Esophageal squamous cell carcinoma (ESCC) is a prevalent malignant tumor of the digestive system that poses a significant threat to human life and health. It is crucial to thoroughly investigate the mechanisms of esophageal carcinogenesis and identify potential key molecular events in its carcinogenesis. Single‐cell transcriptome sequencing is an emerging technology that has gained prominence in recent years for studying molecular mechanisms, which may help to further explore the underlying mechanisms of the ESCC tumor microenvironment in depth. The single‐cell dataset was obtained from GSE160269 in the Gene Expression Omnibus database, including 60 tumor samples and four paracancer samples. The single‐cell data underwent dimensional reduction clustering analysis to identify clusters and annotate expression profiles. Subcluster analysis was conducted for each cellular taxon. Copy number variation analysis of tumor cell subpopulations was performed to primarily identify malignant cells within them. A proposed chronological analysis was performed to obtain the process of cell differentiation. In addition, cell communication, transcription factor analysis, and tumor pathway analysis were also performed. Relevant risk models and key genes were established by univariate COX regression and LASSO analysis. The key genes obtained from the screen were subjected to appropriate silencing and cellular assays, including CCK‐8, 5‐ethynyl‐2′‐deoxyuridine, colony formation, and western blot. Single‐cell analysis revealed that normal samples contained a large number of fibroblasts, T cells, and B cells, with fewer other cell types, whereas tumor samples exhibited a relatively balanced distribution of cell types. Subclassification analysis of immune cells, fibroblasts, endothelial cells, and epithelial cells revealed their specific spatial characteristics. The prognostic risk model, we constructed successfully, achieved accurate prognostic stratification for ESCC patients. The screened key gene, UPF3A, was found to be significantly associated with the development of ESCC by cellular assays. This process might be linked to the phosphorylation of ERK and P38. Single‐cell transcriptome analysis successfully revealed the distribution of cell types and major expressed factors in ESCC patients, which could facilitate future in‐depth studies on the therapeutic mechanisms of ESCC.

中文翻译：

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单细胞转录组测序分析揭示食管鳞状细胞癌的瘤内异质性

食管鳞状细胞癌（ESCC）是一种常见的消化系统恶性肿瘤，对人类生命健康构成重大威胁。深入研究食管癌发生机制并识别其癌变过程中潜在的关键分子事件至关重要。单细胞转录组测序是近年来在研究分子机制方面受到重视的新兴技术，可能有助于进一步深入探讨食管鳞癌肿瘤微环境的潜在机制。单细胞数据集取自Gene Expression Omnibus数据库中的GSE160269，包括60个肿瘤样本和4个癌旁样本。单细胞数据进行降维聚类分析，以识别簇并注释表达谱。对每个细胞分类单元进行亚簇分析。对肿瘤细胞亚群进行拷贝数变异分析，以初步鉴定其中的恶性细胞。进行了建议的时间顺序分析以获得细胞分化的过程。此外，还进行了细胞通讯、转录因子分析和肿瘤通路分析。通过单变量COX回归和LASSO分析建立相关风险模型和关键基因。对从筛选中获得的关键基因进行适当的沉默和细胞测定，包括CCK-8、5-乙炔基-2'-脱氧尿苷、集落形成和蛋白质印迹。单细胞分析显示，正常样本含有大量的成纤维细胞、T细胞和B细胞，其他细胞类型较少，而肿瘤样本则表现出相对均衡的细胞类型分布。对免疫细胞、成纤维细胞、内皮细胞和上皮细胞的亚分类分析揭示了它们特定的空间特征。我们成功构建的预后风险模型实现了 ESCC 患者的准确预后分层。通过细胞分析发现筛选出的关键基因UPF3A与ESCC的发生显着相关。该过程可能与 ERK 和 P38 的磷酸化有关。单细胞转录组分析成功揭示了食管鳞癌患者的细胞类型分布和主要表达因子，有助于今后对食管鳞癌治疗机制的深入研究。