一种新型线粒体相关算法用于预测肺腺癌患者的生存结局及药物敏感性
A novel mitochondria-related algorithm for predicting the survival outcomes and drug sensitivity of patients with lung adenocarcinoma
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影响因子:4
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
DOI:
10.3389/fmolb.2024.1397281
摘要
线粒体一直被认为与恶性肿瘤的发生和发展密切相关，但关于肺腺癌（LUAD）中线粒体的生物信息学分析尚未报道。本研究建立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，用于预测终末期LUAD患者的生存结局和肿瘤免疫状态。我们将LUAD患者分为三类簇，簇1的生存预后最佳。簇3的患者中PDL1（编码程序性细胞死亡配体1）和HAVCR2（编码乙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预后显著优于高风险组。结合TNM分期，风险评分可作为LUAD患者的独立预后指标。预后特征作为一种新颖有效的生物标志物，有助于选择抗肿瘤药物。低风险组患者中，CTLA4（编码细胞毒性T淋巴细胞相关蛋白4）和HAVCR2的表达较高；高风险组患者对顺铂、多西他赛、厄洛替尼、吉西他滨和紫杉醇更敏感，而低风险组则可能更受吉非替尼的益处。我们构建的这套算法结合共识聚类与风险评估，能有效预测生存结局，为终末期LUAD患者的抗肿瘤药物治疗提供指导。
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.