线粒体历来被认为与恶性肿瘤的发生、发展密切相关。然而，肺腺癌（LUAD）线粒体的生物信息学分析尚未见报道。在本研究中，我们构建了一种新颖且可靠的算法，包括共识聚类分析和风险评估模型，以预测生存结果和肿瘤免疫患有 LUAD 的患者被分为三组，第一组的患者表现出最佳的生存结果。第 3 组患者的 PDL1（编码程序性细胞死亡 1 配体 11）和 HAVCR2（编码甲型肝炎病毒细胞受体 2）表达最高，肿瘤突变负荷 (TMB) 最高。在风险评估模型中，低风险组的患者往往有明显更好的生存结果。此外，风险评分与分期相结合可以作为 LUAD 患者可靠的独立预后指标。预后特征是选择抗肿瘤药物的新颖且有效的生物标志物。低风险患者往往具有较高的 CTLA4（编码细胞毒性 T 淋巴细胞相关蛋白 4）和 HAVCR2 表达。此外，高风险组的患者对顺铂、多西他赛、厄洛替尼、吉西他滨和紫杉醇更敏感，而低风险患者可能会从吉非替尼中受益更多。我们构建了一种新颖且可靠的算法，包括共识聚类分析和风险预测生存结果的评估模型，为晚期 LUAD 患者抗肿瘤药物治疗提供可靠的指南。版权所有 © 2024 吴、陈、葛、罗、潘、沉、谢和周。

Mitochondria have always been considered too be closely related to the occurrence and development of malignant tumors. However, the bioinformatic analysis of mitochondria in lung adenocarcinoma (LUAD) has not been reported yet.In the present study, we constructed a novel and reliable algorithm, comprising a consensus cluster analysis and risk assessment model, to predict the survival outcomes and tumor immunity for patients with terminal LUAD.Patients with LUAD were classified into three clusters, and patients in cluster 1 exhibited the best survival outcomes. The patients in cluster 3 had the highest expression of PDL1 (encoding programmed cell death 1 ligand 11) and HAVCR2 (encoding Hepatitis A virus cellular receptor 2), and the highest tumor mutation burden (TMB). In the risk assessment model, patients in the low-risk group tended to have a significantly better survival outcome. Furthermore, the risk score combined with stage could act as a reliable independent prognostic indicator for patients with LUAD. The prognostic signature is a novel and effective biomarker to select anti-tumor drugs. Low-risk patients tended to have a higher expression of CTLA4 (encoding cytotoxic T-lymphocyte associated protein 4) and HAVCR2. Moreover, patients in the high-risk group were more sensitive to Cisplatin, Docetaxel, Erlotinib, Gemcitabine, and Paclitaxel, while low-risk patients would probably benefit more from Gefitinib.We constructed a novel and reliable algorithm comprising a consensus cluster analysis and risk assessment model to predict survival outcomes, which functions as a reliable guideline for anti-tumor drug treatment for patients with terminal LUAD.Copyright © 2024 Wu, Chen, Ge, Luo, Pan, Shen, Xie and Zhou.