AUTHOR=Zhao Xuan , Bao Yulin , Meng Bi , Xu Zijian , Li Sijin , Wang Xu , Hou Rui , Ma Wen , Liu Dan , Zheng Junnian , Shi Ming 

TITLE=From rough to precise: PD-L1 evaluation for predicting the efficacy of PD-1/PD-L1 blockades

JOURNAL=Frontiers in Immunology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.920021

DOI=10.3389/fimmu.2022.920021

ISSN=1664-3224

ABSTRACT=Developing biomarkers for accurately predicting the efficacy of immune checkpoint inhibitors (ICIs) therapies is conducive to avoiding unwanted side effects and economic burden. At the moment, the quantification of programmed cell death ligand 1 (PD-L1) in tumour tissues is clinically used as one of companion diagnostic assays of response to anti-PD-1/PD-L1 therapy. However, current assays for evaluating PD-L1 remains imperfect. Recent studies are promoting the methodologies of PD-L1 evaluation from rough to precise. Standardization of PD-L1 IHC tests are being promoted by using optimized reagents, platforms, and cut-off values. Novel in vivo probes and liquid biopsy probably benefit to map the spatio-temporal heterogeneity of PD-L1 expression. Optimized combination detection indexes are further improving the accuracy of PD-L1 in predicting the efficacy of ICIs. The combinations of AI with novel technologies are conducive to the intelligence of PD-L1 as a predictive biomarker. In this review, we will provide an overview of the recent progress in this rapidly growing area and discuss the clinical and technical challenges.