Background
Accumulating evidence has revealed that epithelial-mesenchymal transition (EMT) plays a crucial role in tumor progression and the immune microenvironment, which further results in a high rate of recurrence and metastasis. The EMT immune signaling pathway provides a great perspective for designing personalized therapies.
Methods
In this study, 1223 RNA-seq samples were obtained from the TCGA-BRCA dataset. A total of 381 EMT-related differentially expressed genes were analyzed and combined with clinical parameters, and the matrix was randomly divided into training and testing cohorts at a ratio of 7:3. The training cohort was used to develop an EMT signature, including GKN2, FZD2, NDRG2, SCUBE2, ALX4, CCL19, SDC1, EZR, CPEB1, and HRG genes, and the accuracy of this signature was validated by testing and GSE158309 cohorts.
Results
A risk score model and clinical parameters were used to establish a nomogram for predicting prognosis. The C-index (0.719), calibration curves, and model comparison with four previous studies demonstrated the reliability of the EMT signature, the biological phenotypes of which were tested for functional enrichment, immune infiltration, and tumor mutation. Additionally, patients' responses to immunotherapy and chemotherapy were assessed. Our results showed that the low-risk group had higher immune infiltration, tumor mutational burden, microsatellite instability levels, immune checkpoint inhibitor expression, tumor immune dysfunction and exclusion scores, and immunophenoscore, which could predict patient sensitivity to immunotherapy. Moreover, low-risk patients exhibit better sensitivity to chemotherapy.
Conclusion
This novel EMT signature offers excellent potential for predicting the prognosis, tumor immune heterogeneity, and therapeutic responses in breast cancer.
扫码关注我们
求助内容:
应助结果提醒方式:
