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Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.
Azizi, Elham; Carr, Ambrose J; Plitas, George; Cornish, Andrew E; Konopacki, Catherine; Prabhakaran, Sandhya; Nainys, Juozas; Wu, Kenmin; Kiseliovas, Vaidotas; Setty, Manu; Choi, Kristy; Fromme, Rachel M; Dao, Phuong; McKenney, Peter T; Wasti, Ruby C; Kadaveru, Krishna; Mazutis, Linas; Rudensky, Alexander Y; Pe'er, Dana.
Affiliation
  • Azizi E; Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Carr AJ; Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Department of Biological Sciences, Columbia University, New York, NY, USA.
  • Plitas G; Howard Hughes Medical Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Ludwig Center at Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer C
  • Cornish AE; Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Konopacki C; Howard Hughes Medical Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Prabhakaran S; Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Nainys J; Department of Biological Sciences, Columbia University, New York, NY, USA; Sector of Microtechnologies, Institute of Biotechnology, Vilnius University, Vilnius, Lithuania.
  • Wu K; Howard Hughes Medical Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Ludwig Center at Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer C
  • Kiseliovas V; Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Sector of Microtechnologies, Institute of Biotechnology, Vilnius University, Vilnius, Lithuania.
  • Setty M; Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Choi K; Department of Biological Sciences, Columbia University, New York, NY, USA.
  • Fromme RM; Breast Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Dao P; Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • McKenney PT; Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT 06877, USA.
  • Wasti RC; Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT 06877, USA.
  • Kadaveru K; Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT 06877, USA.
  • Mazutis L; Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Rudensky AY; Howard Hughes Medical Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Ludwig Center at Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer C
  • Pe'er D; Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Parker Institute for Cancer Immunotherapy, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. Electronic address: peerd@mskcc.org.
Cell ; 174(5): 1293-1308.e36, 2018 08 23.
Article in En | MEDLINE | ID: mdl-29961579
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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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Receptors, Antigen, T-Cell / Gene Expression Regulation, Neoplastic / Sequence Analysis, RNA / Single-Cell Analysis / Tumor Microenvironment Type of study: Prognostic_studies Limits: Female / Humans Language: En Journal: Cell Year: 2018 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Receptors, Antigen, T-Cell / Gene Expression Regulation, Neoplastic / Sequence Analysis, RNA / Single-Cell Analysis / Tumor Microenvironment Type of study: Prognostic_studies Limits: Female / Humans Language: En Journal: Cell Year: 2018 Document type: Article Affiliation country: United States