Molecular characterization, biological function, tumor microenvironment association and clinical significance of m6A regulators in lung adenocarcinoma

Li, Yin; Gu, Jie; Xu, Fan; Zhu, Qinqing; Chen, Yiwei; Ge, Di

doi:10.1093/bib/bbaa225

Cited by 118 publications

(109 citation statements)

References 91 publications

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“…12 Recently, several bioinformatics studies have shown that the dysregulation of m 6 A regulators is involved in LUAD. 13,14 The specific role of m 6 A regulators in lncRNAs remains unclear; therefore, understanding the mechanism of m 6 A-related lncRNAs in the development of LUAD may be useful for prognostic targets.…”

Section: Introductionmentioning

confidence: 99%

m6A-related lncRNAs are potential biomarkers for predicting prognoses and immune responses in patients with LUAD

Huang

et al. 2021

Molecular Therapy - Nucleic Acids

168

141

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Lung adenocarcinoma (LUAD) is the most frequent subtype of lung cancer worldwide. However, the survival rate of LUAD patients remains low. N6-methyladenosine (m 6 A) and long noncoding RNAs (lncRNAs) play vital roles in the prognostic value and the immunotherapeutic response of LUAD. Thus, discerning lncRNAs associated with m 6 A in LUAD patients is critical. In this study, m 6 A-related lncRNAs were analyzed and obtained by coexpression. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were conducted to construct an m 6 Arelated lncRNA model. Kaplan-Meier analysis, principalcomponent analysis (PCA), functional enrichment annotation, and nomogram were used to analyze the risk model. Finally, the potential immunotherapeutic signatures and drug sensitivity prediction targeting this model were also discussed. The risk model comprising 12 m 6 A-related lncRNAs was identified as an independent predictor of prognoses. By regrouping the patients with this model, we can distinguish between them more effectively in terms of the immunotherapeutic response. Finally, candidate compounds aimed at LUAD subtype differentiation were identified. This risk model based on the m 6 Abased lncRNAs may be promising for the clinical prediction of prognoses and immunotherapeutic responses in LUAD patients.

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Section: Introductionmentioning

confidence: 99%

m6A-related lncRNAs are potential biomarkers for predicting prognoses and immune responses in patients with LUAD

Huang

et al. 2021

Molecular Therapy - Nucleic Acids

168

141

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“…Research based on the heterogeneity of m 6 A regulators to identify distinct subtypes of sepsis (27), of which the GSEA and CIBERSORT analyses found different immunocompetent status (such as Th1 cells, T cells CD4 activated, NK cells activated and B cells activated) among subtypes and indicated the potential relation among m 6 A regulators and leukocyte infiltration. Studies also have shown that m 6 A regulators contribute to TME formation (28) and affect the abundance of TILs (29) as well as response to ICIs treatment (30).…”

Section: Introductionmentioning

confidence: 99%

Pan-Cancer Molecular Characterization of m6A Regulators and Immunogenomic Perspective on the Tumor Microenvironment

et al. 2021

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PurposeN6-methyladenosine (m6A) methylation plays a critical role in diverse biological processes. However, knowledge regarding the constitution of m6A on tumor microenvironment (TME) and tumor-infiltrating lymphocytes (TILs) across cancer types is still lacking. We performed comprehensive immuno-genomic analyses to reveal molecular characterization of the m6A regulators and immune-related genes (IRGs) across TME and TIL heterogeneity.MethodsWe comprehensively analyzed the properties of m6A regulators in genomic profiles from The Cancer Genome Atlas (TCGA) according to expression perturbations of crucial IRGs, CD274, CD8A, GZMA, and PRF1. The four IRGs were proved to be reliable biomarkers of TILs and TME via CIBERSORT and ESTIMATE analyses, and their co-expression relationship was certified by TIMER analysis. Based on their median values, the samples from the pan-cancer tissues (N = 11,057) were classified into eight TME types. The RNA expression levels of 13 m6A regulators were compared across TME subtypes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was also used to classify TME clusters, expression variants of IRGs and m6A regulators were verified among TME clusters. Meanwhile, the correlation between m6A regulators and tumor mutational burden (TMB) were tested. Finally, the impacts of IRGs and TME clusters in clinical characteristics and outcomes were revealed.ResultsCD274, CD8A, GZMA, and PRF1 showed similar TILs’ characteristics, of which the level of T cells CD8 and T cells CD4 memory activated are consistent with the expression levels of the four IRGs and higher immune infiltration. Besides, CD274, CD8A, GZMA, and PRF1 were positively correlated with the stromal score or immune score in almost all 33 tumor types. All of four IRGs showed impact between tumor pathological stages or clinical outcomes. Among TME type I to type IV, m6A regulators’ expression drift changed from high-level to low-level in ESCA, BLCA, HNSC, CESC, BRCA, and GBM. However among TME type V to type VIII, m6A regulators drew a shift from low-level to high-level expression in CESC, BLCA, ESCA, KIRP, HNSC, BRCA, KIRC, COAD, LAML, GBM, and KICH. In ssGSEA analyses, IRGs’ expression levels were elevated with the immune infiltration degree and m6A regulators’ expression level varied among three TIL subgroups. With different TMB levels, expression differences of m6A regulators were observed in BLCA, BRCA, COAD, LGG, LUAD, LUSC, STAD, THCA, and UCEC.ConclusionWe identified four crucial IRGs affecting TILs, TME characteristics and clinical parameters. Expression variants of m6A regulators among the subgroups of TME types and ssGSEA clusters suggested that m6A regulators may be essential factors for phenotypic modifications of IRGs and thus affecting TME characteristics across multiple tumor types.

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“…Previous studies have shown that molecular heterogeneities are tightly associated with therapeutic outcomes and prognosis of patients in various cancer types [ 14 , 62 ], we wondered whether there were distinct molecular phenotypes in ESCC that contributed to patients' survival differences. To answer this question, we first screened all survival-related genes in GSE53625 and TCGA ESCC cohorts separately ( Fig.…”

Section: Resultsmentioning

confidence: 99%

“…With the continuous accumulation of data, researchers can now explore the key characteristics of diseases in a larger cohort based on appropriate data integration strategy and obtain more convincing results supported by multiple pieces of evidence [ 12 , 13 ]. Such strategies have been widely applied to study the molecular features of various cancer types such as lung adenocarcinoma, hepatocellular carcinoma, and gastric cancer [14] , [15] , [16] . However, compared with other common cancer types, such approaches were less applied to study the molecular features of ESCC.…”

Section: Introductionmentioning

confidence: 99%

Transcriptomics based multi-dimensional characterization and drug screen in esophageal squamous cell carcinoma

Chen

et al. 2021

EBioMedicine

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Background Esophageal squamous cell carcinoma (ESCC) remains one of the deadly cancer types. Comprehensively dissecting the molecular characterization and the heterogeneity of ESCC paves the way for developing more promising therapeutics. Methods Expression profiles of multiple ESCC datasets were integrated. ATAC-seq and RNA-seq were combined to reveal the chromatin accessibility features. A prognosis-related subtype classifier (PrSC) was constructed, and its association with the tumor microenvironment (TME) and immunotherapy was assessed. The key gene signature was validated in clinical samples. Based on the TME heterogeneity of ESCC patients, potential subtype-specific therapeutic agents were screened. Findings The common differentially expressed genes (cDEGs) in ESCC were identified. Up-regulated genes (HEATR1, TIMELESS, DTL, GINS1, RUVBL1, and ECT2) were found highly important in ESCC cell survival. The expression alterations of PRIM2, HPGD, NELL2, and TFAP2B were associated with chromatin accessibility changes. PrSC was a robust scoring tool that was not only associated with the prognosis of ESCC patients, but also could reflect the TME heterogeneity. TNS1 high fibroblasts were associated with immune exclusion. TG-101348 and Vinorelbine were identified as potential subtype-specific therapeutic agents. Besides, the application of PrSC into two immunotherapy cohorts indicated its potential value in assessing treatment response to immunotherapy. Interpretation Our study depicted the multi-dimensional characterization of ESCC, established a robust scoring tool for the prognosis assessment, highlighted the role of TNS1 high fibroblasts in TME, and identified potential drugs for clinical use. Funding A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

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Molecular characterization, biological function, tumor microenvironment association and clinical significance of m6A regulators in lung adenocarcinoma

Cited by 118 publications

References 91 publications

m6A-related lncRNAs are potential biomarkers for predicting prognoses and immune responses in patients with LUAD

m6A-related lncRNAs are potential biomarkers for predicting prognoses and immune responses in patients with LUAD

Pan-Cancer Molecular Characterization of m6A Regulators and Immunogenomic Perspective on the Tumor Microenvironment

Transcriptomics based multi-dimensional characterization and drug screen in esophageal squamous cell carcinoma

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