Beyond tumor mutational burden: potential and limitations in using exosomes to predict response to immunotherapy

Expert Rev Mol Diagn. 2019 Dec;19(12):1079-1088. doi: 10.1080/14737159.2020.1688144. Epub 2019 Nov 10.


Introduction: Immune checkpoint blockade (ICB) has ushered in a new era of cancer therapeutics. The standard for determining which patients might benefit from ICB-based therapies is through the assessment of tumor mutational burden using formalin-fixed paraffin-embedded (FFPE) tumor tissue samples; however, this strategy is imperfect. The discovery of exosomal PD-L1 has placed these nano-vesicles to the forefront of immunotherapy biomarker development. Exosomes and other extracellular vesicles contain proteins and nucleic acids specific to their cell of origin and their production is increased in disease state such as cancer and can be isolated from most types of liquid biopsy. Given this opportunity, a large-scale bioengineering effort has centered on developing technologies capable of isolating distinct subsets of exosomes and interrogating their content for biomarker discovery.Areas covered: This review investigates the current state of small extracellular vesicles (sEVs), focusing on exosomes, as they relate to biomarkers of IBC. We will discuss technologies being developed to both capture and evaluate exosomal cargo and as some of the challenges they face.Expert opinion: The advancement of microfluidic technologies, along with rapidly evolving methodologies in RNAseq and proteomics, are making the potential of utilizing exosomes as prognostic and diagnostic biomarkers of ICB into a likely reality.

Keywords: Extracellular vesicle; exosomes; tumor mutational burden.

Publication types

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

MeSH terms

  • Biomarkers, Tumor / genetics*
  • Biomarkers, Tumor / metabolism
  • Exosomes / genetics*
  • Exosomes / metabolism
  • Genomics / methods
  • Humans
  • Immunotherapy*
  • Mutation Accumulation*
  • Neoplasms / genetics*
  • Neoplasms / therapy


  • Biomarkers, Tumor