Immune cells are a major component of the tumor microenvironment (TME). The spatial organization of immune cell subpopulations within the TME is recognized to have biologic significance and clinical relevance. For example, spatial organization of immune cell subsets within the TME is critical for the inhibition of cytotoxic T-cell activity through direct interaction of ligand (PD-L1) with receptor (PD-1)). However, precise spatial deconvolution is limited by the lack of imaging algorithms for in situ multiplex single cell analyses as flow cytometry does not preserve data in the spatial dimension. To this end, we have developed a hyperspectral imaging platform designed for analyzing multichannel immunohistochemical-stained tissue sections for generating cell density data and reconstructing spatial architecture for tumor biology as well as clinical association studies.

Whole-tissue sections from 20 lung adenocarcinomas with at least 5 years’ follow-up were stained for CD3 (pan-T cell), CD8 (cytotoxic T cell), and CD79a (B cell and plasma cell) and counterstained with hematoxylin. Multispectral images were acquired for five fields of view and analyzed to quantify cell types. Regions of Interest (ROIs) were then identified and analyzed in order to quantify cell-cell spatial relationships. Nonrandom patterns of immune cell distributions were identified using the Monte Carlo resampling method (500 iterations). Cell counts, densities, spatial relationships, and significant immune cell distributions were associated with clinical features (Kruskal-Wallis p<0.001).

Our analysis generated 234 image files for analysis, with an average of 16,400 cells per image. The densities of intratumoral CD8+ cytotoxic T cells were significantly higher in nonrecurrent cases, agreeing with literature reports. Similarly, cell sociology deductions identified relationships associated with metastasis: tumor cells in nonmetastatic cases had increased numbers of CD8+ cytotoxic T-cell neighbors. Following Monte Carlo analysis, nonrandom cell~cell spatial proximities emerged that were not identified at a cell density level.

We have developed a hyperspectral imaging platform capable of quantifying cell-cell spatial relationships within tissue sections. This technology can be applied to larger clinical cohorts for the study of therapeutically targetable immune cell subsets with the goal of identifying patterns that correlate with clinical response and patient outcome.

This abstract is also being presented as Poster B16.

Citation Format: Katey S.S. Enfield, Spencer D. Martin, Sonia H.Y. Kung, Paul Gallagher, Calum E. MacAulay, Martial Guillaud, Wan L. Lam. Hyperspectral imaging tools capture the spatial organization of cell subsets within the tumor microenvironment [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr PR11.