肿瘤细胞治疗研究
英文原题：Targeting regulated cell death pathways in lung cancer: mechanisms, therapeutic strategies, and clinical translation.
肺癌是全球癌症死亡的主要原因，其治疗效果受到高度异质性、耐药性和免疫抑制性肿瘤微环境的限制。
肺癌是全球癌症死亡的主要原因，其疗效受到高度异质性、耐药性和免疫抑制性肿瘤微环境的限制。本综述主要聚焦非小细胞肺癌（NSCLC），系统分析肺癌中八条关键调控性细胞死亡（RCD）通路。这些通路包括凋亡、自噬、坏死性凋亡、铁死亡、铜死亡、焦亡、免疫原性细胞死亡（ICD）和溶酶体依赖性细胞死亡（LDCD）。机制剖析揭示了这些通路之间复杂的串扰和动态平衡。例如，通过 EGFR/PI3K/Akt/mTOR 信号通路逃逸凋亡可促进生存，而自噬则表现出由 RBBP4 和 AURKA-CXCL5 轴等因素调控的背景依赖性双重作用。重要的是，若干 RCD 通路发挥强效免疫调节功能。坏死性凋亡通过释放损伤相关分子模式（DAMPs）激活 T 细胞，而铁死亡通过 GPX4 失活增强 NK 细胞细胞毒性。在治疗进展方面，协同策略显示出前景，例如小檗碱与 EGFR-TKIs 联用通过 EGFR 降解诱导凋亡，以及 (-)-Guaiol 触发 ICD 以与 PD-1/PD-L1 抑制剂协同作用。新型诱导剂，包括 Auranofin（铁死亡）、TMEM100 激动剂（坏死性凋亡）和铜死亡纳米药物（如 DE-Cu 4 O 3 NPs），显示出临床前潜力。基于 RCD 相关基因的预后模型（如 LDCD 特征）可预测免疫特征和对免疫检查点抑制剂（ICIs）的应答。然而，临床转化面临瓶颈，包括通路串扰复杂、免疫抑制微环境重塑困难、EGFR突变患者ICI应答率低，以及缺乏标准化生物标志物和优化递送系统。未来研究应优先开展多种死亡通路的协同靶向，利用整合多组学数据的先进计算工具解析RCD网络的复杂性并优化治疗预测，同时加强跨学科转化研究。最终，深入理解RCD网络将为肺癌精准治疗的范式转变铺平道路。
Lung cancer is the leading cause of global cancer mortality, with treatment efficacy limited by high heterogeneity, drug resistance, and an immunosuppressive tumor microenvironment. Focusing primarily on non-small cell lung cancer (NSCLC), this review systematically analyzes eight key regulated cell death (RCD) pathways in lung cancer. These pathways are apoptosis, autophagy, necroptosis, ferroptosis, cuproptosis, pyroptosis, immunogenic cell death (ICD), and lysosome-dependent cell death (LDCD). Mechanistic dissection reveals complex crosstalk and a dynamic equilibrium among these pathways. For instance, apoptosis escape via EGFR/PI3K/Akt/mTOR signaling promotes survival, while autophagy exhibits a context-dependent dual role regulated by factors such as RBBP4 and the AURKA-CXCL5 axis. Importantly, several RCD pathways exert potent immunomodulatory functions. Necroptosis activates T cells by releasing damage-associated molecular patterns (DAMPs), while ferroptosis enhances NK cell cytotoxicity through GPX4 inactivation. Regarding therapeutic advances, synergistic strategies show promise, such as berberine with EGFR-TKIs inducing apoptosis via EGFR degradation, and (-)-Guaiol triggering ICD to synergize with PD-1/PD-L1 inhibitors. Novel inducers, including Auranofin (ferroptosis), TMEM100 agonists (necroptosis), and cuproptosis nanomedicines (e.g., DE-Cu 4 O 3 NPs), demonstrate preclinical potential. Prognostic models based on RCD-related genes (e.g., LDCD signatures) can predict immune features and response to immune checkpoint inhibitors (ICIs). However, clinical translation faces bottlenecks, including intricate pathway crosstalk, difficulties in remodeling the immunosuppressive niche, low ICI response in EGFR-mutant patients, and a lack of standardized biomarkers and optimized delivery systems. Future research should prioritize coordinated targeting of multiple death pathways, utilize advanced computational tools integrated with multi-omics data to decipher RCD network complexity and optimize treatment prediction, and strengthen interdisciplinary translational efforts. Ultimately, a deep understanding of the RCD network paves the way for a paradigm shift toward precision therapy in lung cancer.
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