Fibroblast growth factor 11 (FGF11) accelerates tumor proliferation in a variety of cancer types. This study aimed to examine the link between FGF11 and the prognosis of lung adenocarcinoma. FGF11 was searched in the Tumor Cancer Genome Atlas (TCGA) and ImmProt databases. The link between FGF11 and lung cancer clinical data was investigated using TCGA and Kaplan–Meier (KM)-plotter databases, and we developed a prediction model. Putative mechanisms of action were investigated using Gene Ontology (GO) and KEGG enrichment analyses. The GeneMANIA and STRING databases were used to search for genes that interact with FGF11, and the Tumor Immune Estimation Resource (TIMER) database was used to discover connections between FGF11 and immune cells, as well as any correlations with immune-related genes. We found that FGF11 expression was higher in the lung adenocarcinoma tissue than in the paracancerous tissue, and patients with high FGF11 expression had a lower overall survival, progression-free survival, and disease specific survival rate than those with low FGF11 expression. The expression of FGF11 was inversely linked to six types of infiltrating immune cells in the TIMER database and was associated with EGFR, VEGFA, BRAF, and MET expressions. The FGF11 gene is negatively correlated with the expression of most immune cells, mainly with various functional T cells including Th1, Th1-like, Treg, and Resting Treg characterization genes. These results indicate that FGF11 has the potential to be a new lung adenocarcinoma biomarker. It increases tumor cell immune escape by boosting T cell exhaustion in the tumor microenvironment, contributing to the poor prognosis of the patients with lung adenocarcinoma. These results provide incentive to further research FGF11 as a possible biomarker and drug target for patients with lung adenocarcinoma.

中文翻译：

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成纤维细胞生长因子 11 通过促进 T 细胞耗竭实现肿瘤细胞免疫逃逸并预测肺腺癌患者的不良预后

成纤维细胞生长因子 11 (FGF11) 可加速多种癌症类型的肿瘤增殖。本研究旨在探讨 FGF11 与肺腺癌预后之间的联系。在肿瘤癌症基因组图谱 (TCGA) 和 ImmProt 数据库中搜索了 FGF11。使用 TCGA 和 Kaplan–Meier (KM)-plotter 数据库研究了 FGF11 和肺癌临床数据之间的联系，并且我们开发了一个预测模型。使用基因本体论 (GO) 和 KEGG 富集分析研究了假定的作用机制。GeneMANIA 和 STRING 数据库用于搜索与 FGF11 相互作用的基因，肿瘤免疫估计资源 (TIMER) 数据库用于发现 FGF11 与免疫细胞之间的联系，以及与免疫相关基因的任何相关性。我们发现 FGF11 在肺腺癌组织中的表达高于癌旁组织，并且 FGF11 高表达患者的总生存期、无进展生存期和疾病特异性生存率均低于 FGF11 低表达患者。FGF11 的表达与 TIMER 数据库中的六种浸润性免疫细胞呈负相关，并与 EGFR、VEGFA、BRAF 和 MET 表达相关。FGF11基因与大多数免疫细胞的表达呈负相关，主要与各种功能性T细胞包括Th1、Th1-like、Treg和Resting Treg表征基因呈负相关。这些结果表明FGF11有可能成为一种新的肺腺癌生物标志物。它通过促进肿瘤微环境中的 T 细胞耗竭来增加肿瘤细胞的免疫逃逸，导致肺腺癌患者预后不良。这些结果为进一步研究 FGF11 作为肺腺癌患者可能的生物标志物和药物靶标提供了动力。