摘要
      食管鳞状细胞癌（ESCC）是食管癌症的主要亚型。由于自噬相关基因（ARGs）在包括ESCC在内的许多肿瘤的发病机制中发挥着关键作用，本研究的目的是基于ARGs的表达谱建立自噬相关的预后风险特征，并为改善临床结果的预测提供一种新方法。我们从公开数据（GSE53625）中获得了ESCC的表达谱，并提取了ARGs的部分。进行差异表达分析和富集分析以确认异常自噬相关的生物功能。对RNA微阵列数据（GSE53625）进行单变量和多变量Cox回归分析，以构建与自噬相关的预后风险特征。通过受试者操作特征（ROC）分析、生存分析和Brier评分来评估模型的性能。该模型经过了引导程序内部验证。通过基因集富集分析（GSEA）探讨了基因标记的潜在分子机制。Spearman相关系数检验了风险评分与免疫状态和脱铁性贫血之间的相关性。通过qRT-PCR和免疫组织化学验证基因和蛋白质在ESCC细胞系和ESCC组织中的表达水平。我们构建并验证了179名ESCC患者的自噬相关预后风险特征。高危组患者的长期生存率低于低危组（log秩，P值 < 0.001）。ROC分析和Brier评分证实了签名的可靠性。GSEA结果显示，高危ESCC患者中的癌症和自噬相关信号通路和低危ESCC患者的免疫调节信号通路显著富集。相关分析表明，风险特征可以有效预测免疫治疗的效果。约33.97%（71/209）的脱铁相关基因与风险评分显著相关。最后，qRT-PCR和免疫组织化学实验的结果与生物信息学分析一致。简言之，我们构建了一种新的自噬相关基因标记（VIM、UFM1、TSC2、SRC、MEFV、CTTN、CFTR和CDKN1A），它可以改善ESCC患者临床结果的预测。
Abstract
Esophageal squamous cell carcinoma (ESCC) is the main subtype of esophageal cancer. Since autophagy-related genes (ARGs) play a key role in the pathogenesis of many tumors, including ESCC, the purpose of this study is to establish an autophagy-related prognostic risk signature based on ARGs expression profile, and to provide a new method for improving prediction of clinical outcomes. We obtained the expression profiles of ESCC from public data (GSE53625) and extracted the portion of ARGs. Differential expression analysis and enrichment analysis were performed to confirm abnormal autophagy-related biological functions. Univariate and multivariate Cox regression analyses were performed on RNA microarray data (GSE53625) to construct a prognostic risk signature associated with autophagy. The performance of the model was evaluated by receiver operating characteristic (ROC) analysis, survival analysis and Brier score. The model was subjected to bootstrap internal validation. The potential molecular mechanism of gene signature was explored by gene set enrichment analysis (GSEA). Spearman correlation coefficient examined the correlation between risk score and immune status and ferroptosis. The expression levels of genes and proteins were validated by qRT-PCR and immunohistochemistry in ESCC cell lines and ESCC tissues. We constructed and validated an autophagy-related prognostic risk signature in 179 patients with ESCC. The long-term survival of patients in high-risk group was lower than that in low-risk group (log-rank, P value < 0.001). ROC analysis and Brier score confirmed the reliability of the signature. GSEA results showed significant enrichment of cancer- and autophagy-related signaling pathways in the high-risk ESCC patients and immunoregulatory signaling pathways in the low-risk ESCC patients. Correlation analysis showed that the risk signature can effectively predict the effect of immunotherapy. About 33.97% (71/209) ferroptosis-related genes were significantly correlated with risk scores. Finally, the results of qRT-PCR and immunohistochemistry experiments were consistent with bioinformatics analysis. In brief, we constructed a novel autophagy-related gene signature (VIM, UFM1, TSC2, SRC, MEFV, CTTN, CFTR and CDKN1A), which could improve the prediction of clinical outcomes in patients with ESCC.

https://www.nature.com/articles/s41598-022-05922-4