Frontiers in Oncology (Feb 2022)

Research Progress of Anti-PD-1/PD-L1 Immunotherapy Related Mechanisms and Predictive Biomarkers in NSCLC

  • Fenglong Bie,
  • Fenglong Bie,
  • He Tian,
  • He Tian,
  • Nan Sun,
  • Nan Sun,
  • Ruochuan Zang,
  • Moyan Zhang,
  • Peng Song,
  • Lei Liu,
  • Yue Peng,
  • Guangyu Bai,
  • Bolun Zhou,
  • Shugeng Gao

DOI
https://doi.org/10.3389/fonc.2022.769124
Journal volume & issue
Vol. 12

Abstract

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Programmed cell death-1 (PD-1)/programmed death-ligand 1 (PD-L1) is an important pair of immune checkpoints (IC), which play an essential role in the immune escaping process of tumors. Anti-PD-1/PD-L1 immunotherapy can block the suppression effect of the immune system produced by tumor cells through the PD-1/PD-L1 axis and restore the pernicious effect of the immune system on tumor cells. The specific mechanism of anti-PD-1/PD-L1 immunotherapy is closely related to PI3K (phosphatidylinositol 3-kinase)/AKT (AKT serine/threonine kinase 1), JNK (c-Jun N-terminal kinase), NF-kB (nuclear factor-kappa B subunit 1), and other complex signaling pathways. Patients receiving anti-PD-1/PD-L1 immunotherapy are prone to drug resistance. The mechanisms of drug resistance mainly include weakening recognition of tumor antigens by immune cells, inhibiting activation of immune cells, and promoting the production of suppressive immune cells and molecules. Anti-PD-1/PD-L1 immunotherapy plays a vital role in non-small cell lung cancer (NSCLC). It is essential to find better efficacy prediction-related biomarkers and screen patients suitable for immunotherapy. At present, common biomarkers related to predicting immune efficacy mainly include PD-L1 expression level in tumors, tumor mutation burden (TMB), microsatellite instability (MSI)/mismatch repair (MMR), mutations of driver gene, etc. However, the screening efficacy of each indicator is not ideal, and the combined application of multiple indicators is currently used. This article comprehensively reviews anti-PD-1/PD-L1 immunotherapy-related mechanisms, drug resistance-related mechanisms, and therapeutic efficacy-related predictive biomarkers.

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