免疫逃避最近成为肺腺癌（LUAD）免疫治疗效果的障碍之一。然而， LUAD中免疫逃逸标志物的临床意义和功能大多未被澄清。在本研究中，我们通过系统集成10种机器学习算法，构建了一个稳定准确的免疫逃避评分（IERS）。为了探索潜在的机制，我们进一步研究了不同IERS亚型的临床意义，功能状态，TME相互作用和基因组改变。此外，我们通过细胞实验验证了模型中最重要的变量。IERS是全生存的独立风险因素，优于传统的临床变量和已发布的分子标志物。基于IERS的风险分层可很好地应用于LUAD患者。此外，高IERS与更强的肿瘤增殖和免疫抑制有关。低IERS表现出丰富的淋巴细胞浸润和活跃的免疫活性。最后，高IERS对LUAD的一线化疗更为敏感，而低IERS对免疫治疗更为敏感。总之，IERS可能作为一个有前途的临床工具，以改善个体LUAD患者的风险分层和临床管理，并增进对免疫逃避的理解。版权所有© 2023 Wang、Huang、Zhou和Li。

Immune escape has recently emerged as one of the barriers to the efficacy of immunotherapy in lung adenocarcinoma (LUAD). However, the clinical significance and function of immune escape markers in LUAD have largely not been clarified.In this study, we constructed a stable and accurate immune escape score (IERS) by systematically integrating 10 machine learning algorithms. We further investigated the clinical significance, functional status, TME interactions, and genomic alterations of different IERS subtypes to explore potential mechanisms. In addition, we validated the most important variable in the model through cellular experiments.The IERS is an independent risk factor for overall survival, superior to traditional clinical variables and published molecular signatures. IERS-based risk stratification can be well applied to LUAD patients. In addition, high IERS is associated with stronger tumor proliferation and immunosuppression. Low IERS exhibited abundant lymphocyte infiltration and active immune activity. Finally, high IERS is more sensitive to first-line chemotherapy for LUAD, while low IERS is more sensitive to immunotherapy.In conclusion, IERS may serve as a promising clinical tool to improve risk stratification and clinical management of individual LUAD patients and may enhance the understanding of immune escape.Copyright © 2023 Wang, Huang, Zhou and Li.