Standard Protocols for Characterising Primary and In Vitro-Generated Human Hepatocytes

Area of Science:

• Hepatology and Regenerative Medicine
• Stem Cell Biology and Differentiation

Background:

• Pluripotent stem cells (PSCs) and direct reprogramming yield unlimited human hepatocyte-like cells (HLCs) for disease modeling, drug development, and regenerative therapies.
• Primary human hepatocytes (PHHs) are crucial for liver research but face limitations including dedifferentiation, donor organ scarcity, scalability issues, and batch variability.
• High-quality, 'off-the-shelf' HLCs are essential to overcome the limitations of PHHs and advance liver research and clinical applications.

Purpose of the Study:

• To review and discuss biological assays and methods for robustly evaluating the quality of in vitro-generated hepatocyte-like cells (HLCs).
• To highlight the critical need for standardized quality assessment of HLCs for reliable biomedical applications.
• To emphasize the importance of using 24-hour cultured primary human hepatocytes (PHHs) as a reference standard for HLC quality evaluation.

Main Methods:

• Discussion of various biological assays and phenotyping methods used for HLC quality assessment.
• Comparative analysis of HLCs against established standards.
• Literature review of current techniques for HLC differentiation and characterization.

Main Results:

• HLCs derived from PSCs or direct reprogramming represent a promising alternative to primary hepatocytes.
• Standardized quality evaluation is crucial for the successful application of HLCs in disease modeling, drug development, and cell therapy.
• Primary human hepatocytes, specifically those cultured for 24 hours, serve as a vital reference for assessing HLC quality.

Conclusions:

• Robust evaluation methods are necessary to ensure the quality and reliability of in vitro-derived HLCs.
• Establishing standardized quality control measures will facilitate the clinical translation of HLC-based therapies.
• The use of PHHs as a reference standard is key to validating HLC performance and ensuring consistency across studies.