背景:乳腺癌(BC)是女性中最常见的癌症,约占全球女性所有癌症死亡人数的15%。在临床实践中,具有小肿瘤大小和发生远处转移(DM)的BC患者的潜在机制仍然难以捉摸。
方法:我们整合了来自基因表达综合(GEO)数据库的10个RNAseq数据集的BCs的基因表达,以使用加权基因共表达网络(WGCNA)分析和LASSOcox回归,创建了具有小肿瘤大小(≤2cm)的BC患者的无远处转移生存期(DMFS)的遗传预测模型。
结果:ABHD11、DDX39A、G3BP2,GOLM1,IL1R1,MMP11,PIK3R1,SNRPB2和VAV3是通过WGCNA鉴定的中心转移基因,并用于使用多变量Cox回归创建风险评分。在中位数风险评分的切点值处,在训练队列[风险比(HR)4.51,p<0.0001]和验证队列(HR5.48,p=0.003)中,高风险评分(≥中位风险评分)组的DM风险高于低风险评分组.3-的列线图预测模型,5-,7年DMFS显示出良好的预测结果,C指数为0.72-0.76。富集的途径是免疫调节和细胞-细胞信号传导。EGFR充当PIK3R1、IL1R1、MMP11、GOLM1和VAV3的蛋白质-蛋白质相互作用网络的中心基因。
结论:预后基因特征可预测肿瘤小的BCs的DMFS。通过EGFR连接的PIK3R1,IL1R1,MMP11,GOLM1和VAV3的蛋白质-蛋白质相互作用网络值得进一步实验以阐明潜在的机制。
BACKGROUND: Breast cancer (BC) is the most common cancer in women and accounts for approximately 15% of all cancer deaths among women globally. The underlying mechanism of BC patients with small tumor size and developing distant metastasis (DM) remains elusive in clinical practices.
METHODS: We integrated the gene expression of BCs from ten RNAseq datasets from Gene Expression Omnibus (GEO) database to create a genetic prediction model for distant metastasis-free survival (DMFS) in BC patients with small tumor sizes (≤ 2 cm) using weighted gene co-expression network (WGCNA) analysis and LASSO cox regression.
RESULTS: ABHD11, DDX39A, G3BP2, GOLM1, IL1R1, MMP11, PIK3R1, SNRPB2, and VAV3 were hub metastatic genes identified by WGCNA and used to create a risk score using multivariable Cox regression. At the cut-point value of the median risk score, the high-risk score (≥ median risk score) group had a higher risk of DM than the low-risk score group in the training cohort [hazard ratio (HR) 4.51, p < 0.0001] and in the validation cohort (HR 5.48, p = 0.003). The nomogram prediction model of 3-, 5-, and 7-year DMFS shows good prediction results with C-indices of 0.72-0.76. The enriched pathways were immune regulation and cell-cell signaling. EGFR serves as the hub gene for the protein-protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3.
CONCLUSIONS: Prognostic gene signature was predictive of DMFS for BCs with small tumor sizes. The protein-protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3 connected by EGFR merits further experiments for elucidating the underlying mechanisms.