# Dual Immunological Prognostic Models for Risk Stratification and Treatment Insights in Triple-Negative Breast Cancer

## TL;DR

This study develops two immunological models to predict outcomes and guide treatment in triple-negative breast cancer by analyzing tumor-immune interactions.

## Contribution

The novel dual immunological prognostic models offer new insights into TNBC heterogeneity and potential immunotherapy responses.

## Key findings

- Two immunological models (SPSM and IPSM) effectively stratify TNBC patients into distinct risk groups.
- Low-risk patients show an immunologically active microenvironment and higher immune checkpoint gene expression.
- Potential therapeutic agents like imatinib and bortezomib were identified for further investigation.

## Abstract

Triple-negative breast cancer (TNBC) represents the most aggressive breast cancer subtype, with its highly heterogeneous tumor microenvironment posing substantial challenges for precision diagnosis and therapy. To address this, we aim to construct a novel prognostic framework based on tumor-immune interactions. Through integrative analysis of single-cell RNA sequencing data from 30 TNBC samples (106,132 cells), we identify key tumor expression metaprograms and uncover their interaction with an immunosuppressive dendritic-cell subset, a process associated with the NECTIN1–NECTIN4 axis. Leveraging these interactions, we developed and validated two immunological prognostic models using multi-cohort transcriptomic data, including the stress response tumor cell and pDC_CLEC4C prognostic model (SPSM) and the immune response tumor cell and pDC_CLEC4C prognostic model (IPSM). These models effectively stratified TNBC patients into distinct risk groups, with the low-risk group characterized by an immunologically active microenvironment and elevated expression of immune checkpoint genes, suggesting a potential responsiveness to immunotherapy. Furthermore, we identified several potential therapeutic agents, including imatinib and bortezomib. Collectively, our dual-model framework provides a tool for risk stratification, offers translational insights for precision treatment, and presents new directions for understanding TNBC heterogeneity and therapeutic development.