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

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.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2025-11-25
DOI
https://doi.org/10.1038/s41467-025-65477-6
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Mariya Mardamshina, Ofra Golani, Liat Fellus-Alyagor, Bruria Shalmon et al.
Nature Communications
Single-cell and spatial transcriptomics
article

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

Mariya Mardamshina, Ofra Golani, Liat Fellus-Alyagor, Bruria Shalmon, Tamar Geiger, Daniela Necula, Anjana Shenoy, Shiri Karagach, Kateryna Krol, Roded Sharan, Yoseph Addadi, Daniel Pirak, Iris Barshack, Gali Arad, Nitay Itzhacky, Vishnu Mohan, Einav Nili Gal‐Yam, Irina Marin
article en

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.

Nature CommunicationsVol. 16(1)
Tel Aviv University (IL), Sheba Medical Center (IL), Weizmann Institute of Science (IL)
Tel Aviv University
Openalex Percentile: Top 67%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.