Suppr超能文献

用于前列腺癌早期生化复发预后价值的N6-甲基腺嘌呤长链非编码RNA特征的构建与验证

Construction and validation of N6-methyladenosine long non-coding RNAs signature of prognostic value for early biochemical recurrence of prostate cancer.

作者信息

Liu Jingchao, Zhang Wei, Wang Jiawen, Lv Zhengtong, Xia Haoran, Zhang Zhipeng, Zhang Yaoguang, Wang Jianye

机构信息

Department of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No. 1 DaHua Road, Dong Dan, Beijing, 100730, China.

Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, 9 DongDan SANTIAO, Beijing, 100730, China.

出版信息

J Cancer Res Clin Oncol. 2023 May;149(5):1969-1983. doi: 10.1007/s00432-022-04040-y. Epub 2022 Jun 22.

Abstract

PURPOSE

Early biochemical recurrence (eBCR) indicated a high risk for potential recurrence and metastasis in prostate cancer. The N6-methyladenosine (m6A) methylation modification played an important role in prostate cancer progression. This study aimed to develop a m6A lncRNA signature to accurately predict eBCR in prostate cancer.

METHODS

Pearson correlation analysis was first conducted to explore m6A lncRNAs and univariate Cox regression analysis was further performed to identify m6A lncRNAs of prognostic roles for predicting eBCR in prostate cancer. The m6A lncRNA signature was constructed by least absolute shrinkage and selection operator analysis (LASSO) in training cohort and further validated in test cohort. Furthermore, half maximal inhibitory concentration (IC50) values were utilized to explore potential effective drugs for high-risk group in this study.

RESULTS

Five hundred and thirty-eighth m6A lncRNAs were searched out through Pearson correlation analysis and 25 out of 538 m6A lncRNAs were identified to pose prediction roles for eBCR in prostate cancers. An m6A lncRNA signature including 5 lncRNAs was successfully built in training cohort. The high-risk group derived from m6A lncRNA signature could efficiently predict eBCR occurrence in both training (p < 0.001) and test cohort (p = 0.002). ROC analysis also confirmed that lncRNA signature in this study posed more accurate prediction roles for eBCR occurrence when compared with PSA, TNM stages and Gleason scores. Drug sensitivity analysis further discovered that various drugs could be potentially utilized to treat high-risk samples in this study.

CONCLUSIONS

The m6A lncRNA signature in this study could be utilized to efficiently predict eBCR occurrence, various clinical characteristic and immune microenvironment for prostate cancer.

摘要

目的

早期生化复发(eBCR)提示前列腺癌存在潜在复发和转移的高风险。N6-甲基腺苷(m6A)甲基化修饰在前列腺癌进展中起重要作用。本研究旨在开发一种m6A长链非编码RNA(lncRNA)特征,以准确预测前列腺癌的eBCR。

方法

首先进行Pearson相关性分析以探索m6A lncRNAs,进一步进行单变量Cox回归分析以鉴定对预测前列腺癌eBCR具有预后作用的m6A lncRNAs。通过最小绝对收缩和选择算子分析(LASSO)在训练队列中构建m6A lncRNA特征,并在测试队列中进一步验证。此外,利用半数最大抑制浓度(IC50)值探索本研究中高危组的潜在有效药物。

结果

通过Pearson相关性分析筛选出538个m6A lncRNAs,其中25个被鉴定对前列腺癌的eBCR具有预测作用。在训练队列中成功构建了包含5个lncRNAs的m6A lncRNA特征。源自m6A lncRNA特征的高危组能够有效预测训练队列(p < 0.001)和测试队列(p = 0.002)中eBCR的发生。ROC分析还证实,与前列腺特异性抗原(PSA)、TNM分期和Gleason评分相比,本研究中的lncRNA特征对eBCR的发生具有更准确的预测作用。药物敏感性分析进一步发现,本研究中的多种药物可潜在用于治疗高危样本。

结论

本研究中的m6A lncRNA特征可用于有效预测前列腺癌eBCR的发生、各种临床特征和免疫微环境。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验