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. 2021 Apr 16:12:665133.
doi: 10.3389/fimmu.2021.665133. eCollection 2021.

Novel Biomarkers of Dynamic Blood PD-L1 Expression for Immune Checkpoint Inhibitors in Advanced Non-Small-Cell Lung Cancer Patients

Qiao Yang  1   2 , Mingjing Chen  1 , Jiaoyang Gu  1   3 , Kai Niu  1 , Xianlan Zhao  1 , Linpeng Zheng  1 , Zihan Xu  1 , Yongxin Yu  1 , Feng Li  1 , Lingxin Meng  1 , Zhengtang Chen  1 , Wenlei Zhuo  1 , Luping Zhang  1 , Jianguo Sun  1
Affiliations

Novel Biomarkers of Dynamic Blood PD-L1 Expression for Immune Checkpoint Inhibitors in Advanced Non-Small-Cell Lung Cancer Patients

Qiao Yang et al. Front Immunol. .

Abstract

Background: Immune checkpoint inhibitors (ICIs) have become a high-profile regimen for malignancy recently. However, only a small subpopulation obtains long-term clinical benefit. How to select optimal patients by reasonable biomarkers remains a hot topic.

Methods: Paired tissue samples and blood samples from 51 patients with advanced malignancies were collected for correlation analysis. Dynamic changes in blood PD-L1 (bPD-L1) expression, including PD-L1 mRNA, exosomal PD-L1 (exoPD-L1) protein and soluble PD-L1 (sPD-L1), were detected after 2 months of ICIs treatment in advanced non-small-cell lung cancer (NSCLC) patients. The best cutoff values for progression-free survival (PFS) and overall survival (OS) of all three biomarkers were calculated with R software.

Results: In 51 cases of various malignancies, those with positive tissue PD-L1 (tPD-L1) had significantly higher PD-L1 mRNA than those with negative tPD-L1. In 40 advanced NSCLC patients, those with a fold change of PD-L1 mRNA ≥ 2.04 had better PFS, OS and best objective response (bOR) rate. In addition, a fold change of exoPD-L1 ≥ 1.86 was also found to be associated with better efficacy and OS in a cohort of 21 advanced NSCLC cases. The dynamic change of sPD-L1 was not associated with efficacy and OS. Furthermore, the combination of PD-L1 mRNA and exoPD-L1 could screen better patients for potential benefit from ICIs treatment.

Conclusion: There was a positive correlation between bPD-L1 and tPD-L1 expression. Increased expression of PD-L1 mRNA, exoPD-L1, or both in early stage of ICIs treatment could serve as positive biomarkers of efficacy and OS in advanced NSCLC patients.

Keywords: NSCLC; biomarker; blood PD-L1; exosome; immune checkpoint inhibitors.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The correlation of tPD-L1 and bPD-L1 in 33 NSCLC patients. (A) The correlation of PD-L1 mRNA and tPD-L1. (B) The correlation of sPD-L1 and tPD-L1. tPD-L1, tissue PD-L1; bPD-L1, blood PD-L1; sPD-L1, soluble PD-L1; NSCLC, non-small-cell lung cancer. P values were calculated by independent-samples t-test.
Figure 2
Figure 2
Dynamic changes in multimodal bPD-L1 expression during early treatment. (A) Dynamic changes in PD-L1 mRNA (CT values). (B) Dynamic changes in exoPD-L1. (C) Dynamic changes in sPD-L1. (D) An overview of fold changes of the three biomarkers. bPD-L1, blood PD-L1; CT, cycle threshold; exo-PD-L1, exosomal PD-L1; sPD-L1 soluble PD-L1.
Figure 3
Figure 3
Dynamic change in PD-L1 mRNA expression to predict efficacy and OS in the expanded 40 NSCLC cohort. (A) PFS analysis based on fold change of PD-L1 mRNA expression. (B) OS analysis based on fold change of PD-L1 mRNA expression. (C) bOR of each patient stratified by fold change of PD-L1 mRNA expression. OS, overall survival; PFS, progression-free survival; bOR, best objective response; HR, hazard ratio; CI, confidence interval. P values were calculated by log-rank test.
Figure 4
Figure 4
Efficacy and OS analyses based on fold change of exoPD-L1 or sPD-L1 expression in the 21 NSCLC cohort. (A) PFS analysis based on fold change of exoPD-L1 expression. (B) OS analysis based on fold change of exoPD-L1 expression. (C) bOR of each patient stratified by fold change of exoPD-L1 expression. (D) PFS analysis based on fold change of sPD-L1 expression. (E) OS analysis based on fold change of sPD-L1 expression. (F) bOR of each patient stratified by fold change of sPD-L1 expression. OS, overall survival; exoPD-L1, exosomal PD-L1; sPD-L1, soluble PD-L1; PFS, progression-free survival; bOR, best objective response; HR, hazard ratio; CI, confidence interval. P values were calculated by log-rank test.
Figure 5
Figure 5
Efficacy and OS analyses based on the combination of PD-L1 mRNA and exoPD-L1 expression in the 21 NSCLC cohort. (A) PFS analysis based on the combination of two biomarkers. (B) OS analysis based on the combination of two biomarkers. (C) bOR of each patient stratified by the combination of two biomarkers. OS, overall survival; exoPD-L1, exosomal PD-L1; PFS, progression-free survival; bOR, best objective response. P values were calculated by log-rank test.
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