Dataset Information

Highly multiplexed 2-dimensional imaging mass cytometry analysis of HBV-infected liver.

ABSTRACT: Studies of human hepatitis B virus (HBV) immune pathogenesis are hampered by limited access to liver tissues and technologies for detailed analyses. Here, utilizing imaging mass cytometry (IMC) to simultaneously detect 30 immune, viral, and structural markers in liver biopsies from patients with hepatitis B e antigen+ (HBeAg+) chronic hepatitis B, we provide potentially novel comprehensive visualization, quantitation, and phenotypic characterizations of hepatic adaptive and innate immune subsets that correlated with hepatocellular injury, histological fibrosis, and age. We further show marked correlations between adaptive and innate immune cell frequencies and phenotype, highlighting complex immune interactions within the hepatic microenvironment with relevance to HBV pathogenesis.

SUBMITTER: Traum D

PROVIDER: S-EPMC8119221 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Publications

Highly multiplexed 2-dimensional imaging mass cytometry analysis of HBV-infected liver.

Traum Daniel D Wang Yue J YJ Schwarz Kathleen B KB Schug Jonathan J Wong David Kh DK Janssen Harry LA H Terrault Norah A NA Khalili Mandana M Wahed Abdus S AS Murray Karen F KF Rosenthal Phillip P Ling Simon C SC Rodriguez-Baez Norberto N Sterling Richard K RK Lau Daryl Ty DT Block Timothy M TM Feldman Michael D MD Furth Elizabeth E EE Lee William M WM Kleiner David E DE Lok Anna S AS Kaestner Klaus H KH Chang Kyong-Mi KM

JCI insight 20210408 7

Studies of human hepatitis B virus (HBV) immune pathogenesis are hampered by limited access to liver tissues and technologies for detailed analyses. Here, utilizing imaging mass cytometry (IMC) to simultaneously detect 30 immune, viral, and structural markers in liver biopsies from patients with hepatitis B e antigen+ (HBeAg+) chronic hepatitis B, we provide potentially novel comprehensive visualization, quantitation, and phenotypic characterizations of hepatic adaptive and innate immune subsets ...[more]

PMID: 33621209

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Project description:Imaging Mass Cytometry (IMC) combines laser ablation and mass spectrometry to quantitate metal-conjugated primary antibodies incubated in intact tumor tissue slides. This strategy allows spatially-resolved multiplexing of dozens of simultaneous protein targets with 1μm resolution. Each slide is a spatial assay consisting of high-dimensional multivariate observations (m-dimensional feature space) collected at different spatial positions and capturing data from a single biological sample or even representative spots from multiple samples when using tissue microarrays. Often, each of these spatial assays could be characterized by several regions of interest (ROIs). To extract meaningful information from the multi-dimensional observations recorded at different ROIs across different assays, we propose to analyze such datasets using a two-step graph-based approach. We first construct for each ROI a graph representing the interactions between the m covariates and compute an m dimensional vector characterizing the steady state distribution among features. We then use all these m-dimensional vectors to construct a graph between the ROIs from all assays. This second graph is subjected to a nonlinear dimension reduction analysis, retrieving the intrinsic geometric representation of the ROIs. Such a representation provides the foundation for efficient and accurate organization of the different ROIs that correlates with their phenotypes. Theoretically, we show that when the ROIs have a particular bi-modal distribution, the new representation gives rise to a better distinction between the two modalities compared to the maximum a posteriori (MAP) estimator. We applied our method to predict the sensitivity to PD-1 axis blockers treatment of lung cancer subjects based on IMC data, achieving 97.3% average accuracy on two IMC datasets. This serves as empirical evidence that the graph of graphs approach enables us to integrate multiple ROIs and the intra-relationships between the features at each ROI, giving rise to an informative representation that is strongly associated with the phenotypic state of the entire image.

Dataset Information

Highly multiplexed 2-dimensional imaging mass cytometry analysis of HBV-infected liver.

Publications

Highly multiplexed 2-dimensional imaging mass cytometry analysis of HBV-infected liver.

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