Strategies for Selecting Reliable Reference-Gene Combinations Across 2D and 3D Cell Culture Models

Reliable RT-qPCR normalization in dynamic 2D/3D cell models requires more than identifying genes with low expression variability. In the present study, we evaluated 11 candidate reference genes in AML12 hepatocytes and 3T3-L1 adipocytes cultured under corresponding 2D and 3D conditions to determine whether conventional stability assessment was sufficient for selecting a reliable normalization combination. All candidates passed the initial screening in AML12 cells, whereas Actb, 18S, and Gapdh failed one or more predefined stability criteria in 3T3-L1 cells. geNorm pairwise variation indicated that two-gene normalization was sufficient in both models (V2/3 < 0.15). Nevertheless, linear mixed-effects analysis revealed a significant effect of culture condition on 9 of the 11 candidates in AML12 cells and on all 11 candidates in 3T3-L1 cells. Further analyses using PCA, hierarchical clustering, and BestKeeper-based correlation showed that high expression stability and strong inter-reference concordance coexisted with coordinated condition-dependent variation and associations with biologically regulated target genes. Consequently, some of the algorithmically top-ranked pairs did not exhibit the most favorable profile in terms of expression independence, while the choice of normalizer affected both the magnitude and the statistical interpretation of target-gene responses. Based on these findings, we propose a multistep, model-specific strategy that treats expression stability, inter-reference concordance, expression redundancy, condition dependence, and biological independence as distinct characteristics. This approach shifts the focus from selecting the “most stable” genes toward experimental validation of the reference-gene combination itself and of its impact on biological interpretation.