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首页> 外文期刊>BMC Medical Informatics and Decision Making >A prognostic index based on a fourteen long non-coding RNA signature to predict the recurrence-free survival for muscle-invasive bladder cancer patients
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A prognostic index based on a fourteen long non-coding RNA signature to predict the recurrence-free survival for muscle-invasive bladder cancer patients

机译：基于四个长期非编码RNA签名的预后指数，以预测肌肉侵入性膀胱癌患者的无复发存活

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摘要

Bladder cancer (BC) is regarded as one of the most fatal cancer around the world. Nevertheless, there still lack of sufficient markers to predict the prognosis of BC patients. Herein, we aim to establish a prognosis predicting signature based on long-noncoding RNA (lncRNA) for the invasive BC patients. The lncRNA expression profile was downloaded from The Cancer Genome Atlas (TCGA) database, along with the correlated clinicopathological information. The univariate Cox regression test was employed to screen out the recurrence-free survival (RFS)-related lncRNAs. Then, the LASSO method was conducted to construct the signature based on these RFS-related lncRNA candidates. Genes correlated with these fourteen lncRNAs were extracted from the mRNA expression profile, with the Pearson correlation coefficient??0.60 or????0.40. Subsequently, the Proteomap pathway enrichment analyses were conducted to classify the function of these correlated genes. Furthermore, the multivariate analyses were executed to reveal the independent role of the proposed signature with the clinicopathological features. We established an lncRNA-based RFS predicting signature by the LASSO Cox regression test, and proved its usage and stability on both the training and validation cohorts by the Kaplan-Meier and receiver operating characteristic (ROC) curves. Notably, the multivariate Cox regression analysis found that our classifier was an independent indicator for muscle-invasive BC patients rather than sex, age and tumor grade, with higher predictive value than the existing ones. Besides, we did the pathway analyses for these genes that highly correlated with the proposed fourteen lncRNAs, as well as the differentially expressed genes (DEGs) derived from the high-risk vs. low-risk groups, and the recurrence vs. non-recurrence groups, respectively. Notably, these results were consistent, and these genes were mostly enriched in the transcription factors, G protein-coupled receptors, MAPK signaling pathways, which were proved significantly associated with tumor progression and drug resistance. Our results suggested that the fourteen-lncRNA-based RFS predicting signature is an independent indicator for BC patients. Further prospective studies with more samples are needed to verify our findings.
机译：膀胱癌（BC）被认为是世界各地最致命的癌症之一。然而，仍然缺乏足够的标志物来预测BC患者的预后。在此，我们的目标是基于侵袭性BC患者的长期性RNA（LNCRNA）建立预测预测签名。从癌症基因组Atlas（TCGA）数据库以及相关的临床病理信息，下载LNCRNA表达谱。使用单变量的Cox回归试验以筛选出可复制的存活率（RFS）相关的LNCRNA。然后，进行套索方法以基于这些RFS相关的LNCRNA候选构建签名。从mRNA表达谱系中提取与这十四克朗的基因相关，Pearson相关系数θ> 0.60或Δ

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