LAUSR

Background: Breast cancer is a heterogeneous disease. Small tumors with extensive lymph node involvement (STEL) in breast cancer often reflect a biologically aggressive phenotype and poor prognosis. The aim of this study was to identify key genes associated with STEL and investigate their prognostic values in breast cancer. Methods: RNA-sequencing data of breast cancer were acquired from The Cancer Genome Atlas (TCGA) database for differential analysis, and weighted gene correlation network analysis (WGCNA) was performed to identify coexpressed gene modules associated with tumor size and lymph node metastasis. Gene set enrichment analysis was used to investigate the biofunctions of the identified genes. A combination of least absolute shrinkage and selection operator and Cox regression analyses was conducted to establish the risk predictive signature, and time-dependent receiver-operating characteristic and Kaplan‒Meier analyses were used to evaluate its prediction precision. Quantitative reverse transcriptional polymerase chain reaction was used to validate the expression levels of the key genes from the signature. Results: A total of 2777 genes from 3 coexpressed gene modules were identified by WGCNA, and 880 differentially expressed genes were screened by transcriptome analysis. The 63 overlapping genes between the 2 gene sets were considered STEL-associated genes, and a 9-gene risk predictive signature was established based on them, with area under curves at 3, 5, and 7 years reaching 0.810, 0.811, and 0.753, respectively. Conclusion: This study demonstrated the transcriptome profile of STEL breast cancer and successfully established a risk predictive signature with satisfactory accuracy. These findings might provide new insight into understanding the genetic etiology of breast cancer.