Background: Invasive ductal carcinoma (IDC) is the most common breast cancer worldwide. Nowadays, due to IDC heterogeneity and its high capacity for metastasis, it is necessary to discover novel diagnostic and prognostic biomarkers. Thus, this study aimed to identify new prognostic genes of IDC using an integrated bioinformatics approach. Methods: Using the Gene Expression Omnibus (GEO) database, we downloaded publicly available data of the whole-genome mRNA expression profile from the first three stages of IDC in two expression profiling datasets, GSE29044 and GSE32291; intra-group data repeatability tests were conducted using Pearson’s correlation test, and the differentially expressed genes (DEGs) were identified using the online tool GEO2R, followed by the construction of a protein‑protein interaction network (PPI-net) with the common DEGs identified in the three analyzed stages using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software, from these PPI-net we identify the hub genes (prognostic genes). Results: We found seven genes [WW domain-containing E3 ubiquitin-protein ligase 1 (WWP1), STIP1 homology and U-box containing protein 1 (STUB1), F-box and WD repeat domain containing 7 (FBXW7), kelch like family member 13 (KLHL13), ubiquitin-conjugating enzyme E2 Q1 (UBE2Q1), tripartite motif-containing 11 (TRIM11), and the beta-transducin repeat containing E3 ubiquitin-protein ligase (BTRC)] as potential candidates for IDC prognostic biomarkers, which were mainly enriched in the Ubiquitin-specific protease activity, cytoskeletal protein binding, and ligase activity. The role of these genes in the pathophysiology of IDC is not yet well characterized, representing a way to improve our understanding of the process of tumorigenesis and the underlying molecular events of IDC. Conclusions: Genes identified may lead to the discovery of new prognostic targets and precise therapeutics for IDC.