (PE) is a complex multisystem disease and its etiology remains unclear. The aim of this study was to identify potential immune-related diagnostic genes for PE, analyze the role of immune cell infiltration in PE, and explore the mechanism underlying PE-induced disruption of immune tolerance at the maternal-fetal interface. Methods We used the PE dataset GES25906 from Gene Expression Omnibus and immune-related genes from ImmPort database. The differentially expressed genes (DEGs) were identified using the “limma” package, and the differentially expressed immune-related genes (DEIGs) were extracted from the DEGs and immune-related genes using Venn diagrams. The potential functions of DEIGs were determined by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Furthermore, the protein–protein interaction network was obtained from the STRING database, and it was visualized using Cytoscape software. Least absolute shrinkage and selection operator logistic regression was used to verify the diagnostic markers of PE and build a predicting model. The model was validated using datasets GSE66273 and GSE75010. Finally, CIBERSORT was used to evaluate the infiltration of immune cells in PE tissues. Results Six genes (ACTG1, ENG, IFNGR1, ITGB2, NOD1, and SPP1) enriched in Th17 cell differentiation, cytokine-cytokine receptor interaction, innate immune response, and positive regulation of MAPK cascade pathways were identified, and a predicting model was built. Datasets GSE66273 and GSE75010 were used to validate the model, and the area under the curve was 0.8333 and 0.8107, respectively. Immune cell infiltration analysis revealed an increase in plasma cells and gamma delta T cells and a decrease in resting natural killer cells in the high score group according to the predictive model risk values. Conclusions We developed a risk model to predict PE and proved that immune imbalance at the maternal-fetal interface plays a key role in the pathogenesis of PE.

Profiles of immune‐related genes and immune cell infiltration in the tumor microenvironment of diffuse lower‐grade gliomas

2020 ◽  
Vol 235 (10) ◽  
pp. 7321-7331 ◽  
Author(s):  
Xiangyang Deng ◽  
Dongdong Lin ◽  
Xiaojia Zhang ◽  
Xuchao Shen ◽  
Zelin Yang ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Lower Grade ◽  
Immune Cell Infiltration ◽  
Immune Related Genes

scholarly journals Comprehensive Analysis of YTH Domain Family in Lung Adenocarcinoma: Expression Profile, Association with Prognostic Value, and Immune Infiltration

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Kuan Hu ◽  
Lei Yao ◽  
Yuanliang Yan ◽  
Lei Zhou ◽  
Juanni Li
Keyword(s):  
T Cells ◽  
Lung Adenocarcinoma ◽  
Prognostic Value ◽  
Immune Cell ◽  
Expression Profiles ◽  
Family Members ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Domain Family ◽  
Yth Domain

Background. All YTH domain family members are m6A reader proteins accounting for the methylation modulation involved in the process of tumorgenesis and tumor progression. However, the expression profiles and roles of the YTH domain family in lung adenocarcinoma (LUAD) remain to be further illustrated. Methods. GEPIA2 and TNMplot databases were used to generate the expression profiles of the YTH family. Kaplan-Meier plotter database was employed to analysis the prognostic value of the YTH family. Coexpression profiles and genetic alterations analysis of the YTH family were undertaken using the cBioPortal database. YTH family protein-associated protein-protein interaction (PPI) network was identified by using STRING. Functional enrichment analysis was performed with the help of the WebGestalt database. The correlation analysis between the YTH family and immune cell infiltration in LUAD was administrated by using the TIMER2.0 database. Results. mRNA expression of YTHDC1 and YTHDC2 was significantly lower in LUAD, whereas YTHDF1, YTHDF2, and YTHDF3 with apparently higher expression. YTHDF2 expression was observed to be the highest in the nonsmoker subgroup, and its expression gradually decreased with the increased severity of smoking habit. LUAD patients with low expression of YTHDC2, YTHDF1, and YTHDF2 were correlated with a better overall survival (OS) time. The YTHDF1 genetic alteration rate was 26%, which was the highest in the YTH family. The major cancer-associated functions of YTH family pointed in the direction of immunomodulation, especially antigen processing and presentation. Most of the YTH family members were significantly correlated with the infiltration of CD4+ T cells, CD8+ T cells, macrophages, and neutrophils, indicating the deep involvement of the YTH domain family in the immune cell infiltration in LUAD. Conclusion. The molecular and expression profiles of the YTH family were dysregulated in LUAD. YTH family members (especially YTHDC2) were promising biomarkers and potential therapeutic targets that may bring benefit for the patients with LUAD.

scholarly journals Identification of new biomarkers and pathways associated with treatment and prognosis in melanoma patients

2020 ◽  
Author(s):  
Biao Huang ◽  
Wei Han ◽  
Zu-Feng Sheng ◽  
Guo-Liang Shen
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Tumor Microenvironment ◽  
Prognostic Value ◽  
Immune Cell ◽  
Gene Interaction ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Strong Positive Correlation ◽  
Hub Genes

Abstract Background Skin cutaneous melanoma (SKCM) is known as the most malignancy and treatment-resistant in human tumor, causing about 72% of deaths in skin carcinoma. However, the potential mechanism and new effective targets remain to be further elucidated. Available datasets such as Gene Expression Omnibus (GEO) can be utilized to search for novel therapeutic targets and prognostic biomarkers. Methods Three data sets were downloaded from GEO database . The differentially expressed genes (DEGs) were identified via Venn software. Protein‐protein interaction network of DEGs was developed and the module hub genes analysis was constructed by Cytoscape. Subsequently, multiple online tools and Kaplan-Meier survival curves were analyzed to detect underlying signaling pathways, gene expression, drug-gene interaction and prognostic value of hub genes. In addition, we explored the correlation between hub genes and immune cell infiltration. At last, the related miRNA, lncRNA networks were constructed by R software. Results A total of 308 DEGs and 12 hub genes were identified. Function and pathway enrichment results demonstrated a correlation between DEGs and the tumor microenvironment, immune response and melanoma tumorigenesis. Subsequently, we focused on assessing potential value of 12 hub genes. Seven hub genes ( CCL4, CCL5, NMU, GAL, CXCL9, CXCL10, CXCL13 ) were identified with significant overall survival for prognosis. What’s more, five of these seven hub genes were found to be related to clinical stages (P values<0.05). In addition, the most important pathways of hub genes include interleukin-10 signaling, peptide ligand-binding receptors, which play important roles in tumor microenvironment for immune activation or immunosuppressive by regulating the infiltration of immune cells. Our results revealed a strong positive correlation between gene expression (CCL4, CCL5, CXCL9, CXCL10 and CXCL13) and immune cell infiltration (B-cell, CD8+ T cells, CD4+ T cells, macrophages, Neutrophils, Dendritic cells). Interestingly, 8 of 12 hub genes (CXCL10, CCL4, CCL5, IL6, CXCL2, PTGER3, GAL, NPY1R) were also found in the predicted drug-gene interaction. The related miRNA, lncRNA for diagnosis and prognosis were found in networks. Conclusion In conclusion, CCL4, CCL5, NMU, GAL, CXCL9, CXCL10, CXCL13 were of high prognostic value and may be potential targets for the diagnosis and therapy of patients with melanoma.

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