Abstract 5139: PD1-PDL1 interaction as a superior predictor for response to immune checkpoint therapy in NSCLC patients
Authors: Patrick Micke, Amanda Lindberg, Rebecca Artursson, Louise Hellberg, Hui Yu, Max Backman, Johan Botling, Hans Brunnström, Artur Mezheyeuski, Johan Isaksson, Carina Strell
Journal: Cancer Research (2024)

Abstract Background: Immune checkpoint therapies (ICT) are now widely introduced in clinical oncology and most often guided by PDL1 expression in diagnostic biopsies. However, the predictive value of this testing is only modest, leading to over- and undertreatment. Conceptually, the prevention of binding of ligand PDL1 to PD1 receptor is decisive for the efficacy of ICT. Therefore, directly detecting the spatial PD1-PDL1 interaction would provide more predictive information. Methods: A second-generation in situ proximity ligation assay (isPLA; Navinci Diagnostics) was established to detect PD1-PD-L1 interactions in diagnostic patient samples and linked to an automated analysis pipeline (QuPath). For basic validation, we used pan-cancer tissue microarrays (TMA) including 16 solid tumor types, and a non-small cell lung cancer (NSCLC) TMA (359 ICT-naïve surgically treated patients). In addition, we analyzed diagnostic tissue biopsies from 75 advanced NSCLC patients treated with anti-PD1-PDL1 regiments. Results: The pan-cancer analysis revealed varying levels of PD1-PDL1 interaction among the solid cancer types, with the lowest levels detected in liver cancer and the highest in testicular cancer. A general positive association was observed between the literature-reported objective ICT response rate (ORR) per tumor type and its corresponding PD1-PDL1 interaction status. Conventional immunohistochemical analysis of the ICT-naïve, surgically treated NSCLC cohort revealed variable protein expression level for both, PDL1 and PD1, for 200 cases, but only 108 (54%) of them demonstrated a detectable PD1-PDL1 interaction with our isPLA assay. EGFR mutated cases showed generally lower PD1-PDL1 interaction scores (p=0.01). PD1-PDL1 interaction was not associated with survival (p=0.46). A subsequent analysis of the ICT-NSCLC cohort revealed a significant positive association between PD1-PDL1 interaction status and prolonged overall survival upon ICT (median survival 14.8 vs 32.3 months; p=0.022). The standard tumor proportional score (TPS) of membranous PDL1 expression did not correlate with ICT-specific survival (p=0.40). Conclusions: The second generation isPLA successfully distinguishes a previously difficult-to-define patient subset with positive PD1-PDL1 interaction status. Our data suggest that the PD1-PDL1 interaction is a superior clinical biomarker for patient selection for ICT in NSCLC. The interaction analysis is applicable to sections from minute diagnostics biopsies and accessible by light microscopy either semi-quantitatively by a pathologist or by an automated image analysis program. Thus, the assay holds great potential to be integrated into routine clinical pathological workflow to stratify cancer patients for ICT. Citation Format: Patrick Micke, Amanda Lindberg, Rebecca Artursson, Louise Hellberg, Hui Yu, Max Backman, Johan Botling, Hans Brunnström, Artur Mezheyeuski, Johan Isaksson, Carina Strell. PD1-PDL1 interaction as a superior predictor for response to immune checkpoint therapy in NSCLC patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5139.