Understanding immune phenotypes in human gastric disease tissues by multiplexed immunohistochemistry

Le Ying, Feng Yan, Qiaohong Meng, Xiangliang Yuan, Liang Yu, Bryan R. G. Williams, David W. Chan, Liyun Shi, Yugang Tu, Peihua Ni, Xuefeng Wang, Dakang Xu, Yiqun Hu

Understanding immune phenotypes and human gastric disease in situ requires an approach that leverages multiplexed immunohistochemistry (mIHC) with multispectral imaging to facilitate precise image analyses. We developed a novel 4-color mIHC assay based on tyramide signal amplification that allowed us to reliably interrogate immunologic checkpoints, including programmed death-ligand 1 (PD-L1), cytotoxic T cells (CD8(+)T) and regulatory T cells (Foxp3), in formalin-fixed, paraffin-embedded tissues of various human gastric diseases. By observing cell phenotypes within the disease tissue microenvironment, we were able to determine specific co-localized staining combinations and various measures of cell density. We found that PD-L1 was expressed in gastric ulcer and in tumor cells (TCs), as well as in tumor-infiltrating immune cells (TIICs), but not in normal gastric mucosa or other gastric intraepithelial neoplastic tissues. Furthermore, we found no significant reduction in CD8(+)T cells, whereas the ratio of CD8(+)T:Foxp3 cells and CD8(+)T:PD-L1 cells was suppressed in tumor tissues and elevated in adjacent normal tissues. An unsupervised hierarchical analysis also identified correlations between CD8(+)T and Foxp3(+) tumor-infiltrating lymphocyte (TIL) densities and average PD-L1 levels. Three main groups were identified based on the results of CD8(+)T:PD-L1 ratios in gastric tumor tissues. Furthermore, integrating CD8(+)T:Foxp3 ratios, which increased the complexity for immune phenotype status, revealed 6-7 clusters that enabled the separation of gastric cancer patients at the same clinical stage into different risk-group subsets. Characterizing immune phenotypes in human gastric disease tissues via multiplexed immunohistochemistry may help guide PD-L1 clinical therapy. Observing unique disease tissue microenvironments can improve our understanding of immune phenotypes and cell interactions within these microenvironments, providing the ability to predict safe responses to immunotherapies.