Abstract 2034: Spatial transcriptomics identifies unique pharmacodynamic effects of checkpoint inhibitor treatment on the tumor microenvironment in NSCLC
Authors: Fan Li , Jabado Omar , Pencheva Nora , Coutinho de Souza Patricia , Higgs Brandon , Harris Angelo , Franken Patrick , Muthuswamy Anantharaman , Jure-Kunkel Maria , Couto Suzana , Sasser Kate , Fereshteh Mark 
Published: June 2022

Abstract
Background: Immune checkpoint inhibitor (ICI) therapy has improved outcomes in non-small cell lung cancer (NSCLC), particularly in patients with high tumor infiltrating lymphocytes (TILs). Identifying the pharmacodynamic (PD) impact of ICI on immune cells in the tumor microenvironment (TME) can inform therapeutic development for patients with progressive disease. We sought to identify PD changes in the TME from patients before and after ICI therapy using a spatial transcriptomics platform that allows highly multiplexed profiling of 1,800 genes (Nanostring Digital Spatial Profiler [DSP]).
Methods: Formalin fixed, paraffin embedded (FFPE) tumor tissue from 22 patients was sourced commercially. Patients were treated with neoadjuvant chemotherapy, then underwent a surgical tumor resection. After surgery an adjuvant chemotherapy was administered until progression; patients then received monotherapy ICI (nivolumab or pembrolizumab). Once progressed on ICI, another resection was performed. Patients were then treated with chemotherapy and followed until progression and/or death. The DSP technology was used to independently profile RNA from PanCK+ (tumor) and PanCK- (stroma) regions in the tissue based on fluorescence staining. Six circular regions of 600μm in diameter were selected for analysis using the GeoMx instrument; each area contained CD3+ cells. Additionally, immunohistochemistry for PDL1 and CD3 was performed, images were scored by a pathologist and analyzed with digital pathology algorithms.
Results: Spatial transcriptomic analysis of pre- vs post-ICI treatment in stroma revealed significant increases in T cell genes (CD3E, TCRB, NKG7), T-cell activation markers (CD69, IFNG, OX40, GZMB, ICOS), costimulatory signaling (CD28, CD80, CD86), and immune checkpoints (CTLA4, TIGIT). Ayers et al., JCI 2017 identified 28 genes predictive of ICI response, 12 were significantly upregulated in the stroma post-ICI (26 were present in the DSP panel). We identified genes in the pre-ICI stromal microenvironment that were highly expressed in patients with partial response to ICI, the most significant genes were involved in immune regulation (IFIT1) and extracellular matrix remodeling (MMP3). In contrast, stromal genes highly expressed in patients with progressive disease were associated with T-cell maintenance (ETS1, IL7R, CCL19).
Conclusions: In this study we used spatial transcriptomics to profile tissue regions where T-cells were in close proximity to tumor cells (microns). This focused, local PD analysis confirmed activated T-cells are present post-ICI. Ongoing studies in a larger cohort will be used to identify tumoral mechanisms of resistance and immune dysfunction to inform future therapeutics and combinations.
Citation Format: Li Fan, Omar Jabado, Nora Pencheva, Patricia Coutinho de Souza, Brandon Higgs, Angelo Harris, Patrick Franken, Anantharaman Muthuswamy, Maria Jure-Kunkel, Suzana Couto, Kate Sasser, Mark Fereshteh. Spatial transcriptomics identifies unique pharmacodynamic effects of checkpoint inhibitor treatment on the tumor microenvironment in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2034.