Decades of research and technological advancements are enabling scientists to more fully understand how tumors proliferate, metastasize, and evolve. For example, researchers can now characterize tumors through comprehensive profiling to identify and develop targeted therapeutic interventions for each patient.  

Patient-derived xenograft (PDX) models are rapidly taking the place of traditional cell line approaches to better mimic the complexity of human tumors. To create a PDX model, tumor fragments are taken from a patient and transferred into immunodeficient mice taking with them the histopathological structures of the original tumors. Notably, they are a robust and low-throughput way to model human tumors in vivo.1  

Leukemia in vitro limitations and challenges  

Cancers that impact blood and its formation have a devastating impact on patients and their families. Although several advancements have been made to treat blood cancers, 30-40% of adults fail to achieve complete remission of acute myeloid leukemia (AML) after therapy. These outcomes necessitate novel therapeutics for better patient outcomes. One approach to finding new therapeutics is to look for mutations within AML models but these are often not translatable, resulting in only 10% of drugs showing success in preclinical studies passing early-phase clinical trials. By identifying the causal genes that impact AML, researchers can both develop and use targeted treatments.2  

Researchers believe PDX models are the closest modeling system available  

Head of the Research Unit Apoptosis in Hematopoietic Stem Cells at Helmholtz Munich, Prof. Dr. Med. Irmela Jeremias focuses on identifying the best therapeutic targets and treatment options using preclinical leukemia models and genetic engineering.3  

Despite the specialized challenges involved with developing PDX models, Dr. Jeremias is convinced that PDX models are the closest modeling system available to accurately represent patients.  

“We have the essential genes, pathways, and networks present in the PDX models, so this technique allows us to molecularly mimic in a preclinical in vivo mouse model what will happen when a patient takes a drug targeted against a specific gene,” explained Dr. Jeremias. “Together with the subsequent preclinical treatment trials, I think this is the closest to the patient that we can get.”

After successfully developing an inducible knockdown system in PDX acute leukemia cells, the team set out to target specific genes and assess their function in the tumor. An exciting finding was that this approach could distinguish between individual tumors in order to select patients who might benefit from therapies targeting a gene of interest.

Using mimicry to accurately identify and validate novel treatment options  

PDXs are a robust way to model human tumors in vivo by molecularly mimicking what will happen when a new technique or targeted drug is employed against a particular gene product. These novel models offer an efficient method for accurately simulating and modelling human assessment of biological readouts with less impact on the patient to yield more meaningful cancer research and potential treatment results.

Revvity Inc. does not endorse or make recommendations with respect to research, medication, or treatments. All information presented is for informational purposes only and is not intended as medical advice. For country specific recommendations, please consult your local health care professionals.  

References:

1. Abdolahi, S., Ghazvinian, Z., Muhammadnejad, S. et al. Patient-derived xenograft (PDX) models, applications, and challenges in cancer research. J Transl Med 20, 206 (2022). https://doi.org/10.1186/s12967-022-03405-8
2. Carlet, M., Völse, K., Vergalli, J., Becker, M., Herold, T., Arner, A., Senft, D., Jurinovic, V., Liu, W. H., Gao, Y., Dill, V., Fehse, B., Baldus, C. D., Bastian, L., Lenk, L., Schewe, D. M., Bagnoli, J. W., Vick, B., Schmid, J. P., Wilhelm, A., … Jeremias, I. (2021). In vivo inducible reverse genetics in patients' tumors to identify individual therapeutic targets. Nature communications, 12(1), 5655. https://doi.org/10.1038/s41467-021-25963-z
3. Irmela Jeremias - Helmholtz Munich (helmholtz-munich.de)