Hu Feiming, Hu Chenchen, He Yuanli, Sun Yuanjie, Han Chenying, Zhang Xiyang, Yu Lingying, Shi Daimei, Sun Yubo, Zhang Junqi, Jiang Dongbo, Yang Shuya, Yang Kun
Department of Immunology, The Fourth Military Medical University, Xi'an 710032, China.
Yan'an Key Laboratory of Microbial Drug Innovation and Transformation, School of Basic Medicine, Yan'an University, Yan'an 716000, China.
Biomedicines. 2025 Jan 9;13(1):151. doi: 10.3390/biomedicines13010151.
The tumor microenvironment (TME) plays a crucial role in the progression of lung adenocarcinoma (LUAD). However, understanding its dynamic immune and stromal modulation remains a complex challenge. We utilized the ESTIMATE algorithm to evaluate the immune and stromal components of the LUAD TME from the TCGA database. Correlations between these components and clinical characteristics and patient prognosis were analyzed. Toll-like receptor 7 (TLR7) was identified as a key prognostic biomarker through PPI network and COX regression analysis. Validation of TLR7 expression was conducted using GEO data, qPCR, WB, and IHC. A prognostic model was developed using a nomogram, incorporating TLR7 expression. Enrichment analysis, the Tumor Immune Estimation Resource database, and single-sample gene set enrichment analysis were used to explore TLR7's potential function. The response of the TLR7 subgroup to immunotherapy and drug sensitivity was observed. We found significant associations between the immune and stromal components of LUAD TME and clinical features and prognosis. Specifically, TLR7 was identified as a prognostic biomarker, where lower expression in tumor tissues was linked to worse outcomes. This finding was further confirmed by comparing TLR7 expression in LUAD cells to normal bronchial epithelial cells, revealing lower expression in the tumor cells. Incorporating TLR7 into a nomogram prognostic model resulted in a good predictor of patient survival. Additionally, TLR7 was associated with immune function and positively correlated with various immune cells. Importantly, patients with high TLR7 expression were more likely to benefit from anti-PD-1 checkpoint blockade therapy. We also identified four treatment candidates for patients with high TLR7 expression. TLR7 is a powerful clinical feature that predicts patient prognosis, immunotherapeutic response, and drug candidates, providing additional insights for the treatment of LUAD.
肿瘤微环境(TME)在肺腺癌(LUAD)的进展中起着关键作用。然而,了解其动态免疫和基质调节仍然是一项复杂的挑战。我们利用ESTIMATE算法从TCGA数据库评估LUAD TME的免疫和基质成分。分析了这些成分与临床特征及患者预后之间的相关性。通过蛋白质-蛋白质相互作用(PPI)网络和COX回归分析,将Toll样受体7(TLR7)确定为关键的预后生物标志物。使用GEO数据、qPCR、蛋白质免疫印迹(WB)和免疫组化(IHC)对TLR7表达进行验证。使用列线图建立了一个预后模型,纳入了TLR7表达。利用富集分析、肿瘤免疫估计资源数据库和单样本基因集富集分析来探索TLR7的潜在功能。观察了TLR7亚组对免疫治疗的反应和药物敏感性。我们发现LUAD TME的免疫和基质成分与临床特征及预后之间存在显著关联。具体而言,TLR7被确定为一种预后生物标志物,肿瘤组织中较低的表达与较差的预后相关。通过比较LUAD细胞与正常支气管上皮细胞中的TLR7表达,进一步证实了这一发现,结果显示肿瘤细胞中表达较低。将TLR7纳入列线图预后模型可很好地预测患者生存情况。此外,TLR7与免疫功能相关,与多种免疫细胞呈正相关。重要的是,TLR7高表达的患者更有可能从抗PD-1检查点阻断治疗中获益。我们还为TLR7高表达的患者确定了四种治疗候选药物。TLR7是一种强大的临床特征,可预测患者预后、免疫治疗反应和候选药物,为LUAD的治疗提供了更多见解。