Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment
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Abstract
Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We profiled 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph nodes, using single-cell RNA-seq. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer. Our results have important implications for characterizing tumor-infiltrating immune cells.
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scRNA-seq has been widely used to reveal the characteristics of immunity in different fields.
“It is notable that scRNA-seq has been widely used to reveal the characteristics of immunity in different fields. 6-10”
From Single-Cell RNA Sequencing to Dissect the Immunological Network of Autoimmune Myocarditis. (2020) · cites this paper as [9]
The Results section describes using scRNA-seq to map immune-cell states in breast cancer, and the Introduction mentions other tumor studies using the method. This supports its use to characterize immunity, but the paper does not establish that it was widely used across different fields; the Introduction says such tumor studies had begun and were limited in scale. Page numbers are not available in our copy. (LLM, conf=0.82)
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- Authors
- Azizi, E., Carr, A. J., Plitas, G., Cornish, A. E., Konopacki, C., Prabhakaran, S., Nainys, J., Wu, K., Kiseliovas, V., Setty, M., Choi, K., Fromme, R. M., Dao, P., McKenney, P. T., Wasti, R. C., Kadaveru, K., Mazutis, L., Rudensky, A. Y., & Pe’er, D.
- Affiliations
- Memorial Sloan Kettering Cancer Center (US)
- Vilnius University (LT)
- Columbia University (US)
- Boehringer Ingelheim (United States) (US)
- Corresponding author
- Rudensky, Alexander Y.
- Pe’er, Dana
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 174
- Issue
- 5
- Pages
- 1293-1308.e36
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC6348010
- OpenAlex
- W2810097927
- Cited by
- 1,976
- References
- 16
- Citations by year
- 2026: 196 · 2025: 242 · 2024: 279 · 2023: 282 · 2022: 277 · 2021: 293 · 2020: 224 · 2019: 148 · 2018: 31 · 2017: 1 · 2014: 1
- FWCI
- 61.65
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (R37 AI034206, DP1- HD084071, R01CA164729, U54 CA209975, P30 CA008748)
- Hilton-Ludwig Cancer Prevention Initiative
- Conrad N. Hilton Foundation
- Ludwig Cancer Research
- Gerry Center for Metastasis and Tumor Ecosystems
- American Cancer Society - Fairfield County Roast Committee (PF-17-243-01-RMC)
- HHMI
- Breast Cancer Alliance
- Society of MSK
- Hutham S. Olayan
- Boehringer Ingelheim SHINE
- Boehringer Ingelheim SHINE Program
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Immunology and Microbiology › Immunology › Immune cells in cancer
- Keywords
- breast cancer, tumor microenvironment, tumor-infiltrating immune cells, immune cell phenotypes, single-cell RNA sequencing, T cell receptor repertoire, T cell activation, macrophage polarization
- MeSH terms
- Bayes Theorem, Breast Neoplasms, Female, Humans, Immune System, Immunotherapy, Lymph Nodes, Macrophages, Phenotype, Receptors, Antigen, T-Cell, Gene Expression Regulation, Neoplastic, Cluster Analysis, Lymphocytes, Tumor-Infiltrating, Sequence Analysis, RNA, Computational Biology, Gene Expression Profiling, Single-Cell Analysis, Tumor Microenvironment, Transcriptome
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