Abstract

Breast cancer (BC) is the most frequent cancer in women and the main cause of cancer-related deaths in the globe, according to the World Health Organization. The need for biomarkers that can help predict survival or guide treatment decisions in BC patients is critical in order to provide each patient with an individualized treatment plan due to the wide range of prognoses and therapeutic responses. A reliable prognostic model is essential for determining the best course of treatment for patients. Patients’ clinical and pathological data, as well as their mRNA expression levels at level 3, were gleaned from the TCGA databases. Differentially expressed genes (DEGs) between BC and non-tumor specimens were identified. Tumor immunity analyses have been utilized in order to decipher molecular pathways and their relationship to the immune system. The expressions of KIF4A in BC cells were determined by RT-PCR. To evaluate the involvement of KIF4A in BC cell proliferation, CCK-8 tests were used. In this study, utilizing FC > 4 and p < 0.05, we identified 140 upregulated genes and 513 down-regulated genes. A five-gene signature comprising SFRP1, SAA1, RBP4, KIF4A and COL11A1 was developed for the prediction of overall survivals of BC. Overall survival was distinctly worse for patients in the high-risk group than those in the low-risk group. Cancerous and aggressiveness-related pathways and decreased B cell, T cell CD4+, T cell CD8+, Neutrophil and Myeloid dendritic cells levels were seen in the high-risk group. In addition, we found that KIF4A was highly expressed in BC and its silence resulted in the suppression of the proliferation of BC cells. Taken together, as a possible prognostic factor for BC, the five-gene profile created and verified in this investigation could guide the immunotherapy selection.

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