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 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 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 Histone Methylation Modification Patterns and Relevant M-RiskScore in Acute Myeloid Leukemia

2021 ◽  
Author(s):  
Dade Rong ◽  
Xiaomin Chen ◽  
Daiyuan Liu ◽  
Xiangna Ni ◽  
Zhuomao Mo ◽  
...  
Keyword(s):  
Histone Methylation ◽  
Scoring System ◽  
Myeloid Leukemia ◽  
Somatic Mutations ◽  
Immune Cell ◽  
Molecular Subtypes ◽  
Immune Cell Infiltration ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Acute Myeloid

Abstract Background: Acute myeloid leukemia (AML) is a type of heterogeneous disease with varied prognosis, but current classification methods for AML do not play an ideal role in guiding the therapy. Emerging studies shown alteration of histone methylation is closely related to leukemogenesis. This study aimed at identifying the molecular subtypes associated with histone methylation and establishing a relevant score to predict treatment respond and prognosis in AML.Methods: Gene expression data and clinical characteristics of patients with AML were obtained from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. Molecular subtypes were identified by consensus clustering based on the expression of 24 histone methylation modification regulators (HMMRs). The clinical and biological features of each pattern were investigated by unsupervised clustering, survival, principle component (PCA), somatic mutations, gene set variation (GSVA), tumor mutation burden (TMB) and immune cell infiltration analyses. Different expression analysis and lasso regression analysis was conducted to establish the scoring system that was explored in the role of prognosis by using receivers operating curve (ROC) analysis and univariate/multivariate Cox regression analyses. Moreover, correlation analysis was performed to investigate the value of scoring system in chemotherapeutic prediction. Finally, an independent GSE dataset was used as a reference to validate the established clustering system.Results: Two distinct histone methylation modification patterns had been identified that exhibit remarkable differences in several clinical and biological characteristics, including HMMRs’ expression, AML-M0 distribution, mutations of NPM1, survival, tumor mutation burden, somatic mutations, pathways activation and immune cell infiltration. Besides, based on the clustering, we established the scoring system, M-RiskScore. Integrated analysis demonstrated that M-RiskScore-low patients displayed a prominent survival advantage and a better respond to decitabine treatment, while the opposite site was reported to M-RiskScore-high patients but they could benefit more from IA regimen therapy.Conclusion: Our results demonstrate that detection of HMMRs’ expression is potentially useful to AML therapy decisions, and targeting histone methylation would be a more promising strategy for either AML-M0 or NPM1 mutant patients. M-RiskScore is a hopeful independent poor prognostic biomarker and be able to benefits the treatment decisions in AML.

Identification of an Immune-Related Prognostic Signature Associated with Immune Infiltration in Melanoma

2020 ◽  
Author(s):  
Nian Liu ◽  
Zijian Liu ◽  
Xinxin Liu ◽  
Xiaoru Duan ◽  
Yuqiong Huang ◽  
...  
Keyword(s):  
Immune Cell ◽  
Underlying Mechanism ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Signature ◽  
Immune Infiltration ◽  
Mutation Burden ◽  
Melanoma Prognosis ◽  
Melanoma Patients ◽  
Immune Related Genes

Abstract Background: Melanoma is the leading cause of cancer-related death among skin tumors, with an increasing incidence worldwide. Few studies have effectively investigated the significance of an immune-related genes (IRGs) signature for melanoma prognosis. Methods: Here, we constructed an IRGs prognostic signature using bioinformatics methods and evaluated and validated its predictive capability. Then, immune cell infiltration and tumor mutation burden (TMB) landscapes associated with this signature in melanoma were analyzed comprehensively. Results: With the 10-IRG prognostic signature, melanoma patients in the low-risk group showed better survival with distinct features of high immune cell infiltration and TMB. Importantly, melanoma patients in this subgroup were significantly responsive to MAGE-A3 in the validation cohort. Conclusions: This immune-related prognostic signature is thus a reliable tool to predict melanoma prognosis; as the underlying mechanism of this signature is associated with immune infiltration and mutation burden, it might reflect the benefit of immunotherapy to patients.

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