Applications of Single-Cell Omics in Tumor Immunology

Front Immunol. 2021 Jun 9;12:697412. doi: 10.3389/fimmu.2021.697412. eCollection 2021.

Abstract

The tumor microenvironment (TME) is an ecosystem that contains various cell types, including cancer cells, immune cells, stromal cells, and many others. In the TME, cancer cells aggressively proliferate, evolve, transmigrate to the circulation system and other organs, and frequently communicate with adjacent immune cells to suppress local tumor immunity. It is essential to delineate this ecosystem's complex cellular compositions and their dynamic intercellular interactions to understand cancer biology and tumor immunology and to benefit tumor immunotherapy. But technically, this is extremely challenging due to the high complexities of the TME. The rapid developments of single-cell techniques provide us powerful means to systemically profile the multiple omics status of the TME at a single-cell resolution, shedding light on the pathogenic mechanisms of cancers and dysfunctions of tumor immunity in an unprecedently resolution. Furthermore, more advanced techniques have been developed to simultaneously characterize multi-omics and even spatial information at the single-cell level, helping us reveal the phenotypes and functionalities of disease-specific cell populations more comprehensively. Meanwhile, the connections between single-cell data and clinical characteristics are also intensively interrogated to achieve better clinical diagnosis and prognosis. In this review, we summarize recent progress in single-cell techniques, discuss their technical advantages, limitations, and applications, particularly in tumor biology and immunology, aiming to promote the research of cancer pathogenesis, clinically relevant cancer diagnosis, prognosis, and immunotherapy design with the help of single-cell techniques.

Keywords: TCR (T cell receptor); biomarkers; cancer; immunotherapy; single-cell omics.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Biomarkers, Tumor / genetics
  • Biomarkers, Tumor / immunology
  • Computational Biology
  • Drug Resistance, Neoplasm / genetics
  • Drug Resistance, Neoplasm / immunology
  • Epigenomics
  • Flow Cytometry
  • Gene Expression Profiling
  • Genomics
  • Humans
  • Immunotherapy
  • Neoplasms / genetics
  • Neoplasms / immunology*
  • Neoplasms / therapy
  • Prognosis
  • Proteomics
  • RNA-Seq
  • Receptors, Antigen, T-Cell / genetics
  • Single-Cell Analysis / methods*
  • Single-Cell Analysis / statistics & numerical data
  • T-Lymphocytes / immunology
  • Tumor Microenvironment / genetics
  • Tumor Microenvironment / immunology*

Substances

  • Biomarkers, Tumor
  • Receptors, Antigen, T-Cell