基于 NK 细胞相关风险模型的乳腺癌肿瘤免疫微环境与基因突变相关预后标志物深入分析

The natural killer (NK) cell population is unique because it consists of innate lymphocytes capable of detecting and eliminating tumors and virus-infected cells. This research aims to identify a new prognostic signal in breast cancer (BRCA) based on NK-cell-related genes (NKRGs).

A variety of sequencing and gene mutation data, along with clinical information, were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Database (GEO). COX regression and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were conducted to identify prognostic genes.

In addition, the immune-related analysis was performed to evaluate the association between the immune microenvironment and clusters and risk model. The Edu assay, colony assay, wound healing assay, and transwell assay were performed to evaluate the cell proliferative and invasive abilities. A 4-NKRG-based prognostic model was constructed. Patients in high-risk groups were associated with poorer OS in TCGA and GSE42568.

Further, a nomogram was constructed for better prediction of the prognosis of patients with BRCA.

Finally, it was discovered that the over-expression of IFNE could suppress the proliferative and invasive abilities of BRCA cells, which might be a promising biomarker for patients with BRCA. As a result, we developed a novel 4-NKRG signal and nomogram capable of predicting the prognosis of patients with BRCA.

Additionally, this model was closely associated with the immune microenvironment, which opened new therapeutic avenues for the treatment of cancer in the future.