新型趋化因子相关长链非编码 RNA 标志物与食管鳞癌的预后、免疫图谱和治疗敏感性相关。

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is closely correlated with malignant biological characteristics and poor survival. Recently, chemokines have been reported to be involved in the progression of tumors, and they can also regulate the tumor microenvironment. However, it is unclear whether chemokine-related long noncoding RNAs (lncRNAs) affect the prognosis of ESCC. METHODS: We downloaded RNA-seq and clinical data from the Gene Expression Omnibus (GEO database. Chemokine-related lncRNAs were screened by differential analysis and Pearson correlation analysis. Then, prognosis-related lncRNAs were screened by using univariate COX regression, and risk models were constructed after the least absolute shrinkage and selection operator (LASSO) regression and multivariate COX regression. The predictive value of the signature was assessed using Kaplan-Meier test, time-dependent receiver operating characteristic (ROC) curves, decision curve analysis (DCA) and calibration curve. Moreover, a nomogram to predict patients' 1-year 3-year and 5-year prognosis was constructed. Gene set enrichment analyses (GSEA), Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG), evaluation of immune cell infiltration, and estimation of drug sensitivity were also conducted. RESULTS: In this study, 677 chemokine-related lncRNAs were first obtained by differential analysis and Pearson correlation. Then, six chemokine-related lncRNAs were obtained by using univariate COX, LASSO and multivariate COX to construct a novel chemokine-related lncRNAs risk model. The signature manifested favorable predictive validity and accuracy both in the testing and training cohorts. The chemokine-related signature could classify ESCC patients into two risk groups well, which indicated that high-risk group exhibited poor prognostic outcome. In addition, this risk model played an important role in predicting signaling pathways, immune cell infiltration, stromal score, and drug sensitivity in ESCC patients. CONCLUSIONS: These findings elucidated the critical role of novel prognostic chemokine-related lncRNAs in prognosis, immune landscape, and drug therapy, thus throwing light on prognostic evaluation and therapeutic targets for ESCC patients.

背景：食管鳞状细胞癌（ESCC）与恶性生物学特征和较差的生存密切相关。最近，趋化因子被报道参与肿瘤的进展，并且它们还可以调节肿瘤微环境。然而，趋化因子相关长非编码 RNA（lncRNA）是否影响 ESCC 的预后尚不清楚。

方法：我们从基因表达综合数据库（GEO 数据库）下载了 RNA-seq 和临床数据。通过差异分析和 Pearson 相关分析筛选趋化因子相关 lncRNA。然后，通过单变量 COX 回归筛选预后相关 lncRNA，并用最小绝对收缩和选择算子（LASSO）回归和多变量 COX 回归构建风险模型。通过 Kaplan-Meier 检验、时间依赖性接受者操作特征（ROC）曲线、决策曲线分析（DCA）和校准曲线评估签名的预测价值。此外，构建了一个用于预测患者 1 年、3 年和 5 年预后的列线图。还进行了基因集富集分析（GSEA）、基因本体论/京都基因与基因组百科全书（GO/KEGG）、免疫细胞浸润评估和药物敏感性估计。

结果：本研究首先通过差异分析和 Pearson 相关获得了 677 个趋化因子相关 lncRNA。然后，通过单变量 COX、LASSO 和多变量 COX 构建了一个新的趋化因子相关 lncRNA 风险模型，获得了 6 个趋化因子相关 lncRNA。该签名在测试和训练队列中均表现出良好的预测有效性和准确性。趋化因子相关签名可以很好地将 ESCC 患者分为两个风险组，这表明高危组预后不良。此外，该风险模型在预测 ESCC 患者的信号通路、免疫细胞浸润、基质评分和药物敏感性方面发挥着重要作用。

结论：这些发现阐明了新型预后相关趋化因子 lncRNA 在预后、免疫图谱和药物治疗中的关键作用，从而为 ESCC 患者的预后评估和治疗靶点提供了新的思路。