Liu Min, Li Qiao, Meng Xiaohong, Cui Yanan, Sun Weirong, Wang Hongmei, Gao Qingjun
Department of General Medicine, The 8th Medical Center of PLA General Hospital, Beijing, China.
The Eighth Medical Center of Chinese PLA General Hospital, Beijing, China.
Medicine (Baltimore). 2024 Dec 6;103(49):e40569. doi: 10.1097/MD.0000000000040569.
Despite significant advancements in the treatment of non-small cell lung cancer (NSCLC) through immunotherapy, many patients still exhibit resistance to this approach. This study aims to identify the characteristics of individuals who can benefit from immunotherapy, especially immune checkpoint inhibitors (ICIs), and to investigate optimal strategies for patients who experience resistance to it. Data on gene expression patterns and clinical information from NSCLC patients who underwent immunotherapy were obtained from the Gene Expression Omnibus databases. A predictive signature for immunotherapy prognosis was developed using a training dataset and validated with validation datasets. Immune landscape and immunotherapy responsiveness analyses were conducted to assess the risk signature. Additionally, data from a study on immunotherapy were used to evaluate the correlation between MNX1 mutation and the effectiveness of ICIs, including clinical data and whole exome sequencing data. We identified 7 genes in NSCLC using RNA-seq data that were significantly associated with the efficacy of immunotherapy. Based on these genes, a risk signature was created to predict the efficacy of ICIs. Patients in the low-risk group had better outcomes compared to those in the high-risk group after receiving ICIs. Additionally, our analysis of the immune landscape revealed a significant association between the high-risk signature and an immunosuppressive state. We also discovered an unexpected role of tumor-specific MNX1 and HOXD1 in suppressing the immune response against cancer. Notably, NSCLC patients with MNX1 mutations experienced prolonged progression-free survival. Furthermore, we identified several medications that exhibited increased sensitivity in patients with high MNX1 expression, with topoisomerase inhibitors showing the highest level of sensitivity. This could be a potential strategy to improve the efficacy of ICIs. The risk signature has demonstrated its effectiveness in forecasting the prognosis of NSCLC treated with ICIs, enabling better patient stratification and more accurate prediction of immunotherapy response. Moreover, MNX1 and HOXD1 have been identified as key molecules related to immunotherapy resistance. Inhibition of these molecules, combined with current ICIs, offers novel strategies for the management of NSCLC patients.
尽管免疫疗法在非小细胞肺癌（NSCLC）治疗方面取得了重大进展，但许多患者对这种治疗方法仍表现出耐药性。本研究旨在确定能够从免疫疗法，尤其是免疫检查点抑制剂（ICI）中获益的个体特征，并研究对其产生耐药性的患者的最佳治疗策略。从基因表达综合数据库中获取接受免疫疗法的NSCLC患者的基因表达模式和临床信息数据。使用训练数据集开发免疫疗法预后的预测特征，并通过验证数据集进行验证。进行免疫微环境和免疫疗法反应性分析以评估风险特征。此外，一项免疫疗法研究的数据用于评估MNX1突变与ICI疗效之间的相关性，包括临床数据和全外显子测序数据。我们使用RNA测序数据在NSCLC中鉴定出7个与免疫疗法疗效显著相关的基因。基于这些基因，创建了一个风险特征来预测ICI的疗效。接受ICI治疗后，低风险组患者的预后优于高风险组。此外，我们对免疫微环境的分析揭示了高风险特征与免疫抑制状态之间的显著关联。我们还发现肿瘤特异性MNX1和HOXD1在抑制针对癌症的免疫反应中具有意想不到的作用。值得注意的是，携带MNX1突变的NSCLC患者无进展生存期延长。此外，我们确定了几种在MNX1高表达患者中表现出更高敏感性的药物，其中拓扑异构酶抑制剂的敏感性最高。这可能是提高ICI疗效的一种潜在策略。该风险特征已证明其在预测接受ICI治疗的NSCLC预后方面的有效性，能够实现更好的患者分层和更准确地预测免疫疗法反应。此外，MNX1和HOXD1已被确定为与免疫疗法耐药相关的关键分子。抑制这些分子并结合当前的ICI，为NSCLC患者的管理提供了新的策略。
