Measures of spatial heterogeneity in the liver tissue micro-environment as predictive factors for fibrosis score.
Biomarker analysis
Cell type co-localization
Chronic hepatitis B
Classification
Getis-ord
Hepatocyte immune cell interaction
Immune hotspot
Immunofluorescence
Immunology
Liver fibrosis
Log-Gaussian cox
Morisita–Horn
Point process
Shannon diversity index
Single cell data
Spatial heterogeneity
Tissue micro-environment
Journal
Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250
Informations de publication
Date de publication:
10 2023
10 2023
Historique:
received:
28
04
2023
revised:
02
08
2023
accepted:
14
08
2023
medline:
27
9
2023
pubmed:
28
8
2023
entrez:
27
8
2023
Statut:
ppublish
Résumé
The organization and interaction between hepatocytes and other hepatic non-parenchymal cells plays a pivotal role in maintaining normal liver function and structure. Although spatial heterogeneity within the tumor micro-environment has been proven to be a fundamental feature in cancer progression, the role of liver tissue topology and micro-environmental factors in the context of liver damage in chronic infection has not been widely studied yet. We obtained images from 110 core needle biopsies from a cohort of chronic hepatitis B patients with different fibrosis stages according to METAVIR score. The tissue sections were immunofluorescently stained and imaged to determine the locations of CD45 positive immune cells and HBsAg-negative and HBsAg-positive hepatocytes within the tissue. We applied several descriptive techniques adopted from ecology, including Getis-Ord, the Shannon Index and the Morisita-Horn Index, to quantify the extent to which immune cells and different types of liver cells co-localize in the tissue biopsies. Additionally, we modeled the spatial distribution of the different cell types using a joint log-Gaussian Cox process and proposed several features to quantify spatial heterogeneity. We then related these measures to the patient fibrosis stage by using a linear discriminant analysis approach. Our analysis revealed that the co-localization of HBsAg-negative hepatocytes with immune cells and the co-localization of HBsAg-positive hepatocytes with immune cells are equally important factors for explaining the METAVIR score in chronic hepatitis B patients. Moreover, we found that if we allow for an error of 1 on the METAVIR score, we are able to reach an accuracy of around 80%. With this study we demonstrate how methods adopted from ecology and applied to the liver tissue micro-environment can be used to quantify heterogeneity and how these approaches can be valuable in biomarker analyses for liver topology.
Identifiants
pubmed: 37634463
pii: S0010-4825(23)00847-8
doi: 10.1016/j.compbiomed.2023.107382
pii:
doi:
Substances chimiques
Hepatitis B Surface Antigens
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
107382Informations de copyright
Copyright © 2023 Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest None Declared.