T细胞耗竭（T-cell exhaustion，Tex）被认为是肺腺癌免疫治疗耐药性和预后不良的原因之一。因此，我们使用加权相关网络分析方法在癌症基因图谱（TCGA）中识别与Tex相关的基因。基于Tex相关基因的无监督聚类方法将患者分为聚类1和聚类2。然后，我们采用随机森林和最小绝对收缩选择算子方法识别出9个关键基因，构建风险评分。患者被分为低风险组和高风险组。多变量Cox分析显示风险评分是TCGA和GSE72094队列中的独立预后因子。此外，聚类2中风险评分高的患者具有最差的预后。免疫应答预测分析显示低风险组具有更高的免疫、基质、评估分数，较高的免疫表型评分（IPS），较低的肿瘤免疫失调和排斥分数，这表明低风险组对免疫检查点抑制剂（ICIs）治疗有较好的反应。同时，我们还包括了两个独立的免疫治疗队列，这些队列也证实了低风险组对ICIs治疗的良好反应。此外，我们还发现了两组在化疗和靶向药物敏感度方面的差异。最后，我们建立了一种预测模型以促进临床决策。© 2023. Springer Nature Limited.

T-cell exhaustion (Tex) is considered to be a reason for immunotherapy resistance and poor prognosis in lung adenocarcinoma. Therefore, we used weighted correlation network analysis to identify Tex-related genes in the cancer genome atlas (TCGA). Unsupervised clustering approach based on Tex-related genes divided patients into cluster 1 and cluster 2. Then, we utilized random forest and the least absolute shrinkage and selection operator to identify nine key genes to construct a riskscore. Patients were classified as low or high-risk groups. The multivariate cox analysis showed the riskscore was an independent prognostic factor in TCGA and GSE72094 cohorts. Moreover, patients in cluster 2 with high riskscore had the worst prognosis. The immune response prediction analysis showed the low-risk group had higher immune, stromal, estimate scores, higher immunophenscore (IPS), and lower tumor immune dysfunction and exclusion score which suggested a better response to immune checkpoint inhibitors (ICIs) therapy in the low-risk group. In the meantime, we included two independent immunotherapy cohorts that also confirmed a better response to ICIs treatment in the low-risk group. Besides, we discovered differences in chemotherapy and targeted drug sensitivity between two groups. Finally, a nomogram was built to facilitate clinical decision making.© 2023. Springer Nature Limited.