A N6-methyladenosine-related long noncoding RNA is a potential biomarker for predicting pancreatic cancer prognosis

Yiyang Chen, Wanbang Zhou, Yiju Gong, Xi Ou
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引用次数: 3

Abstract

Pancreatic cancer is a common malignant tumor of the digestive system, with insidious onset, difficult early diagnosis, easy metastasis, and poor prognosis. N6-methyladenosine (m6A) and long non-coding RNA (lncRNA) play important roles in the prognostic value and immunotherapy response of pancreatic adenocarcinoma (PAAD). Therefore, it is crucial to recognize m6A-related-lncRNAs in PAAD patients. In this study, m6A-related lncRNAs were obtained by coexpression analysis. Univariate, the Least Absolute Shrinkage, and Selection Operator (LASSO) and multivariate Cox regression analyses were performed to construct m6A-related lncRNA prognostic models. Kaplan–Meier analysis, principal component analysis, feature-rich annotation, and nomogram were used to analyze the accuracy of risk models. Potential drugs targeting this model are also discussed. A prognostic model based on m6A-related lncRNAs was constructed, potential drugs targeting this m6A-related lncRNAs feature were discovered, and the relationship with immunotherapy response was studied. Finally, a nomogram was established to predict survival in PAAD patients. This m6A-based lncRNAs risk prognostic model may be promising for clinical prediction of prognosis and immunotherapy response in PAAD patients.
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n6 -甲基腺苷相关长链非编码RNA是预测胰腺癌预后的潜在生物标志物
胰腺癌是一种常见的消化系统恶性肿瘤,起病隐匿,早期诊断困难,易转移,预后差。n6 -甲基腺苷(m6A)和长链非编码RNA (lncRNA)在胰腺腺癌(PAAD)的预后价值和免疫治疗应答中发挥重要作用。因此,在PAAD患者中识别m6a相关的lncrna至关重要。本研究通过共表达分析获得了m6a相关的lncrna。采用单因素、最小绝对收缩、选择算子(LASSO)和多因素Cox回归分析构建m6a相关的lncRNA预后模型。采用Kaplan-Meier分析、主成分分析、富特征标注和nomogram分析风险模型的准确性。并讨论了针对该模型的潜在药物。构建基于m6a相关lncRNAs的预后模型,发现靶向m6a相关lncRNAs特征的潜在药物,并研究其与免疫治疗应答的关系。最后,建立了一个nomogram来预测PAAD患者的生存。该基于m6的lncRNAs风险预后模型有望用于临床预测PAAD患者的预后和免疫治疗反应。
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