Yang Yi, Liu Hong-Li, Liu Yi-Jing
Chongqing Key Laboratory of Translational, Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, China.
Front Genet. 2022 May 13;13:912125. doi: 10.3389/fgene.2022.912125. eCollection 2022.
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 < 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.
根据世界卫生组织的数据，乳腺癌（BC）是女性中最常见的癌症，也是全球癌症相关死亡的主要原因。由于乳腺癌患者的预后和治疗反应范围广泛，因此迫切需要能够帮助预测生存或指导治疗决策的生物标志物，以便为每位患者提供个性化的治疗方案。可靠的预后模型对于确定患者的最佳治疗方案至关重要。从TCGA数据库中收集了患者的临床和病理数据以及他们在3级的mRNA表达水平。鉴定了BC与非肿瘤标本之间的差异表达基因（DEG）。利用肿瘤免疫分析来解读分子途径及其与免疫系统的关系。通过RT-PCR测定BC细胞中KIF4A的表达。为了评估KIF4A在BC细胞增殖中的作用，使用了CCK-8试验。在本研究中，利用FC>4和<0.05，我们鉴定出140个上调基因和513个下调基因。开发了一个包含SFRP1、SAA1、RBP4、KIF4A和COL11A1的五基因特征用于预测BC的总生存期。高风险组患者的总生存期明显比低风险组患者差。在高风险组中观察到与癌症和侵袭性相关的途径以及B细胞、T细胞CD4、T细胞CD8、中性粒细胞和髓样树突状细胞水平降低。此外，我们发现KIF4A在BC中高表达，其沉默导致BC细胞增殖受到抑制。综上所述，作为BC可能的预后因素，本研究中创建并验证的五基因谱可指导免疫治疗的选择。
