Duan Ling, Xia Yang, Li Chunmei, Lan Ning, Hou Xiaoming
Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, China.
The First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
Front Genet. 2022 Aug 11;13:906900. doi: 10.3389/fgene.2022.906900. eCollection 2022.
To establish a prediction model based on autophagy-related lncRNAs and investigate the functional enrichment of autophagy-related lncRNAs in colorectal cancer. TCGA database was used to extract the transcriptome data and clinical features of colorectal cancer patients. HADb was used to obtain autophagy-related genes. Pearson correlation analysis was performed to identify autophagy-related lncRNAs. The autophagy-related lncRNAs with prognostic values were selected. Based on the selected lncRNAs, the risk score model and nomogram were constructed, respectively. Calibration curve, concordance index, and ROC curve were performed to evaluate the predictive efficacy of the prediction model. GSEA was performed to figure out the functional enrichment of autophagy-related lncRNAs. A total of 13413 lncRNAs and 938 autophagy-related genes were obtained. A total of 709 autophagy-related genes were identified in colon cancer tissues, and 11 autophagy-related lncRNAs (AL138756.1, LINC01063, CD27-AS1, LINC00957, EIF3J-DT, LINC02474, SNHG16, AC105219.1, AC068580.3, LINC02381, and LINC01011) were finally selected and set as prognosis-related lncRNAs. According to the risk score, patients were divided into the high-risk and low-risk groups, respectively. The survival K-M (Kaplan-Meier) curve showed the low-risk group exhibits better overall survival than the high-risk group. The AUCs under the ROC curves were 0.72, 0.814, and 0.83 at 1, 3, and 5 years, respectively. The C-index (concordance index) of the model was 0.814. The calibration curves at 1, 3, and 5 years showed the predicting values were consistent with the actual values. Functional enrichment analysis showed that autophagy-related lncRNAs were enriched in several pathways. A total of 11 specific autophagy-related lncRNAs were identified to own prognostic value in colon cancer. The predicting model based on the lncRNAs and clinical features can effectively predict the OS. Furthermore, functional enrichment analysis showed that autophagy-related genes were enriched in various biological pathways.
建立基于自噬相关长链非编码RNA的预测模型，并研究自噬相关长链非编码RNA在结直肠癌中的功能富集情况。利用TCGA数据库提取结直肠癌患者的转录组数据和临床特征。使用HADb获取自噬相关基因。进行Pearson相关性分析以鉴定自噬相关长链非编码RNA。选择具有预后价值的自噬相关长链非编码RNA。基于所选的长链非编码RNA，分别构建风险评分模型和列线图。绘制校准曲线、一致性指数和ROC曲线以评估预测模型的预测效能。进行基因集富集分析（GSEA）以明确自噬相关长链非编码RNA的功能富集情况。共获得13413个长链非编码RNA和938个自噬相关基因。在结肠癌组织中鉴定出709个自噬相关基因，最终选择11个自噬相关长链非编码RNA（AL138756.1、LINC01063、CD27-AS1、LINC00957、EIF3J-DT、LINC02474、SNHG16、AC105219.1、AC068580.3、LINC02381和LINC01011）并将其设定为预后相关长链非编码RNA。根据风险评分，将患者分别分为高风险组和低风险组。生存K-M（Kaplan-Meier）曲线显示低风险组的总生存期优于高风险组。ROC曲线下1年、3年和5年的AUC分别为0.72、0.814和0.83。模型的C指数（一致性指数）为0.814。1年、3年和5年的校准曲线显示预测值与实际值一致。功能富集分析表明自噬相关长链非编码RNA在多个通路中富集。共鉴定出11个特定的自噬相关长链非编码RNA在结肠癌中具有预后价值。基于长链非编码RNA和临床特征的预测模型能够有效预测总生存期。此外，功能富集分析表明自噬相关基因在各种生物学通路中富集。
