Dataset Information

An integrated model of N6-methyladenosine regulators to predict tumor aggressiveness and immune evasion in pancreatic cancer.

ABSTRACT:

Background

N6-methyladenosine (m6A) is the most abundant mRNA modification. Whether m6A regulators can determine tumor aggressiveness and risk of immune evasion in pancreatic ductal adenocarcinoma (PDAC) remains unknown.

Methods

An integrated model named "m6Ascore" is constructed based on RNA-seq data of m6A regulators in PDAC. Association of m6Ascore and overall survival is validated across several different datasets. Overlaps of m6Ascore and established molecular classifications of PDAC is examined. Immune infiltration, enriched pathways, somatic copy number alterations (SCNAs), mutation profiles and response to immune checkpoint inhibitors are compared between m6Ascore-high and m6Ascore-low tumors.

Findings

m6Ascore is associated with dismal overall survival and increased tumor recurrence in PDAC as well as several other solid tumors including colorectal cancer and breast cancer. Basal-like (Squamous) PDAC has higher m6Ascore than that in the classical PDAC. Mechanism study showed m6Ascore-high tumors are characterized with reduced immune infiltration and T cells exhaustion. Meanwhile, m6Ascore is associated with genes regulating cachexia and chemoresistance in PDAC. Furthermore, distinct SCNAs patterns and mutation profiles of KRAS and TP53 are present in m6Ascore-high tumors, indicating immune evasion. m6Ascore-low tumors have higher response rates to immune checkpoint inhibitors (ICIs).

Interpretation

These findings indicate m6Ascore can predict aggressiveness and immune evasion in pancreatic cancer. This model has implications for pancreatic cancer prognosis and treatment response to ICIs.

Funding

This work was supported in part by National Institutes of Health (NIH) grants to M. Li (R01 CA186338, R01 CA203108, R01 CA247234 and the William and Ella Owens Medical Research Foundation) and NIH/National Cancer Institute Q39 award P30CA225520 to Stephenson Cancer Center.

SUBMITTER: Zhou Z

PROVIDER: S-EPMC7966986 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Publications

An integrated model of N6-methyladenosine regulators to predict tumor aggressiveness and immune evasion in pancreatic cancer.

Zhou Zhijun Z Zhang Junxia J Xu Chao C Yang Jingxuan J Zhang Yuqing Y Liu Mingyang M Shi Xiuhui X Li Xiaoping X Zhan Hanxiang H Chen Wei W McNally Lacey R LR Fung Kar-Ming KM Luo Wenyi W Houchen Courtney W CW He Yulong Y Zhang Changhua C Li Min M

EBioMedicine 20210310

<h4>Background</h4>N6-methyladenosine (m6A) is the most abundant mRNA modification. Whether m6A regulators can determine tumor aggressiveness and risk of immune evasion in pancreatic ductal adenocarcinoma (PDAC) remains unknown.<h4>Methods</h4>An integrated model named "m6Ascore" is constructed based on RNA-seq data of m6A regulators in PDAC. Association of m6Ascore and overall survival is validated across several different datasets. Overlaps of m6Ascore and established molecular classifications ...[more]

PMID: 33714027

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Project description:BackgroundSeveral studies have revealed that N6-methyladenosine (m6A) regulation is involved in various biological processes and cancer progression. Nevertheless, the potential effects of m6A modifications in the tumor immune microenvironment (TIME) and on immune regulation in pancreatic adenocarcinoma (PAAD) remains unclear.MethodsA consensus clustering algorithm was used to identify different m6A modification patterns and construct an m6A-associated gene signature based on 23 m6A regulators in PAAD. The CIBERSORT and ssGSEA algorithms were used to estimate the components of the immune cells in each sample. The PCA algorithm was used to develop the m6Ascore system for the evaluation of m6A modification patterns in each sample.ResultsTwo m6A modification patterns with different biological properties and prognoses were identified in 176 PAAD patient samples. The features of TIME between the two patterns were similar, with two definite immune phenotypes: immune-inflamed and immune-excluded. Based on the m6A phenotype-associated signature genes, we constructed an m6Ascore system to investigate the m6A modification pattern of each sample, profile the dissection of physiological processes, immune infiltration, clinical prognosis, immunotherapy, and genetic variation. Patients with low m6Ascore scores had better clinical outcomes, enhanced immune infiltration, and lower expression of immunotherapeutic drug targets, such as CD274 and PDCD1LG2. Further research indicated that the m6Ascore and tumor mutation burden were significantly correlated, and patients with low m6Ascore had higher mutation rates in SMAD4 and TTN. Moreover, TNFRSF21 was significantly upregulated in PAAD tumor tissues and cell lines. Lower expression of TNFRSF21 had a prominent advantage in survival and was correlated with a low level of immune infiltration. PAAD samples with different TNFRSF21 expression levels showed significantly distinct sensitivities to chemotherapeutic agents.ConclusionsThis study revealed that m6A modification patterns could play an important role in the diversity and complexity of TIME, and the m6Ascore system could serve as an independent and powerful prognostic biomarker and is latently related to PAAD immunotherapies. Quantitative determination of m6A modification patterns in individual patients will be instrumental in mapping the TIME landscape and further optimizing precision immunotherapy.

Project description:Background Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer, which is one of the most commonly diagnosed tumors and the leading causes of death from cancer around the world. Since RNA methylation is a posttranscriptional modification and affects so much biological progress, it is urged to explore the role of N6-methyladenosine (m6A) methylation in LUAD. Methods We explored the expression of 24 m6A methylation genes, as well as their correlations with LAG3 in 561 LUAD samples from TCGA. Consensus clustering was applied to m6A methylation genes, and two LUAD subgroups were identified. The expression of m6A genes was analyzed by the Wilcoxon test. KEGG and GO enrichment analyses were performed to indicate the pathway affected by differentially expressed genes in the two groups. A prognostic model based on LASSO regression using an eleven-m6A gene signature was constructed according to the expression of these genes. Receiver operating characteristic (ROC) curve was used to confirm the accuracy of the model in the TCGA cohort, as well as in the test cohort from the Gene Expression Omnibus (GEO) database. Results Compared to cluster 1, cluster 2 showed poorer overall survival (OS) and higher LAG3 expression. In addition, KEGG and GO enrichment analyses indicated that differentially expressed genes are enriched in the immune response. We also observed that the expression of LAG3 is positively correlated with IGF2BP2, CBLL1, and HNRNPA2B1 and negatively correlated with YTHDF2, YTHDF3, and FTO. For patients in the TCGA cohort, the AUC score is 0.7, and the AUC score for the GSE50081 cohort is 0.675. Patients with lower risk scores exhibited better overall survival and lower expression of LAG3 than patients with higher risk scores. Conclusions In brief, our results indicated the important role of m6 methylation in affecting the tumor immune microenvironment and the survival of patients with LUAD. The m6A methylation gene signatures might serve as promising therapeutic targets and help the immunotherapy of LUAD in the future.

Project description:BackgroundN6-methyladenosine (m6A)-mediated ribonucleic acid (RNA) methylation is considered to be the most significant and abundant epigenetic modification in eukaryotic cells, and plays an essential role in the carcinogenesis and molecular pathogenesis of hepatocellular carcinoma (HCC). However, the relationship between m6A regulation and immune cell infiltration of the tumor immune microenvironment (TIME) has not yet been clarified. We aimed to investigate the roles of m6A RNA gene regulators in HCC immune regulation and prognosis.MethodsThe Cancer Genome Atlas (TCGA) database was used, and unsupervised clustering of 21 m6A regulators was performed based on differential gene expression. Gene Set Variation Analysis (GSVA), single-sample Gene Set Enrichment Analysis (ssGSEA), the empirical Bayes method, and m6A scores were used in our analyses.ResultsOf 433 samples, 101 (23.22%) had m6A regulatory factor mutations. From these, we identified three m6A subtypes, which correlated with different TIME phenotypes: immune rejection, immune infiltration, and immune deficiency. Tumors with low methyltransferase-like 3 (METTL3) expression had increased infiltration of dendritic cells (DCs) in the TIME. Reduced METTL3 expression also led to an overall increase in expression of major histocompatibility complex (MHC) molecules, costimulatory molecules, and adhesion molecules. The m6A subtypes were scored and analyzed for correlations. Patients with epithelial-mesenchymal transition (EMT) subtypes had lower m6A scores than the other three molecular subtypes. Survival analysis found that patients with low m6A scores had better overall survival [hazard ratio (HR) 1.6 (1.1-2.3)] and a 1.16 times better 5-year survival rate than patients with high m6A scores (56% vs. 48%).ConclusionsOur results demonstrated that three different m6A modification subtypes contribute to immune regulation in HCC and have potential as novel prognostic indicators and immune therapeutic targets.

Dataset Information

An integrated model of N6-methyladenosine regulators to predict tumor aggressiveness and immune evasion in pancreatic cancer.

Background

Methods

Findings

Interpretation

Funding

Publications

An integrated model of N6-methyladenosine regulators to predict tumor aggressiveness and immune evasion in pancreatic cancer.

Similar Datasets

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