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Quantification of m6A RNA methylation modulators pattern was a potential biomarker for prognosis and associated with tumor immune microenvironment of pancreatic adenocarcinoma

机译:M6A RNA甲基化调节剂图案的定量是潜在的生物标志物,用于预后和与胰腺癌肿瘤的肿瘤免疫微环境相关

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m6A is the most prevalent and abundant form of mRNA modifications and is closely related to tumor proliferation, differentiation, and tumorigenesis. In this study, we try to conduct an effective prediction model to investigated the function of m6A RNA methylation modulators in pancreatic adenocarcinoma and estimated the potential association between m6A RNA methylation modulators and tumor microenvironment infiltration for optimization of treatment. Expression of 28 m6A RNA methylation modulators and clinical data of patients with pancreatic adenocarcinoma and normal samples were obtained from TCGA and GTEx database. Differences in the expression of 28 m6A RNA methylation modulators between tumour (n?=?40) and healthy (n?=?167) samples were compared by Wilcoxon test. LASSO Cox regression was used to select m6A RNA methylation modulators to analyze the relationship between expression and clinical characteristics by univariate and multivariate regression. A risk score prognosis model was conducted based on the expression of select m6A RNA methylation modulators. Bioinformatics analysis was used to explore the association between the m6Ascore and the composition of infiltrating immune cells between high and low m6Ascore group by CIBERSORT algorithm. Evaluation of m6Ascore for immunotherapy was analyzed via the IPS and three immunotherapy cohort. Besides, the biological signaling pathways of the m6A RNA methylation modulators were examined by gene set enrichment analysis (GSEA). Expression of 28 m6A RNA methylation modulators were upregulated in patients with PAAD except for MTEEL3. An m6Ascore prognosis model was established, including KIAA1429, IGF2BP2, IGF2BP3, METTL3, EIF3H and LRPPRC was used to predict the prognosis of patients with PAAD, the high risk score was an independent prognostic indicator for pancreatic adenocarcinoma, and a high risk score presented a lower overall survival. In addition, m6Ascore was related with the immune cell infiltration of PAAD. Patients with a high m6Ascore had lower infiltration of Tregs and CD8 T cells but a higher resting CD4 T infiltration. Patients with a low m6Ascore displayed a low abundance of PD-1, CTLA-4 and TIGIT, however, the IPS showed no difference between the two groups. The m6Ascore applied in three immunotherapy cohort (GSE78220, TCGA-SKCM, and IMvigor210) did not exhibit a good prediction for estimating the patients’ response to immunotherapy, so it may need more researches to figure out whether the m6A modulator prognosis model would benefit the prediction of pancreatic patients’ response to immunotherapy. Modulators involved in m6A RNA methylation were associated with the development of pancreatic cancer. An m6Ascore based on the expression of IGF2BP2, IGF2BP3, KIAA1429, METTL3, EIF3H and LRPPRC is proposed as an indicator of TME status and is instrumental in predicting the prognosis of pancreatic cancer patients.
机译:M6A是最普遍和丰富的mRNA修饰形式,与肿瘤增殖,分化和肿瘤发生密切相关。在这项研究中,我们尝试进行有效的预测模型,以研究M6A RNA甲基化调节剂在胰腺腺癌中的功能,并估计M6A RNA甲基化调节剂与肿瘤微环境浸润的潜在关联以进行治疗优化。从TCGA和GTEX数据库获得28M6A RNA甲基化调节剂和胰腺腺癌患者的临床资料和正常样品的临床资料。通过Wilcoxon试验比较了肿瘤(n≤=Δ40)和健康(n≤=Δ40)和健康(n≤=α167)样品的表达的差异。套索COX回归用于选择M6A RNA甲基化调节剂,分析单变量和多元回归的表达和临床特征之间的关系。基于SELECT M6A RNA甲基化调节剂的表达进行风险评分预后模型。生物信息学分析用于通过Cibersort算法探讨M6Ascore与低M6Ascore基团之间的浸润免疫细胞组成之间的关联。通过IP和三种免疫治疗队列分析了对IM6Ascura治疗的M6Ascore评估。此外,通过基因设定富集分析(GSEA)检查M6A RNA甲基化调节剂的生物信号传导途径。除MTEEL3外,Paad患者上调了28M6A RNA甲基化调节剂的表达。建立了M6Ascome预后模型,包括KiaA1429,IGF2BP2,IGF2BP3,MetT13,EIF3H和LRPPRC用于预测Paad患者的预后,高风险评分是胰腺癌的独立预后指标,并且呈现高风险评分较低的整体生存。此外,M6Ascore与Paad的免疫细胞浸润有关。患有高M6Ascore的患者具有降低的Tregs和CD8 T细胞的渗透,但静止的CD4 T渗透较高。患有低M6Ascore的患者显示出低丰度的PD-1,CTLA-4和TIGIT,然而,IPS在两组之间没有差异。在三种免疫疗法队列(GSE78220,TCGA-SKCM和IMVigor210中,施用M6Ascore并没有表现出良好的预测,估计患者对免疫疗法的反应,因此可能需要更多的研究来弄清楚M6A调节剂预后模型是否有益于胰腺患者对免疫疗法反应的预测。参与M6A RNA甲基化的调节剂与胰腺癌的发育有关。提出了基于IGF2BP2,IGF2BP3,KIAA1429,MetT13,EIF3H和LRPPR的表达的M6Ascore作为TME状态的指标,并且有助于预测胰腺癌患者的预后。

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