摘要
      LncRNAs参与自噬调节前列腺癌症（PCA）的发生和发展。因此，它敦促探索前列腺癌中更重要的AR lncRNA。PCa的mRNA数据和临床信息来自TCGA数据库，ARGs来自HADb。通过DE ARGs和lncRNA的相关性分析鉴定AR lncRNA。使用单变量Cox回归、LASSO回归和多变量Cox回归来确定预后AR-lncRNA特征，并构建风险模型。GESA用于高风险和低风险评分组之间的生物功能分析。构建了列线图，并用于预测前列腺癌患者的生存率。使用校准曲线来确定预测模型的准确性。通过相关性分析构建AR相关的ceRNA网络。通过qRT-PCR检测6种AR相关lncRNA的表达。从前列腺癌和正常组织中筛选出222个ARGs和385个AR-lncRNA，并鉴定出17个AR-lnc RNA作为前列腺癌的预后标志。根据预后标志的表达，计算风险评分，并将前列腺癌样本分为高风险评分组和低风险评分组。还检查了预后标志的生物学功能和预测价值。最后，基于每个ARG与其预后标志之间的相关性，基于6个AR-lncRNA、17个miRNA和12个ARG构建了AR-lncRNA-miRNA-mRNA调节网络的三个模块。我们发现，与前列腺增生组织相比，前列腺癌中的AC012085.2、UBXN10-AS1、LINC00261下调，而AP004608.1、AC104667.2、AC008610.1上调。我们的发现为前列腺癌提供了潜在的AR lncRNA预后标志。
ABSTRACT
LncRNAs involve in the autophagy to regulate prostate cancer (PCA) initiation and progression. Therefore, it urges to explore more significant AR-lncRNAs in PCa. mRNA data and clinical information of PCa were achieved from TCGA database, and ARGs were obtained from the HADb. AR-lncRNAs were identified by correlation analysis of DE ARGs and lncRNAs. Univariate Cox regression, LASSO regression, and multivariate Cox regression were used to identify the prognostic AR-lncRNA signature and constructed a risk model. GESA was used to biological function analysis between high- and low-risk score group. A nomogram was constructed and used to predicate the survival of PCa patients. A calibration curve was used to determine the accuracy of the predication model. AR-related ceRNA network was constructed by correlation analysis. Expression of six AR-related lncRNAs were detected by qRT-PCR. 222 ARGs and 385 AR-lncRNAs were screened from PCa and normal tissues, and 17 AR-lncRNAs were identified as prognostic signature for PCa. Based on the expression of prognostic signature, a risk score was calculated, and PCa samples were distributed into high- and low-risk score groups. The biological function and predicated value of the prognostic signature were also examined. Finally, based on the correlation between each ARG and its prognostic signature, three modules of AR-lncRNA-miRNA-mRNA regulatory networks were constructed based on 6 AR-lncRNAs, 17 miRNAs, and 12 ARGs. And we found that AC012085.2, UBXN10-AS1, LINC00261 downregulated, whereas AP004608.1, AC104667.2, AC008610.1 upregulated in PCa compared with BPH tissues. Our finding supplied the potential AR-lncRNAs prognostic signature for PCa.

https://www.tandfonline.com/doi/abs/10.1080/15384101.2022.2065149