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Fibrosis Like Phenotype in TP53KO Hepatic Organoids within a Pro Carcinogenic Tumor Microenvironment (pc-TME)

GSE252464 Homo sapiens Expression profiling by high throughput sequencing 4 samples Submitted 2025/05/06 Platform GPL24676
Summary
The main obstacle to understanding the early stage of HCC is the lack of reliable models that mimic precancerous HCC in humans, leading to delayed diagnoses. In this study, we developed a CRISPR/Cas9-mediated TP53 knockout (TP53KO) human iPSC-derived endodermal hepatic organoid model (eHEPO) to simulate the early stage of liver cancer. Transcriptome analysis confirmed that TP53KO eHEPOs have an enrichment score across various signaling pathways, including inflammation, extracellular matrix (ECM) modification, fibrosis, and tumorigenesis as well as altered proliferation and differentiation balance. Furthermore, we observed enrichment in key regulatory elements, including HIF1A, IFNA, and STAT3, alongside discernible alterations in the Wnt/TGFB signaling pathways. Moreover, the histopathological analysis highlighted the presence of atypical cells with altered morphology, pseudo-glandular-tubular rosettes, inflammatory areas reminiscent of steatohepatitis, and hepatocytes displaying ballooning-like features. In conclusion, our in vitro eHEPO model confirms a faithful representation of human physiological and genomic landscapes, harmonizing closely with the current scientific discourse on the complications of liver cancer initiation, fibrogenesis, and disease progression. It proves to be a valuable tool for examining the impact of TP53-like first-hit genes and inflammation on the transformation of protumorigenic hepatic progenitor cells in diverse environments. We envision that this in vitro model holds promise for exploring the interactive effects of distinct microenvironments and gene knockouts. Additionally, it emerges as a potential platform for identifying candidates for early-stage drug development.
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Direct links to NCBI, no account and no request form: the whole study as GSE252464_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 4 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1060695 and SRA study SRP481102. Searching any of these in the dataset finder brings you back here.

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