From bench to bedside: Single-cell analysis for cancer immunotherapy

Emily F Davis-Marcisak; Atul Deshpande; Genevieve L Stein-O'Brien; Won J Ho; Daniel Laheru; Elizabeth M Jaffee; Elana J Fertig; Luciane T Kagohara

doi:10.1016/j.ccell.2021.07.004

From bench to bedside: Single-cell analysis for cancer immunotherapy

Cancer Cell. 2021 Aug 9;39(8):1062-1080. doi: 10.1016/j.ccell.2021.07.004. Epub 2021 Jul 29.

Authors

Emily F Davis-Marcisak¹, Atul Deshpande², Genevieve L Stein-O'Brien¹, Won J Ho², Daniel Laheru², Elizabeth M Jaffee², Elana J Fertig³, Luciane T Kagohara⁴

Affiliations

¹ McKusick-Nathans Institute of the Department of Genetic Medicine, Johns Hopkins School of Medicine, 550 N Broadway, Suite 1101E, Baltimore, MD 21205, USA; Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, 1650 Orleans Street, Room 485, Baltimore, MD 21287, USA; Convergence Institute, Johns Hopkins University, Baltimore, MD, USA; Bloomberg-Kimmel Immunotherapy Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
² Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, 1650 Orleans Street, Room 485, Baltimore, MD 21287, USA; Convergence Institute, Johns Hopkins University, Baltimore, MD, USA; Bloomberg-Kimmel Immunotherapy Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
³ McKusick-Nathans Institute of the Department of Genetic Medicine, Johns Hopkins School of Medicine, 550 N Broadway, Suite 1101E, Baltimore, MD 21205, USA; Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, 1650 Orleans Street, Room 485, Baltimore, MD 21287, USA; Convergence Institute, Johns Hopkins University, Baltimore, MD, USA; Bloomberg-Kimmel Immunotherapy Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Applied Mathematics and Statistics, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address: ejfertig@jhmi.edu.
⁴ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, 1650 Orleans Street, Room 485, Baltimore, MD 21287, USA; Convergence Institute, Johns Hopkins University, Baltimore, MD, USA; Bloomberg-Kimmel Immunotherapy Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address: ltsukam1@jhmi.edu.

Abstract

Single-cell technologies are emerging as powerful tools for cancer research. These technologies characterize the molecular state of each cell within a tumor, enabling new exploration of tumor heterogeneity, microenvironment cell-type composition, and cell state transitions that affect therapeutic response, particularly in the context of immunotherapy. Analyzing clinical samples has great promise for precision medicine but is technically challenging. Successfully identifying predictors of response requires well-coordinated, multi-disciplinary teams to ensure adequate sample processing for high-quality data generation and computational analysis for data interpretation. Here, we review current approaches to sample processing and computational analysis regarding their application to translational cancer immunotherapy research.

Keywords: computational biology; single-cell proteomics; single-cell transcriptomics; spatial proteomics; spatial transcriptomics; translational medicine; tumor immunology.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Review

MeSH terms

Computational Biology / methods
Data Visualization
Gene Expression Profiling / methods
Humans
Immunotherapy / methods*
Neoplasms / pathology*
Neoplasms / therapy
Proteomics / methods
Single-Cell Analysis / methods*
Tumor Microenvironment

Abstract

Publication types

MeSH terms

Grants and funding