Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASH.
Cell Rep Med
; 4(4): 101016, 2023 04 18.
Article
in En
| MEDLINE
| ID: mdl-37075704
ABSTRACT
Nonalcoholic steatohepatitis (NASH) is the most common chronic liver disease globally and a leading cause for liver transplantation in the US. Its pathogenesis remains imprecisely defined. We combined two high-resolution modalities to tissue samples from NASH clinical trials, machine learning (ML)-based quantification of histological features and transcriptomics, to identify genes that are associated with disease progression and clinical events. A histopathology-driven 5-gene expression signature predicted disease progression and clinical events in patients with NASH with F3 (pre-cirrhotic) and F4 (cirrhotic) fibrosis. Notably, the Notch signaling pathway and genes implicated in liver-related diseases were enriched in this expression signature. In a validation cohort where pharmacologic intervention improved disease histology, multiple Notch signaling components were suppressed.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Non-alcoholic Fatty Liver Disease
/
Deep Learning
Type of study:
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
Cell Rep Med
Year:
2023
Document type:
Article
Affiliation country:
Publication country:
EEUU
/
ESTADOS UNIDOS
/
ESTADOS UNIDOS DA AMERICA
/
EUA
/
UNITED STATES
/
UNITED STATES OF AMERICA
/
US
/
USA