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构建并验证一种与铜死亡相关的长链非编码RNA特征作为结肠癌的新型稳健预后模型。

Construction and validation of a cuproptosis-related lncRNA signature as a novel and robust prognostic model for colon adenocarcinoma.

作者信息

Xu Miaorong, Mu Jiayi, Wang Jiaojiao, Zhou Qin, Wang Jianwei

机构信息

Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Department of Colorectal Surgery, 4th Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, China.

出版信息

Front Oncol. 2022 Jul 28;12:961213. doi: 10.3389/fonc.2022.961213. eCollection 2022.

DOI:10.3389/fonc.2022.961213
PMID:35965536
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9367690/
Abstract

BACKGROUND

Cuproptosis, a newly identified form of programmed cell death, is thought to play a role in tumorigenesis. Long non-coding RNAs (lncRNAs) are reported to be associated with tumor progression and prognosis in colon adenocarcinoma (COAD). However, the role and prognostic value of cuproptosis-related lncRNAs in COAD remains unknown. This study is devoted to constructing and validating a cuproptosis-related lncRNA signature that can predict COAD patient outcomes using bioinformatics methods.

METHODS

The COAD mRNA and lncRNA expression profiles and corresponding clinical data were downloaded from The Cancer Genome Atlas (TCGA) database and 2,567 cuproptosis-related lncRNAs were obtained. A 10 cuproptosis-related-lncRNA prognostic signature was then constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression model and patients were divided into high- and low-risk groups. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve, and a nomogram were employed to evaluate the predictive power of the signature. The immune characteristics and drug sensitivity were also investigated based on the signature. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to verify the risk model. experiments were conducted to validate the expression of the ten lncRNAs during cuproptosis.

RESULTS

The high-risk group was associated with shorter overall survival (OS) time in COAD patients (p<0.001). Multivariate Cox regression indicated that a high-risk score was an independent risk factor for poor prognosis (p<0.001). ROC curve analysis was performed to confirm the validity of the signature (area under the curve (AUC) at 3 years: 0.879). Gene Ontology (GO) enrichment analysis revealed that the signature was highly correlated with the immune response in biological processes. The immune function, the score of the immune cells, and the expression of immune checkpoints were significantly different between the two risk groups. Three drugs, LAQ824, FH535, YM155, were found to be more sensitive in the high-risk group. Finally, the expression levels of the ten lncRNAs comprising the signature were tested by qRT-PCR.

CONCLUSION

A ten-cuproptosis-related lncRNA signature was constructed that provided promising insights into personalized prognosis and drug selection among COAD patients.

摘要

背景

铜死亡是一种新发现的程序性细胞死亡形式,被认为在肿瘤发生中起作用。据报道,长链非编码RNA(lncRNA)与结肠腺癌(COAD)的肿瘤进展和预后相关。然而,铜死亡相关lncRNA在COAD中的作用和预后价值仍不清楚。本研究致力于使用生物信息学方法构建和验证一种可预测COAD患者预后的铜死亡相关lncRNA特征。

方法

从癌症基因组图谱(TCGA)数据库下载COAD的mRNA和lncRNA表达谱以及相应的临床数据,获得2567个铜死亡相关lncRNA。然后使用最小绝对收缩和选择算子(LASSO)算法和Cox回归模型构建一个包含10个铜死亡相关lncRNA的预后特征,并将患者分为高风险和低风险组。采用Kaplan-Meier分析、受试者工作特征(ROC)曲线和列线图来评估该特征的预测能力。还基于该特征研究了免疫特征和药物敏感性。进行定量逆转录聚合酶链反应(qRT-PCR)以验证风险模型。进行实验以验证这10种lncRNA在铜死亡过程中的表达。

结果

高风险组与COAD患者较短的总生存期(OS)相关(p<0.001)。多变量Cox回归表明,高风险评分是预后不良的独立危险因素(p<0.001)。进行ROC曲线分析以确认该特征的有效性(3年时曲线下面积(AUC):0.879)。基因本体(GO)富集分析表明,该特征在生物学过程中与免疫反应高度相关。两个风险组之间的免疫功能、免疫细胞评分和免疫检查点的表达存在显著差异。发现三种药物LAQ824、FH535、YM155在高风险组中更敏感。最后,通过qRT-PCR检测了构成该特征的10种lncRNA的表达水平。

结论

构建了一个包含10个铜死亡相关lncRNA的特征,为COAD患者的个性化预后和药物选择提供了有前景的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99bb/9367690/2642fdef963f/fonc-12-961213-g009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99bb/9367690/f65db86391ac/fonc-12-961213-g007.jpg
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