Limited treatment strategies are available for squamous-cell lung cancer (SQLC) patients. Few studies have addressed whether immune-related genes (IRGs) or the tumor immune microenvironment can predict the prognosis for SQLC patients. Our study aimed to construct a signature predict prognosis for SQLC patients based on IRGs.

We constructed and validated a signature from SQLC patients in The Cancer Genome Atlas (TCGA) using bioinformatics analysis. The underlying mechanisms of the signature were also explored with immune cells and mutation profiles.

A total of 464 eligible SQLC patients from TCGA dataset were enrolled and were randomly divided into the training cohort (n = 232) and the testing cohort (n = 232). Eight differentially expressed IRGs were identified and applied to construct the immune signature in the training cohort. The signature showed a significant difference in overall survival (OS) between low-risk and high-risk cohorts (P < 0.001), with an area under the curve of 0.76. The predictive capability was verified with the testing and total cohorts. Multivariate analysis revealed that the 8-IRG signature served as an independent prognostic factor for OS in SQLC patients. Naive B cells, resting memory CD4 T cells, follicular helper T cells, and M2 macrophages were found to significantly associate with OS. There was no statistical difference in terms of tumor mutational burden between the high-risk and low-risk cohorts.

Our study constructed and validated an 8-IRG signature prognostic model that predicts clinical outcomes for SQLC patients. However, this signature model needs further validation with a larger number of patients.

鳞状细胞肺癌（SQLC）患者的治疗策略有限。很少有研究探讨免疫相关基因（IRG）或肿瘤免疫微环境能否预测SQLC患者的预后。我们的研究旨在基于IRGs为SQLC患者构建特征性的预后预测。

我们使用生物信息学分析在癌症基因组图谱（TCGA）中构建并验证了SQLC患者的签名。还使用免疫细胞和突变图谱探索了签名的潜在机制。

来自TCGA数据集的464名合格的SQLC患者入组，并随机分为训练组（ñ = 232）和测试队列（ñ= 232）。鉴定了八种差异表达的IRG，并将其用于构建训练队列中的免疫信号。签名显示低风险和高风险人群之间的总生存期（OS）有显着差异（P<0.001），曲线下面积为0.76。通过测试和总体队列验证了预测能力。多变量分析显示，8-IRG信号可作为SQLC患者OS的独立预后因素。发现幼稚B细胞，静息记忆CD4 T细胞，滤泡辅助性T细胞和M2巨噬细胞与OS显着相关。高危人群和低危人群在肿瘤突变负担方面无统计学差异。

我们的研究构建并验证了可预测SQLC患者临床预后的8-IRG签名预后模型。但是，此签名模型需要更多患者的进一步验证。