Multi-omics profiling uncovers immune-molecular clusters with distinct chemo-immunotherapeutic vulnerabilities in a

Olivier Castellanet1, Jean Monatte1, Nathan Corvaisier1

  • 1Aix Marseille Univ, CNRS, INSERM, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille (CRCM), Marseille, France.

Molecular Cancer
|January 10, 2026
PubMed
Abstract

Insights

Researchers developed a preclinical model for triple-negative breast cancer (TNBC) to predict patient response to chemo-immunotherapy. This model identified distinct TNBC subtypes, guiding tailored treatment strategies for better outcomes.

Area of Science:

  • Oncology
  • Immunology
  • Genomics

Background:

  • Triple-negative breast cancer (TNBC) is aggressive and heterogeneous, presenting treatment challenges.
  • Predicting patient response to chemo-immunotherapy requires effective stratification methods.

Purpose of the Study:

  • To develop a robust preclinical platform for precision immuno-oncology in TNBC.
  • To stratify TNBC patients for tailored onco-immunotherapies based on intrinsic and immune features.

Main Methods:

  • Multi-parametric analysis (histological, genomic, transcriptomic, proteomic, immune profiling) in a TNBC mouse model.
  • Comparison with human TNBC patient data and tumor microarrays.
  • Syngeneic graft establishment for therapeutic testing of chemotherapy and anti-PD-1 immunotherapy.

Main Results:

  • Identified four distinct TNBC clusters mirroring patient subtypes and clinical outcomes.
  • Demonstrated conservation of tumor hallmarks across serial transplantations, validating the preclinical platform.
  • Revealed cluster-specific treatment vulnerabilities: chemo-immunotherapy for neutrophil-enriched tumors, immunotherapy alone for macrophage-enriched tumors.

Conclusions:

  • The study establishes a valuable preclinical platform for precision immuno-oncology in TNBC.
  • This platform enables stratification of TNBC patients for personalized immunotherapy selection.