scholarly journals Characterization of the Clinical Significance of PD-1/PD-Ls Expression and Methylation in Patients With Low-Grade Glioma

2021 ◽  
Vol 20 ◽  
pp. 153303382110119
Author(s):  
Jie Mei ◽  
Yun Cai ◽  
Rui Xu ◽  
Xuejing Yang ◽  
Weijian Zhou ◽  
...  
Keyword(s):  
Survival Data ◽  
Immune Escape ◽  
Checkpoint Inhibitors ◽  
Expression Patterns ◽  
Low Grade Glioma ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Low Grade ◽  
Programmed Death ◽  
Genome Atlas

Background: Immune checkpoints play crucial roles in the immune escape of cancer cells. However, the exact prognostic values of expression and methylation of programmed-death 1 (PD-1), programmed-death-ligand 1 (PD-L1) and PD-L2 in low-grade glioma (LGG) have not been well-defined yet. Methods: A total 514 LGG samples from the Cancer Genome Atlas (TCGA) dataset containing gene expression, DNA methylation, and survival data were enrolled in our study. Besides, a total of 137 primary LGG samples from the Chinese Glioma Genome Atlas (CGGA) database were also extracted for the survival analysis of the prognostic values of PD-1/PD-Ls expression. Results: PD-1/PD-Ls had distinct co-expression patterns in LGG tissues. The expression and methylation level of PD-1/PD-Ls seemed to be various in different LGG subtypes. Besides, overexpression and hypo-methylation of PD-1/PD-Ls were associated with worse prognosis. In addition, PD-1/PD-Ls expression was positively associated with TIICs infiltration, while their methylation was negatively associated with TIICs infiltration. Moreover, PD-1/PD-Ls and their positively correlated gene mainly participated in immune response related biological processes. Conclusion: To conclude, overexpression and hypo-methylation of PD-1/PD-Ls predicted unfavorable prognosis in LGG patients, suggesting those patients may benefit from PD1/PD-Ls checkpoint inhibitors treatment.

scholarly journals Characterization of clinical significance of PD-1/PD-Ls expression and methylation in patients with low grade glioma

2020 ◽  
Author(s):  
Jie Mei ◽  
Yun Cai ◽  
Rui Xu ◽  
Xuejing Yang ◽  
Weijian Zhou ◽  
...  
Keyword(s):  
Clinical Significance ◽  
Survival Data ◽  
Immune Escape ◽  
Checkpoint Inhibitors ◽  
Expression Patterns ◽  
Methylation Status ◽  
Low Grade Glioma ◽  
Immune Checkpoints ◽  
Low Grade ◽  
Programmed Death

AbstractBackgroundImmune checkpoints play crucial roles in immune escape of cancer cells. However, the exact prognostic values of expression and methylation of programmed death 1 (PD-1), programmed death-ligand 1 (PD-L1) and PD-L2 in low-grade glioma (LGG) have not been defined yet.MethodsA total of 514 LGG samples from TCGA dataset containing both PD-1, PD-L1 and PD-L2 expression, DNA methylation, and survival data were enrolled into our study. The clinical significance of PD-1/PD-Ls expression and methylation in LGG were explored. Besides, the correlation between PD-1/PD-Ls expression and methylation with the infiltration levels of tumor-infiltrating immune cells (TIICs) was assessed. Moreover, GO enticement analysis of PD-1/PD-Ls co-expressed genes was performed as well. R 3.6.2 and GraphPad Prism 8 were applied as main tools for the statistical analysis and graphical exhibition.ResultsPD-1/PD-Ls had distinct co-expression patterns in LGG tissues. The expression and methylation status of PD-1/PD-Ls seemed to be various in different LGG subtypes. Besides, upregulated PD-1/PD-Ls expression and hypo-methylation of PD-1/PD-Ls were associated with worse survival in LGG patients. In addition, PD-1/PD-Ls expression was revealed to be positively associated with TIICs infiltration, while their methylation was negatively associated with TIICs infiltration. Moreover, the PD-1/PDLs correlated gene profiles screening and Gene Ontology (GO) enrichment analysis uncovered that PD-1/PDLs and their positively correlated gene mainly participated in immune response related biological processes.ConclusionsHigh expression and hypo-methylation of PD-1/PD-Ls significantly correlated with unfavorable survival in LGG patients, suggesting LGG patients may benefit from PD1/PD-Ls checkpoint inhibitors treatment.

scholarly journals Six Immune Associated Genes Construct Prognostic Model Evaluate Low-Grade Glioma

2020 ◽  
Vol 11 ◽  
Author(s):  
Yin Qiu Tan ◽  
Yun Tao Li ◽  
Teng Feng Yan ◽  
Yang Xu ◽  
Bao Hui Liu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Risk Score ◽  
Survival Rates ◽  
Low Grade Glioma ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Sequencing Analysis ◽  
Six Genes ◽  
Genome Atlas ◽  
Overall Survival Rates

BackgroundThe immunotherapy of Glioma has always been a research hotspot. Although tumor associated microglia/macrophages (TAMs) proves to be important in glioma progression and drug resistance, our knowledge about how TAMs influence glioma remains unclear. The relationship between glioma and TAMs still needs further study.MethodsWe collected the data of TAMs in glioma from NCBI Gene Expression Omnibus (GEO) that included 20 glioma samples and 15 control samples from four datasets. Six genes were screened from the Differential Expression Gene through Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, protein–protein interaction (PPI) network and single-cell sequencing analysis. A risk score was then constructed based on the six genes and patients’ overall survival rates of 669 patients from The Cancer Genome Atlas (TCGA). The efficacy of the risk score in prognosis and prediction was verified in Chinese Glioma Genome Atlas (CGGA).ResultsSix genes, including CD163, FPR3, LPAR5, P2ry12, PLAUR, SIGLEC1, that participate in signal transduction and plasma membrane were selected. Half of them, like CD163, FPR3, SIGLEC1, were mainly expression in M2 macrophages. FPR3 and SIGLEC1 were high expression genes in glioma associated with grades and IDH status. The overall survival rates of the high risk score group was significantly lower than that of the low risk score group, especially in LGG.ConclusionJoint usage of the 6 candidate genes may be an effective method to diagnose and evaluate the prognosis of glioma, especially in Low-grade glioma (LGG).

scholarly journals Multi Omics Profiling and Clustering Low Grade Glioma Based on Integrated Stress Status

2021 ◽  
Author(s):  
Xiaolin Ren ◽  
Xin Chen ◽  
Chen Zhu ◽  
Anhua Wu
Keyword(s):  
Stress Response ◽  
High Risk ◽  
Malignant Transformation ◽  
Immune Cell ◽  
High Risk Group ◽  
Low Grade Glioma ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Integrated Stress Response ◽  
Genome Atlas

Abstract Background: Although the prognosis of low-grade glioma (LGG) is better than that of glioblastoma (GBM), there are still some patients who will develop into high-grade glioma. Integrated stress response contributed to the malignant transformation of tumor. As there is few research focus on the integrated stress status in LGG, it is urgent to profile and re-classify LGG based on integrated stress response (ISR). Methods: Glioma patients were obtained from the Chinese Glioma Genome Atlas ( the Cancer Genome Atlas (TCGA) and GSE16011 cohorts. Statistical 8 analyses were conducted by GraphPad Prism and R language. Results: We quantified four types of integrated stress response respectively. The relationship between the four stress states and the clinical characteristics of LGG was analyzed. Then we re-classified the patients based on these four scores, we found that cluster 1 had the worst prognosis, whereby cluster 3 had the best prognosis. We also established an accurate ISR risk signature to predicting cluster 1. We found that immune response and suppressive immune cell components were more enriched in the high-risk group. We also profiled the genomic difference between low and high risk groups, including the non-missense mutation of drivel genes and the condition of copy number variation (CNV). Conclusion: LGG patients could be divided into four clusters based on the integrated stress status, cluster 1 exhibited malignant transformation trends. ISR signature could reflect the traits of cluster 1 well, high ISR score indicated worse prognosis and enriched inhibitory immune microenvironments.

scholarly journals A Novel 10-Gene Signature Predicts Poor Prognosis in Low Grade Glioma

2021 ◽  
Vol 20 ◽  
pp. 153303382199208
Author(s):  
Wentao Liu ◽  
Jiaxuan Zou ◽  
Rijun Ren ◽  
Jingping Liu ◽  
Gentang Zhang ◽  
...  
Keyword(s):  
Risk Score ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Gene Signature ◽  
Low Grade Glioma ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Normal Brain ◽  
Cox Regression Analysis ◽  
Genome Atlas

Aim: Low grade glioma (LGG) is a lethal brain cancer with relatively poor prognosis in young adults. Thus, this study was performed to develop novel molecular biomarkers to effectively predict the prognosis of LGG patients and finally guide treatment decisions. Methods: survival-related genes were determined by Kaplan-Meier survival analysis and multivariate Cox regression analysis using the expression and clinical data of 506 LGG patients from The Cancer Genome Atlas (TCGA) database and independently validated in a Chinese Glioma Genome Atlas (CGGA) dataset. A prognostic risk score was established based on a linear combination of 10 gene expression levels using the regression coefficients of the multivariate Cox regression models. GSEA was performed to analyze the altered signaling pathways between the high and low risk groups stratified by median risk score. Results: We identified a total of 1489 genes significantly correlated with patients’ prognosis in LGG. The top 5 protective genes were DISP2, CKMT1B, AQP7, GPR162 and CHGB, the top 5 risk genes were SP1, EYA3, ZSCAN20, ITPRIPL1 and ZNF217 in LGG. The risk score was predictive of poor overall survival and relapse-free survival in LGG patients. Pathways of small cell lung cancer, pathways in cancer, chronic myeloid leukemia, colorectal cancer were the top 4 most enriched pathways in the high risk group. SP1, EYA3, ZSCAN20, ITPRIPL1, ZNF217 and GPR162 were significantly up-regulated, while DISP2, CKMT1B, AQP7 were down-regulated in 523 LGG tissues as compared to 1141 normal brain controls. Conclusions: The 10-gene signature may become novel prognostic and diagnostic biomarkers to considerably improve the prognostic prediction in LGG.

scholarly journals Downregulation of LUZP2 Is Correlated with Poor Prognosis of Low-Grade Glioma

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yong Li ◽  
Gang Deng ◽  
Yangzhi Qi ◽  
Huikai Zhang ◽  
Hongxiang Jiang ◽  
...  
Keyword(s):  
Nervous System ◽  
Brain Tumors ◽  
System Development ◽  
Tumor Grade ◽  
Nervous System Development ◽  
Low Grade Glioma ◽  
The Cancer Genome Atlas ◽  
Biological Behavior ◽  
Low Grade ◽  
Genome Atlas

Background. LUZP2 is a protein limitedly expressed in the brain and spinal cord, while there are few studies on it in brain tumors. Low-grade glioma (LGG) is one of the most common brain tumors. However, the biological behavior of LGG is not very clear at present. This study was aimed at exploring the role of LUZP2 in LGG. Methods. By data mining in The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), the expression, clinical characteristics, and potential regulatory mechanism of LUZP2 in LGG were assessed. The regulatory miRNAs of LUZP2 were predicted using miRDB, TargetScan, and miRTarBase. Meanwhile, the potential biological function of coexpressed genes was investigated by GO and KEGG analyses. Results. LUZP2 expression was downregulated with the increase of tumor grade (p<0.05). Low LUZP2 expression independently predicted poor OS in LGG in TCGA cohort and the CGGA part B and part C cohorts (all p<0.001). Additionally, LUZP2 was targeted by miR-142-5p according to 2 prediction databases and 1 validated database, which was negatively related to LUZP2 mRNA expression (p<0.001). Kaplan-Meier analyses demonstrated that low miR-142-5p expression was significantly associated with poor OS (p<0.001). Furthermore, coexpression genes of LUZP2 were significantly involved in nervous system development and metabolic pathways.Conclusions. LUZP2 may be crucial for nervous system extracellular matrix development and serve as an important clinical biomarker for LGG patients. miR-142-5p upregulation could be the upstream regulator that contributed to LUZP2 downregulation.

scholarly journals Metabolic Signature-Based Subtypes May Pave Novel Ways for Low-Grade Glioma Prognosis and Therapy

2021 ◽  
Vol 9 ◽  
Author(s):  
Ganglei Li ◽  
Zhanxiong Wu ◽  
Jun Gu ◽  
Yu Zhu ◽  
Tiesong Zhang ◽  
...  
Keyword(s):  
R Package ◽  
Low Grade Glioma ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Response Patterns ◽  
Survival Times ◽  
Characteristic Index ◽  
Metabolic Characteristics ◽  
Different Response ◽  
Genome Atlas

Metabolic signatures are frequently observed in cancer and are starting to be recognized as important regulators for tumor progression and therapy. Because metabolism genes are involved in tumor initiation and progression, little is known about the metabolic genomic profiles in low-grade glioma (LGG). Here, we applied bioinformatics analysis to determine the metabolic characteristics of patients with LGG from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). We also performed the ConsensusClusterPlus, the CIBERSORT algorithm, the Estimate software, the R package “GSVA,” and TIDE to comprehensively describe and compare the characteristic difference between three metabolic subtypes. The R package WGCNA helped us to identify co-expression modules with associated metabolic subtypes. We found that LGG patients were classified into three subtypes based on 113 metabolic characteristics. MC1 patients had poor prognoses and MC3 patients obtained longer survival times. The different metabolic subtypes had different metabolic and immune characteristics, and may have different response patterns to immunotherapy. Based on the metabolic subtype, different patterns were exhibited that reflected the characteristics of each subtype. We also identified eight potential genetic markers associated with the characteristic index of metabolic subtypes. In conclusion, a comprehensive understanding of metabolism associated characteristics and classifications may improve clinical outcomes for LGG.

scholarly journals Immune-checkpoint engagement as predictive biomarkers in clear cell renal cell carcinoma and melanoma

2020 ◽  
Author(s):  
Lissete Sánchez-Magraner ◽  
James Miles ◽  
Claire Baker ◽  
Christopher J Applebee ◽  
Dae-Jin Lee ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Expression Patterns ◽  
Predictive Biomarkers ◽  
Immune Checkpoints ◽  
Ligand Interaction ◽  
Receptor Ligand ◽  
Programmed Death ◽  
Cell Cell

ABSTRACTMany cancers are termed immuno-evasive due to expression of immuno-modulatory ligands. Programmed death ligand-1 (PD-L1) and cluster of differentiation 80/86 (CD80/86) interact with their receptors, programmed death receptor-1 (PD-1) and cytotoxic T-lymphocyte associated protein-4 (CTLA-4), on tumour infiltrating leukocytes, thus eliciting immunosuppression. Immunotherapies aimed at blocking these interactions are revolutionising cancer treatments, albeit in an inadequately described patient subset.Our prognostic assay, utilising amplified two-site time-resolved Förster resonance energy transfer (iFRET), quantifies PD-1/ PD-L1 and CTLA-4/ CD80 cell-cell interactions in single cell assays and tumour biopsies. iFRET efficiencies demonstrate, in cell-cell engagement models, that receptor-ligand interactions are significantly lower with anti-PD-1 or anti-CTLA-4 blocking antibodies. In patient samples, iFRET detects immune-cell/tumour-cell interaction variance in different cancers. These results revealed inter-cancer, inter-patient and intra-tumoural heterogeneity of engaged immune-checkpoints, contradicting their ligand expression patterns. Exploiting spatio-temporal interactions of immune-checkpoint proteins defined biomarker functionality for determining whether checkpoint inhibitors are appropriate treatments.Statement of SignificanceQuantitative photophysics exploitation in determining immune-checkpoint engagement, as predictive biomarkers in cancers led to revealing inter-cancer, inter-patient and intra-tumoural heterogeneity of the engaged immune-checkpoints. This receptor-ligand interaction did not reflect simple expression patterns of these immuno-modulatory proteins. Our findings may affect immunotherapies aimed at blocking these intercellular interactions in patients.

scholarly journals Identification of Gender-Specific Molecular Differences in Glioblastoma (GBM) and Low-Grade Glioma (LGG) by the Analysis of Large Transcriptomic and Epigenomic Datasets

2021 ◽  
Vol 11 ◽  
Author(s):  
Md Tipu Khan ◽  
Bharat Prajapati ◽  
Simran Lakhina ◽  
Mridula Sharma ◽  
Sachin Prajapati ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Network Analysis ◽  
Signaling Pathways ◽  
Low Grade Glioma ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Male And Female ◽  
Males And Females ◽  
Gender Based ◽  
Genome Atlas

Differences in the incidence and outcome of glioma between males and females are well known, being more striking for glioblastoma (GB) than low-grade glioma (LGG). The extensive and well-annotated data in publicly available databases enable us to analyze the molecular basis of these differences at a global level. Here, we have analyzed The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases to identify molecular indicators for these gender-based differences by different methods. Based on the nature of data available/accessible, the transcriptomic profile was studied in TCGA by using DeSeq2 and in CGGA by T-test, after correction based. Only IDH1 wild-type tumors were studied in CGGA. Using weighted gene co-expression network analysis (WGCNA), network analysis was done, followed by the assessment of modular differential connectivity. Differentially affected signaling pathways were identified. The gender-based effects of differentially expressed genes on survival were determined. DNA methylation was studied as an indicator of gender-based epigenetic differences. The results clearly showed gender-based differences in both GB and LGG, whatever method or database was used. While there were differences in the results obtained between databases and methods used, some major signaling pathways such as Wnt signaling and pathways involved in immune processes and the adaptive immune response were common to different assessments. There was also a differential gender-based influence of several genes on survival. Also, the autosomal genes NOX, FRG1BP, and AL354714.2 and X-linked genes such as PUDP, KDM6A, DDX3X, and SYAP1 had differential DNA methylation and expression profile in male and female GB, while for LGG, these included autosomal genes such as CNIH3 and ANKRD11 and X-linked genes such as KDM6A, MAOB, and EIF2S3. Some, such as FGF13 and DDX3X, have earlier been shown to have a role in tumor behavior, though their dimorphic effects in males and females have not been identified. Our study thus identifies several crucial differences between male and female glioma, which could be validated further. It also highlights that molecular studies without consideration of gender can obscure critical elements of biology and emphasizes the importance of parallel but separate analyses of male and female glioma.

scholarly journals The regulation of immune checkpoints by the hypoxic tumor microenvironment

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11306
Author(s):  
Min Hu ◽  
Yongfu Li ◽  
Yuting Lu ◽  
Miao Wang ◽  
Yingrui Li ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Immune Escape ◽  
Epithelial Mesenchymal Transition ◽  
Malignant Tumors ◽  
Checkpoint Inhibitors ◽  
New Drugs ◽  
Immune Checkpoints ◽  
Mesenchymal Transition ◽  
Programmed Death ◽  
Domain 3

The tumor microenvironment (TME) influences the occurrence and progression of tumors, and hypoxia is an important characteristic of the TME. The expression of programmed death 1 (PD1)/programmed death-ligand 1 (PDL1), cytotoxic T-lymphocyte-associated antigen 4 (CTLA4), and other immune checkpoints in hypoxic malignant tumors is often significantly increased, and is associated with poor prognosis. The application of immune checkpoint inhibitors (ICIs) for treating lung cancer, urothelial carcinoma, and gynecological tumors has achieved encouraging efficacy; however, the rate of efficacy of ICI single-drug treatment is only about 20%. In the present review, we discuss the possible mechanisms by which the hypoxic TME regulates immune checkpoints. By activating hypoxia-inducible factor-1α (HIF-1α), regulating the adenosine (Ado)-A2aR pathway, regulating the glycolytic pathway, and driving epithelial-mesenchymal transition (EMT) and other biological pathways, hypoxia regulates the expression levels of CTLA4, PD1, PDL1, CD47, lymphocyte activation gene 3 (LAG3), T-cell immunoglobulin and mucin domain 3 (TIM3), and other immune checkpoints, which interfere with the immune effector cell anti-tumor response and provide convenient conditions for tumors to escape immune surveillance. The combination of HIF-1α inhibitors, Ado-inhibiting tumor immune microenvironment regulatory drugs, and other drugs with ICIs has good efficacy in both preclinical studies and phase I-II clinical studies. Exploring the effects of TME hypoxia on the expression of immune checkpoints and the function of infiltrating immune cells has greatly clarified the relationship between the hypoxic TME and immune escape, which is of great significance for the development of new drugs and the search for predictive markers of the efficacy of immunotherapy for treating malignant tumors. In the future, combination therapy with hypoxia pathway inhibitors and ICIs may be an effective anti-tumor treatment strategy.

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