Back

Multi-Cellular Human Liver Organoids Enable Complete Maturation of Induced Pluripotent Hepatocyte-like Cells Through Purely Endogenous Signals

Gandhi, N. N.; Rajagopalan, P.

2025-10-10 bioengineering
10.1101/2025.10.09.681454 bioRxiv
Show abstract

Induced pluripotent stem cells (iPSCs) require further maturation before they can substitute primary human cells. Induced pluripotent stem cell hepatocyte-like cells (iHLCs) exhibit significantly lower hepatic functions than primary human hepatocytes (PHHs). Maturation of iHLCs has relied unsuccessfully on administering chemical cocktails in widely differing temporal patterns that are 106-fold higher in concentration than in vivo. Hence, there is no reproducible approach for iHLC maturation. We report the assembly of a multicellular 3D human liver organoid that recapitulates the in vivo hepatic microenvironment. Intra-and intercellular signaling between human hepatic cells and iHLCs results in their maturation. Within seven-days, iHLCs in organoids expressed markers of hepatocyte maturation that were statistically similar to PHHs including alphafetoprotein (AFP), hepatic nuclear factor (HNF)-4, and albumin. Ki67+ iHLCs decreased by 2-fold from Days 1 to 14. Expression of two cytochrome P450 (CYP) enzymes, CYP3A4 and CYP2E1, in iHLCs were statistically similar to PHHs by Days 7 and 14, respectively. Biotransformation of acetaminophen and ethanol were statistically similar to PHHs by Day 14. On Day 1, the concentration of endogenously secreted prostaglandin E2 (PGE2) was identical to values reported in adult humans. Over the 14-day culture, the concentrations of endogenously secreted hepatocyte growth factor (HGF) and Oncostatin M (OSM) increased until they were 26-36% of in vivo values. The organoids are secreting critically important maturation molecules that are similar to levels reported in healthy humans. These trends demonstrate how closely the multi-cellular organoids are emulating in vivo-like behavior while undergoing further maturation.

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

1
Scientific Reports
3102 papers in training set
Top 5%
10.4%
2
Cytotherapy
14 papers in training set
Top 0.1%
7.4%
3
Stem Cell Research & Therapy
30 papers in training set
Top 0.1%
6.6%
4
Biofabrication
32 papers in training set
Top 0.1%
5.0%
5
PLOS ONE
4510 papers in training set
Top 33%
4.4%
6
Stem Cell Reports
118 papers in training set
Top 0.1%
4.4%
7
Stem Cells Translational Medicine
11 papers in training set
Top 0.1%
3.3%
8
Nature Communications
4913 papers in training set
Top 43%
2.8%
9
Biotechnology and Bioengineering
49 papers in training set
Top 0.3%
2.7%
10
Metabolic Engineering
68 papers in training set
Top 0.3%
2.2%
11
Advanced Healthcare Materials
71 papers in training set
Top 0.8%
2.1%
50% of probability mass above
12
Frontiers in Bioengineering and Biotechnology
88 papers in training set
Top 0.9%
2.1%
13
Hepatology Communications
21 papers in training set
Top 0.2%
1.9%
14
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 4%
1.7%
15
iScience
1063 papers in training set
Top 17%
1.5%
16
Cell Reports Methods
141 papers in training set
Top 3%
1.3%
17
The FASEB Journal
175 papers in training set
Top 2%
1.3%
18
Frontiers in Cellular and Infection Microbiology
98 papers in training set
Top 4%
1.3%
19
Journal of Biological Engineering
10 papers in training set
Top 0.1%
1.1%
20
Frontiers in Neuroscience
223 papers in training set
Top 6%
1.0%
21
Lab on a Chip
88 papers in training set
Top 1.0%
0.9%
22
Biomaterials
78 papers in training set
Top 0.9%
0.9%
23
ACS Synthetic Biology
256 papers in training set
Top 3%
0.8%
24
Methods
29 papers in training set
Top 0.4%
0.8%
25
Toxicological Sciences
38 papers in training set
Top 0.5%
0.8%
26
ACS Omega
90 papers in training set
Top 4%
0.8%
27
International Journal of Molecular Sciences
453 papers in training set
Top 16%
0.7%
28
EMBO Molecular Medicine
85 papers in training set
Top 4%
0.7%
29
Advanced Science
249 papers in training set
Top 19%
0.7%
30
Advanced Materials Technologies
27 papers in training set
Top 0.6%
0.7%