Immune and clinical features of CD96 expression in glioma by large-scale analysis

Abstract Background: Immune checkpoints target regulatory pathways in T cells which enhance antitumor immune responses and elicit durable clinical responses . As a novel immune checkpoint, CD96 is an attractive key target for cancer immunotherapy. However, there is no integrative investigation of CD96 in glioma. Our study explored the relationship between CD96 expression and clinical prognosis in glioma. Methods: A total of 1,024 RNA and clinical data were enrolled in this study, including 325 samples from the Chinese Glioma Genome Atlas (CGGA) database and 699 samples from The Cancer Genome Atlas (TCGA) dataset. R language was used to perform statistical analysis and draw figures. Results: CD96 had a consistently positive relationship with glioblastoma and highly enriched in IDH-wildtype and mesenchymal subtype glioma. GO enrichment and GSVA analyses suggested that CD96 was more involved in immune functions, especially related to T cell-mediated immune response in glioma. Subsequent immune infiltration analysis manifes ted that CD96 was positively correlated with infiltrating levels of CD4+ T and CD8+ T cells, macrophages , neutrophils, and DCs in GBM and LGG. Additionally, CD96 was tightly associated with other immune checkpoints including PD-1 , CTLA-4 , TIGIT , and TIM-3 . Univariate and multivariate Cox analysis demonstrated that CD96 acts as an independent indicator of poor prognosis in glioma. Conclusion: CD96 expression was increased in malignant phenotype and negatively associated with overall survival (OS) in glioma. CD96 also showed a positive correlation with other immune checkpoints, immune response, and inflammatory activity. Our findings indicate that CD96 is a promising clinical target for further immunotherapeutic in glioma patients.

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ANXA2 is correlated with the molecular features and clinical prognosis of glioma, and acts as a potential marker of immunosuppression

Scientific Reports ◽

10.1038/s41598-021-00366-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kaiming Ma ◽

Xin Chen ◽

Weihai Liu ◽

Yang Yang ◽

Suhua Chen ◽

...

Keyword(s):

Immune Response ◽

Poor Prognosis ◽

Suppressor Cells ◽

High Grade Glioma ◽

The Cancer Genome Atlas ◽

Clinical Value ◽

Clinical Prognosis ◽

Molecular Features ◽

Potential Marker ◽

Genome Atlas

AbstractRecent studies have shown that ANXA2 is important in the development of many cancers, while its role in glioma-related immune response remains unclear. We aimed to comprehensively investigate its biological characteristics and clinical value in glioma. We analyzed 699 glioma samples from The Cancer Genome Atlas as training cohort and 325 samples from the Chinese Glioma Genome Atlas as validation cohort. All the statistical analyses and figures were generated with R. ANXA2 was overexpressed significantly in high-grade glioma, isocitrate dehydrogenase wild-type and mesenchymal-subtype glioma. ANXA2 was a special indicator of mesenchymal subtype. The survival analysis showed that highly-expressed ANXA2 was related to worse survival status as an independent factor of poor prognosis. Further gene ontology analysis showed that ANXA2 was mainly involved in immune response and inflammatory activities of glioma. Subsequent correlation analysis showed that ANXA2 was positively correlated with HCK, LCK, MHC II, STAT1 and interferon but negatively with IgG. Meanwhile, ANXA2 was positively related to the infiltration of tumor-related macrophages, regulatory T cells and myeloid-derived suppressor cells. Our study revealed that ANXA2 is a biomarker closely related to the malignant phenotype and poor prognosis of glioma, and plays an important role in immune response, inflammatory activity and immunosuppression.

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The Prognostic Value of Risk Score Based on Immunogenenomic Landscape Analysis in Glioma

10.21203/rs.2.20513/v1 ◽

2020 ◽

Author(s):

Haitao Luo ◽

Kai Huang ◽

Chuming Tao ◽

Mioaojing Wu ◽

Minhua Ye ◽

...

Keyword(s):

Risk Score ◽

Cox Regression ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Low Grade ◽

Clinical Prognosis ◽

Cox Analysis ◽

Genome Atlas

Abstract Background: Glioma is a lethal intracranial tumor, and inflammation plays an important role in the initiation and development of glioma. Hence, there is an urgent need to conduct a bioinformatics analysis of immune-related genes (IRGs) for glioma. The present study aims to explore the association of the risk score with clinical outcomes and predict the prognosis with glioma. Methods: In The Cancer Genome Atlas (TCGA) database, 462 low grade glioma (LGG) samples and 166 glioblastoma (GBM) samples were reviewed, and IRGs correlated with the prognosis were selected by performing a survival analysis and establishing a Cox regression model. The potential molecular mechanism of these IRGs were also explored with assistance of computational biology. The risk score based on seven survival-associated IRGs was determined with the help of the multivariable Cox analysis, the patients were divided into two subgroups according to their risk score. Results: It was found that these differentially expressed IRGs were involved with the cytokine-cytokine receptor through functional enrichment analysis. The risk score based on the seven IRGs (SSTR5、CXCL10、CCL13、SAA1、CCL21、CCL27 and HTR1A) performed well in predicting patient’s the overall survival (OS), and correlated with age, 1p/19q codeletion status, IDH status, and WHO grades, both in the training (TCGA) datasets and the validation ((Chinese Glioma Genome Atlas) CGGA) datasets. The risk score also could reflect infiltration through several types of immune cells. Conclusions: This present study screened some IRGs associated with the patient’s clinical characteristic and prognosis, connect to the immune repertoire, demonstrated the importance of the risk score as a promising biomarker for estimating the clinical prognosis of glioma.

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Bioinformatic Analysis of Immune Significance of RYR2 Mutation in Breast Cancer

BioMed Research International ◽

10.1155/2021/8072796 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Zhiquan Xu ◽

Ling Xiang ◽

Rong Wang ◽

Yongfu Xiong ◽

He Zhou ◽

...

Keyword(s):

Breast Cancer ◽

Immune Response ◽

T Cells ◽

Immune Cell ◽

Cox Regression ◽

Cancer Genome ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Specific Gene ◽

Clinical Prognosis

Background. Currently, immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in BC are not fully understood. Methods. Comprehensive bioinformatic analyses were performed using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Survival curves were analyzed via Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were used for prognosis analysis. Gene set enrichment analysis (GSEA) was performed to explore regulatory mechanisms and functions. The CIBERSORT algorithm was used to calculate the tumor-infiltrating immune cell fractions. Results. We analyzed somatic mutation data of BC from TCGA and ICGC datasets and found that 19 frequently mutated genes were reported in both cohorts, namely, SPTA1, TTN, MUC17, MAP3K1, CDH1, FAT3, SYNE1, FLG, HMCN1, RYR2 (ryanodine receptor 2), GATA3, MUC4, PIK3CA, KMT2C, TP53, PTEN, ZFHX4, MUC16, and USH2A. Among them, we observed that RYR2 mutation was significantly associated with higher TMB and better clinical prognosis. Moreover, GSEA revealed that RYR2 mutation-enriched signaling pathways were related to immune-associated pathways. Furthermore, based on the CIBERSORT algorithm, we found that RYR2 mutation enhanced the antitumor immune response by enriching CD8+ T cells, activated memory CD4+ T cells, and M1 macrophages. Conclusion. RYR2 is frequently mutated in BC, and its mutation is related to increased TMB and promotes antitumor immunity; thus, RYR2 may serve as a valuable biomarker to predict the immune response.

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ANXA2 is Correlated With the Molecular Features and Clinical Prognosis of Glioma, and Acts as a Potential Marker of Immunosuppression

10.21203/rs.3.rs-665909/v1 ◽

2021 ◽

Author(s):

Kaiming Ma ◽

Xin Chen ◽

Weihai Liu ◽

Yang Yang ◽

Suhua Chen ◽

...

Keyword(s):

Immune Response ◽

Suppressor Cells ◽

High Grade Glioma ◽

The Cancer Genome Atlas ◽

Sequencing Data ◽

Clinical Value ◽

Clinical Prognosis ◽

Molecular Features ◽

Potential Marker ◽

Genome Atlas

Abstract Background: Recent studies have shown that ANXA2 plays a crucial role in the development of many cancers, while its role in glioma remains unclear. Thus, our study aimed to investigate the molecular biological characteristics and clinical value of ANXA2 in glioma. Methods: We analyzed the RNA sequencing data of 325 glioma samples from the Chinese Glioma Genome Atlas (CGGA) as the training cohort and the RNA expression data of 699 samples from The Cancer Genome Atlas (TCGA) database as the validation cohort, totaling approximately 1024 samples. Results: We found that ANXA2 was overexpressed significantly in high-grade glioma (HGG), isocitrate dehydrogenase (IDH) wild-type glioma and mesenchymal-subtype glioma. Receiver operating characteristic (ROC) analysis revealed that ANXA2 was a potential indicator of the mesenchymal subtype. Kaplan–Meier curve analysis revealed that high expression of ANXA2 indicated significantly poorer survival in glioma and HGG patients. Multivariate Cox analysis also demonstrated that ANXA2 acted as an independent indicator of poor prognosis in glioma patients. Further gene ontology (GO) analysis showed that ANXA2-related genes were mainly involved in the innate immune response and inflammatory response of glioma, and these genes were positively correlated with the expression of ANXA2. Then, we selected seven immune-related meta-genes and found that ANXA2 was positively correlated with HCK, LCK, MHC II, STAT1 and interferon but negatively correlated with IgG. Subsequent correlation analysis of infiltrating immune cells showed that ANXA2 was positively correlated with the infiltration of tumor-related macrophages (TAMs), regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs), suggesting that ANXA2 may be involved in the immunosuppression of glioma.Conclusion: Our study revealed that ANXA2 is closely related to the malignant glioma phenotype and poor patient prognosis. ANXA2 also plays an important role in the immune response and inflammatory activity and can be considered a biomarker of immunosuppression in glioma. These findings suggest that ANXA2 may be a promising target for the further development of immunotherapeutic for glioma.

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Tumor Immune Microenvironment Landscape in Glioma Identifies a Prognostic and Immunotherapeutic Signature

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.717601 ◽

2021 ◽

Vol 9 ◽

Author(s):

Chunyu Zhang ◽

Lirui Guo ◽

Zhongzhou Su ◽

Na Luo ◽

Yinqiu Tan ◽

...

Keyword(s):

Large Scale ◽

The Cancer Genome Atlas ◽

Immune Microenvironment ◽

Mutation Burden ◽

Tumor Immune Microenvironment ◽

Cancer Genome Atlas ◽

Patient Prognosis ◽

Selection Operator ◽

Cox Analysis ◽

Genome Atlas

The tumor immune microenvironment (TIME) has been recognized to be associated with sensitivity to immunotherapy and patient prognosis. Recent research demonstrates that assessing the TIME patterns on large-scale samples will expand insights into TIME and will provide guidance to formulate immunotherapy strategies for tumors. However, until now, thorough research has not yet been reported on the immune infiltration landscape of glioma. Herein, the CIBERSORT algorithm was used to unveil the TIME landscape of 1,975 glioma observations. Three TIME subtypes were established, and the TIMEscore was calculated by least absolute shrinkage and selection operator (LASSO)–Cox analysis. The high TIMEscore was distinguished by an elevated tumor mutation burden (TMB) and activation of immune-related biological process, such as IL6-JAK-STAT3 signaling and interferon gamma (IFN-γ) response, which may demonstrate that the patients with high TIMEscore were more sensitive to immunotherapy. Multivariate analysis revealed that the TIMEscore could strongly and independently predict the prognosis of gliomas [Chinese Glioma Genome Atlas (CGGA) cohort: hazard ratio (HR): 2.134, p < 0.001; Gravendeel cohort: HR: 1.872, p < 0.001; Kamoun cohort: HR: 1.705, p < 0.001; The Cancer Genome Atlas (TCGA) cohort: HR: 2.033, p < 0.001; the combined cohort: HR: 1.626, p < 0.001], and survival advantage was evident among those who received chemotherapy. Finally, we validated the performance of the signature in human tissues from Wuhan University (WHU) dataset (HR: 15.090, p = 0.008). Our research suggested that the TIMEscore could be applied as an effective predictor for adjuvant therapy and prognosis assessment.

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Galectin-9/TIM-3 as a Key Regulator of Immune Response in Gliomas With Chromosome 1p/19q Codeletion

Frontiers in Immunology ◽

10.3389/fimmu.2021.800928 ◽

2021 ◽

Vol 12 ◽

Author(s):

Guanzhang Li ◽

Ruoyu Huang ◽

Wenhua Fan ◽

Di Wang ◽

Fan Wu ◽

...

Keyword(s):

Immune Response ◽

Inflammatory Responses ◽

The Cancer Genome Atlas ◽

Antitumor Immune Response ◽

Immune Checkpoints ◽

Sequencing Data ◽

Chromosome 1P ◽

Genome Atlas

Gliomas with chromosome 1p/19q codeletion were considered a specific tumor entity. This study was designed to reveal the biological function alterations tightly associated with 1p/19q codeletion in gliomas. Clinicopathological and RNA sequencing data from glioma patients were obtained from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. Gene set variation analysis was performed to explore the differences in biological functions between glioma subgroups stratified by 1p/19q codeletion status. The abundance of immune cells in each sample was detected using the CIBERSORT analytical tool. Single-cell sequencing data from public databases were analyzed using the t-distributed stochastic neighbor embedding (t-SNE) algorithm, and the findings were verified by in vitro and in vivo experiments and patient samples.We found that the activation of immune and inflammatory responses was tightly associated with 1p/19q codeletion in gliomas. As the most important transcriptional regulator of Galectin-9 in gliomas, the expression level of CCAAT enhancer-binding protein alpha in samples with 1p/19q codeletion was significantly decreased, which led to the downregulation of the immune checkpoints Galectin-9 and TIM-3. These results were validated in three independent datasets. The t-SNE analysis showed that the loss of chromosome 19q was the main reason for the promotion of the antitumor immune response. IHC protein staining, in vitro and in vivo experiments verified the results of bioinformatics analysis. In gliomas, 1p/19q codeletion can promote the antitumor immune response by downregulating the expression levels of the immune checkpoint TIM-3 and its ligand Galectin-9.

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Immune Checkpoint Ligand Reverse Signaling: Looking Back to Go Forward in Cancer Therapy

Cancers ◽

10.3390/cancers11050624 ◽

2019 ◽

Vol 11 (5) ◽

pp. 624 ◽

Cited By ~ 7

Author(s):

Daniele Lecis ◽

Sabina Sangaletti ◽

Mario P. Colombo ◽

Claudia Chiodoni

Keyword(s):

Clinical Trials ◽

T Cells ◽

Clinical Response ◽

Immune Checkpoint ◽

Checkpoint Inhibitors ◽

Immune Checkpoints ◽

Immune Functions ◽

Regulatory Pathways ◽

Reverse Signaling ◽

Programmed Death

The so-called immune checkpoints are pathways that regulate the timing and intensity of the immune response to avoid an excessive reaction and to protect the host from autoimmunity. Immune checkpoint inhibitors (ICIs) are designed to target the negative regulatory pathways of T cells, and they have been shown to restore anti-tumor immune functions and achieve considerable clinical results. Indeed, several clinical trials have reported durable clinical response in different tumor types, such as melanoma, renal cell carcinoma (RCC) and non-small cell lung cancer (NSCLC). Nonetheless, after the initial enthusiasm, it is now evident that the majority of patients do not benefit from ICIs, due to innate or acquired tumor resistance. It is therefore mandatory to find ways to identify those patients who will respond and to find ways to induce response in those who at present do not benefit from ICIs. In this regard, the expression of programmed death ligand 1 (PD-L1) on neoplastic cells was the first, and most obvious, biomarker exploited to predict the activity of anti-programmed death 1 (PD-1) and/or anti-PD-L1 antibodies. As expected, a correlation was confirmed between the levels of PD-L1 and the efficacy of anti-PD-1 therapy in melanoma, NSCLC and RCC. However, further results from clinical trials showed that some patients display a clinical response regardless of tumor cell PD-L1 expression levels, while others do not benefit from ICI treatment despite the expression of PD-L1 on neoplastic elements. These findings strongly support the notion that other factors may be relevant for the efficacy of ICI-based treatment regimens. Furthermore, although the current dogma indicates that the PD-1/PD-L1 axis exerts its regulatory effects via the signal transduced in PD-1-expressing T cells, recent evidence suggests that a reverse signaling may also exist downstream of PD-L1 in both tumor and immune cells. The reverse signaling of PD-L1, but also of other immune checkpoints, might contribute to the pro-tumoral/immune suppressive environment associated with tumor development and progression. Clarifying this aspect could facilitate the prediction of patients’ clinical outcomes, which are so far unpredictable and result in response, resistance or even hyper-progressive disease in some cases.

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Identification and development of a novel invasion-related gene signature for prognosis prediction in colon adenocarcinoma

Cancer Cell International ◽

10.1186/s12935-021-01795-1 ◽

2021 ◽

Vol 21 (1) ◽

Cited By ~ 1

Author(s):

Jiahua Liu ◽

Chunhui Jiang ◽

Chunjie Xu ◽

Dongyang Wang ◽

Yuguang Shen ◽

...

Keyword(s):

T Cells ◽

External Validation ◽

Colon Adenocarcinoma ◽

Gene Signature ◽

The Cancer Genome Atlas ◽

Immune Infiltration ◽

Prognosis Prediction ◽

Protein Levels ◽

Limma Package ◽

Cox Analysis

AbstractThe overall survival of metastatic colon adenocarcinoma (COAD) remains poor, so it is important to explore the mechanisms of metastasis and invasion. This study aimed to identify invasion-related genetic markers for prognosis prediction in patients with COAD. Three molecular subtypes (C1, C2, and C3) were obtained based on 97 metastasis-related genes in 365 COAD samples from The Cancer Genome Atlas (TCGA). A total of 983 differentially expressed genes (DEGs) were identified among the different subtypes by using the limma package. A 6-gene signature (ITLN1, HOXD9, TSPAN11, GPRC5B, TIMP1, and CXCL13) was constructed via Lasso-Cox analysis. The signature showed strong robustness and could be used in the training, testing, and external validation (GSE17537) cohorts with stable predictive efficiency. Compared with other published signatures, our model showed better performance in predicting outcomes. Pan-cancer expression analysis results showed that ITLN1, TSPAN11, CXCL13, and GPRC5B were downregulated and TIMP1 was upregulated in most tumor samples, including COAD, which was consistent with the results of the TCGA and GEO cohorts. Western blot analysis and immunohistochemistry were performed to validate protein expression. Tumor immune infiltration analysis results showed that TSPAN11, GPRC5B, TIMP1, and CXCL13 protein levels were significantly positively correlated with CD4+ T cells, macrophages, neutrophils, and dendritic cells. Further, the TIMP1 and CXCL13 proteins were significantly related to the tumor immune infiltration of CD8+ T cells. We recommend using our signature as a molecular prognostic classifier to assess the prognostic risk of patients with COAD.

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GALNT14 expression in renal clear cell carcinoma and its effect on prognosis

10.21203/rs.3.rs-761157/v1 ◽

2021 ◽

Author(s):

Yuqin Wei ◽

Fan Wu ◽

Shengfeng Zhang ◽

Yanlin Tan ◽

Qunying Wu ◽

...

Keyword(s):

Cell Carcinoma ◽

Cox Regression ◽

Clear Cell ◽

Clear Cell Carcinoma ◽

Renal Clear Cell Carcinoma ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Regulatory Pathways ◽

Cox Analysis ◽

The Relationship

Abstract Background The expression of GALNT14 in kidney renal clear cell carcinoma (KIRC) and its clinical significance remains unknown. Methods The KIRC data expressed by GALNT14 was downloaded from The Cancer Genome Atlas (TCGA) database. The expression of GALNT14 was analyzed by R software, Perl software and online analysis database. The relationship between GALNT14 expression and clinicopathological features in KIRC was analyzed by univariate, multivariate Cox regression and some databases. Gene Expression Profling Interactive Analysis (GEPIA), Starbase v3.0, UALCAN, and Kaplan-Meier were used to analyze the relationship between GALNT14 expression and overall survival (OS) in KIRC. UALCAN detects the expression of GALNT14 methylation in KIRC. Linkedomics and Genemania were used to analyze the gene co-expression of GALNT14. Gene Set Enrichment Analysis (GSEA) was performed to search for potential regulatory pathways. Results We found that GALNT14 was overexpressed in KIRC (p=1.433e-25). Patients with high GALNT14 expression in KIRC had a better prognosis than patients with low GALNT14 expression (p=0.008). In addition, high GALNT14 expression in KIRC was significantly associated with low T stage and positive OS (p<0.05). Univariate Cox analysis showed that GALNT14 was positively correlated with OS (p<0.001). Multivariate Cox analysis showed that GALNT14 was associated with OS (p<0.001), age (p=0.01) and histological grade (p=0.02). GALNT14 methylation is low expressed in KIRC (p<0.001). GSEA analysis showed that GALNT14 was enriched in histidine metabolism, peroxisome, and renin-angiotensin system pathways. Conclusion GALNT14 can be used as an independent prognostic factor for renal clear cell carcinoma and a potential target for clinical diagnosis and treatment of KIRC.

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