Abstract Background Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy characterized by rapid progression and poor prognosis. This study integrates bioinformatics with experimental validation to characterize the role of Frizzled-3 (FZD3), a Wnt receptor, in SCLC progression. Methods We analyzed transcriptomic data from 102 SCLC and 55 normal lung tissues retrieved from the Gene Expression Omnibus (datasets GSE6044, GSE40275, and GSE60052). Differential expression analysis was performed using the limma package, followed by GO and KEGG pathway enrichment analyses. To screen for robust prognostic markers, we employed machine learning algorithms—specifically LASSO and Random Forest—to select hub genes. The prognostic significance of FZD3 was assessed using multivariate Cox regression and Kaplan-Meier survival analysis. Validation assays, including qRT-PCR, Western blotting, and functional assays (proliferation, migration, invasion, and apoptosis), were conducted in SCLC cell lines and clinical specimens. Results A total of 1,192 differentially expressed genes were identified. Enrichment analysis revealed significant involvement in immune-related pathways and Wnt signaling. FZD3 was selected as a key hub gene and found to be upregulated in SCLC tissues and cell lines. High FZD3 expression was correlated with advanced clinical stage(by Kruskal-Wallis test), and poor prognosis (by Survival analysis). In vitro function assays demonstrated that FZD3 knockdown significantly attenuated SCLC cell proliferation, migration, and invasion while inducing apoptosis. Conclusion FZD3 is frequently overexpressed in SCLC and serves as an independent prognostic indicator for poor survival. Our findings elucidate the oncogenic role of FZD3 in SCLC, highlighting its potential as a therapeutic target and prognostic biomarker.
Lu et al. (2026) studied this question.