Targeting the PD-1/ PD-L1 interaction in nasopharyngeal carcinoma

David Johnson1, Brigette B Y Ma2

  • 1Department of Clinical Oncology, Prince of Wales Hospital, Hong Kong Special Administrative Region.

Oral Oncology
|January 17, 2021
PubMed

Insights

Targeting the PD-1/PD-L1 pathway shows promise for Epstein-Barr virus-associated nasopharyngeal cancer (NPC). Clinical trials are evaluating PD-1 antibodies alone and in combination for recurrent, metastatic, and advanced NPC.

Area of Science:

  • Immunology
  • Oncology
  • Virology

Background:

  • Programmed cell death receptor-1 (PD-1) and its ligand (PD-L1) pathway upregulation is a key immune evasion mechanism in Epstein-Barr virus (EBV)-associated nasopharyngeal cancer (NPC).
  • Targeting the PD-1/PD-L1 axis is a significant area of research for NPC treatment.
  • At least 8 antibodies targeting this axis are in clinical evaluation for various NPC stages.

Purpose of the Study:

  • To review the scientific rationale for targeting the PD-1/PD-L1 axis in NPC.
  • To summarize current clinical trials investigating PD-1/PD-L1 inhibitors in NPC.
  • To discuss predictive biomarkers for response to PD-1/PD-L1 therapies in NPC.

Main Methods:

  • Review of scientific literature and clinical trial data.
  • Analysis of therapeutic strategies involving PD-1/PD-L1 antibodies in NPC.
  • Evaluation of combinatorial approaches with chemotherapy, radiotherapy, and other immunotherapies.

Main Results:

  • PD-1 antibodies as monotherapy show objective response rates of 20-30% in patients with recurrent/metastatic (R/M) NPC in Phase II trials.
  • The predictive role of PD-L1 expression in NPC is still under investigation.
  • Combinatorial strategies are actively being evaluated in various clinical trial designs.

Conclusions:

  • Targeting the PD-1/PD-L1 axis represents a promising therapeutic strategy for EBV-associated NPC.
  • Ongoing clinical trials are exploring various treatment settings and combinations.
  • Further research is needed to define predictive biomarkers for optimal patient selection.