scholarly journals m6A Methylation Modification Patterns and Tumor Microenvironment Infiltration Characterization in Pancreatic Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Mengyu Sun ◽  
Meng Xie ◽  
Tongyue Zhang ◽  
Yijun Wang ◽  
Wenjie Huang ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Tumor Microenvironment ◽  
Clustering Algorithm ◽  
Immune Cell ◽  
Biological Processes ◽  
Consensus Clustering ◽  
Tumor Mutation Burden ◽  
Immune Infiltration ◽  
Signature Genes ◽  
Mutation Burden

Recent studies have shown that RNA N6-methyladenosine (m6A) modification plays an important part in tumorigenesis and immune-related biological processes. However, the comprehensive landscape of immune cell infiltration characteristics in the tumor microenvironment (TME) mediated by m6A methylation modification in pancreatic cancer has not yet been elucidated. Based on consensus clustering algorithm, we identified two m6A modification subtypes and then determined two m6A-related gene subtypes among 434 pancreatic cancer samples. The TME characteristics of the identified gene subtypes were highly consistent with the immune-hot phenotype and the immune-cold phenotype respectively. According to the m6A score extracted from the m6A-related signature genes, patients can be divided into high and low m6A score groups. The low score group displayed a better prognosis and relatively strong immune infiltration. Further analysis showed that low m6A score correlated with lower tumor mutation burden and PD-L1 expression, and indicated a better response to immunotherapy. In general, m6A methylation modification is closely related to the diversity and complexity of immune infiltration in TME. Evaluating the m6A modification pattern and immune infiltration characteristics of individual tumors can help deepen our understanding of the tumor microenvironment landscape and promote a more effective clinical practice of immunotherapy.

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 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.

Increased neutrophil infiltration and lower prevalence of tumor mutation burden and microsatellite instability are hallmarks of RAS mutant colorectal cancers.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3563-3563
Author(s):  
Emil Lou ◽  
Yasmine Baca ◽  
Joanne Xiu ◽  
Andrew Nelson ◽  
Subbaya Subramanian ◽  
...  
Keyword(s):  
T Cells ◽  
B Cells ◽  
Cd8 T Cells ◽  
Immune Cell ◽  
Neutrophil Infiltration ◽  
Cell Fraction ◽  
Colorectal Cancers ◽  
Tumor Mutation Burden ◽  
Immune Infiltration ◽  
Mutation Burden

3563 Background: The tumor microenvironment (TME) of colorectal cancers (CRC) is modulated by oncogenic drivers such as KRAS. The TME comprises a broad landscape of immune infiltration. How tumor genomics associates with the immune cell landscape is less known. We aim to characterize immune cell types in RAS wild-type (WT) and mutant (MT) CRC, and to examine the prevalence of immuno-oncologic (IO) biomarkers (e.g. tumor mutation burden (TMB), PD-L1, MSI-H/dMMR) in these tumors. We performed genomic and transcriptomic analysis to confirm associations of mutant RAS with immune infiltration of the TME conducive to metastasis vs. potential response to immunotherapies. Methods: A total of 7,801 CRC were analyzed using next-generation sequencing on DNA (NextSeq, 592 Genes and WES, NovaSEQ), RNA (NovaSeq, whole transcriptome equencing) and IHC (Caris Life Sciences, Phoenix, AZ). MSI/MMR was tested by FA, IHC and NGS. TMB-H was based on a cut-off of > 10 mutations per MB). Immune cell fraction was calculated by QuantiSeq (Finotello 2019, Genome Medicine). Significance was determined by X2 and Fisher-Exact and p adjusted for multiple comparisons (q) was <0.05. Results: Mutant KRAS was seen in 48% of mCRC tumors; NRAS in 3.7%, HRAS in 0.1%. The distribution was similar in patients < or >= than 50 yrs. In MSS tumors, there was a significantly higher neutrophil infiltration in KRAS MT (median cell fraction 6.6% vs. 5.9%) and NRAS MT (6.9%) overall and also when individual codons were studied. B cells, M2 macrophages, CD8+ T cells, dendritic cells and fibroblasts were lower in KRAS mutant tumors; B cells and M1 macrophages are lower in NRAS (q<0.05). dMMR/MSI-H was significantly more prevalent in RAS WT (9.1%) than in KRAS (2.9%) or NRAS MT (1.8%) tumors, and highest in HRAS MT tumors (60%, q<0.05).TMB-H was more prevalent in RAS WT (11%) than KRAS (5.8%) or NRAS (5.1%) MT, and highest in HRAS MT tumors (70%, all q<0.05). In MSS tumors, KRAS MT tumors showed more TMB-H than WT (3.1% vs. 2.1%, q<0.05), especially in KRAS non 12/13/61 mutations (5.5%, vs. 2.1%, q<0.05) and G12C (4.4%, p<0.05). PD-L1 expression was studied: in MSS tumors, KRAS-G12D (10.4%) and G13 MT (11.8%) showed higher mutation rates than RAS WT tumors (q<0.05). Conclusions: KRAS & NRAS mutations are associated with increased neutrophil abundance, with codon specific differences, while HRAS shows no difference. Overall CD8+ T cells and B cells are less abundant in KRAS & NRAS mutants; substantial variability was seen amongst different protein changes. RAS mutations were more prevalent overall than generally reported, but did not vary by age. These results demonstrate significant differences in the TME of RAS mutant CRC that identify variable susceptibilities to immuno-oncologic agents, and provide further detailed characterization of heterogeneity between RAS variants, at the molecular as well as immunogenic levels.

scholarly journals ­­Prognostic analysis of tumor mutation burden combined with immune infiltration of Thymic epithelial tumors

2020 ◽  
Author(s):  
Pinglang Ruan ◽  
Dan Liu ◽  
Lili Wang ◽  
Ling Qin ◽  
Yurong Tan
Keyword(s):  
T Cell ◽  
Immune Cell ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Thymic Epithelial Tumors ◽  
Tumor Mutation Burden ◽  
Immune Genes ◽  
Immune Infiltration ◽  
Epithelial Tumors ◽  
Mutation Burden

Abstract Background: Thymic epithelial tumors (TETs) are uncommon neoplasms with poor prognosis and limited effective therapeutic options. This study aims to investigate the prognosis of tumor mutation burden (TMB) and the potential association with immune infiltrates in TETs. Methods: Tumor mutation burden (TMB) was calculated using Maftools package and the samples were classified into high-TMB and low- TMB groups. Differentially expressed genes (DEGs) combined with immune cell infiltration and survival rate were analyzed between the low-TMB and high-TMB groups.Results: Single nucleotide polymorphism (SNP) occurred more frequently than insertion or deletion, and C>T was the most common single nucleotide variants (SNV) in TETs. The results of Kaplan–Meier curve indicated that a high TMB was associated with worse clinical outcomes of TETs. Moreover, 3 hub immune genes associated with immune infiltration were significantly associated with prognosis. Besides, the TMB-related signature (TMBRS) model based on the three hub immune genes possessed good predictive value with area under curve (AUC) 0.729, and patients with higher TMBRS scores showed worse TETs outcomes. In addition, infiltration levels of native CD4+ T cell, activated memory CD4+ T cell and follicular helper T cells in low-TMB group were higher than those in high-TMB group, which were correlated positively with prognosis of TETs. Conclusion: TETs patients with low TMB have better prognosis than those with high TMB, and TMB might affect the development of TETs by regulating immune infiltration.

scholarly journals The effect of NLRP3 on tumors based on pan-cancer research

2021 ◽  
Author(s):  
Desheng Tang ◽  
Wei Li ◽  
Zhengjie Xu ◽  
Suxiao Jiang ◽  
Kun Fang
Keyword(s):  
Tumor Microenvironment ◽  
Immune Cell ◽  
Cox Regression ◽  
Tumor Mutation Burden ◽  
Cox Regression Analysis ◽  
Related Data ◽  
Immune Resistance ◽  
Kaplan Meier ◽  
Mutation Burden ◽  
The Relationship

Abstract NLRP3 is a multi-protein complex in cells, which can directly or indirectly affect the tumor microenvironment and participate in tumor growth, invasion and metastasis. Tumor and normal tissue gene sequencing was downloaded, clinical and mutation-related data was obtained from the TCGA website, and Kaplan-Meier and cox regression analysis was used to analyze the relationship between NLRP3 and overall survival (OS) as well as Hazard ratio (HR). The correlation between NLRP3 and tumor microenvironment score, immune cell invasion, and immune resistance indicators (tumor mutation burden and microsatellite instability) was performed. Finally, the function of NLRP3 in tumors was analyzed by GSEA.Inflammation is one of the important factors that cause cancer.

257 Development of a diagnostic platform which matches therapies to the tumor microenvironment dominant biology

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A280-A280
Author(s):  
Kristen Strand-Tibbitts
Keyword(s):  
Tumor Microenvironment ◽  
Genomic Stability ◽  
Standard Of Care ◽  
Tumor Type ◽  
Biological Processes ◽  
Tumor Mutation Burden ◽  
Gene Signatures ◽  
Mutation Burden ◽  
Check Point Inhibitors ◽  
Exploratory Data

BackgroundTumor microenvironment (TME)-targeting agents such as anti-angiogenic therapies and check-point inhibitors (CPIs), have shown both promise and variability in effectiveness depending on the tumor type. For immune-targeting agents like CPIs, efforts to identify features or biomarkers that predispose responding patients include but are not limited to genomic stability, tumor mutation burden, and PD-L1 expression. Oncologie is developing a RNA-based platform that identifies subsets of patients based on multiple aspects of the biological processes (dominant biology) existing within the tumor microenvironment.MethodsRNA data from publicly available sources including microarray, RNASeq exome and whole RNA were analyzed with respect to gene signatures that describe four different microenvironmental phenotypes. Phenotypes were then evaluated for relationships to clinical efficacy endpoints. From these RNA signatures and driven by machine learning methodologies, drug-specific algorithms were developed and applied to retrospectively to clinical data. Comparative analyses were explored between gene signatures, commonly used biomarkers (eg. presence of microsatellite DNA, expression levels of PD-L1, etc) and within-patient metadata to better understand better how this approach can be utilized in prospective clinical studies.ResultsAttributes in RNA expression identified using Oncologie’s platform have retrospectively characterized responders to CPIs or anti-angiogenic drugs, demonstrating a relationship between clinical response and biomarker positive and negative patient populations. Exploratory data summarizing the use of the this platform demonstrates its utility for enriching response to both immune- and angiogenesis-targeting drugs. Relative expression changes between archival and fresh biopsies demonstrate changes in the TME with time and/or following targeted therapy. Lastly, cross-tumor comparisons support a tumor-agnostic utility of this approach. Detailed comparisons of this biomarker approach relative to other available biomarkers will be presented for standard of care drugs and those in the Oncologie pipeline based on retrospective analyses.ConclusionsRNA based descriptors of biology may be a useful approach to enrich for response to targeted therapies whose mechanism of action is to modify the TME biology.

Exploration of Tumor Mutation Burden Combined with Immune Infiltrates in the Prognosis of Lung Adenocarcinoma

2021 ◽  
Author(s):  
Zhenyu Zhao ◽  
Boxue He ◽  
Qidong Cai ◽  
Pengfei Zhang ◽  
Xiong Peng ◽  
...  
Keyword(s):  
High Risk ◽  
Lung Adenocarcinoma ◽  
Clinical Application ◽  
Risk Group ◽  
High Risk Group ◽  
Immune Microenvironment ◽  
Tumor Mutation Burden ◽  
Immune Signature ◽  
Immune Infiltration ◽  
Mutation Burden

Abstract Background: Lung adenocarcinoma (LUAD) accounts for a majority of cancer-related deaths worldwide annually. A recent study shows that immunotherapy is an effective method of LUAD treatment, and tumor mutation burden (TMB) was associated with the immune microenvironment and affected the immunotherapy. Exploration of the gene signature associated with tumor mutation burden and immune infiltrates in predicting prognosis in lung adenocarcinoma in this study, we explored the correlation of TMB with immune infiltration and prognosis in LUAD.Materials and Methods: In this study, we firstly got mutation data and LUAD RNA-Seq data of the LUAD from The Cancer Genome Atlas (TCGA), and according to the TMB we divided the patients into high/low-TMB levels groups. The gene ontology (GO) pathway enrichment analysis and KOBAS-Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis were utilized to explore the molecular function of the differentially expressed genes (DEGs) between the two groups. The function enrichment analyses of DEGs were related to the immune pathways. Then, the ESTIMATE algorithm, CIBERSORT, and ssGSEA analysis were utilized to identify the relationship between TMB subgroups and immune infiltration. According to the results, Venn analysis was utilized to select the immune-related genes in DEGs. Univariate and Lasso Cox proportional hazards regression analyses were performed to construct the signature which positively associated with the immune infiltration and affected the survival. Finally, we verified the correlation between the signature and immune infiltration. Result: The exploration of the immune infiltration suggested that high-TMB subgroups positively associated with the high level of immune infiltration in LUAD patients. According to the TMB-related immune signature, the patients were divided into High/Low-risk groups, and the high-risk group was positively associated with poor prognostic. The results of the PCA analysis confirmed the validity of the signature. We also verified the effectiveness of the signature in GSE30219 and GSE72094 datasets. The ROC curves and C-index suggested the good clinical application of the TMB-related immune signature in LUAD prognosis. Another result suggested that the patients of the high-risk group were positively associated with higher TMB levels, PD-L1expression, and immune infiltration levels.Conclusion: In conclusion, our signature provides potential biomarkers for studying aspects of the TMB in LUAD such as TMB affected immune microenvironment and prognosis. This signature may provide some biomarkers which could improve the biomarkers of PD-L1 immunotherapy response and were inverted for the clinical application of the TMB in LUAD. LUAD male patients with higher TMB-levels and risk scores may benefit from immunotherapy. The high-risk patients along with higher PD-L1 expression of the signature may suitable for immunotherapy and improve their survival by detecting the TMB of LUAD.

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.

Identification of Immune-Related Prognostic Biomarkers in Pancreatic Cancer

2020 ◽  
Vol 12 (12) ◽  
pp. 1355-1367
Author(s):  
Xiaoyan Lin ◽  
Jiakang Ma ◽  
Kaikai Ren ◽  
Mingyu Hou ◽  
Bo Zhou ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Tumor Microenvironment ◽  
Risk Score ◽  
Immune Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Individual Treatment ◽  
Survival Prediction ◽  
Lasso Regression ◽  
Immune Related Genes

Immunotherapy for pancreatic cancer (PC) faces significant challenges. It is urgent to find immunerelated genes for targeted therapy. We aimed to identify immune-related messenger ribonucleic acids (mRNAs) with multiple methods of comprehensive immunoenrichment analysis in predicting survival of PC. PC genomics and clinical data were downloaded from TCGA. We analyzed relative enrichment of 29 immune cells using ssGSEA and classified PC samples into three immuneinfiltrating subgroups. Immune cell infiltration level and pathways were evaluated by ESTIMATE data and KEGG. Independent risk factors were derived from the combined analysis of WGCNA, LASSO regression and Cox regression analyses. Immune risk score was calculated according to four mRNAs to identify its value in predicting survival. PPI analysis was used to analyze the connections and potential pathways among genes. Finally, PC samples were classified into three immuneinfiltrating subgroups. Immunity high subgroup had higher immune score, soakage of immune cells, HLA/PD-L1 expression level, immune-related pathways enrichment and better survivability. Four potential prognostic immune-related genes (ITGB7, RAC2, DNASE1L3, and TRAF1) were identified. Immune risk score could be a potential survival prediction indictor with high sensitivity and specificity (AUC values = 0.708, HR = 1.445). A PPI network with seven nodes and five potential targeted pathways were generated. In conclusion, we estimated the state of immune infiltration in the PC tumor microenvironment by calculating stromal and immune cells enrichment with ssGSEA algorithms, and identified four prognostic immune-related genes that affect the proportion and distribution of immune cells infiltration in the tumor microenvironment. They lay a theoretical foundation to be important immunity targets of individual treatment in PC.

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