| Literature DB >> 29961579 |
Elham Azizi1, Ambrose J Carr2, George Plitas3, Andrew E Cornish1, Catherine Konopacki4, Sandhya Prabhakaran1, Juozas Nainys5, Kenmin Wu6, Vaidotas Kiseliovas7, Manu Setty1, Kristy Choi8, Rachel M Fromme9, Phuong Dao1, Peter T McKenney10, Ruby C Wasti11, Krishna Kadaveru11, Linas Mazutis1, Alexander Y Rudensky12, Dana Pe'er13.
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.Entities:
Keywords: Bayesian modeling; T cell activation; TCR utilization; breast cancer; single-cell RNA-seq; tumor microenvironment; tumor-infiltrating immune cells
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Year: 2018 PMID: 29961579 PMCID: PMC6348010 DOI: 10.1016/j.cell.2018.05.060
Source DB: PubMed Journal: Cell ISSN: 0092-8674 Impact factor: 41.582