Department of Thoracic Surgery, Sun Yat-Sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in Southern China, Guangzhou, China.
Lung Cancer Research Center, Sun Yat-Sen University, Guangzhou, China.
Cancer Med. 2023 Feb;12(4):4968-4980. doi: 10.1002/cam4.5190. Epub 2022 Sep 3.
Inflammation is known to have an intricate relationship with tumorigenesis and tumor progression while it is also closely related to tumor immune microenvironment. Whereas the role of inflammation-related genes (IRGs) in lung squamous carcinoma (LUSC) is barely understood. Herein, we recognized IRGs associated with overall survival (OS), built an IRGs signature for risk stratification and explored the impact of IRGs on immune infiltration landscape of LUSC patients.
The RNA-sequencing and clinicopathological data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, which were defined as training and validation cohorts. Cox regression and least absolute shrinkage and selection operator analyses were performed to build an IRG signature. CIBERSORT, microenvironment cell populations-counter and tumor immune dysfunction and rejection (TIDE) algorithm were used to perform immune infiltration analysis.
A two-IRG signature consisting of KLF6 and SGMS2 was identified according to the training set, which could categorize patients into two different risk groups with distinct OS. Patients in the low-risk group had more anti-tumor immune cells infiltrated while patient with high-risk had lower TIDE score and higher levels of immune checkpoint molecules expressed. The IRG signature was further identified as an independent prognostic factor of OS. Subsequently, a prognostic nomogram including IRG signature, age, and cancer stage was constructed for predicting individualized OS, whose concordance index values were 0.610 (95% CI: 0.568-0.651) in the training set and 0.652 (95% CI: 0.580-0.724) in validation set. Time-dependent receiver operator characteristic curves revealed that the nomogram had higher prediction accuracy compared with the traditional tumor stage alone.
The IRG signature was a predictor for patients with LUSC and might serve as a potential indicator of the efficacy of immunotherapy. The nomogram based on the IRG signature showed a relatively good predictive performance in survival.
炎症与肿瘤发生和肿瘤进展有着错综复杂的关系，同时也与肿瘤免疫微环境密切相关。然而，炎症相关基因（IRGs）在肺鳞状细胞癌（LUSC）中的作用还知之甚少。在此，我们鉴定了与总生存期（OS）相关的 IRGs，构建了一个用于风险分层的 IRG 特征，并探讨了 IRGs 对 LUSC 患者免疫浸润景观的影响。
从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）下载了 LUSC 患者的 RNA-seq 和临床病理数据，将其定义为训练和验证队列。使用 Cox 回归和最小绝对收缩和选择算子分析构建 IRG 特征。使用 CIBERSORT、微环境细胞群计数器和肿瘤免疫功能障碍和排斥（TIDE）算法进行免疫浸润分析。
根据训练集确定了由 KLF6 和 SGMS2 组成的两个 IRG 特征，可以将患者分为具有不同 OS 的两个不同风险组。低风险组患者的抗肿瘤免疫细胞浸润更多，而高风险组患者的 TIDE 评分较低，免疫检查点分子表达水平较高。IRG 特征进一步被确定为 OS 的独立预后因素。随后，构建了一个包含 IRG 特征、年龄和癌症分期的预后列线图，用于预测个体化 OS，其在训练集和验证集中的一致性指数值分别为 0.610（95%CI：0.568-0.651）和 0.652（95%CI：0.580-0.724）。时间依赖性接收者操作特征曲线表明，与传统的肿瘤分期相比，该列线图具有更高的预测准确性。
IRG 特征是 LUSC 患者的预测因子，可能是免疫治疗疗效的潜在指标。基于 IRG 特征的列线图在生存方面表现出较好的预测性能。
