Purpose: In many cancers, the expression of immunomodulatory ligands leads to immunoevasion, as exemplified by the interaction of PD-L1 with PD-1 on tumor-infiltrating lymphocytes. Profound advances in cancer treatments have come with the advent of immunotherapies directed at blocking these immuno-suppressive ligand-receptor interactions. However, although there has been success in the use of these immune checkpoint interventions, correct patient stratification for these therapies has been challenging.

Materials And Methods: To address this issue of patient stratification, we have quantified the intercellular PD-1/PD-L1 interaction in formalin-fixed paraffin-embedded tumor samples from patients with non-small cell lung carcinoma, using a high-throughput automated quantitative imaging platform (quantitative functional proteomics [QF-Pro]).

Results: The multisite blinded analysis across a cohort of 188 immune checkpoint inhibitor-treated patients demonstrated the intra- and intertumoral heterogeneity of PD-1/PD-L1 immune checkpoint engagement and notably showed no correlation between the extent of PD-1/PD-L1 interaction and PD-L1 expression. Importantly, PD-L1 expression scores used clinically to stratify patients correlated poorly with overall survival; by contrast, patients showing a high PD-1/PD-L1 interaction had significantly better responses to anti-PD-1/PD-L1 treatments, as evidenced by increased overall survival. This relationship was particularly strong in the setting of first-line treatments.

Conclusion: The functional readout of PD-1/PD-L1 interaction as a predictive biomarker for the stratification of patients with non-small-cell lung carcinoma, combined with PD-L1 expression, should significantly improve the response rates to immunotherapy. This would both capture patients excluded from checkpoint immunotherapy (high PD-1/PD-L1 interaction but low PD-L1 expression, 24% of patients) and additionally avoid treating patients who despite their high PD-L1 expression do not respond and suffer from side effects.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10414696PMC
http://dx.doi.org/10.1200/JCO.22.01748DOI Listing

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