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一种用于浆液性卵巢癌患者风险分类和预后预测的铂耐药相关长链非编码RNA特征

A Platinum Resistance-Related lncRNA Signature for Risk Classification and Prognosis Prediction in Patients with Serous Ovarian Cancer.

作者信息

Zhu Yan, Chen Jiongyu, Zhou Li, Zhang Lina, Liu Yuxin, Zhuang Yixuan, Peng Lin, Huang Yi-Teng

机构信息

Health Care Center, The First Affiliated Hospital of Shantou University Medical College, Shantou 515041, Guangdong, China.

Medical Laboratory, Shenzhen Luohu People's Hospital, Shenzhen 518001, Guangdong, China.

出版信息

J Oncol. 2022 Nov 9;2022:7625138. doi: 10.1155/2022/7625138. eCollection 2022.

Abstract

Accurate risk stratification for patients with serous ovarian cancer (SOC) is pivotal for treatment decisions. In this study, we identified a lncRNA-based signature for predicting platinum resistance and prognosis stratification for SOC patients. We analyzed the RNA-sequencing data and the relevant clinical information of 295 SOC samples obtained from The Cancer Genome Atlas (TCGA) database and 180 normal ovarian tissues from the Genotype-Tissue Expression (GTEx) database. A total of 284 differentially expressed lncRNAs were screened out between platinum-sensitive and platinum-resistant groups by univariate Cox regression analysis. Then, a signature consisting of eight prognostic lncRNAs was used to construct a lncRNA score model by least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis. The ROC analysis showed that this signature had a good predictive performance for chemotherapy response in the training set (AUC = 0.8524) and the testing and whole sets with 0.8142 and 0.8393 of AUC, respectively. Dichotomized by the risk score of lncRNAs (lncScore), the high-risk patients showed significantly shorter progression-free survival (PFS) and overall survival (OS). Based on the final Cox model, a nomogram comprising the 8-lncRNA signature and 3 clinicopathological risk factors was then established for clinical application to predict the 1, 2, and 3-year PFS of SOC patients. The gene set enrichment analysis (GSEA) revealed that genes in the high-risk group were active in ATP synthesis, coupled electron transport, and mitochondrial respiratory chain complex assembly. Overall, our findings demonstrated the potential clinical significance of the 8-lncRNA-based classifier as a novel biomarker for outcome prediction and therapy decisions in SOC patients with platinum treatment.

摘要

浆液性卵巢癌(SOC)患者的准确风险分层对于治疗决策至关重要。在本研究中,我们确定了一种基于长链非编码RNA(lncRNA)的特征,用于预测SOC患者的铂耐药性和预后分层。我们分析了从癌症基因组图谱(TCGA)数据库获得的295个SOC样本以及来自基因型-组织表达(GTEx)数据库的180个正常卵巢组织的RNA测序数据和相关临床信息。通过单变量Cox回归分析,在铂敏感组和铂耐药组之间共筛选出284个差异表达的lncRNA。然后,通过最小绝对收缩和选择算子(LASSO)回归及多变量Cox回归分析,使用由8个预后lncRNA组成的特征构建lncRNA评分模型。受试者工作特征(ROC)分析表明,该特征在训练集(AUC = 0.8524)、测试集(AUC = 0.8142)和全集(AUC = 0.8393)中对化疗反应具有良好的预测性能。根据lncRNA的风险评分(lncScore)进行二分法分析,高危患者的无进展生存期(PFS)和总生存期(OS)显著缩短。基于最终的Cox模型,建立了一个包含8-lncRNA特征和3个临床病理风险因素的列线图,用于临床应用以预测SOC患者的1年、2年和3年PFS。基因集富集分析(GSEA)显示,高危组中的基因在ATP合成、偶联电子传递和线粒体呼吸链复合物组装中活跃。总体而言,我们的研究结果证明了基于8-lncRNA的分类器作为一种新型生物标志物在铂治疗的SOC患者结局预测和治疗决策中的潜在临床意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/276a/10202609/32bd3238c83a/JO2022-7625138.001.jpg

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