Scientific Reports (Mar 2025)

Comprehensive immunophenotyping reveals distinct tumor microenvironment alterations in anti-PD-1 sensitive and resistant syngeneic mouse model

  • Hiroyuki Inoue,
  • Takayuki Hamasaki,
  • Kazuhiko Inoue,
  • Akira Nakao,
  • Noriyuki Ebi,
  • Hirofumi Minomo,
  • Ichiro Nagata,
  • Masaki Fujita,
  • Naoto Horai

DOI
https://doi.org/10.1038/s41598-025-91979-w
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 12

Abstract

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Abstract The advent of immune checkpoint inhibitors targeting the PD-1/PD-L1 pathway has revolutionized cancer treatment, resulting in improved clinical outcomes. However, resistance remains a critical challenge. This study aimed to comparatively elucidate immunophenotypic changes in syngeneic mouse models sensitive (MC-38) or resistant (LLC1) to anti-PD-1 monoclonal antibody (mAb) treatment. In the sensitive MC-38 model, anti-PD-1 therapy increased dendritic cells (DCs) and macrophages, while decreasing myeloid-derived suppressor cells (MDSCs) within the tumor microenvironment. Enhanced expression of antigen presentation molecules (MHC I/II) and costimulatory molecules (CD80/CD86) was observed on tumor-associated DCs and macrophages. Tumor-infiltrating CD4+T, CD8+T, regulatory T, NK, and NKT cells also significantly increased. Importantly, treatment boosted lymphocyte cytotoxic potential, with perforin identified as a key marker of efficacy. Notably, perforin expression in CD4+T and NKT cells strongly negatively correlated with tumor volume. In contrast, the resistant LLC1 model exhibited minimal immunophenotypic changes upon treatment. These findings highlight critical immune modifications induced by anti-PD-1 therapy, particularly the role of perforin, and the DC/MDSC ratio in predicting therapeutic outcomes. This research offers valuable insights into potential predictive biomarkers and informs strategies to overcome resistance, emphasizing the complex interplay between anti-PD-1 treatment and the tumor microenvironment, ultimately aiming to improve immunotherapy response rates.

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