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Construction and Validation of an m6A RNA Methylation Regulators-Based Prognostic Signature for Esophageal Cancer.

ABSTRACT: Purpose:N6-methyladenosine (m6A) is reported to play a critical role in cancer through various mechanisms. We aimed to construct and validate an m6A RNA methylation regulators-based prognostic signature for Esophageal cancer (ESCA). Materials and Methods:The RNA sequencing transcriptome data of 13 m6A RNA methylation regulators as well as clinical data were obtained from The Cancer Genome Atlas (TCGA) ESCA database. The differential expression of the regulators between ESCA tissues and normal tissues was assessed. Consensus clustering was conducted to explore the different ESCA clusters based on the expression of these regulators. LASSO Cox regression analysis was used to generate a prognostic signature based on m6A RNA methylation regulators expression. Results:Eight regulators (KIAA1429, HNRNPC, RBM15, METTL3, WTAP, YTHDF1, YTHDC1, and YTHDF2) were found to be significantly upregulated in ESCA tissues. Significant differences of survival rate and clinicopathological features were found between the two clusters. A prognostic signature, which consists of HNRNPC and ALKBH5, was constructed based on the TCGA ESCA cohort, which can serve as an independent prognostic predictor. The results of bioinformatics analysis were further successfully validated in the clinical ESCA cohort by qRT-PCR and immunohistochemistry staining. Conclusion:Our study constructed and validated an m6A RNA methylation regulators-based prognostic signature. This might provide important information for developing diagnostic and therapeutic strategies.

SUBMITTER: Xu LC

PROVIDER: S-EPMC7352013 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Construction and Validation of an m6A RNA Methylation Regulators-Based Prognostic Signature for Esophageal Cancer.

Xu Li-Chao LC Pan Jing-Xin JX Pan Hong-da HD

Cancer management and research 20200706

<h4>Purpose</h4>N6-methyladenosine (m6A) is reported to play a critical role in cancer through various mechanisms. We aimed to construct and validate an m6A RNA methylation regulators-based prognostic signature for Esophageal cancer (ESCA).<h4>Materials and methods</h4>The RNA sequencing transcriptome data of 13 m6A RNA methylation regulators as well as clinical data were obtained from The Cancer Genome Atlas (TCGA) ESCA database. The differential expression of the regulators between ESCA tissue ...[more]

PMID: 32753956

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Project description:BackgroundEpigenetic reprogramming reportedly has a crucial role in prostate cancer (PCa) progression. RNA modification is a hot topic in epigenetics, and N6-methyladenosine (m6A) accounts for approximately 60% of RNA chemical modifications. The aim of this study was to evaluate the m6A modification patterns in PCa patients and construct a risk prediction model using m6A RNA regulators.Materials and methodsAnalyses were based on the levels of 25 m6A regulators in The Cancer Genome Atlas (TCGA). Differentially expressed gene (DEG) and survival analyses were performed according to TCGA-PRAD clinicopathologic and follow-up information. To detect the influences of m6A regulators and their DEGs, consensus clustering analysis was performed, and tumor mutational burden (TMB) estimation and tumor microenvironment (TME) cell infiltration were assessed. mRNA levels of representative genes were verified using clinical PCa data.ResultsDiverse expression patterns of m6A regulators between tumor and normal (TN) tissues were detected regarding Gleason score (GS), pathological T stage (pT), TP53 mutation, and survival comparisons, with HNRNPA2B1 and IGFBP3 being intersecting genes. HNRNPA2B1 was upregulated in advanced stages (GS > 7, pT3, HR > 1, and TP53 mutation), as verified using clinical PCa tissue. Three distinct m6A modification patterns were identified through consensus clustering analysis, but no significant difference was found among these groups in recurrence-free survival (RFS) analysis. Six DEGs of m6A clusters (m6Aclusters) were screened through univariate Cox regression analysis. MMAB and PAIAP2 were intersecting genes for the five clinical factors. MMAB, which was upregulated in PCa compared with TN, was verified using clinical PCa samples. Three distinct subgroups were established according to the 6 DEGs. Cluster A involved the most advanced stages and had the poorest RFS. The m6A score (m6Ascore) was calculated based on the 6 genes, and the low m6Ascore group showed poor RFS with a negative association with infiltration for 16 of 23 immune-related cells.ConclusionWe screened DEGs of m6Aclusters and identified 6 genes (BAIAP2, TEX264, MMAB, JAGN1, TIMM8AP1, and IMP3), with which we constructed a highly predictive model with prognostic value by dividing TCGA-PRAD into three distinct subgroups and performing m6Ascore analysis. This study helps to elucidate the integral effects of m6A modification patterns on PCa progression.

Dataset Information

Construction and Validation of an m6A RNA Methylation Regulators-Based Prognostic Signature for Esophageal Cancer.

Publications

Construction and Validation of an m6A RNA Methylation Regulators-Based Prognostic Signature for Esophageal Cancer.

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