scholarly journals Increased Immune Gene Expression and Immune Cell Infiltration in High-Grade Astrocytoma Distinguish Long-Term from Short-Term Survivors

2012 ◽  
Vol 189 (4) ◽  
pp. 1920-1927 ◽  
Author(s):  
Andrew M. Donson ◽  
Diane K. Birks ◽  
Stephanie A. Schittone ◽  
Bette K. Kleinschmidt-DeMasters ◽  
Derrick Y. Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Gene ◽  
Immune Cell Infiltration ◽  
High Grade ◽  
Short Term ◽  
Immune Gene Expression ◽  
High Grade Astrocytoma

scholarly journals Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study

2020 ◽  
Author(s):  
Manik Garg ◽  
Dominique-Laurent Couturier ◽  
Jérémie Nsengimana ◽  
Nuno A. Fonseca ◽  
Matthew Wongchenko ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Cell ◽  
Primary Melanoma ◽  
Gene Expression Signature ◽  
Stage Ii ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Expression Signature ◽  
Expression Score

AbstractPurposePredicting outcomes after resection of primary melanoma remains crude, primarily based on tumour thickness. We explored gene expression signatures for their ability to better predict outcomes.MethodsDifferential expression analysis of 194 primary melanomas resected from patients who either developed distant metastasis (n=89) or did not (n=105) was performed. We identified 121 metastasis-associated genes that were included in our prognostic signature, “Cam_121”. Several machine learning classification models were trained using nested leave- one-out cross validation (LOOCV) to test the signature’s capacity to predict metastases, as well as regression models to predict survival. The prognostic accuracy was externally validated in two independent datasets.ResultsCam_121 performed significantly better in predicting distant metastases than any of the models trained with the clinical covariates alone (pAccuracy=4.92×10−3), as well as those trained with two published prognostic signatures. Cam_121 expression score was strongly associated with progression-free survival (HR=1.7, p=3.44×10−6), overall survival (HR=1.73, p=7.71×10−6) and melanoma-specific survival (HR=1.59, p=0.02). Cam_121 expression score also negatively correlated with measures of immune cell infiltration (ρ=−0.73, p<2.2×10−16), with a higher score representing reduced tumour lymphocytic infiltration and a higher absolute 5-year risk of death in stage II melanoma.ConclusionsThe Cam_121 primary melanoma gene expression signature outperformed currently available alternatives in predicting the risk of distant recurrence. The signature confirmed (using unbiased approaches) the central prognostic importance of immune cell infiltration in long-term patient outcomes and could be used to identify stage II melanoma patients at highest risk of metastases and poor survival who might benefit most from adjuvant therapies.Translational relevancePredicting outcomes after resection of primary melanoma is currently based on traditional histopathological staging, however survival outcomes within these disease stages varies markedly. Since adjuvant systemic therapies are now being used routinely, accurate prognostic information is needed to better risk stratify patients and avoid unnecessary use of high cost, potentially harmful drugs, as well as to inform future adjuvant strategies. The Cam_121 gene expression signature appears to have this capability and warrants evaluation in prospective clinical trials.

scholarly journals Germline genetic polymorphisms influence tumor gene expression and immune cell infiltration

2018 ◽  
Vol 115 (50) ◽  
pp. E11701-E11710 ◽  
Author(s):  
Yoong Wearn Lim ◽  
Haiyin Chen-Harris ◽  
Oleg Mayba ◽  
Steve Lianoglou ◽  
Arthur Wuster ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cancer Immunotherapy ◽  
Genetic Variants ◽  
Immune Cell ◽  
Response To Therapy ◽  
Cell Infiltration ◽  
Cancer Type ◽  
Immune Cell Infiltration ◽  
Durable Response ◽  
The Impact

Cancer immunotherapy has emerged as an effective therapy in a variety of cancers. However, a key challenge in the field is that only a subset of patients who receive immunotherapy exhibit durable response. It has been hypothesized that host genetics influences the inherent immune profiles of patients and may underlie their differential response to immunotherapy. Herein, we systematically determined the association of common germline genetic variants with gene expression and immune cell infiltration of the tumor. We identified 64,094 expression quantitative trait loci (eQTLs) that associated with 18,210 genes (eGenes) across 24 human cancers. Overall, eGenes were enriched for their being involved in immune processes, suggesting that expression of immune genes can be shaped by hereditary genetic variants. We identified the endoplasmic reticulum aminopeptidase 2 (ERAP2) gene as a pan-cancer type eGene whose expression levels stratified overall survival in a subset of patients with bladder cancer receiving anti–PD-L1 (atezolizumab) therapy. Finally, we identified 103 gene signature QTLs (gsQTLs) that were associated with predicted immune cell abundance within the tumor microenvironment. Our findings highlight the impact of germline SNPs on cancer-immune phenotypes and response to therapy; and these analyses provide a resource for integration of germline genetics as a component of personalized cancer immunotherapy.

scholarly journals Colon Cancer and SARS-CoV-2: Impact of ACE2 Expression in Susceptibility to COVID-19

2020 ◽  
Author(s):  
Mohsen Ahmadi ◽  
Negin Saffarzadeh ◽  
Mohammad Amin Habibi ◽  
Fatemeh Hajiesmaeili ◽  
Nima Rezaei
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Immune Cell ◽  
Expression Patterns ◽  
Methylation Status ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Survival Outcomes ◽  
Immune Cell Infiltration ◽  
Ace2 Gene

AbstractNovel coronavirus disease (COVID-19) pandemic has become a global health emergency. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) interacts with angiotensin-converting enzyme 2 (ACE2) to enter the cells and infects diverse human tissues. It has been reported that a few conditions, including cancer, predispose individuals to SARS-CoV-2 infection and severe form of COVID-19. These findings led us to evaluate the susceptibility of colon adenocarcinoma (COAD) patients to SARS-CoV-2 infection by investigation of ACE2 expression in their tumor tissues. The expression analysis revealed that both mRNA and protein levels of ACE2 had increased in colon cancer samples than normal group. Next, the prognosis analysis has indicated that the upregulation of ACE2 was not correlated with patient survival outcomes. Further assessment displayed the hypomethylation of the ACE2 gene promoter in COAD patients. Surprisingly, this methylation status has a strong negative correlation with ACE2 gene expression. The functional enrichment analysis of the genes that had similar expression patterns with ACE2 in colon cancer tissues demonstrated that they mainly enriched in Vitamin digestion and absorption, Sulfur relay system, and Fat digestion and absorption pathways. Finally, we found that ACE2 gene expression had a significant association with the immune cell infiltration levels in COAD patients. In conclusion, it has plausible that COAD patients are more likely to be infected with SARS-CoV-2 and experience severe injuries. Moreover, COVID-19 would bring unfavorable survival outcomes of patients with colon cancer by the way of immune cell infiltration linked process. The present study highlights the importance of preventive actions for COAD patients during the COVID-19 pandemic.

scholarly journals Identification of Methylated Differentially Expressed Hub Genes and Immune Infiltration in Diabetic Retinopathy

2021 ◽  
Author(s):  
Qi Zhou ◽  
Xin Xiong ◽  
Min Tang ◽  
Yingqing Lei ◽  
Hongbin Lv
Keyword(s):  
Gene Expression ◽  
Extracellular Matrix ◽  
Immune Cell ◽  
Interaction Network ◽  
Bioinformatic Analysis ◽  
Differentially Expressed ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Hub Genes ◽  
Critical Pathways

Abstract BackgroundDiabetic retinopathy (DR), a severe complication of diabetes mellitus (DM), is a global social and economic burden. However, the pathological mechanisms mediating DR are not well-understood. This study aimed to identify differentially methylated and differentially expressed hub genes (DMGs and DEGs, respectively) and associated signaling pathways, and to evaluate immune cell infiltration involved in DR. MethodsTwo publicly available datasets were downloaded from the Gene Expression Omnibus database. Transcriptome and epigenome microarray data and multi-component weighted gene coexpression network analysis (WGCNA) were utilized to determine hub genes within DR. One dataset was utilized to screen DEGs and to further explore their potential biological functions using functional annotation analysis. A protein-protein interaction network was constructed. Gene set enrichment and variation analyses (GSVA and GSEA, respectively) were utilized to identify the potential mechanisms mediating the function of hub genes in DR. Infiltrating immune cells were evaluated in one dataset using CIBERSORT. The Connectivity Map (CMap) database was used to predict potential therapeutic agents. ResultsIn total, 673 DEGs (151 upregulated and 522 downregulated genes) were detected. Gene expression was significantly enriched in the extracellular matrix and sensory organ development, extracellular matrix organization, and glial cell differentiation pathways. Through WGCNA, one module was found to be significantly related with DR (r=0.34, P =0.002), and 979 hub genes were identified. By comparing DMGs, DEGs, and genes in WGCNA, we identified eight hub genes in DR ( AKAP13, BOC, ACSS1, ARNT2, TGFB2, LHFPL2, GFPT2, TNFRSF1A ), which were significantly enriched in critical pathways involving coagulation, angiogenesis, TGF-β, and TNF-α-NF-κB signaling via GSVA and GSEA. Immune cell infiltration analysis revealed that activated natural killer cells, M0 macrophages, resting mast cells, and CD8 + T cells may be involved in DR. ARNT2, TGFB2, LHFPL2 , and AKAP13 expression were correlated with immune cell processes, and ZG-10, JNK-9L, chromomycin-a3, and calyculin were identified as potential drugs against DR. Finally, TNFRSF1A , GFPT2 , and LHFPL2 expression levels were consistent with the bioinformatic analysis. ConclusionsOur results are informative with respect to correlations between differentially methylated and expressed hub genes and immune cell infiltration in DR, providing new insight towards DR drug development and treatment.

scholarly journals YAP1 is a Prognostic Biomarker and Correlated with Immune Cell Infiltration in Pancreatic Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Kai Sun ◽  
Xue-de Zhang ◽  
Xiao-yang Liu ◽  
Pei Lu
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Prognostic Value ◽  
Immune Cell ◽  
Prognostic Biomarker ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Long Term Outcome

Yes-associated protein-1 (YAP1) is an important effector of the Hippo pathway and has crosstalk with other cancer signaling pathways. It induces an immunosuppressive tumor microenvironment by activating pathways in several cellular components. However, the mechanisms by which it drives immune infiltration in pancreatic cancer remain poorly understood. We analyzed the expression of YAP1 as well as its prognostic value and correlations with immune infiltrates in various cancers, with a focus on pancreatic cancer. In particular, using the Oncomine database and Gene Expression Profiling Interactive Analysis (GEPIA) database, we found that YAP1 is differentially expressed between tumor tissues and control tissues in a number of cancers and in particular, is elevated in pancreatic cancer. Using the Kaplan–Meier plotter, GEPIA, and Long-term Outcome and Gene Expression Profiling database of pan-cancers (LOGpc), we further established the prognostic value of YAP1. We found that YAP1 expression was significantly related to outcomes in multiple types of cancer based on data from The Cancer Genome Atlas, particularly in pancreatic cancer. Correlations between YAP1 and immune cell infiltration and immune cell marker expression were examined using Tumor Immune Estimation Resource and GEPIA. High expression levels of YAP1 were significantly associated with a variety of immune markers and immune cell subsets in pancreatic cancer. These results suggest that YAP1 is correlated with patient outcomes and tumor immune cell infiltration in multiple cancer types and is a valuable prognostic biomarker in pancreatic cancer.

scholarly journals Prognostic Significance of STC2 and DNA methylation in Head and Neck Squamous Cell Carcinoma: A Study Based on the TCGA and GEO Databases

2021 ◽  
Author(s):  
Guangyao Li ◽  
Daquan Wu ◽  
Lei Zhou ◽  
Dan You ◽  
Xinsheng Huang
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Squamous Cell Carcinoma ◽  
Survival Rate ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Tp53 Mutation ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration

Abstract Background: Head and neck squamous cell carcinoma (HNSC) is a popular malignancy type that brings about poor prognosis with a low survival rate worldwide. Stanniocalcin 2 (STC2) is a glycosylated peptide hormone and shows the potential to become a new biomarker for the evaluation of malignant tumors. The purpose of this study was to explore the prognostic implications of STC2 and DNA methylation in HNSC and the role of STC2 expression in immune cell infiltration.Methods: STC2 gene expression data were collected from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. Univariate and multivariate analyses were employed to screen prognostic risk factors. The relationship between STC2 expression and TP53 mutation in HNSC was explored. TCGA data were utilized to analyze how STC2 expression affected immune cell infiltration in HNSC.Results: STC2 was highly expressed in HNSC patients (P < 0.01), especially those with a lower overall survival rate (P < 0.0001). TP53 mutation might be a risk factor of STC2 overexpression in HNSC (P = 0.0015). STC2 expression was negatively correlated with STC2 methylation (Spearman: -0.43, P < 0.001). Hypermethylation or hypomethylation at the eight CpG sites most related to STC2 expression was identified as independent factors for HNSC prognosis. STC2 was positively correlated with cancer-associated fibroblasts infiltration and associated with the infiltration of various immune cells.Conclusion: STC2 can be regarded as a vital prognostic biomarker of HNSC due to its essential roles in immune cell infiltration.

scholarly journals Immune cell infiltration characteristics and related core genes in lupus nephritis: results from bioinformatic analysis

2019 ◽  
Author(s):  
Yiling Cao ◽  
Weihao Tang ◽  
Wanxin Tang
Keyword(s):  
Gene Expression ◽  
Lupus Nephritis ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Spearman Correlation ◽  
Core Genes

Abstract Objects Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN. Methods Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues of living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Result Five types of immune cells revealed important associations with LN, and monocytes emerged to be the prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8, were closely related to clinical features. Conclusion This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.

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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