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| 多组学整合策略在预测肺癌免疫治疗疗效中的研究进展 |
| Progress of Multi-Omics Integration Strategies for Predicting the Efficacy of Lung Cancer Immunotherapy |
| 投稿时间：2025-09-01 修订日期：2025-11-11 |
| DOI： |
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| 中文关键词: 肺癌 肿瘤免疫治疗 多组学 精准诊疗 |
| 英文关键词:Lung cancer Cancer immunotherapy Multi-omics Precision medicine |
| 基金项目:浙江省医药卫生健康项目(2022KY1283) |
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| 中文摘要: |
| 近年来,免疫检查点抑制剂的应用已彻底改变肺癌的治疗、管理及预后,但疗效存在显著个体差异,现有的单一生物标志物因存在一定局限性而难以满足精准需求。多组学整合策略通过综合基因组、转录组、蛋白质组及空间组学等多维度数据,系统解析肿瘤微环境异质性及免疫调控网络,显著提升了免疫治疗疗效预测的准确性。本文系统综述了多组学技术在肿瘤微环境解析及在肺癌免疫治疗预测中的应用进展,并指出数据整合、算法优化、检测成本高昂及前瞻性验证不足等挑战,以期为推动肺癌免疫治疗精准化提供理论依据与方向参考。 |
| 英文摘要: |
| In recent years, the application of immune checkpoint inhibitors has revolutionized the treatment, management, and prognosis of lung cancer. However, there is significant individual variability in treatment efficacy, and existing single biomarkers are insufficient to meet the demands of precision medicine due to their inherent limitations. Multi-omics integration strategies, by synthesizing multidimensional data from genomics, transcriptomics, proteomics, and spatial omics, enable a systematic dissection of tumor microenvironment heterogeneity and immune regulatory networks, thereby significantly enhancing the accuracy of immunotherapy efficacy prediction. This review comprehensively summarizes the advances in multi-omics technologies for deciphering the tumor microenvironment and their application in predicting responses to lung cancer immunotherapy. Furthermore, it highlights prevailing challenges such as data integration complexities, algorithm optimization, high detection costs, and a lack of robust prospective validation. The aim is to provide a theoretical foundation and future perspectives for advancing precision immunotherapy in lung cancer. |
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