Integrated spatial proteomic analysis of breast cancer heterogeneity unravels cancer cell phenotypic plasticity

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Abstract

Tumor heterogeneity drives drug resistance and relapse, influencing immune evasion and tumor progression. While intratumor heterogeneity has been extensively studied at the genomic level, its functional outcomes and interactions with the tumor microenvironment remain underexplored. In contrast, the functional outcome of heterogeneity and the interplay with the tumor microenvironment have not been addressed. In this study, we integrate multi-region spatial MS-based proteomics of 280 tumor regions, exome sequencing, and imaging to investigate spatial proteomic heterogeneity in breast cancer. Our findings reveal increased proteomic heterogeneity with tumor progression, independent of genomic heterogeneity but closely associated with microenvironmental differences. Integration with immune and stromal imaging highlighted a dynamic interplay where low-grade tumors exhibit constrained immune infiltration, and upon progression to higher grades, macrophages and T cells infiltrate. However, anti-inflammatory pathways involving kynurenine and prostaglandins are more highly expressed in infiltrated regions, suggesting that anti-tumorigenic activities are inhibited. Integration with the global protein network provides potential targetable mediators of immune evasion in breast cancer that can serve as the basis for future development of personalized breast cancer therapies.

Original languageEnglish
Article number10482
JournalNature Communications
Volume16
DOIs
Publication statusPublished - 25 Nov 2025

Funding

We thank the members of the Geiger lab for fruitful discussions and technical assistance. We thank Dr. Gilgi Friedlander from the Montoux Bioinformatics team at the Nancy and Stephen Grand Israel National Center for Personalized Medicine for genomic data analyses. We thank Dr. Adi Zundelevich for assistance with patient cohort assembly, members of the Pathology Department at the Sheba Medical Center for assistance in tissue selection and processing, and the Israel National Biobank for Research (MIDGAM) for assistance in tissue selection. We thank the Satchi-Fainaro lab at Tel Aviv University for assistance in tissue staining. Figure 1 was created with BioRender.com. We thank the Constantiner Institute for partial support. This work was funded by European Council ERC-starting grant # 639534 and the European Council ERC-consolidator grant # 101044574. We thank the members of the Geiger lab for fruitful discussions and technical assistance. We thank Dr. Gilgi Friedlander from the Montoux Bioinformatics team at the Nancy and Stephen Grand Israel National Center for Personalized Medicine for genomic data analyses. We thank Dr. Adi Zundelevich for assistance with patient cohort assembly, members of the Pathology Department at the Sheba Medical Center for assistance in tissue selection and processing, and the Israel National Biobank for Research (MIDGAM) for assistance in tissue selection. We thank the Satchi-Fainaro lab at Tel Aviv University for assistance in tissue staining. Figure was created with BioRender.com. We thank the Constantiner Institute for partial support. This work was funded by European Council ERC-starting grant # 639534 and the European Council ERC-consolidator grant # 101044574.

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Biochemistry,Genetics and Molecular Biology
  • General
  • General Physics and Astronomy

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