A Novel Five-Gene Signature Related to Clinical Outcome and Immune Microenvironment in Breast Cancer

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.

Keywords: Kif4A; biomarker; breast cancer; immune cell infiltration; signature.

FIGURE 1

The identification of DGEs in BC based on TCGA datasets. (A) Heat map of all DGEs between BC specimens and normal breast specimens. (B) Volcanic map of DGEs based on the standard of FC > 4.

FIGURE 2

Function Enrichment Analysis of DEGs. (A,B) KEGG and G Analysis of 140 upregulated genes in BC. (C,D) KEGG and G Analysis of 513 down-regulated genes in BC.

FIGURE 3

Identification of survival-related DGEs in BC patients. (A) high expression of SFRP1, SAA1 and RBP4 were associated with favorable long-term survival in BC patients. (B) High expression of KIF4A, UBE2C and COL11A1 was associated with poor prognosis in BC patients.

FIGURE 4

(A) The expression of the six survival-related genes in BC specimens and normal breast cancer specimens from TCGA and GTEx data. (B) The associations between the expressions of the six survival-related genes.

FIGURE 5

LASSO regression analysis of TCGA datasets identifies a five-gene risk profile for overall survival. (A) Adjustment of the proportional hazards model’s tuning parameters using cross-validation. (B) Scan of six BC genes with the LASSO coefficient spectrum. (C) Patient survival and BC status, as well as risk score distribution. (D) Kaplan-Meier was used to categorise patients based on their median risk of developing BC. (E) The risk signature’s predictive power was demonstrated using ROC curves.

FIGURE 6

The relationships between the risk score model and immune cell infiltration were investigated based on TCGA samples.

FIGURE 7

BC mutation cohorts in TCGA datasets. (A,B) Waterfall diagram depicting the TCGA BC cohort’s top 10 most frequently mutated genes, including KIF4A. (C) Overview of mutations in all BC samples.

FIGURE 8

Knockdown of KIF4A suppressed the proliferation of BC cells. (A) The expression of KIF4A in BC sample and normal samples were determined using GSE7904 datasets. (B) Analysis of KIF4A gene expression in BC cell lines was carried out using qRT-PCR. (C) RT-PCR was used to examine KIF4A expressions in MCF-7 and BT-20 cells transfected with si-NC or si-KIF4A. (D,E) CCK8 assays for the assessment of the effect of KIF4A knockdown on the proliferation of MCF-7 and BT-20 cells. **p < 0.01, ***p < 0.001.