Construction and Evaluation of a Prognostic Model Based on Metastasis-Associated Genes in Breast Cancer

Abstract

Abstract Objective: The aim of the study was to investigate the gene expression profile features in distant metastatic breast cancer (BC) patients, identify the metastasis-associated genes correlated with prognosis, and construct a survival rate nomogram. Methods: Transcriptome data of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database, and divided into metastatic and non-metastatic groups. Differentially expressed genes (DEGs) were analyzed between the two groups, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed to explore the potential functions of DEGs. Univariate COX, LASSO regression, and multivariate Cox regression models were applied to screen prognostic-related genes, and a prediction model was established. Results: A total of 215 DEGs were identified. FAM9C, CRISP2, TFPI2, TUBA3E, IL12Rβ2, BP1 and CSN3 were independent influencing factors for overall survival (OS) rate. Area under the curve (AUC) values outweighed 0.6, and calibration curves did not deviate from the reference line. Conclusion: The metastasis-related genes prognostic nomogram for BC patients established in this study had favourablepredictive power that could provide a theoretical reference for subsequent studies.