Abstract 6768: The potential predictive role of spatial phenotyping in non-small cell lung cancer

Abstract

Abstract Background Lung cancers are the leading cause of cancer-related deaths with a 5-year-survival of only ~20%. Whilst immunotherapies have led to durable and prolonged survival, only a subset of patients remain responsive. Additional biomarkers are thus needed to better predict if patients will respond or develop resistance against immune checkpoint inhibitor (ICI) therapies. Spatial phenotyping of the tumor microenvironment (TME) is now recognized as a proxy for ICI therapy outcomes. Our study employs an end-to-end spatial biology strategy to survey non-small-cell lung cancer (NSCLC) tissues for new biomarkers that could guide immunotherapy treatments. Methods We phenotyped pre-treatment biopsies from non-small-cell lung cancer (NSCLC) patients treated with single-agent Nivolumab. We first performed 57-plex whole-slide Single Cell Spatial Phenotyping on the PhenoCycler®-Fusion platform. Next, we developed the spatial analysis of a larger NSCLC cohort using customizable PhenoCode Signature Panels (PSP) for high-throughput immune profile (CD3/CD8/CD20/CD68/PanCK + CD4 add-in) and immuno-contexture (CD8/CD68/PD-L1/FoxP3/PanCK + PD-1 add-in) imaging. The PSP panel content combines the barcode-based antibody chemistry from the PhenoCycler platform with the signal amplification of Opal chemistry from the PhenoImager platform. PSP panels were profiled across n=27 NSCLC biopsies and provided a wider breadth of tissue profiling. Results Our whole-slide single-cell spatial phenotyping analyses revealed high phenotypic diversity in the TME of patients responsive and resistant to ICI therapy. However, higher-throughput analyses of the same tissues using targeted PSP panels revealed no significant differences in quantities of immune cell lineages, including T-cells and macrophages. On the contrary, we discovered multiple quantifiable and statistically significant spatial signatures that appear to be predictive of treatment benefit, which confirms the potential biomarker value of spatial associations in patient tissues. Conclusions This study amounts to a uniquely comprehensive Single Cell Spatial Phenotyping analysis of pre-treatment NSCLC biopsies from a single-agent Nivolumab study. Our data catalogue the diversity in the immune microenvironment of NSCLC but highlighted that immune cell quantification is insufficient to stratify patient cohorts. Single-cell spatial phenotyping, on the other hand, promises to reveal new biomarkers that may aid in better stratification of patients in pre-treatment evaluations. Citation Format: Ning Ma, Aditya Pratapa, James Monkman, Ken O’Byrne, Oliver Braubach, Arutha Kulasinghe. The potential predictive role of spatial phenotyping in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6768.