Abstract
Background/Objectives: Lung adenocarcinoma (LUAD), the predominant subtype of non-small cell lung cancer (NSCLC), is frequently diagnosed at advanced stages with distant metastasis, underscoring the need for effective prognostic biomarkers. Fibroblast growth factor 2 (FGF2), a multifunctional regulator, has shown to play contradictory roles in cancer progression. Methods: We analyzed three independent Gene Expression Omnibus (GEO) datasets (GSE19804, GSE18842, and GSE19188) to identify consistently dysregulated genes in LUAD. Functional enrichment (GO, KEGG, and cancer hallmark analysis), protein–protein interaction (PPI) network construction, and hub gene prioritization were performed using public bioinformatic tools. Survival analyses were conducted via the Kaplan–Meier Plotter. The expression of FGF2 was validated across multiple platforms, including TCGA, CPTAC, TNMplot, LCE, and the Human Protein Atlas. Functional assays (Transwell migration and wound healing) demonstrated that exogenous FGF2 significantly suppressed LUAD cell motility in vitro. Results: A total of 949 differentially expressed genes (DEGs) were commonly identified across datasets, with enrichment in cell adhesion and metastasis-related pathways. Among the 11 hub genes identified, FGF2 was consistently downregulated in LUAD tissues across all datasets and stages. Higher FGF2 expression was associated with longer overall and progression-free survival. In vitro, FGF2 treatment significantly suppressed the migration and wound healing abilities of LUAD cell lines. Conclusions: FGF2 is downregulated in LUAD and inversely associated with metastatic progression and poor prognosis. The observed reduction in cancer cell motility upon FGF2 treatment in vitro, together with its expression pattern, supports a potential tumor-suppressive role and suggests that FGF2 may serve as a candidate non-invasive biomarker for monitoring LUAD metastasis.
| Original language | English |
|---|---|
| Article number | 250 |
| Journal | Diagnostics |
| Volume | 16 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Jan 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- bioinformatic analysis
- differentially expressed genes (DEGs)
- fibroblast growth factor 2 (FGF2)
- lung adenocarcinoma (LUAD)
- metastasis
ASJC Scopus subject areas
- Internal Medicine
- Clinical Biochemistry
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