| 吴韫涵,陈遐林.多组学整合策略在预测肺癌免疫治疗疗效中的研究进展[J].肿瘤学杂志,2026,32(3):192-198. |
| 多组学整合策略在预测肺癌免疫治疗疗效中的研究进展 |
| Multi-Omics Integration for Predicting Response to Immunotherapy in Lung Cancer： Advances and Applications |
| 投稿时间：2025-09-01 |
| DOI：10.11735/j.issn.1671-170X.2026.03.B003 |
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| 中文关键词: 肺肿瘤 免疫治疗 多组学 精准诊疗 |
| 英文关键词:lung neoplasms 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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| 摘要点击次数: 27 |
| 全文下载次数: 8 |
| 中文摘要: |
| 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，但患者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学、转录组学、蛋白质组学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。全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: |
| Abstract： The advent of immune checkpoint inhibitors has transformed the therapeutic landscape for lung cancer. Despite this progress， significant interpatient heterogeneity in treatment response persists， and conventional single biomarkers often fall short in guiding precision therapy due to inherent limitations such as spatial-temporal variability and suboptimal predictive power. Multi-omics integration strategies address this gap by holistically analyzing layered data from genomics， transcriptomics， proteomics， and spatial omics. This approach provides a comprehensive， systems-level view of tumor microenvironment heterogeneity and the complex immune regulatory networks， leading to substantially improved accuracy in predicting immunotherapy outcomes. This review synthesizes recent advances in applying multi-omics technologies to dissect the tumor microenvironment and their pivotal role in forecasting responses to immunotherapy in lung cancer. We also discuss key translational challenges， including technical hurdles in data integration and algorithm development， economic barriers related to high costs， and the critical need for prospective validation in clinical trials. By outlining these aspects， this paper aims to offer a consolidated framework and forward-looking insights to propel the field toward more precise and effective immunotherapeutic strategies for lung cancer patients. |
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