Suppr超能文献

鉴定一种新型免疫相关长非编码 RNA 标志物,用于预测膀胱癌的预后。

Identification of a novel immune-related long noncoding RNA signature to predict the prognosis of bladder cancer.

机构信息

Department of Urology, The 4th Affiliated Hospital of China Medical University, Shenyang, 110032, China.

Liaoning Provincial Key Laboratory of Basic Research for Bladder Diseases, Shenyang, 110000, China.

出版信息

Sci Rep. 2022 Mar 2;12(1):3444. doi: 10.1038/s41598-022-07286-1.

Abstract

Tumour immune regulation has attracted widespread attention, and long noncoding RNAs (lncRNAs) play an important role in this process. Therefore, we evaluated patient prognosis by exploring the relationship between bladder cancer (BLCA) and immune-related lncRNAs (IRlncRNAs). Transcriptome data and immune-related genes were analysed for coexpression, and then, the IRlncRNAs were analysed to determine the differentially expressed IRlncRNAs (DEIRlncRNAs) between normal and tumour samples in The Cancer Genome Atlas. The screened lncRNAs were pairwise paired and combined with clinical data, and finally, a signature was constructed by Lasso regression and Cox regression in 13 pairs of DEIRlncRNAs. According to the Akaike information criterion (AIC) values of the 1-year receiver operating characteristic curve, BLCA patients were stratified into high- or low-risk groups. The high-risk group had a worse prognosis. A comprehensive analysis showed that differences in risk scores were associated with the immune status of BLCA-infiltrated patients. The identified signature was correlated with the expression of immune checkpoint inhibitor-related molecules and sensitivity to chemotherapeutic drugs. We also identified three BLCA clusters with different immune statuses and prognoses that are also associated with immunotherapy response and drug sensitivity. In conclusion, we constructed a powerful predictive signature with high accuracy and validated its prognostic value.

摘要

肿瘤免疫调控受到广泛关注,长链非编码 RNA(lncRNA)在这一过程中发挥重要作用。因此,我们通过探讨膀胱癌(BLCA)与免疫相关 lncRNA(IRlncRNA)的关系来评估患者预后。对转录组数据和免疫相关基因进行共表达分析,然后在癌症基因组图谱中分析正常和肿瘤样本之间差异表达的免疫相关 lncRNA(DEIRlncRNA)。筛选出的 lncRNA 进行两两配对,并与临床数据相结合,最后通过 Lasso 回归和 Cox 回归在 13 对 DEIRlncRNA 中构建特征。根据 1 年接收器操作特性曲线的赤池信息量准则(AIC)值,将 BLCA 患者分层为高风险或低风险组。高风险组的预后较差。综合分析表明,风险评分的差异与 BLCA 浸润患者的免疫状态有关。鉴定的特征与免疫检查点抑制剂相关分子的表达和对化疗药物的敏感性相关。我们还鉴定了三个具有不同免疫状态和预后的 BLCA 簇,这些簇也与免疫治疗反应和药物敏感性相关。总之,我们构建了一个具有高精度和验证其预后价值的强大预测特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c993/8891323/ac1a20dd6eaa/41598_2022_7286_Fig1_HTML.jpg

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