Journal: Frontiers in Immunology

Article Title: Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

doi: 10.3389/fimmu.2021.769425

Figure Lengend Snippet: Pan-cancer expression and alterations of m6A regulators. (A) Diagram of m6A regulators modification and its biological function. (B) The gene expression of m6A regulators in 31 cancer types based on TCGA + GTEx databases. (C) The gene expression of m6A regulators in 21 cancer types based on oncomine database, which integrates RNA and DNA-seq data from GEO, TCGA and published literatures. (D) The gene expression of m6A regulators in 23 cancer cell lines based on CCLE database.

Article Snippet: To further confirm the expression patterns in PAAD, we assessed m6A regulator mRNA expression among normal, tumor and metastatic tissues based on the TNMplot database and protein expression based on the Human Protein Atlas (HPA) database ( , ).

Techniques: Expressing, Modification, Gene Expression, DNA Sequencing

Journal: Frontiers in Immunology

Article Title: Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

doi: 10.3389/fimmu.2021.769425

Figure Lengend Snippet: The landscape of genetic and transcriptional alterations of m6A regulators in pancreatic cancer. (A) The difference of mRNA expression levels of 16 m6A regulators between normal and PAAD samples. (B) The interaction of expression of 16 m6A regulators in PAAD. The m6A regulators in three RNA modification types were depicted by circles in different colors. The lines connecting m6A regulators represented their positive/negative correlation with each other. The size of each circle represented the prognosis effect of each regulator and scaled by P-value. (C) 101 of the 905 PAAD patients in 6 studies experienced genetic alterations of 16 m6A regulators. (D) Kaplan-Meier plots comparing OS in cases with and without 16 m6A regulators alterations in patients with PAAD. (E) the CNV alteration frequency of 16 m6A regulators in PAAD. *p < 0.05; ****p < 0.0001.

Article Snippet: To further confirm the expression patterns in PAAD, we assessed m6A regulator mRNA expression among normal, tumor and metastatic tissues based on the TNMplot database and protein expression based on the Human Protein Atlas (HPA) database ( , ).

Techniques: Expressing, RNA modification

Journal: Frontiers in Immunology

Article Title: Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

doi: 10.3389/fimmu.2021.769425

Figure Lengend Snippet: Survival in cluster1/2 subtypes and the landscape of immune infiltration in the TME of PAAD. (A) Consensus clustering matrix for k=2. (B) Principal component analysis confirmed the two clusters, Cluster 1 (red), Cluster 2 (blue). (C) Kaplan-Meier curves of overall survival (OS) for patients with PAAD in cluster1/2 subtypes. (D) The heatmap showed the comparison of fraction of tumor-infiltrating immune cells in two clusters. (E) The correlation of the infiltrating levels of each immune cell in cluster 1 and cluster 2 subtypes, respectively. Bubble size and color represents correlation coefficient r, when p-value > 0.05 without bubbles. (F) Average expression of 16 m6A genes in different cell-types at single cell level across two datasets. *p < 0.05; ***p < 0.001; ****p < 0.0001.

Article Snippet: To further confirm the expression patterns in PAAD, we assessed m6A regulator mRNA expression among normal, tumor and metastatic tissues based on the TNMplot database and protein expression based on the Human Protein Atlas (HPA) database ( , ).

Techniques: Comparison, Expressing

Journal: Frontiers in Immunology

Article Title: Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

doi: 10.3389/fimmu.2021.769425

Figure Lengend Snippet: The correlation between clusters and tumor immune microenvironment. (A) . The associated landscape among immunescore, stromalscore, and estimatescore and molecular characteristics (cluster subtypes, Risk subtypes, immune infiltration subtypes, and survival status). Columns showed PAAD samples sorted by immunescore from low to high. (B) ImmuneScore, StromalScore, and estimatescore in two cluster subtypes. (C) Immune-activation-relevant genes and immune-checkpoint-relevant genes expressed in two cluster subtypes. (D) The correlation of the expression level of 16 m6A regulators and immune-activation-relevant and immune-checkpoint-relevant genes. (E) . The association overview between TIDE score and molecular characteristics (cluster subtypes, Risk subtypes, immune infiltration subtypes, and survival status). Columns showed PAAD samples sorted by TIDE score from low to high. (F) Kaplan-Meier curves for overall survival (OS) of all PAAD patients with high and low TIDE score. (G) Comparison of TIDE score in two cluster subtypes. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001; "ns" p > 0.05.

Article Snippet: To further confirm the expression patterns in PAAD, we assessed m6A regulator mRNA expression among normal, tumor and metastatic tissues based on the TNMplot database and protein expression based on the Human Protein Atlas (HPA) database ( , ).

Techniques: Activation Assay, Expressing, Comparison

Journal: Frontiers in Immunology

Article Title: Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

doi: 10.3389/fimmu.2021.769425

Figure Lengend Snippet: Construction and validation of prognostic signature of m6A regulators in PAAD cohort. (A) The associational landscape among risk score and molecular characteristics (cluster subtypes, immune infiltration subtypes, and survival status). Columns showed PAAD samples sorted by risk score from low to high. (C) Principal component analysis confirmed the two risk groups, high risk (red) and low risk (blue). (B, E) Distribution of risk score, OS, and OS status and heatmap of the six prognostic m6A regulator signatures in the training cohort (B) and validation cohort (E) . (D, F) Kaplan-Meier curves of OS for patients with PAAD based on the risk score in the training cohort (D) and validation cohort (F) .

Article Snippet: To further confirm the expression patterns in PAAD, we assessed m6A regulator mRNA expression among normal, tumor and metastatic tissues based on the TNMplot database and protein expression based on the Human Protein Atlas (HPA) database ( , ).

Techniques: Biomarker Discovery

Journal: Frontiers in Immunology

Article Title: Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

doi: 10.3389/fimmu.2021.769425

Figure Lengend Snippet: Correlation between risk score and immune sensitivity. (A) The heatmap showed the comparison of fraction of tumor-infiltrating immune cells in two risk subtypes. (B) ImmuneScore and StromalScore in high and low risk subtypes. (C) Immune-activation-relevant genes and immune-checkpoint-relevant genes expressed in high and low risk subtypes. (D) TIDE score in high and low risk subtypes. (E) The correlation of the risk score and infiltrating levels of tumor-infiltrating immune cells and immune-activation-relevant genes and immune-checkpoint-relevant genes expression. (F) The association landscape among 16 m6A regulators expression and known clinical features and molecular characteristics (ImmuneScore, StromalScore, PD1 expression, PD-L1 expression, TIDE score, cluster subtypes, immune infiltration subtypes, and survival status). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001;"ns" p > 0.05.

Article Snippet: To further confirm the expression patterns in PAAD, we assessed m6A regulator mRNA expression among normal, tumor and metastatic tissues based on the TNMplot database and protein expression based on the Human Protein Atlas (HPA) database ( , ).

Techniques: Comparison, Activation Assay, Expressing

Journal: Frontiers in Immunology

Article Title: Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

doi: 10.3389/fimmu.2021.769425

Figure Lengend Snippet: The role of risk score in the prediction of immunotherapeutic benefits. (A) Kaplan-Meier curves for patients with high and low risk score in the IMvigor210 cohort. (B) Rate of clinical response (complete response [CR]/partial response [PR] and stable disease [SD]/progressive disease [PD] to anti-PD-L1 immunotherapy in high and low risk score subgroups in the IMvigor210 cohort). (C) Violin plots depicted the differences in risk score in good prognosis and poor prognosis’ groups in the GSE148476 cohort. p < 0.001. (D) Alluvial diagram of m6A clusters distribution in groups with different clusters, risk score, immune infiltration, and survival outcomes. From the outside to the inside, each ring represents Cluster, risk group, immune infiltration, and survival status, respectively. (E) Kaplan-Meier curves for patients in the training cohort stratified by groups with different m6A gene clusters and risk score.

Article Snippet: To further confirm the expression patterns in PAAD, we assessed m6A regulator mRNA expression among normal, tumor and metastatic tissues based on the TNMplot database and protein expression based on the Human Protein Atlas (HPA) database ( , ).

Techniques:

Journal: Frontiers in Immunology

Article Title: Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

doi: 10.3389/fimmu.2021.769425

Figure Lengend Snippet: The underlying mechanism and pathways in the risk score model. (A) Correlation between risk score and the steps of the cancer immunity cycle. (B) Correlation between risk score and the enrichment score of immunotherapy-predicted pathways. (C) PAAD-specific cancer driver genes expressed in groups with different m6A gene clusters, immune infiltration, risk score, TIDE score, and survival status. The statistics results presented in the picture was analyzed between high and low risk subgroups. (D) The most altered genes frequency in six m6A genes altered and unaltered group. (E) GSEA showed multiple cancer-related signaling pathway are positively enriched in high-risk group. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Article Snippet: To further confirm the expression patterns in PAAD, we assessed m6A regulator mRNA expression among normal, tumor and metastatic tissues based on the TNMplot database and protein expression based on the Human Protein Atlas (HPA) database ( , ).

Techniques:

Journal: Frontiers in Immunology

Article Title: Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

doi: 10.3389/fimmu.2021.769425

Figure Lengend Snippet: Validation of the expression of m6A regulators in PAAD patient tissues and cell lines. (A, B) The protein expression level of six risk-score-gene in PAAD cell lines and PAAD tissues and adjacent tissues. (C, D) UMAP visualization of dataset PAAD_CRA001160 and PAAD_GSE111672, respectively. (E, F) The distribution of six risk-score-genes expression in different cell types in PAAD at single cell level.

Article Snippet: To further confirm the expression patterns in PAAD, we assessed m6A regulator mRNA expression among normal, tumor and metastatic tissues based on the TNMplot database and protein expression based on the Human Protein Atlas (HPA) database ( , ).

Techniques: Biomarker Discovery, Expressing

Journal: Frontiers in Immunology

Article Title: Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

doi: 10.3389/fimmu.2021.769425

Figure Lengend Snippet: Spatial transcriptome analysis of m6A regulators. A, B, Clustering of the PDAC-A (A) and PDAC-B (B) spatial transcriptome spots. Colors represent different clustering. C, D, Standardized expression levels of m6A regulators in PDAC-A (C) and PDAC-B (D) datasets in spatial transcriptome.

Article Snippet: To further confirm the expression patterns in PAAD, we assessed m6A regulator mRNA expression among normal, tumor and metastatic tissues based on the TNMplot database and protein expression based on the Human Protein Atlas (HPA) database ( , ).

Techniques: Expressing