ArticleJournal of oncology2023
Fibroblast Growth Factor 11 Enables Tumor Cell Immune Escape by Promoting T Cell Exhaustion and Predicts Poor Prognosis in Patients with Lung Adenocarcinoma.
Article in Journal of oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The trial behind it
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- NCAPD2 Modulates MHC-I Antigen Presentation via the PI3K/AKT Axis to Drive Metastatic Progression in Gastric Cancer.Digestive diseases and sciences · 2026Article
- Pathology and Therapeutic Significance of Fibroblast Growth Factors.Targets (Basel) · 2025Article
- Distinct myeloid-derived suppressor cell populations in human glioblastoma.Science (New York, N.Y.) · 2025Article
- Uncovering Candidate Genes Associated with Cardiovascular Disease in Patients with Arteriovenous Fistula and End-Stage Renal Disease.Cardiorenal medicine · 2025Article
- LINC00342 regulates the PI3K-AKT signaling pathway via the miR-149-5p/FGF11 axis and affects the progression of oral cancer.Discover oncology · 2024Article
- Fibroblast Growth Factor 11 (FGF11) Promotes Progression and Cisplatin Resistance Through the HIF-1α/FGF11 Signaling Axis in Ovarian Clear Cell Carcinoma.Cancer management and research · 2023Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
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