Research progress of biomarkers in the prediction of anti-PD-1/PD-L1 immunotherapeutic efficiency in lung cancer

Front Immunol. 2023 Jul 3:14:1227797. doi: 10.3389/fimmu.2023.1227797. eCollection 2023.

Abstract

Currently, anti-PD-1/PD-L1 immunotherapy using immune checkpoint inhibitors is widely used in the treatment of multiple cancer types including lung cancer, which is a leading cause of cancer death in the world. However, only a limited proportion of lung cancer patients will benefit from anti-PD-1/PD-L1 therapy. Therefore, it is of importance to predict the response to immunotherapy for the precision treatment of patients. Although the expression of PD-L1 and tumor mutation burden (TMB) are commonly used to predict the clinical response of anti-PD-1/PD-L1 therapy, other factors such as tumor-specific genes, dMMR/MSI, and gut microbiome are also promising predictors for immunotherapy in lung cancer. Furthermore, invasive peripheral blood biomarkers including blood DNA-related biomarkers (e.g., ctDNA and bTMB), blood cell-related biomarkers (e.g., immune cells and TCR), and other blood-related biomarkers (e.g., soluble PD-L1 and cytokines) were utilized to predict the immunotherapeutic response. In this review, the current achievements of anti-PD-1/PD-L1 therapy and the potential biomarkers for the prediction of anti-PD-1/PD-L1 immunotherapy in lung cancer treatment were summarized and discussed.

Keywords: CtDNA; anti-PD-1/PD-L1 immunotherapy; bTMB; biomarker; cytokines among these immune checkpoints; dMMR/MSI; immune checkpoint; lung cancer.

Publication types

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

MeSH terms

  • B7-H1 Antigen* / metabolism
  • Biomarkers, Tumor / genetics
  • Humans
  • Immunotherapy
  • Lung Neoplasms* / drug therapy
  • Mutation

Substances

  • B7-H1 Antigen
  • Biomarkers, Tumor

Grants and funding

This work was partly supported by the National Natural Science Foundation of China (Nos. 81972558 and 82273137), the “Startup funding of First Hospital, JLU”, and the Natural Science Foundation of Jilin Province (Nos. 20200201473JC, 20200201367JC, and 20210204165YY).