TFP12 as a key regulator of sentinel lymph node metastasis in breast cancer

Breast cancer remains one of the most prevalent malignancies worldwide, with sentinel lymph nodes (SLNs) serving as critical gateways for early metastasis. While SLN status is routinely used for clinical staging, the molecular features of SLN-associated genes and their prognostic significance are not fully understood. This study elucidates the functional roles of SLN-associated genes in breast carcinogenesis, establishing a molecular subtyping framework with prognostic significance through integrated multi-omics analysis.

Differential expression analysis utilizing high-throughput sequencing was conducted to identify SLN-associated genes. Additionally, Molecular subtyping was performed through ConsensusClusterPlus, followed by implementation of a least absolute shrinkage and selection operator (LASSO) regression-based predictive modeling framework to establish the optimal prognostic stratification system. Finally, functional annotation analyses integrated multi-platform databases systematically decoded the biological networks underlying the prognostic model. Functional validation through Transwell migration and scratch wound healing assays confirmed TFP12's impact in breast cancer.

This study revealed 218 SLN-associated genes, with functional enrichment predominantly involving TNF signaling pathway regulation. We discovered that EPCAM, TIMP1, and CD19 are potent regulators of the expression of these 14 genes. ConsensusClusterPlus application stratified breast cancer samples into two distinct molecular subtypes. LASSO regression constructed a prognostic model showing significant associations with immune cell infiltration dynamics and therapeutic resistance mechanisms. In the subsequent basic experimental verification, our analysis revealed that TFP12 suppresses breast cancer invasion and migration, with significant correlations to metastasis-related genes CCL19 and NGFR, as confirmed by overexpressing cell lines and The Cancer Genome Atlas (TCGA) database analysis.

This investigation reveals the pivotal role of SLN-associated genes, thereby elucidating the intricate mechanisms underlying the progression of breast cancer. The established prognostic framework provides mechanistic perspectives for developing actionable therapeutic targets in translational oncology.