Wang Ruolan, Huang Yanhua, He Juan, Jin Shan, Li Xin, Tan Kun, Xia Wei
College of Pharmacy, Dali University, Dali, 671000, Yunnan, China.
Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China.
Discov Oncol. 2024 Feb 16;15(1):37. doi: 10.1007/s12672-024-00887-4.
Endoplasmic reticulum stress (ERS) acts critical roles on cell growth, proliferation, and metastasis in various cancers. However, the relationship between ERs and lung squamous cell carcinoma (LUSC) prognoses still remains unclear.
The consensus clustering analysis of ERS-related genes and the differential expression analysis between clusters were investigated in LUSC based on TCGA database. Furthermore, ERS-related prognostic risk models were constructed by LASSO regression and Cox regression analyses. Then, the predictive effect of the risk model was evaluated by Kaplan-Meier, Cox regression, and ROC Curve analyses, as well as validated in the GEO cohort. According to the optimal threshold, patients with LUSC were divided into high- and low- risk groups, and somatic mutations, immune cell infiltration, chemotherapy response and immunotherapy effect were systematically analyzed.
Two ERS-related clusters were identified in patients with LUSC that had distinct patterns of immune cell infiltration. A 5-genes ERS-related prognostic risk model and nomogram were constructed and validated. Kaplan-Meier curves and Cox regression analysis showed that ERS risk score was an independent prognostic factor (p < 0.001, HR = 1.317, 95% CI = 1.159-1.496). Patients with low-risk scores presented significantly lower TIDE scores and significantly lower IC50 values for common chemotherapy drugs such as cisplatin and gemcitabine.
ERS-related risk signature has certain prognostic value and may be a potential therapeutic target and prognostic biomarker for LUSC patients.
内质网应激(ERS)在多种癌症的细胞生长、增殖和转移中发挥关键作用。然而,ERS与肺鳞状细胞癌(LUSC)预后之间的关系仍不清楚。
基于TCGA数据库,对LUSC中ERS相关基因进行共识聚类分析,并对聚类间的差异表达进行分析。此外,通过LASSO回归和Cox回归分析构建ERS相关的预后风险模型。然后,通过Kaplan-Meier分析、Cox回归分析和ROC曲线分析评估风险模型的预测效果,并在GEO队列中进行验证。根据最佳阈值,将LUSC患者分为高风险组和低风险组,并对体细胞突变、免疫细胞浸润、化疗反应和免疫治疗效果进行系统分析。
在LUSC患者中鉴定出两个ERS相关聚类,它们具有不同的免疫细胞浸润模式。构建并验证了一个包含5个基因的ERS相关预后风险模型和列线图。Kaplan-Meier曲线和Cox回归分析表明,ERS风险评分是一个独立的预后因素(p < 0.001,HR = 1.317,95% CI = 1.159 - 1.496)。低风险评分的患者表现出显著更低的TIDE评分以及对于顺铂和吉西他滨等常用化疗药物显著更低的IC50值。
ERS相关风险特征具有一定的预后价值,可能是LUSC患者潜在的治疗靶点和预后生物标志物。