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Boost oncology drug discovery with XenoBase®, featuring the largest cell line selection and exclusive 3D organoid models. Benefit from OrganoidXplore™ and OmniScreen™ for rapid, in-depth analysis.

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When to Use Conventional Cell Line Derived Xenograft Models

With the creation and increased use of “new” xenograft models (such as patient-derived xenografts, or PDX), we are often asked which is the right model to use for different in vivo studies, and when to use conventional “cell line derived” xenografts vs the patient-derived alternatives.

To help answer this question, this post looks at the history of traditional xenografts, and when they should be employed in preclinical studies.

Xenograft Models - A Long Legacy of Historical Use

“Cell line derived” conventional xenograft models have been routinely used in cancer drug discovery, and cancer research in general, for the better part of half a century. Some of the very first models utilized in cancer research were transplantable murine syngeneic allografts(1). Both xenogeneic and syngeneic cancer models have been fertile ground for discovery – with fundamental concepts in cancer biology such as “fractional cell kill” and cancer cell “stemness” coming from studies in xenogeneic and syngeneic cancer models.

Background and Key Uses of Cell Line Derived Xenografts

The fundamental basis of a traditional xenograft model is the fact that it is derived from cells in culture. This provides the perfect tool for early stage in vivo drug discovery. Using cells in culture, investigators are able to screen vast libraries of small molecule compounds for cell killing activity. A deep understanding of the molecular profiles of the large array of cancer cell lines available facilitates the directed application of drug discovery.

Therefore, cell models harboring specific molecular changes can be selected, and medicinal chemists can design molecules to target them. Recent work from The Broad Institute of Harvard and MIT shows that many cell lines can now be multiplexed in small molecule anticancer drug screens(2) providing even higher throughput and an assessment of selectivity within the same screen.

Cell Line Derived Xenografts Carry Forward Information

Another utility of conventional xenografts is the ability to carry forward information learned during screening and in vitro characterization, into the next dimension of drug discovery – Pharmacology. In this case, an expected activity discovered in vitro, can be assessed in vivo in the context of host determined factors, such as ADME and Pharmacokinetics.

This means that while a cell line based in vitro program shows us that an agent “works”, the in vivo cell line derived xenograft program allows us to assess “how much does it take” to work. This complex relationship between dose, exposure, and activity, known as the PK/PD relationship, established through the use of xenograft models is critically important to inform both future Toxicology studies, and Phase I clinical trial design.

Complementary Xenograft Models for a Comprehensive Drug Discovery Program

While traditional xenografts are the most useful in vivo tool for the early stage drug development processes detailed above, they do have their downsides. The fact that they are adapted to tissue culture changes them.

The selection pressure imposed by culturing cells on plastic, results in the outgrowth of clones of cells that are no longer representative of the original specimen – the cell lines drift from original disease. Therefore, when moving towards later stage clinical trial and highly predictive in vivo data is needed, patient-derived xenograft models, better recapitulating patient tumors and disease are used instead.

In this way, the two xenograft models can fit together to form a complementary and comprehensive in vivo drug discovery program, right from early stage research to clinical trial readiness, placing a potential drug in the best position for success.

  1. This history of our understanding of murine mammary tumors (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3098677/) also incorporates our parallel evolving understanding of virology and immunology.
  2. https://www.ncbi.nlm.nih.gov/pubmed/26928769

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