# Recognition of immunogenomic signature and prognostic value of the subtype of epithelial-mesenchymal transition in breast cancer

## TL;DR

This study identifies a new EMT gene signature that predicts breast cancer prognosis and treatment response based on immune and genomic features.

## Contribution

A novel EMT-related gene signature is developed to predict prognosis and treatment sensitivity in breast cancer patients.

## Key findings

- The EMT signature includes genes like GKN2, FZD2, and NDRG2, validated for accuracy in predicting patient outcomes.
- Low-risk patients show higher immune infiltration and better sensitivity to chemotherapy and immunotherapy.
- The signature's reliability is confirmed using C-index, calibration curves, and comparison with previous studies.

## Abstract

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.

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.

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.

This novel EMT signature offers excellent potential for predicting the prognosis, tumor immune heterogeneity, and therapeutic responses in breast cancer.

•We identified a novel EMT signature to predict prognosis of breast cancer patients.•We demonstrated the reliability of the EMT signature by several ways.•The low-risk patients exhibit better sensitivity to chemotherapy.

We identified a novel EMT signature to predict prognosis of breast cancer patients.

We demonstrated the reliability of the EMT signature by several ways.

The low-risk patients exhibit better sensitivity to chemotherapy.