预测肺鳞癌中铜死亡风险和临床结局。

BACKGROUND: Lung squamous cell carcinoma (LUSC) is an important subtype of non-small cell lung cancer. Its special clinicopathological features and molecular background determine the limitations of its treatment. A recent study published on Science defined a newly regulatory cell death (RCD) form - cuproptosis. Which manifested as an excessive intracellular copper accumulation, mitochondrial respiration-dependent, protein acylation-mediated cell death. Different from apoptosis, pyroptosis, necroptosis, ferroptosis and other forms of regulatory cell death (RCD). The imbalance of copper homeostasis in vivo will trigger cytotoxicity and further affect the occurrence and progression of tumors. Our study is the first to predict the prognosis and immune landscape of cuproptosis-related genes (CRGs) in LUSC. METHODS: The RNA-seq profiles and clinical data of LUSC patients were downloaded from TCGA and GEO databases and then combined into a novel cohort. R language packages are used to analyze and process the data, and CRGs related to the prognosis of LUSC were screened according to the differentially expressed genes (DEGs). After analyzed the tumor mutation burden (TMB), copy number variation (CNV) and CRGs interaction network. Based on CRGs and DEGs, cluster analysis was used to classify LUSC patients twice. The selected key genes were used to construct a CRGs prognostic model to further analyze the correlation between LUSC immune cell infiltration and immunity. Through the risk score and clinical factors, a more accurate nomogram was further constructed. Finally, the drug sensitivity of CRGs in LUSC was analyzed. RESULTS: Patients with LUSC were divided into different cuproptosis subtypes and gene clusters, showing different levels of immune infiltration. The risk score showed that the high-risk group had higher tumor microenvironment score, lower tumor mutation load frequency and worse prognosis than the low-risk group. In addition, the high-risk group was more sensitive to vinorelbine, cisplatin, paclitaxel, doxorubicin, etoposide and other drugs. CONCLUSIONS: Through bioinformatics analysis, we successfully constructed a prognostic risk assessment model based on CRGs, which can not only accurately predict the prognosis of LUSC patients, but also evaluate the patient 's immune infiltration status and sensitivity to chemotherapy drugs. This model shows satisfactory predictive results and provides a reference for subsequent tumor immunotherapy.

背景：肺鳞状细胞癌（LUSC）是非小细胞肺癌的重要亚型。其特殊的临床病理特征和分子背景决定了其治疗的局限性。最近发表在《科学》杂志上的一项研究定义了一种新的调节性细胞死亡（RCD）形式——铜死亡。其表现为细胞内铜积累过多，依赖于线粒体呼吸，蛋白酰化介导的细胞死亡。与细胞凋亡、细胞焦亡、坏死性凋亡、铁死亡等其他形式的调节性细胞死亡（RCD）不同。体内铜平衡失调会引发细胞毒性，进一步影响肿瘤的发生和发展。我们的研究首次预测了 LUSC 中铜死亡相关基因（CRGs）的预后和免疫图谱。

方法：从 TCGA 和 GEO 数据库中下载 LUSC 患者的 RNA-seq 谱和临床数据，并将其合并为一个新的队列。使用 R 语言包分析和处理数据，根据差异表达基因（DEGs）筛选与 LUSC 预后相关的 CRGs。在分析肿瘤突变负荷（TMB）、拷贝数变异（CNV）和 CRGs 相互作用网络后。基于 CRGs 和 DEGs，对 LUSC 患者进行了两次聚类分析。选择关键基因构建 CRGs 预后模型，进一步分析 LUSC 免疫细胞浸润与免疫的相关性。通过风险评分和临床因素，进一步构建了更准确的列线图。最后，分析了 CRGs 在 LUSC 中的药物敏感性。

结果：将 LUSC 患者分为不同的铜死亡亚型和基因簇，表现出不同水平的免疫浸润。风险评分显示，高危组肿瘤微环境评分较高，肿瘤突变负荷频率较低，预后较差。此外，高危组对长春瑞滨、顺铂、紫杉醇、多柔比星、依托泊苷等药物更为敏感。

结论：通过生物信息学分析，我们成功构建了基于 CRGs 的预后风险评估模型，不仅能准确预测 LUSC 患者的预后，还能评估患者的免疫浸润状态和对化疗药物的敏感性。该模型具有令人满意的预测结果，为后续肿瘤免疫治疗提供了参考。