|
摘要：
|
|
摘要：目的 基于生物信息学方法分析肝细胞癌（hepatocellular carcinoma，HCC）自
噬相关长链非编码RNA（long noncoding RNA，lncRNA）生物标志物，用于评估HCC
的临床预后及指导治疗。方法 从TCGA数据库中下载HCC全转录组数据以及对应的
临床数据，在人类自噬数据库（http://www.autophagy.lu/）下载自噬相关基因，通过
共表达分析找到自噬相关lncRNA。然后，根据K-M分析及Cox分析构建临床预后模
型预测HCC患者生存风险及临床相关性分析。最后，针对这些自噬相关lncRNA进行
GSEA功能富集分析和临床样本验证。结果 共筛选出919条自噬相关lncRNA，其中
AC009403.1、AC099850.3、AL365203.2、AL117336.3和AC015908.3具有临床预后价
值且能预测HCC患者生存风险。根据构建的风险模型将高表达AC015908.3患者归为
低风险患者，AC099850.3，AL117336.3和AL365203.2归为高风险患者，独立预后分
析也验证了构建的预后模型能够预后肝癌患者的生存风险。GSEA功能富集分析发现
这5条自噬相关lncRNA主要富集在补体凝血级联、脂肪酸代谢、药物代谢与细胞色素
P450、视黄醇代谢、氨基酸代谢、嘧啶代谢、剪接体、嘌呤代谢、碱基切除修复和
细胞周期等通路。PCR结果显示，相对于正常肝脏组织，AC009403.1（6.36 ± 2.44 vs
12.67 ± 3.58；t = 11.21，P ＜ 0.001）、AC099850.3（9.48 ± 3.08 vs 16.11 ± 4.52；t =
9.45，P ＜ 0.001）、AL365203.2（5.89 ± 2.33 vs 13.05 ± 4.19；t = 10.45，P ＜ 0.001）、
AL117336.3（5.44 ± 2.60 vs 16.41 ± 6.90；t = 9.28，P ＜ 0.001）在HCC组织中高表达，
AC015908.3在HCC组织低表达（12.43 ± 4.56 vs 6.03 ± 1.94；t = 9.13，P ＜ 0.001）。结
论 5条自噬相关lncRNA构建的风险预测模型能够预测HCC患者的临床预后，且通过生
物代谢和细胞增殖等生物学过程参与HCC发生发展。
|
|
Abstract: Objective To analyze long-chain non-coding RNA (lncRNA) biomarkers related
to hepatocellular carcinoma (HCC) autophagy by bioinformatics methods for evaluating the
clinical prognosis of HCC and guiding treatment. Methods HCC transcriptome data and
corresponding clinical data were downloaded from TCGA database and autophagy-related
genes were downloaded from the human autophagy database (http://www.autophagy.lu/),
co-expression analysis was used to find autophagy-related lncRNA. Then, based on K-M
analysis and Cox analysis, a clinical prognosis model was constructed to predict the survival
risk and clinical correlation analysis of patients with HCC. Finally, GSEA functional
enrichment analysis and clinical sample verification were performed on these autophagyrelated lncRNA. Results A total of 919 autophagy-related lncRNAs were selected, among which AC009403.1, AC099850.3, AL365203.2, AL117336.3 and AC015908.3 have clinical
prognostic value and can predict the survival risk of patients with HCC. According to the
constructed model, patients with high expression of AC015908.3 were classified as low-risk
group, and patients with high expression of AC099850.3, AL117336.3 and AL365203.2 were
classified as high-risk group. Independent prognostic analysis also verified that the prognostic
model we constructed can prognose the survival risk of patients with HCC. GSEA functional
enrichment analysis showed that these 5 autophagy-related lncRNAs were mainly enriched in
the complement coagulation cascade, fatty acid metabolism, drug metabolism and cytochrome
P450, retinol metabolism, amino acid metabolism, pyrimidine metabolism, spliceosome, purine
metabolism, alkali Basal excision repair and cell cycle and other pathways. PCR results showed
that compared with normal liver tissue, AC009403.1 (6.36 ± 2.44 vs 12.67 ± 3.58; t = 11.21, P ＜
0.001), AC099850.3 (9.48 ± 3.08 vs 16.11 ± 4.52; t = 9.45, P ＜ 0.001), AL365203.2 (5.89 ± 2.33
vs 13.05 ± 4.19; t = 10.45, P ＜ 0.001), AL117336.3 (5.44 ± 2.60 vs 16.41 ± 6.90; t = 9.28, P ＜ 0.001)
were higher expressed in liver cancer tissues, and AC015908.3 was lower expressed in liver
cancer tissues (12.43 ± 4.56 vs 6.03 ± 1.94; t = 9.13, P < 0.001). Conclusions The prediction
models constructed from the five autophagy-related lncRNA can predict the clinical prognosis
of patients with HCC and participate in the development of HCC through biological processes
such as biological metabolism and cell proliferation.
|
|
基金项目：
|
|
|
|
作者简介：
|
|
|
|
参考文献：
|
|
|
|
服务与反馈：
|
|
【文章下载】【加入收藏】
|
|
|
|