# A Predictive Immunological Signature Associated with Pathological Response in Breast Cancer Treated with Neoadjuvant Chemotherapy

## TL;DR

This study identifies immune-related features that predict how breast cancer patients respond to chemotherapy, offering potential new tools for personalized treatment.

## Contribution

The study introduces a predictive immunological signature based on immune cell ratios and contextualized metrics for chemotherapy response in breast cancer.

## Key findings

- A biased cytotoxic tumor environment is linked to better chemosensitivity in breast cancer.
- Immune balance features like CD8/CD4 ratio outperform molecular phenotype alone in predicting response to chemotherapy.
- Baseline immune cell abundance and checkpoint expression did not differ significantly across response groups.

## Abstract

Background/Objectives: Breast cancer is a heterogeneous and complex disease with significant individual differences in molecular immunophenotype, biological behavior, histopathological morphology, and response to chemotherapy. The presence of tumor-infiltrating lymphocytes (TILs) has gained considerable attention due to growing evidence of their involvement in therapeutic efficacy, particularly in the response to neoadjuvant chemotherapy (NACT). Different immune cell subsets’ frequency, location, and functional orientation vary substantially between tumor types and individuals with apparently identical cancers. Currently, next-generation sequencing (NGS) has provided key insights into the composition of the tumor microenvironment. Simultaneously, immunohistochemistry (IHC) of paraffin-embedded biopsies allows the visualization of marker proteins within the immune infiltrate, thereby enhancing our understanding of the role of immune cells in cancer therapy. Methods: This exploratory study evaluated immune cell tumor infiltration using NGS with immune cell deconvolution, as well as automated IHC on Tru-Cut biopsies from 57 patients with locally advanced breast cancer. Image analysis was performed using Qupath v0.6.0 software. The percentage of infiltrating CD4+ or CD8+ T cells was determined, along with the expression of the markers FoxP3, LAG3, CTLA4, PD1, and TIM-3. We aimed to gain insights into the tumor microenvironment and its influence on the response to NACT in patients with breast cancer. Results: Transcriptomic immune deconvolution approaches suggested that a biased cytotoxic tumor environment is linked to chemosensitivity. IHC assays of individual markers reveal that baseline immune cell abundance and individual checkpoint expression did not differ significantly across the response groups. However, the functional organization and coordination of the tumor immune microenvironment showed distinct associations with chemosensitivity. Conclusions: Features representing immune balance, such as CD8/CD4 ratio and T cell-contextualized metrics, emerged as candidate predictors of pathological response to NACT, outperforming molecular phenotype alone in this exploratory cohort.