Identification of gene expression profiles and immune cell infiltration signatures between low and high tumor mutation burden groups in bladder cancer

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.

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Tumor Mutation Burden, Immune Cell Infiltration, and Construction of Immune-Related Genes Prognostic Model in Head and Neck Cancer

International Journal of Medical Sciences ◽

10.7150/ijms.51064 ◽

2021 ◽

Vol 18 (1) ◽

pp. 226-238

Author(s):

Ai-Min Jiang ◽

Meng-Di Ren ◽

Na Liu ◽

Huan Gao ◽

Jing-Jing Wang ◽

...

Keyword(s):

Head And Neck Cancer ◽

Head And Neck ◽

Neck Cancer ◽

Prognostic Model ◽

Immune Cell ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Tumor Mutation Burden ◽

Mutation Burden ◽

Immune Related Genes

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Characterization of gene expression profiles of esophageal cancer patients with different nonsynonymous tumor mutation burden

Thoracic Cancer ◽

10.1111/1759-7714.13537 ◽

2020 ◽

Vol 11 (8) ◽

pp. 2270-2278

Author(s):

Jiawei Li ◽

Haiqing Chen ◽

Haifa Guo ◽

Mantang Qiu ◽

Fan Yang

Keyword(s):

Gene Expression ◽

Esophageal Cancer ◽

Cancer Patients ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Tumor Mutation Burden ◽

Mutation Burden

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

10.21203/rs.2.12276/v1 ◽

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.

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

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.779367 ◽

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.

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

Cancer Cell International ◽

10.1186/s12935-021-01774-6 ◽

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.

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

Frontiers in Immunology ◽

10.3389/fimmu.2021.782551 ◽

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.

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Effect of Immune Cell Infiltration on Occurrence of Pulmonary Hypertension in Pulmonary Fibrosis Patients Based on Gene Expression Profiles

Frontiers in Medicine ◽

10.3389/fmed.2021.671617 ◽

2021 ◽

Vol 8 ◽

Author(s):

Feng Zhu ◽

Lili Zuo ◽

Rui Hu ◽

Jin Wang ◽

Zhihua Yang ◽

...

Keyword(s):

Gene Expression ◽

Pulmonary Hypertension ◽

Random Forest ◽

Pulmonary Fibrosis ◽

Immune Cells ◽

Cross Validation ◽

Immune Cell ◽

Expression Profiles ◽

Cell Infiltration ◽

Immune Cell Infiltration

Pulmonary hypertension (PH) is a frequent complication in patients with pulmonary fibrosis (PF), whereas the mechanism was not well-understood. This study aimed to explore the influence of immune cell infiltration on PH status based on the genomic expression profiles. Microarray data of GSE24988 were downloaded from the GEO database, including 116 lung tissue samples derived from PF patients with various PH status. Proportion of infiltrated immune cells was evaluated using CIBERSORT, a gene expression-based de-convolution algorithm. A random forest classifier was constructed and out of bag (OOB) cross-validation was carried out for PH prediction. The proportions of immune infiltration cells varied differently in PH samples except T regulatory cells (p-value = 0). Compared with non-PH samples, increased number of naive B cells and plasma cells were identified in PH samples, whereas activated dendritic cells and M2 macrophages were relatively lower (p < 0.05). In the random forest model, these four types of immune cells obtained a higher variable importance score than other cells, including mean decreased accuracy and mean decreased gini evaluation. We ran the OOB cross-validation in each sample of datasets (training set and testing set) and obtained 79 and 69% accuracy, respectively. Abnormal proportions of four types of immune cells were identified in PH samples compared with non-PH samples, suggesting their involvement in PH development. In summary, the immune cell infiltration in PF patients is associated with the PH status of patients, which deserves further investigation in the future.

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