目的·构建肺癌患者恶性胸腔积液（malignant pleural effusion，MPE）肿瘤细胞来源的肿瘤异种移植（patient-derived tumor xenograft，PDX）模型，并进行实验验证。方法·从基因表达综合数据集（Gene Expression Omnibus，GEO）下载人肺癌伴MPE单细胞转录组测序公共数据GSE131907和人肺癌实体瘤单细胞转录组测序公共数据GSE203360，对数据进行聚类、差异基因本体功能富集分析，明确应用MPE建模的可行性。同时收集肺癌患者的MPE样本，经离心、裂解红细胞等富集细胞操作后，将其植入非肥胖型糖尿病重症联合免疫缺陷（non-obese diabetic/severe combined immunodeficient，NOD/SCID）小鼠皮下，待移植瘤生长至1 000 mm3时进行瘤体传代及保存。对稳定传代移植瘤进行组织病理学检测，通过苏木精-伊红染色（hematoxylin-eosin staining，H-E染色）观察细胞组织形态，免疫组织化学法（immunohistochemistry，IHC）检测肺癌标志物表达情况。结果·经单细胞数据分析发现MPE中肿瘤细胞的增殖功能更强，提示MPE中肿瘤细胞PDX建模或具备更佳成瘤效果；共收集35例肺癌MPE样本，成功构建13例PDX模型，成功率达37.14%；在组织病理学检测中，H-E染色可见移植瘤组织细胞异型性明显，IHC检测显示细胞角蛋白7（cytokeratin 7，CK7）、甲状腺转录因子1（thyroid transcription factor-1，TTF1）和天冬氨酸蛋白酶A（Napsin A）等肺癌标志物均呈阳性表达。结论·通过富集肺癌患者MPE中的肿瘤细胞，成功构建了更为简便高效、可实时动态建模的PDX模型。该模型保留了肺癌患者肿瘤细胞的恶性特征及蛋白表达特性，为肺癌伴MPE患者的基础研究和临床用药指导提供了重要的实验模型工具。

Objective ·To establish a patient-derived tumor xenograft (PDX) model using tumor cells sourced from malignant pleural effusion (MPE) in patients with lung cancer, and to conduct experimental validation. Methods ·Gene expression data were downloaded from the Gene Expression Omnibus (GEO), including single-cell RNA sequencing data for lung cancer with MPE (GSE131907) and for solid lung cancer (GSE203360). Data were clustered, and differential gene ontology functional enrichment analysis was performed to ascertain the feasibility of modeling by using MPE. MPE samples from patients with lung cancer were collected and processed through centrifugation and red blood cell lysis to enrich cells. The enriched cells were then implanted subcutaneously into non-obese diabetic/severe combined immunodeficient (NOD/SCID) mice. Tumor growth was monitored, and when tumors reached 1 000 mm3, they were passaged and preserved. Histopathological examination was conducted on stable passaged tumors, the cell morphology was observed via hematoxylin-eosin (H-E) staining and the expression of lung cancer biomarkers was detected by using immunohistochemistry (IHC). Results ·Single-cell data analysis revealed stronger proliferative functions of tumor cells in MPE, suggesting that PDX modeling using MPE tumor cells may yield better tumor formation. A total of 35 samples of MPE from lung cancer patients were collected, and 13 PDX models were successfully constructed, with a success rate of 37.14%. Histopathological examination showed significant cellular atypia by H-E staining, and IHC result showed positive expression of lung cancer biomarkers such as cytokeratin 7 (CK7), thyroid transcription factor-1 (TTF1), and Napsin A. Conclusion ·By enriching tumor cells from MPE of lung cancer patients, a more convenient, efficient, and dynamically modelable PDX model is successfully constructed. This model retains the malignant characteristics and protein expression features of tumor cells from lung cancer patients, providing an important experimental model tool for basic research and clinical drug guidance for lung cancer patients with MPE.