# Reference Gene Validation for Quantitative PCR Analysis in 2D and 3D AML12 Hepatocyte Models

## TL;DR

This study validates reference genes for accurate gene expression analysis in 2D and 3D liver cell models.

## Contribution

The study introduces a context-dependent, exclusion-based method for validating reference genes in 2D and 3D hepatocyte models.

## Key findings

- Hprt, Ppia, and Actb were identified as the most stable reference genes across 2D and 3D conditions.
- Ywhaz and Rplp0 showed compromised stability due to correlation with Albumin expression.
- B2M, Gapdh, 18S, and Hmbs exhibited increased variability in 2D cultures.

## Abstract

Background/Objectives: Advanced 3D cell culture techniques enhance the physiological relevance of in vitro models, while supporting the 3Rs principles (Reduction, Refinement, and Replacement) of animal experimentation. In this context, 3D collagen-based systems mimic key extracellular matrix properties, enabling more accurate cellular organization and phenotype. However, changes in culture dimensionality can affect RT-qPCR reference gene stability, underscoring the need for careful validation when combining 2D and 3D systems. Methods: AML12 cells were cultured for 7 days under different 2D and collagen-based 3D conditions. The expression stability of nine candidate housekeeping genes was systematically evaluated using established algorithms (BestKeeper, NormFinder, geNorm, RefFinder, and ΔCt method), followed by inter-group statistical and correlation analyses of raw Ct values. Albumin gene expression was used as a target gene. Results: Although all candidate genes initially met acceptable variability thresholds, a stepwise, exclusion-based analysis revealed distinct performance differences. Hprt, Ppia, and Actb emerged as the most stable, showing no intra-group variability or interaction with Albumin expression. Nevertheless, Ywhaz and Rplp0, despite their high stability, were compromised by significant correlation with Albumin. Furthermore, Ywhaz showed significant downregulation under 3D culture conditions. B2M, Gapdh, 18S, and Hmbs exhibited increased variability, likely reflecting metabolic and microenvironmental heterogeneity associated with prolonged 2D cultivation of AML12 cells. Conclusions: Overall, this study highlights the importance of context-dependent, exclusion-based reference gene validation when comparing 2D and 3D models, and demonstrates a new approach for reliable gene expression normalization in complex in vitro culture systems.