Objective: A thorough examination of PLKs in breast cancer, including their expression and prognosis.

Methods: With the help of the Oncomine database, the transcript levels of PLKs in breast cancer were examined. The changes in PLKs expression with tumor stage and indeed the relationship between PLKs expression and stage of cancer in women with breast cancer were scrutinized by using the GEPIA database. Based on Kaplan-Meier plots, breast cancer patients were assessed for their prognosis. Breast cancer gene expression and mutations were analyzed within the cBioPortal database.

Results: According to Oncomine data, PLK1 and PLK4 mRNA expression levels were dramatically elevated in breast cancer patients while PLK2 and PLK5P levels were significantly downregulated. PLK1 and PLK4 expression were discovered to be greater in breast cancer tissues than in healthy tissues following analysis of the GEPIA database (P < 0.05). High levels of PLK1 and PLK4 transcripts have been linked to poor relapse-free survival rates across all patients with breast cancer according to the Kaplan-Meier Plotter database. The high levels of PLK2, PLK3, and PLK5 were associated with a higher recurrence-free survival rate. In the cBioPortal database, PLK was altered in 9.6% of breast cancer samples. Genetic alterations occurred in 15.07% of clinically counted invasive breast cancers, with mutations in 4.11%, gene amplifications in 9.59%, and gene deletion mutations in 1.37%. Additionally, the KEGG database demonstrates that PLKs are crucial for the cell cycle. The findings imply that elevated PLK1 and PLK4 expression in tissues of breast cancer might contribute significantly to the carcinogenesis of breast cancer. Moreover, PLK1 and PLK4 are highly expressed in breast cancer, and their use as molecular markers to identify high-risk subsets from patients with breast cancer is potentially possible.

Conclusions: For the precise therapy of breast cancers, PLK1 and PLK4 are potential targets, while PLK2, PLK3, and PLK5 are brand-new biomarkers for predicting the prognosis of breast cancer.