Wu Xianqiao, Chen Hang, Ge Zhen, Luo Binyu, Pan Hanbo, Shen Yiming, Xie Zuorun, Zhou Chengwei
Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Department of Thoracic Surgery, Ningbo Medical Center LiHuiLi Hospital, Ningbo, Zhejiang, China.
Front Mol Biosci. 2024 Aug 8;11:1397281. doi: 10.3389/fmolb.2024.1397281. eCollection 2024.
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 (encoding programmed cell death 1 ligand 11) and (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 (encoding cytotoxic T-lymphocyte associated protein 4) and . 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.
线粒体一直被认为与恶性肿瘤的发生和发展密切相关。然而，肺腺癌（LUAD）中线粒体的生物信息学分析尚未见报道。
在本研究中，我们构建了一种新的可靠算法，包括共识聚类分析和风险评估模型，以预测晚期LUAD患者的生存结局和肿瘤免疫情况。
LUAD患者被分为三个聚类，聚类1中的患者生存结局最佳。聚类3中的患者 （编码程序性细胞死亡1配体11）和 （编码甲型肝炎病毒细胞受体2）表达最高，肿瘤突变负荷（TMB）也最高。在风险评估模型中，低风险组的患者生存结局往往明显更好。此外，风险评分结合分期可作为LUAD患者可靠的独立预后指标。该预后特征是一种选择抗肿瘤药物的新型有效生物标志物。低风险患者 （编码细胞毒性T淋巴细胞相关蛋白4）和 的表达往往较高。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，而低风险患者可能从吉非替尼中获益更多。
我们构建了一种新的可靠算法，包括共识聚类分析和风险评估模型来预测生存结局，该算法可作为晚期LUAD患者抗肿瘤药物治疗的可靠指南。
