He Qinglian, Li Ziqi, Yin Jinbao, Li Yuling, Yin Yuting, Lei Xue, Zhu Wei
Department of Pathology, Guangdong Medical University, Dongguan, China.
Department of Pathology, Dongguan People's Hospital, Southern Medical University, Dongguan, China.
Front Oncol. 2021 Apr 15;11:566539. doi: 10.3389/fonc.2021.566539. eCollection 2021.
Colorectal cancer (CRC) is a common malignant solid tumor with an extremely low survival rate after relapse. Previous investigations have shown that autophagy possesses a crucial function in tumors. However, there is no consensus on the value of autophagy-associated genes in predicting the prognosis of CRC patients. This work screens autophagy-related markers and signaling pathways that may participate in the development of CRC, and establishes a prognostic model of CRC based on autophagy-associated genes.
Gene transcripts from the TCGA database and autophagy-associated gene data from the GeneCards database were used to obtain expression levels of autophagy-associated genes, followed by Wilcox tests to screen for autophagy-related differentially expressed genes. Then, 11 key autophagy-associated genes were identified through univariate and multivariate Cox proportional hazard regression analysis and used to establish prognostic models. Additionally, immunohistochemical and CRC cell line data were used to evaluate the results of our three autophagy-associated genes EPHB2, NOL3, and SNAI1 in TCGA. Based on the multivariate Cox analysis, risk scores were calculated and used to classify samples into high-risk and low-risk groups. Kaplan-Meier survival analysis, risk profiling, and independent prognosis analysis were carried out. Receiver operating characteristic analysis was performed to estimate the specificity and sensitivity of the prognostic model. Finally, GSEA, GO, and KEGG analysis were performed to identify the relevant signaling pathways.
A total of 301 autophagy-related genes were differentially expressed in CRC. The areas under the 1-year, 3-year, and 5-year receiver operating characteristic curves of the autophagy-based prognostic model for CRC were 0.764, 0.751, and 0.729, respectively. GSEA analysis of the model showed significant enrichment in several tumor-relevant pathways and cellular protective biological processes. The expression of EPHB2, IL-13, MAP2, RPN2, and TRAF5 was correlated with microsatellite instability (MSI), while the expression of IL-13, RPN2, and TRAF5 was related to tumor mutation burden (TMB). GO analysis showed that the 11 target autophagy genes were chiefly enriched in mRNA processing, RNA splicing, and regulation of the mRNA metabolic process. KEGG analysis showed enrichment mainly in spliceosomes. We constructed a prognostic risk assessment model based on 11 autophagy-related genes in CRC.
A prognostic risk assessment model based on 11 autophagy-associated genes was constructed in CRC. The new model suggests directions and ideas for evaluating prognosis and provides guidance to choose better treatment strategies for CRC.
结直肠癌（CRC）是一种常见的恶性实体肿瘤，复发后的生存率极低。先前的研究表明，自噬在肿瘤中具有关键作用。然而，关于自噬相关基因在预测CRC患者预后方面的价值尚无定论。本研究筛选了可能参与CRC发生发展的自噬相关标志物和信号通路，并基于自噬相关基因建立了CRC的预后模型。
利用来自TCGA数据库的基因转录本和来自GeneCards数据库的自噬相关基因数据，获取自噬相关基因的表达水平，随后通过Wilcox检验筛选出自噬相关的差异表达基因。然后，通过单变量和多变量Cox比例风险回归分析确定了11个关键的自噬相关基因，并用于建立预后模型。此外，利用免疫组织化学和CRC细胞系数据评估了我们在TCGA中发现的3个自噬相关基因EPHB2、NOL3和SNAI1的结果。基于多变量Cox分析，计算风险评分并将样本分为高风险和低风险组。进行了Kaplan-Meier生存分析、风险评估和独立预后分析。进行了受试者工作特征分析以评估预后模型的特异性和敏感性。最后，进行了基因集富集分析（GSEA）、基因本体（GO）和京都基因与基因组百科全书（KEGG）分析以确定相关信号通路。
共有301个自噬相关基因在CRC中差异表达。基于自噬的CRC预后模型在1年、3年和5年受试者工作特征曲线下的面积分别为0.764、0.751和0.729。对该模型的GSEA分析显示，在几个与肿瘤相关的通路和细胞保护生物学过程中显著富集。EPHB2、IL-13、MAP2、RPN2和TRAF5的表达与微卫星不稳定性（MSI）相关，而IL-13、RPN2和TRAF5的表达与肿瘤突变负荷（TMB）相关。GO分析表明，11个目标自噬基因主要富集在mRNA加工、RNA剪接和mRNA代谢过程的调控中。KEGG分析显示主要富集在剪接体中。我们构建了基于CRC中11个自噬相关基因的预后风险评估模型。
在CRC中构建了基于11个自噬相关基因的预后风险评估模型。该新模型为评估预后提供了方向和思路，并为选择更好的CRC治疗策略提供了指导。
