Pattern recognition receptors: immune targets to enhance cancer immunotherapy

Ann Oncol. 2017 Aug 1;28(8):1756-1766. doi: 10.1093/annonc/mdx179.


Durable tumor responses and significant levels of disease control rates have been described in more than 20 advanced/metastatic cancer types with B7-family immune checkpoint-targeted anti-CTLA-4, anti-PD-1, and anti-PD-L1 monoclonal antibodies. These results and the recent approvals of ipilimumab, pembrolizumab, nivolumab and atezolizumab are currently revolutionizing the way we envision the future of cancer care. However these clinical benefits are not observed in all cancer types and in every patient. Therefore, our clinical challenge is to identify therapeutic strategies which could overcome the primary and secondary resistances to these novel cancer immunotherapies. Pattern recognition receptors (PRRs) are other critical costimulatory molecules of immune cells, notably myeloid cells (macrophages and dendritic cells). They were initially described as sensors for 'danger signals' released by pathogens (e.g. viral DNA and bacterial proteins). We know now that PRRs can also be recruited and activated upon recognition of endogenous stress signals such as molecules released upon self-cell death (e.g. ATP and HMGB1). Natural endo/exogenous or synthetic PRRs agonists have notably the ability to activate phagocytosis and antigen presentation by myeloid cells residing in the tumor micro-environment. In pre-clinical models, these PRRs agonists have also been shown to overcome the resistance to T-cell targeted immune checkpoints anti-CTLA-4 and anti-PD-1/PD-L1. This manuscript reviews the current knowledge on this major family of immune receptors and the molecules targeting them which are currently in clinical development.

Keywords: cancer; immune checkpoints; immunotherapy; pattern recognition receptors.

Publication types

  • Review

MeSH terms

  • Humans
  • Immunotherapy*
  • Neoplasms / immunology
  • Neoplasms / therapy*
  • Receptors, Pattern Recognition / agonists*


  • Receptors, Pattern Recognition