Chen Yunfei, Tong Yunfeng, Ye Xinyuan, Yang Yehao, Li Hui, Wu Haicheng, Zhai Wanchen, Li Yuwei, Zhang Qian, Zhou Linjing, Sun Jing, Fan Yun
Postgraduate Training Base Alliance, Wenzhou Medical University, Wenzhou, 325035, China.
Department of Thoracic Medical Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China.
Discov Oncol. 2025 May 25;16(1):923. doi: 10.1007/s12672-025-02781-z.
Small cell lung cancer (SCLC) is still one of the most formidable challenges in oncology. In this study, we introduce an innovative risk scoring model rooted in cancer-associated fibroblast (CAF)-related functional genes, designed to predict patient prognosis and illuminate the microenvironment of SCLC. Through Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves, our model could effectively classify patients into high- and low-risk groups, with distinct survival outcomes and remarkable predictive accuracy, which has been evidenced by the AUC values. The low-risk patients showed a more active immune environment, characterized by more infiltration of dendritic cells, natural killer cells, and higher expression of immune co-stimulation molecules. On the contrary, high-risk patients displayed an enrichment of DNA repair and glycolysis pathways associated with tumor aggressiveness and treatment resistance. These results suggest that the risk model offers a nuanced view of response to immunotherapy that may guide the identification of patients who may benefit from immunotherapy. Moreover, we also verified the function of the key gene UBE2E2 by SCLC cell line experiments. Silencing UBE2E2 results in decreased cell proliferation and migration as well as increased apoptosis, which enhances its important role in SCLC biology. In summary, our study highlights the prognostic potential of the CAF-related functional gene risk model and its implications for predicting immune microenvironment status and guiding SCLC treatment strategies.
小细胞肺癌（SCLC）仍然是肿瘤学中最严峻的挑战之一。在本研究中，我们引入了一种基于癌症相关成纤维细胞（CAF）相关功能基因的创新风险评分模型，旨在预测患者预后并阐明SCLC的微环境。通过Kaplan-Meier生存分析和受试者工作特征（ROC）曲线，我们的模型能够有效地将患者分为高风险组和低风险组，两组具有不同的生存结果和显著的预测准确性，AUC值已证明了这一点。低风险患者表现出更活跃的免疫环境，其特征是树突状细胞、自然杀伤细胞浸润更多，免疫共刺激分子表达更高。相反，高风险患者显示出与肿瘤侵袭性和治疗抗性相关的DNA修复和糖酵解途径的富集。这些结果表明，该风险模型提供了对免疫治疗反应的细致入微的观点，可能有助于识别可能从免疫治疗中获益的患者。此外，我们还通过SCLC细胞系实验验证了关键基因UBE2E2的功能。沉默UBE2E2会导致细胞增殖和迁移减少以及凋亡增加，这增强了其在SCLC生物学中的重要作用。总之，我们的研究突出了CAF相关功能基因风险模型的预后潜力及其在预测免疫微环境状态和指导SCLC治疗策略方面的意义。
