Hub metastatic gene signature and risk score of breast cancer patients with small tumor sizes using WGCNA

Abstract

Abstract Background Breast cancer (BC) is the most common cancer in women and accounts for approximately 15% of all cancer deaths among women globally. The underlying mechanism of BC patients with small tumor size and developing distant metastasis (DM) remains elusive in clinical practices. Methods We integrated the gene expression of BCs from ten RNAseq datasets from Gene Expression Omnibus (GEO) database to create a genetic prediction model for distant metastasis-free survival (DMFS) in BC patients with small tumor sizes (≤ 2 cm) using weighted gene co-expression network (WGCNA) analysis and LASSO cox regression. Results ABHD11, DDX39A, G3BP2, GOLM1, IL1R1, MMP11, PIK3R1, SNRPB2, and VAV3 were hub metastatic genes identified by WGCNA and used to create a risk score using multivariable Cox regression. At the cut-point value of the median risk score, the high-risk score (≥ median risk score) group had a higher risk of DM than the low-risk score group in the training cohort [hazard ratio (HR) 4.51, p < 0.0001] and in the validation cohort (HR 5.48, p = 0.003). The nomogram prediction model of 3-, 5-, and 7-year DMFS shows good prediction results with C-indices of 0.72–0.76. The enriched pathways were immune regulation and cell–cell signaling. EGFR serves as the hub gene for the protein–protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3. Conclusion Prognostic gene signature was predictive of DMFS for BCs with small tumor sizes. The protein–protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3 connected by EGFR merits further experiments for elucidating the underlying mechanisms. Graphical abstract