Establishment and validation of the prognostic risk model based on the anoikis-related genes in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a malignant condition in humans. Anoikis-related genes (ARGs) are crucial to cancer progression. Therefore, more studies on the relationship between ARGs and ESCC are warranted.
The study acquired ESCC-related transcriptome data from TCGA. Differentially expressed ARGs (DE-ARGs) were obtained by differential analysis and candidates were filtered out by survival analysis. Prognostic genes were determined by Cox and LASSO regression. A risk model was constructed based on prognostic gene expressions. An immune infiltration study was done to explain how these genes contribute to ESCC development. The IC50 test was adopted to assess the clinical response of chemotherapy drugs. Single cell analysis was performed on the GSE145370 dataset. Moreover, the prognostic gene expressions were detected by qRT-PCR.
53 DE-ARGs were screened and four candidate genes including PBK, LAMC2, TNFSF10 and KL were obtained. Cox and LASSO regression identified the two prognostic genes, TNFSF10 and PBK. Immuno-infiltration analysis revealed positive associations of PBK with Macrophages M0 cells, and TNFSF10 with Macrophages M1 cells. The IC50 values of predicted drugs, in the case of Tozasertib 1096 and WIKI4 1940, were significantly variant between risk groups. Single cell analysis revealed that TNFSF10 and PBK levels were higher in epithelial cells than in other cells. The prognostic genes expression results by qRT-PCR were compatible with the dataset analysis.
The study established an ARG prognosis model of ESCC. It provided a reference for the research of ARGs in ESCC.

食管鳞状细胞癌（Esophageal squamous cell carcinoma, ESCC）是一类人类恶性肿瘤。失巢凋亡相关基因（Anoikis-related genes, ARGs）在肿瘤进展过程中发挥关键调控作用，因此开展更多关于ARGs与ESCC关联的相关研究具有重要价值。

本研究从癌症基因组图谱（The Cancer Genome Atlas, TCGA）数据库获取ESCC相关转录组数据。通过差异分析筛选得到差异表达失巢凋亡相关基因（Differentially expressed ARGs, DE-ARGs），并经生存分析进一步筛选候选基因；通过Cox回归与最小绝对收缩和选择算子（Least Absolute Shrinkage and Selection Operator, LASSO）回归分析确定预后相关基因，基于预后基因的表达水平构建ESCC风险预测模型。此外，本研究开展免疫浸润分析以阐明上述基因在ESCC发生发展中的作用机制，采用半数抑制浓度（Half maximal inhibitory concentration, IC50）实验评估化疗药物的临床响应情况。对GSE145370数据集进行单细胞测序分析，并通过实时荧光定量聚合酶链反应（quantitative real-time polymerase chain reaction, qRT-PCR）验证预后基因的表达水平。

本研究共筛选得到53个DE-ARGs，最终获得PBK、LAMC2、TNFSF10及KL共4个候选基因；经Cox回归与LASSO回归分析，最终确定TNFSF10与PBK为核心预后基因。免疫浸润分析结果显示，PBK与M0型巨噬细胞呈正相关，TNFSF10与M1型巨噬细胞呈正相关。预测化疗药物的IC50值（如Tozasertib 1096与WIKI4 1940）在不同风险分组间存在显著差异。单细胞测序分析结果表明，TNFSF10与PBK在上皮细胞中的表达水平显著高于其他细胞类型。qRT-PCR验证所得的预后基因表达结果与数据集分析结果具有良好的一致性。

本研究成功构建了ESCC的ARGs预后模型，可为ESCC中ARGs相关研究提供重要参考依据。