Wang Yancheng, Gao Zhen, Li Meng, Feng Zhen, Wang Hui
Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong First Medical University, Jinan, China.
Department of Thoracic Surgery, Shandong Provincial Hospital, Shandong University, Jinan, China.
Front Med (Lausanne). 2025 May 21;12:1586253. doi: 10.3389/fmed.2025.1586253. eCollection 2025.
The classical prognostic indicators of lung cancer are no longer sufficient for prognostic stratification and individualized treatment of highly heterogeneous non-small cell lung cancer (NSCLC). This study aimed to establish a radiomics model to predict CD74 expression level in NSCLC patients and to explore its role in the tumor immune response and its prognostic value.
The prediction model was developed based on 122 NSCLC transcriptome samples, including 68 paired enhanced CT and transcriptome samples. Survival analysis, gene set variation analysis, and immune cell infiltration analysis were used to investigate the relationship between CD74 expression and tumor immune response. Logistic regression (LG) and support vector machine (SVM) analysis were used to construct the prediction model. The performance of the model was assessed with respect to its calibration, discrimination, and clinical usefulness.
High CD74 expression is an independent prognostic factor for NSCLC and is positively correlated with antigen presentation and processing gene expression and antitumor immune cell infiltration. The radiomics prediction models for CD74 expression demonstrated good predictive performance. The areas under the receiver operating characteristic curves for the LG and SVM radiomics models were 0.778 and 0.729, respectively, in the training set and 0.772 and 0.701, respectively, in the validation set. The calibration and decision curve analysis curves demonstrated good fit and clinical benefit.
CD74 expression significantly impacts the prognosis of NSCLC patients. The radiomics model based on contrast-enhanced CT exhibits good performance and clinical practicability in predicting CD74 expression.
肺癌的经典预后指标已不足以对高度异质性的非小细胞肺癌（NSCLC）进行预后分层和个体化治疗。本研究旨在建立一种放射组学模型，以预测NSCLC患者的CD74表达水平，并探讨其在肿瘤免疫反应中的作用及其预后价值。
基于122例NSCLC转录组样本建立预测模型，其中包括68对增强CT和转录组样本。采用生存分析、基因集变异分析和免疫细胞浸润分析来研究CD74表达与肿瘤免疫反应之间的关系。使用逻辑回归（LG）和支持向量机（SVM）分析构建预测模型。从校准、区分度和临床实用性方面评估模型的性能。
高CD74表达是NSCLC的独立预后因素，且与抗原呈递和加工基因表达以及抗肿瘤免疫细胞浸润呈正相关。CD74表达的放射组学预测模型表现出良好的预测性能。在训练集中，LG和SVM放射组学模型的受试者操作特征曲线下面积分别为0.778和0.729，在验证集中分别为0.772和0.701。校准和决策曲线分析曲线显示出良好的拟合度和临床获益。
CD74表达显著影响NSCLC患者的预后。基于对比增强CT的放射组学模型在预测CD74表达方面表现出良好的性能和临床实用性。
