scholarly journals Association Between Tumor Mutation Burden and Prognosis in Lower-Grade Glioma: An Exploratory Study 

2021 ◽  
Author(s):  
Di Cao ◽  
Jun Wang ◽  
Yan Lin ◽  
Guangwei Li
Keyword(s):  
Immune Cell ◽  
Differential Expression Analysis ◽  
Cell Infiltration ◽  
Lower Grade ◽  
Immune Cell Infiltration ◽  
Hub Genes ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Lower Grade Glioma ◽  
Genome Atlas

Abstract Background: The therapeutic efficacy of immune checkpoint inhibitor therapy is highly influenced by tumor mutation burden (TMB). The relationship between TMB and prognosis in lower-grade glioma is still unclear. We aimed to explore the relationships and mechanisms between them in lower-grade glioma.Methods: We leveraged somatic mutation data from The Cancer Genome Atlas (TCGA). Clinical cases were divided into high- and low-TMB groups based on the median of TMB. Infiltrating immune cells were analyzed using CIBERSORT and differential expression analysis between the prognostic groups performed. The key genes were identified as intersecting between immune-related genes. Cox regression and survival analysis were performed on the intersecting genes. A total of 7 hub genes were identified. The effect of somatic copy number alterations (SCNA) of the hub genes on immune cell infiltration was analyzed using TIMER, which was used to determine the risk factors and immune infiltration status in LGG. Subsequently, based on hub genes, a TMB Prognosis Index (TMBPI) model was constructed to predict the risk in LGG patients. Besides, this model was validated using data from TCGA and Chinese Glioma Genome Atlas (CGGA).Results: High-TMB favored worse prognosis (P＜0.001) and macrophage infiltration was an independent risk factor (P＜0.001). In the high-TMB group (P=0.033, P=0.009), the proportion of macrophages M0 and M2 increased and monocytes decreased (P=0.006). Besides, the SCNA of the hub genes affected the level of immune cell infiltration by varying degrees among which IGF2BP3, NPNT, and PLA2G2A had a significant impact. The AUC of the ROC curve at 1-, 3- and 5-years were all above 0.74.Conclusions: This study implies that high-TMB correlated with unfavorable prognosis in lower-grade glioma. And high-TMB may have an impact on prognosis by changing tumor microenvironment, caused by the SCNAs of genes. The TMBPI model accurately predicted prognosis in LGG patients.

scholarly journals Molecular Characterization of the Clinical and Tumor Immune Microenvironment Signature of 5-methylcytosine-Related Regulators in non-small Cell Lung Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Taisheng Liu ◽  
Liyi Guo ◽  
Guihong Liu ◽  
Xiaoshan Hu ◽  
Xiaoning Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Check Point ◽  
Clinical Prognosis ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Immune Check Point Inhibitor

Background: DNA methylation is an important epigenetic modification, among which 5-methylcytosine methylation (5mC) is generally associated with tumorigenesis. Nonetheless, the potential roles of 5mC regulators in the tumor microenvironment (TME) remain unclear.Methods: The 5mC modification patterns of 1,374 lung adenocarcinoma samples were analyzed systematically. The correlation between the 5mC modification and tumor microenvironment cell infiltration was further assessed. The 5mCscore was developed to evaluate tumor mutation burden, immune check-point inhibitor response, and the clinical prognosis of individual tumors.Results: Three 5mC modification patterns were established based on the clinical characteristics of 21 5mC regulators. According to the differential expression of 5mC regulators, three distinct 5mC gene cluster were also identified, which showed distinct TME immune cell infiltration patterns and clinical prognoses. The 5mCscore was constructed to evaluate the tumor mutation burden, immune check-point inhibitor response, and prognosis characteristics. We found that patients with a low 5mCscore had significant immune cell infiltration and increased clinical benefit.Conclusion: This study indicated that the 5mC modification is involved in regulating TME infiltration remodeling. Targeting 5mC modification regulators might be a novel strategy to treat lung cancer.

scholarly journals Tumor mutation burden in connection with immune-related survival in uterine corpus endometrial carcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ling Zhao ◽  
Xueshu Fu ◽  
Xiling Han ◽  
Yanjun Yu ◽  
Yaping Ye ◽  
...  
Keyword(s):  
T Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Cd8 T Cell ◽  
Prognostic Models ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Tumor Mutation Burden ◽  
Immune Genes ◽  
Mutation Burden

Abstract Background UCEC is the most common gynecological malignancy in many countries, and its mechanism of occurrence and development is related to tumor mutation burden (TMB) and immune cell infiltration. Therefore, it is necessary to systematically explore the TMB-related gene profile in immune cells to improve the prognosis of UCEC. Methods We integrated TMB-related genes with basic clinical information of UCEC patients based on TCGA dataset. Differentially expressed genes (DEGs) were selected through differential expression screening, PPI, and enrichment analysis. Additionally, we analyzed the components of immune cell infiltration of the DEGs to obtain the differential immunity-related genes. A single factor and multifactor Cox regression analyses were conducted to establish new prognostic indicators of OS and DFS based on TMB-related immune genes. To further study the correlation between survival and immune cell infiltration, a Cox model based on these immune infiltration compositions was built. Using the clinical variables, we established nomograms for OS and DFS. Results 393 DEGs were significantly associated with clinical outcomes and the immune component in patients with UCEC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway and protein-protein interaction network (PPI) analyses revealed the role of these genes and information on related pathways. Then, two prognostic models were established based on the differential immune genes for OS (GFAP and MX2) and DFS (MX2, GFAP, IGHM, FGF20, and TRAV21). In DFS, the differential immune genes were related to CD4+ T cell, CD8+ T cell, macrophage, and neutrophil (all P < 0.05). B cell and CD8+ T cell were independent prognostic factors from among the immune cell elements in UCEC. Finally, the risk scores of these models were combined with the clinical elements-based nomogram models, and the AUC values were all over 0.7. Conclusions Our results identified several clinically significant differential immune genes and established relevant prognostic models, providing a basis for the molecular analysis of TMB and immune cells in UCEC, and identified potential prognostic and immune-related genes for UCEC. We added clinical related conditions for further analysis to confirm the identity of the genes and clinical elements-based models.

scholarly journals Characterization of m6A RNA Methylation Regulators Predicts Survival and Immunotherapy in Lung Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Minggao Zhu ◽  
Yachao Cui ◽  
Qi Mo ◽  
Junwei Zhang ◽  
Ting Zhao ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Lung Adenocarcinoma ◽  
Immune Cell ◽  
Clinical Success ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Consensus Clustering ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Score Model

N6-methyladenosine (m6A) RNA modification is a reversible mechanism that regulates eukaryotic gene expression. Growing evidence has demonstrated an association between m6A modification and tumorigenesis and response to immunotherapy. However, the overall influence of m6A regulators on the tumor microenvironment and their effect on the response to immunotherapy in lung adenocarcinoma remains to be explored. Here, we comprehensively analyzed the m6A modification patterns of 936 lung adenocarcinoma samples based on 24 m6A regulators. First, we described the features of genetic variation in these m6A regulators. Many m6A regulators were aberrantly expressed in tumors and negatively correlated with most tumor-infiltrating immune cell types. Furthermore, we identified three m6A modification patterns using a consensus clustering method. m6A cluster B was preferentially associated with a favorable prognosis and enriched in metabolism-associated pathways. In contrast, m6A cluster A was associated with the worst prognosis and was enriched in the process of DNA repair. m6A cluster C was characterized by activation of the immune system and a higher stromal cell score. Surprisingly, patients who received radiotherapy had a better prognosis than patients without radiotherapy only in the m6A cluster C group. Subsequently, we constructed an m6A score model that qualified the m6A modification level of individual samples by using principal component analysis algorithms. Patients with high m6A score were characterized by enhanced immune cell infiltration and prolonged survival time and were associated with lower tumor mutation burden and PD-1/CTLA4 expression. The combination of the m6A score and tumor mutation burden could accurately predict the prognosis of patients with lung adenocarcinoma. Furthermore, patients with high m6A score exhibited greater prognostic benefits from radiotherapy and immunotherapy. This study demonstrates that m6A modification is significantly associated with tumor microenvironment diversity and prognosis. A comprehensive evaluation of m6A modification patterns in single tumors will expand our understanding of the tumor immune landscape. In addition, our m6A score model demonstrated that the level of immune cell infiltration plays a significant role in cancer immunotherapy and provides a basis to increase the efficiency of current immune therapies and promote the clinical success of immunotherapy.

scholarly journals m6A Modification Patterns With Distinct Immunity, Metabolism, and Stemness Characteristics in Soft Tissue Sarcoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhen-Dong Huang ◽  
Lu-Lu Lin ◽  
Zi-Zhen Liu ◽  
Chao Hu ◽  
Hui-Yun Gu ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Soft Tissue Sarcoma ◽  
Immune Cell ◽  
Machine Learning Algorithms ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Number Variation ◽  
M6a Rna Methylation

N6-methyladenosine (m6A) RNA methylation has been shown to have prognostic value in cancer. Nonetheless, its potential role regarding immunity, metabolism, and stemness in soft tissue sarcoma (STS) remains unknown. We comprehensively estimated the m6A modification patterns and corresponding immunity, metabolism, and stemness characteristics based on 568 STS samples and 21 m6A regulators. The m6Ascore was constructed to quantify m6A modification patterns in individuals using machine learning algorithms. Two distinct m6A modification patterns among the STS patients were identified, which exhibited differences in prognosis, immune cell infiltration, metabolic pathways, stemness, somatic mutation, and copy number variation. Thereafter, immunity-, metabolism-, and stemness phenotype-related genes associated with m6A modification were identified. Furthermore, patients with lower m6Ascores had increased antitumor immune responses, survival benefit under immunotherapy, tumor mutation burden, immunogenicity, and response to anti-PD-1/L1 immunotherapy. Immunotherapy sensitivity was validated using the IMvigor210 dataset. STS patients with lower m6Ascore might be more sensitive to docetaxel and gemcitabine. Finally, pan-cancer analysis illustrated the significant correlations of m6Ascore with clinical outcomes, immune cell infiltration, metabolism, and stemness. This study revealed that m6A modification plays an important role in immunity, metabolism, and stemness in STS. Evaluating the m6A modification pattern and development of m6Ascore may help to guide more effective immunotherapy and chemotherapy strategies.

scholarly journals Tumor Mutation Burden and Immune Invasion Characteristics in Triple Negative Breast Cancer: Genome High-Throughput Data Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Chundi Gao ◽  
Huayao Li ◽  
Cun Liu ◽  
Xiaowei Xu ◽  
Jing Zhuang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mutation Rate ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Immune Cell ◽  
Cancer Genome ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Tumor Mutation Burden ◽  
Mutation Burden

In recent years, the emergence of immunotherapy has provided a new perspective for the treatment and management of triple-negative breast cancer (TNBC). However, the relationship between tumor mutation burden (TMB) and immune infiltration and the prognosis of TNBC remains unclear. In this study, to explore the immunogenicity of TNBC, we divided patients with TNBC into high and low TMB groups based on the somatic mutation data of TNBC in The Cancer Genome Atlas (TCGA), and screened out genes with mutation rate ≥10. Then, Kaplan-Meier survival analysis revealed that the 5-year survival rate of the high TMB group was much higher than that of the low TMB group and the two groups also showed differences in immune cell infiltration. Further exploration found that the FAT3 gene, which displays significant difference and a higher mutation rate between the two groups, is not only significantly related to the prognosis of TNBC patients but also exhibits difference in immune cell infiltration between the wild group and the mutant group of the FAT3 gene. The results of gene set enrichment analysis and drug sensitivity analysis further support the importance of the FAT3 gene in TNBC. This study reveals the characteristics of TMB and immune cell infiltration in triple-negative breast cancer and their relationship with prognosis, to provide new biomarkers and potential treatment options for the future treatment of TNBC. The FAT3 gene, as a risk predictor gene of TNBC, is considered a potential biological target and may provide new insight for the treatment of TNBC.

scholarly journals METTL7B is a novel prognostic biomarker of lower-grade glioma based on pan-cancer analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhipeng Jiang ◽  
Wen Yin ◽  
Hecheng Zhu ◽  
Jun Tan ◽  
Youwei Guo ◽  
...  
Keyword(s):  
Immune Cell ◽  
Epithelial Mesenchymal Transition ◽  
Prognostic Biomarker ◽  
Disease Free Survival ◽  
Cell Infiltration ◽  
Lower Grade ◽  
Immune Cell Infiltration ◽  
Mesenchymal Transition ◽  
Lower Grade Glioma ◽  
Cancer Types

AbstractMethyltransferase-like 7B (METTL7B) is a member of the methyltransferase-like protein family that plays an important role in the development and progression of tumors. However, its prognostic value and the correlation of METTL7B expression and tumor immunity in some cancers remain unclear. By analyzing online data, we found that METTL7B is abnormally overexpressed in multiple human tumors and plays an important role in the overall survival (OS) of patients with 8 cancer types and disease-free survival (DFS) of patients with 5 cancer types. Remarkably, METTL7B expression was positively correlated with the OS and DFS of patients with lower-grade glioma (LGG). In addition, a positive correlation between METTL7B expression and immune cell infiltration in LGG was observed. Moreover, we identified a strong correlation between METTL7B expression and immune checkpoint gene expression in kidney chromophobe (KICH), LGG and pheochromocytoma and paraganglioma (PCPG). Furthermore, METTL7B was involved in the extracellular matrix (ECM) and immune-related pathways in LGGs. Finally, in vitro experiments showed that knockdown of METTL7B inhibited the growth, migration, invasion and the epithelial–mesenchymal transition (EMT) of LGG cells. METTL7B expression potentially represents a novel prognostic biomarker due to its significant association with immune cell infiltration in LGG.

scholarly journals Identification of Hub Genes and Immune Cell Infiltration Characteristics in Alzheimer’s Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Ming Hu ◽  
Jianhua Wang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Immune Cells ◽  
Immune Cell ◽  
Differential Expression Analysis ◽  
Cell Infiltration ◽  
Control Group ◽  
Immune Cell Infiltration ◽  
Hub Genes ◽  
Significant Difference

The purpose of this study was to identify hub genes closely correlated with Alzheimer's disease (AD) and their association with immune cell infiltration. In this work, 119 overlapping differentially expressed genes (DEGs) were obtained from GSE5281 and GSE122063 datasets through differential expression analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the 119 DEGs, revealing some important biological functions and key pathways. AD immune cell infiltration analysis revealed a significant difference in the proportion of immune cells between the AD group and the control group. Finally, correlation analysis between target hub genes and immune cells indicated that GFAP had a positive or negative correlation with some specific immune cells. Our results provided useful clues, which will help to explain the molecular mechanism of AD and search for precise prognostic markers and potential therapeutic targets.

scholarly journals Molecular profile reveals immune-associated markers of medulloblastoma for different subtypes

2021 ◽  
Author(s):  
shenglan li ◽  
Zhuang Kang ◽  
jinyi Chen ◽  
Can Wang ◽  
Zehao Cai ◽  
...  
Keyword(s):  
Immune Cell ◽  
Intracranial Tumor ◽  
Cell Infiltration ◽  
Molecular Profile ◽  
Immune Cell Infiltration ◽  
Ppi Network ◽  
Hub Genes ◽  
Data Set ◽  
Hub Gene ◽  
External Data

Abstract Background Medulloblastoma is a common intracranial tumor among children. In recent years, research on cancer genome has established four distinct subtypes of medulloblastoma: WNT, SHH, Group3, and Group4. Each subtype has its own transcriptional profile, methylation changes, and different clinical outcomes. Treatment and prognosis also vary depending on the subtype. Methods Based on the methylation data of medulloblastoma samples, methylCIBERSORT was used to evaluate the level of immune cell infiltration in medulloblastoma samples and identified 10 kinds of immune cells with different subtypes. Combined with the immune database, 293 Imm-DEGs were screened. Imm-DEGs were used to construct the co-expression network, and the key modules related to the level of differential immune cell infiltration were identified. Three immune hub genes (GAB1, ABL1, CXCR4) were identified according to the gene connectivity and the correlation with phenotype in the key modules, as well as the PPI network involved in the genes in the modules. Results The subtype marker was recognized according to the immune hub, and the subtype marker was verified in the external data set, the methylation level of immune hub gene among different subtypes was compared and analyzed, at the same time, tissue microarray was used for immunohistochemical verification, and a multi-factor regulatory network of hub gene was constructed. Conclusions Identifying subtype marker is helpful to accurately identify the subtypes of medulloblastoma patients, and can accurately evaluate the treatment and prognosis, so as to improve the overall survival of patients.

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