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

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.

Comprehensive assessment of PD-L1 and PD-L2 dysregulation in gastrointestinal cancers

Epigenomics ◽  
2020 ◽  
Author(s):  
Qijie Zhao ◽  
Jinan Guo ◽  
Yueshui Zhao ◽  
Jing Shen ◽  
Parham Jabbarzadeh Kaboli ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Signaling Pathways ◽  
Underlying Mechanism ◽  
Comprehensive Analysis ◽  
The Cancer Genome Atlas ◽  
Gastrointestinal Cancers ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background: PD-L1 and PD-L2 are ligands of PD-1. Their overexpression has been reported in different cancers. However, the underlying mechanism of PD-L1 and PD-L2 dysregulation and their related signaling pathways are still unclear in gastrointestinal cancers. Materials & methods: The expression of PD-L1 and PD-L2 were studied in The Cancer Genome Atlas and Genotype-Tissue Expression databases. The gene and protein alteration of PD-L1 and PD-L2 were analyzed in cBioportal. The direct transcription factor regulating PD-L1/ PD-L2 was determined with ChIP-seq data. The association of PD-L1/PD-L2 expression with clinicopathological parameters, survival, immune infiltration and tumor mutation burden were investigated with data from The Cancer Genome Atlas. Potential targets and pathways of PD-L1 and PD-L2 were determined by protein enrichment, WebGestalt and gene ontology. Results: Comprehensive analysis revealed that PD-L1 and PD-L2 were significantly upregulated in most types of gastrointestinal cancers and their expressions were positively correlated. SP1 was a key transcription factor regulating the expression of PD-L1. Conclusion: Higher PD-L1 or PD-L2 expression was significantly associated with poor overall survival, higher tumor mutation burden and more immune and stromal cell populations. Finally, HIF-1, ERBB and mTOR signaling pathways were most significantly affected by PD-L1 and PD-L2 dysregulation. Altogether, this study provided comprehensive analysis of the dysregulation of PD-L1 and PD-L2, its underlying mechanism and downstream pathways, which add to the knowledge of manipulating PD-L1/PD-L2 for cancer immunotherapy.

scholarly journals Large-scale profiling of microRNAs for The Cancer Genome Atlas

2015 ◽  
Vol 44 (1) ◽  
pp. e3-e3 ◽  
Author(s):  
Andy Chu ◽  
Gordon Robertson ◽  
Denise Brooks ◽  
Andrew J. Mungall ◽  
Inanc Birol ◽  
...  
Keyword(s):  
Large Scale ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

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

2020 ◽  
Author(s):  
Qiang Zhang ◽  
Hua Zhong ◽  
Yinchun Fan ◽  
Qian Liu ◽  
Jiancheng Song ◽  
...  
Keyword(s):  
Immune Response ◽  
T Cells ◽  
Large Scale ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Immune Functions ◽  
Clinical Prognosis ◽  
Regulatory Pathways ◽  
Cox Analysis ◽  
Genome Atlas

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.

scholarly journals Deciphering N6-Methyladenosine-Related Genes Signature to Predict Survival in Lung Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jie Zhu ◽  
Min Wang ◽  
Daixing Hu
Keyword(s):  
Lung Adenocarcinoma ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Lasso Regression ◽  
Gene Expressions ◽  
Tumor Tissues ◽  
Cancer Genome Atlas ◽  
Selection Operator ◽  
Cox Analysis

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death. Among these, lung adenocarcinoma (LUAD) accounts for most cases. Due to the improvement of precision medicine based on molecular characterization, the treatment of LUAD underwent significant changes. With these changes, the prognosis of LUAD becomes diverse. N6-methyladenosine (m6A) is the most predominant modification in mRNAs, which has been a research hotspot in the field of oncology. Nevertheless, little has been studied to reveal the correlations between the m6A-related genes and prognosis in LUAD. Thus, we conducted a comprehensive analysis of m6A-related gene expressions in LUAD patients based on The Cancer Genome Atlas (TCGA) database by revealing their relationship with prognosis. Different expressions of the m6A-related genes in tumor tissues and non-tumor tissues were confirmed. Furthermore, their relationship with prognosis was studied via Consensus Clustering Analysis, Principal Components Analysis (PCA), and Least Absolute Shrinkage and Selection Operator (LASSO) Regression. Based on the above analyses, a m6A-based signature to predict the overall survival (OS) in LUAD was successfully established. Among the 479 cases, we found that most of the m6A-related genes were differentially expressed between tumor and non-tumor tissues. Six genes, HNRNPC, METTL3, YTHDC2, KIAA1429, ALKBH5, and YTHDF1 were screened to build a risk scoring signature, which is strongly related to the clinical features pathological stages (p<0.05), M stages (p<0.05), T stages (p < 0.05), gender (p=0.04), and survival outcome (p=0.02). Multivariate Cox analysis indicated that risk value could be used as an independent prognostic factor, revealing that the m6A-related genes signature has great predictive value. Its efficacy was also validated by data from the Gene Expression Omnibus (GEO) database.

Analysing large scale TGCT data from The Cancer Genome Atlas (TCGA): Challenges and considerations

2019 ◽  
Vol 18 (4) ◽  
pp. 38
Author(s):  
S. Smith ◽  
K. Amin ◽  
S. Fang ◽  
T. Morrison ◽  
N. Coleman ◽  
...  
Keyword(s):  
Large Scale ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals CXCL11 Correlates with Anti-tumor Immune Microenvironment and Improved Prognosis in Colon Cancer

2020 ◽  
Author(s):  
Yingying Cao ◽  
Youwei Zhang ◽  
Nanlin Jiao ◽  
Tiantian Sun ◽  
Yanru Ma ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Tumor Development ◽  
Specific Effect ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Immune Microenvironment ◽  
Antibody Treatment ◽  
Tumor Immune Microenvironment ◽  
Cancer Genome Atlas ◽  
Immunological Regulation

Abstract Background: CXCL11 has been considered to be responsible for tumor development, but the specific effect of CXCL11 in colon cancer was still obscure. Therefore, the prognostic value and immunological regulation effect of CXCL11 in colon cancer were evaluated in this study.Methods: Three independent datasets were used for mRNA-related analysis: one dataset from the Cancer Genome Atlas (TCGA, n=451) and two single-cell RNA sequencing (scRNA-seq) datasets from Gene Expression Omnibus (GEO): GSE146771 and GSE132465. In addition, the patient cohort (the Yijishan Hospital cohort, YJSHC, n=108) was utilized for cell infiltration-related analysis, accordingly. Both CXCL11 mRNA expression and CXCL11+ (CXCL11-producing) cells were assessed in colon cancer, whose effect on prognosis and immunological regulation was also studied. Results: High CXCL11 expression were associated with better prognosis in colon cancer, which was still significant even if clinicopathological factors were adjusted. Furthermore, CXCL11 positively correlated with anti-tumor cells infiltration, such as CD8+ T cells and natural killer cells. Meanwhile, CXCL11 correlated positively with several genes associated with DC, NK and T recruitment，and a gene set of cytotoxic genes. Notably, CXCL11 correlated positively with several immune checkpoint related genes including of PD-L1. Conclusions: CXCL11 contributed to anti-tumor immune microenvironment and could improve prognosis in patients with colon cancer. Especially, it’s a potential approach that inducible expression of CXCL11 by genetic and pharmacological interventions is able to improve prognosis and response to anti-PD-1 (programmed cell death protein-1) antibody treatment in colon cancer. However, it requires to be verified by further prospective investigations.

scholarly journals The Bioinformatics-Based Analysis Identifies 7 Immune-Related Genes as Prognostic Biomarkers for Colon Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Jie Pan ◽  
Zongqi Weng ◽  
Chaorong Xue ◽  
Bingqiang Lin ◽  
Mengxin Lin
Keyword(s):  
Colon Cancer ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Prognostic Biomarkers ◽  
Protein Protein Interaction ◽  
Causative Factors ◽  
Cancer Genome Atlas ◽  
Selection Operator ◽  
Cox Analysis ◽  
Immune Related Genes

Colon cancer poses a great threat to human health. Currently, there is no effective treatment for colon cancer due to its complex causative factors. Immunotherapy has now become a new method for tumor treatment. In this study, 487 DEGs were screened from The Cancer Genome Atlas (TCGA) database and ImmPort database, and GeneOntology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed. Hierarchical clustering of all samples revealed a significant correlation between colon cancer and immunity. The weighted gene co-expression network analysis (WGCNA) algorithm was used to identify key gene modules associated with immunity in colon cancer, here, module grey60 showed the highest correlation. A protein-protein interaction (PPI) network was constructed using the STRING database to screen hub genes, and subsequently, 7 immune-related genes the most closely associated with colon cancer were identified by differential expression in cancer and paracancer. Finally, a risk prediction model was developed using least absolute shrinkage and selection operator (LASSO) COX analysis, and the accuracy of the model was validated by GSE14333. This study determined that IRF4 and TNFRSF17 were immune-related genes in colon cancer, providing immune-related prognostic biomarkers for colon cancer.

scholarly journals NRAS Expression is Associated With Prognosis and Tumor Immune Microenvironment in Lung Adenocarcinoma

2021 ◽  
Author(s):  
Yueren Yan ◽  
Zhendong Gao ◽  
Han Han ◽  
Yue Zhao ◽  
Yang Zhang ◽  
...  
Keyword(s):  
T Cells ◽  
Lung Adenocarcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Expression Level ◽  
Immune Microenvironment ◽  
Kaplan Meier ◽  
Tumor Immune Microenvironment ◽  
Cox Analysis

Abstract Purpose: NRAS plays a pivotal role in progression of various kinds of somatic malignancies; however, the correlation between NRAS and lung adenocarcinoma is less known. We aim to analyze the prognostic value of NRAS expression in lung adenocarcinoma, and explore the relationship between NRAS and tumor immune microenvironment. Methods: We obtained the transcriptome pofiles and clinical data of LUAD from The Cancer Genome Atlas database and three Genome Expression Omnibus datasets. Specimens from 325 patients with completely resected lung adenocarcinoma were collected for immunohistochemical assays of NRAS, PD-L1, PD-1 and TIM-3. Then we performed gene set enrichment analysis to investigate cancer-related and immune-related signaling pathways. TIMER algorithms were performed to evaluate tumor immune infiltrating cells and immune-related biomarkers.Results: Compared with adjacent non-tumor tissue, NRAS expression was significantly upregulated in LUAD tissue. NRAS expression was significantly correlated with more advanced stage and positive lymph nodes. Kaplan-Meier curves and Cox analysis suggested that high NRAS expression led to a poor prognosis, and could be an independent prognostic factor in LUAD patients. Besides, NRAS expression was positively correlated with CD8+ T cells, macrophages, and neutrophils, and negatively correlated with B cells and CD4+ T cells. The expression level of NRAS was positively correlated with PD-L1, PD-1, and TIM-3 both at RNA and protein level. Conclusions: To conclude, we found NRAS a novel prognostic biomarker in LUAD. Besides, the expression level of NRAS may influence the prognosis of LUAD via various kinds of cancer-related pathways and remodeling TIM.

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