J Immunol Res. 2026;2026(1):e9427482. doi: 10.1155/jimr/9427482.
ABSTRACT
Intensive usage of cancer cell lines as cellular model system in cancer research caused the generation of variant subtypes during the last decades. Genetic aberrations, altered transcriptomic profiles as well as changed protein expression have been reported for diverse cancer cell lines resulting in hampered reproducibility of experimental results within the scientific community. Remarkably, the human leukemic THP-1 cell line, the most prominent model for immune cell research questions, was demonstrated to be a subject of branched evolution through diverse cultivation conditions; however, little is known about its impact on THP-1 as monocyte model. This study compares the whole transcriptomic landscape of THP-1 cells from two different depositors during differentiation into various immune states. Numerous genes showed significant altered transcript expression in immune-related signaling pathways, which pervade through macrophage differentiation. These differences are reflected in key biological processes such as metabolic pathways, including glycolysis and lipid metabolism. Furthermore, analysis of immune cell surface markers by flow cytometry and determination of cytokine levels using LEGENDplex revealed variations in protein expression, such as increased interleukin 10 (IL-10) raising questions about its impact on differentiation potential and immune function. These alterations have been evaluated by immune functional assays, including phagocytosis, determination of superoxide (SOX) levels as well as caspase-1 activity. In addition, the transcriptomic comparison to a primary immune cell dataset revealed high similarity between the THP-1 subtypes. However, minor discrepancies compared to primary cell types were identified, which could influence their immunological behavior. These findings suggest that the variability between THP-1 subtypes may undermine the reliability of THP-1-based immunological research, especially when attempting to replicate experiments across laboratories.
PMID:42605270 | DOI:10.1155/jimr/9427482