一种新型的线粒体相关算法，用于预测肺腺癌患者的生存结果和药物敏感性
A novel mitochondria-related algorithm for predicting the survival outcomes and drug sensitivity of patients with lung adenocarcinoma
影响因子:4.00000
分区:生物学3区 / 生化与分子生物学3区
发表日期:2024
作者:
Xianqiao Wu, Hang Chen, Zhen Ge, Binyu Luo, Hanbo Pan, Yiming Shen, Zuorun Xie, Chengwei Zhou
摘要
线粒体始终被认为与恶性肿瘤的发生和发展密切相关。然而，尚未报道对肺腺癌（LUAD）中线粒体的生物信息分析。在本研究中，我们构建了一种新颖且可靠的算法，包括共识群集分析和风险评估模型，以预测与LUAD的患者相比，以预测患者的生存和肿瘤免疫性。最好的生存结果。群集3中的患者的PDL1表达最高（编码程序性细胞死亡1配体11）和HAVCR2（编码肝炎A病毒受体2）和最高的肿瘤突变负担（TMB）。在风险评估模型中，低风险组的患者的生存效果明显更好。此外，风险评分与阶段相结合可以作为LUAD患者的可靠独立预后指标。预后特征是选择抗肿瘤药物的新型生物标志物。低危患者倾向于更高的CTLA4表达（编码细胞毒性T-淋巴细胞相关蛋白4）和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终端luad。
Abstract
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.