Abstract 2089: Highly multiplexed analysis of immune cell subsets in non-small cell lung cancer: validation of protein and RNA analysis by the Nanostring Digital Spatial Profiling (DSP) platform

Abstract

Abstract Background: Highly multiplexed spatial analysis of tumor tissue is necessary to improve understanding of anti-tumor immunity. Moreover, spatial interrogation of protein and nucleic acid targets simultaneously can better characterize immune cell subsets and targets such as cytokines that are difficult to detect by immunohistochemistry (IHC). NanoString's Digital Spatial Profıling (DSP) technology can detect and quantify proteins and RNA at highly multiplexed levels. We compared DSP to flow cytometry (FCM), IHC and in-situ hybridization (ISH) to assess its sensitivity and specificity. Ongoing studies will assess the prevalence and distribution of immune cell subsets, cytokines and tumor cells in 10 non-small cell lung cancer (NSCLC) cases. Methods: 20 FFPE NSCLC cases and 1 peripheral blood mononuclear cell (PBMC) pellet were assayed on the DSP platform. Regions of interest (300 um x 400 um) or single cell masks were selected from H&E or fluorescence-stained sections. Serial sections were then probed with a cocktail of primary antibodies conjugated to DNA oligos via a UV-cleavable linker for 29 protein and probes for 39 RNA targets. Oligos from the ROIs were then released via UV-mediated linker cleavage and quantitated on the nCounter® Analysis System. Repeat analysis was performed on 10 cases to assess reproducibility between serial sections. A subset of cases was stained for CD3, CD4, CD8, CD45, PD-1, and PD-L1 by IHC and counted by image analysis. FCM was performed on the PBMC sample. Counts from both methods were compared to nCounter counts. Results: Comparison of DSP to FCM in PBMC showed good correlation (R2=0.65). Correlation between DSP counts and IHC was robust for CD3 (R2=0.72), CD4 (R2=0.80), and CD45 (R2=0.90). 21 of 29 protein markers showed good/excellent reproducibility (R2 >0.70) on separate DSP runs. 7 of 29 showed fair/good reproducibility across tissue sections (R2=0.50-0.70). RNA analysis of NSCLC samples by both DSP and ISH is ongoing. Analysis of both PBMC and NSCLC samples suggests that target abundance and section-to-section variability may explain differences in performance and reproducibility between sections. For example, low abundance in NSCLC tissue and section-to-section variability was observed for CD19 and CD56 with corresponding lower correlation between replicates (R2=0.68 and R2=0.52, respectively). Conclusion: DSP shows high section to section reproducibility and fair/good correlation with FCM and IHC. We find performance can be affected by differences in antibody clones or lots and/or section to section variability, particularly for low abundance cell types. Multiplexed RNA analysis of NSCLC samples is ongoing and will document the sensitivity and specificity of DSP compared to traditional ISH and the potential utility of DSP in assessing cytokines in the tumor microenvironment. Citation Format: James Ziai, Patrick Caplazi, Jérémie Decalf, Yan Liang, Patricia de Almeida, Daniel Zollinger, Alison Van Schoiack, Joseph Beechem, Jane Grogan, Matthew Albert. Highly multiplexed analysis of immune cell subsets in non-small cell lung cancer: validation of protein and RNA analysis by the Nanostring Digital Spatial Profiling (DSP) platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2089.