Table 1_Subtype cluster analysis unveiled the correlation between m6A- and cuproptosis-related lncRNAs and the prognosis, immune microenvironment, and treatment sensitivity of esophageal cancer.docx

ObjectiveEsophageal cancer (EC) is characterized by a high degree of malignancy and poor prognosis. N6-methyladenosine (m6A), a prominent post-transcriptional modification of mRNA in mammalian cells, plays a pivotal role in regulating various cellular and biological processes. Similarly, cuproptosis has garnered attention for its potential implications in cancer biology. This study seeks to elucidate the impact of m6A- and cuproptosis-related long non-coding RNAs (m6aCRLncs) on the prognosis of patients with EC.
MethodsThe EC transcriptional data and corresponding clinical information were retrieved from The Cancer Genome Atlas (TCGA) database, comprising 11 normal samples and 159 EC samples. Data on 23 m6A regulators and 25 cuproptosis-related genes were sourced from the latest literature. The m6aCRLncs linked to EC were identified through co-expression analysis. Differentially expressed m6aCRLncs associated with EC prognosis were screened using the limma package in R and univariate Cox regression analysis. Subtype clustering was performed to classify EC patients, enabling the investigation of differences in clinical outcomes and immune microenvironment across patient clusters. A risk prognostic model was constructed using least absolute shrinkage and selection operator (LASSO) regression. Its robustness was evaluated through survival analysis, risk stratification curves, and receiver operating characteristic (ROC) curves. Additionally, the model’s applicability across various clinical features and molecular subtypes of EC patients was assessed. To further explore the model’s utility in predicting the immune microenvironment, single-sample gene set enrichment analysis (ssGSEA), immune cell infiltration analysis, and immune checkpoint differential expression analysis were conducted. Drug sensitivity analysis was performed to identify potential therapeutic agents for EC. Finally, the mRNA expression levels of m6aCRLncs in EC cell lines were validated using reverse transcription quantitative polymerase chain reaction (RT-qPCR).
ResultsWe developed a prognostic risk model based on five m6aCRLncs, namely ELF3-AS1, HNF1A-AS1, LINC00942, LINC01389, and MIR181A2HG, to predict survival outcomes and characterize the immune microenvironment in EC patients. Analysis of molecular subtypes and clinical features revealed significant differences in cluster distribution, disease stage, and N stage between high- and low-risk groups. Immune profiling further identified distinct immune cell populations and functional pathways associated with risk scores, including positive correlations with naive B cells, resting CD4+ T cells, and plasma cells, and negative correlations with macrophages M0 and M1. Additionally, we identified key immune checkpoint-related genes with significant differential expression between risk groups, including TNFRSF14, TNFSF15, TNFRSF18, LGALS9, CD44, HHLA2, and CD40. Furthermore, nine candidate drugs with potential therapeutic efficacy in EC were identified: Bleomycin, Cisplatin, Cyclopamine, PLX4720, Erlotinib, Gefitinib, RO.3306, XMD8.85, and WH.4.023. Finally, RT-qPCR validation of the mRNA expression levels of m6aCRLncs in EC cell lines demonstrated that ELF3-AS1 expression was significantly upregulated in the EC cell lines KYSE-30 and KYSE-180 compared to normal esophageal epithelial cells.
ConclusionThis study elucidates the role of m6aCRLncs in shaping the prognostic outcomes and immune microenvironment of EC. Furthermore, it identifies potential therapeutic agents with efficacy against EC. These findings hold significant promise for enhancing the survival of EC patients and provide valuable insights to inform clinical decision-making in the management of this disease.

1. 研究目的
食管癌（Esophageal cancer, EC）具有恶性程度高、预后差的临床特征。N6-甲基腺苷（N6-methyladenosine, m6A）是哺乳动物细胞内mRNA的一类重要转录后修饰方式，在调控多种细胞及生物学进程中发挥关键作用。同样，铜死亡（cuproptosis）因其在癌症生物学中的潜在研究价值而受到广泛关注。本研究旨在阐明m6A与铜死亡相关长链非编码RNA（m6A- and cuproptosis-related long non-coding RNAs, m6aCRLncs）对食管癌患者预后的影响。

2. 研究方法
从癌症基因组图谱（The Cancer Genome Atlas, TCGA）数据库获取食管癌转录组数据及对应临床信息，共纳入11例正常样本与159例食管癌样本。从最新发表文献中收集23个m6A调控因子及25个铜死亡相关基因。通过共表达分析筛选与食管癌相关的m6aCRLncs。利用R语言limma包及单变量Cox回归分析，筛选与食管癌预后相关的差异表达m6aCRLncs。开展亚型聚类以对食管癌患者进行分类，进而探究不同患者亚组的临床结局与免疫微环境差异。采用最小绝对收缩和选择算子回归（least absolute shrinkage and selection operator, LASSO）构建风险预后模型，通过生存分析、风险分层曲线及受试者工作特征（receiver operating characteristic, ROC）曲线评估模型的稳健性。此外，评估该模型在食管癌患者不同临床特征与分子亚型中的适用性。为进一步探究模型在免疫微环境预测中的应用价值，开展单样本基因集富集分析（single-sample gene set enrichment analysis, ssGSEA）、免疫细胞浸润分析及免疫检查点差异表达分析。通过药物敏感性分析筛选食管癌潜在治疗药物。最后，采用逆转录定量聚合酶链反应（reverse transcription quantitative polymerase chain reaction, RT-qPCR）验证m6aCRLncs在食管癌细胞系中的mRNA表达水平。

3. 研究结果
本研究构建了基于5个m6aCRLncs（ELF3-AS1、HNF1A-AS1、LINC00942、LINC01389及MIR181A2HG）的预后风险模型，用于预测食管癌患者的生存结局并解析其免疫微环境。分子亚型与临床特征分析显示，高低风险组在聚类分布、疾病分期及N分期上存在显著差异。免疫特征分析进一步鉴定出与风险评分相关的独特免疫细胞群与功能通路：其中风险评分与初始B细胞、静息CD4+T细胞及浆细胞呈正相关，与M0型及M1型巨噬细胞呈负相关。此外，本研究鉴定出高低风险组间存在显著差异表达的关键免疫检查点相关基因，包括TNFRSF14、TNFSF15、TNFRSF18、LGALS9、CD44、HHLA2及CD40。同时筛选出9种对食管癌具有潜在治疗效力的候选药物：博来霉素、顺铂、环巴胺、PLX4720、厄洛替尼、吉非替尼、RO.3306、XMD8.85及WH.4.023。最后，RT-qPCR验证结果显示，相较于正常食管上皮细胞，ELF3-AS1在食管癌细胞系KYSE-30与KYSE-180中的表达水平显著上调。

4. 研究结论
本研究阐明了m6aCRLncs在塑造食管癌患者预后结局与免疫微环境中的作用，并鉴定出具有抗食管癌潜力的潜在治疗药物。上述研究成果为改善食管癌患者生存预后提供了重要思路，同时为该疾病的临床诊疗决策提供了有价值的参考依据。