This is an exciting paper, in which human colon stem cells were used to reconstruct human colon epithelium – a step toward colon reconstruction – in a mouse model. The transplanted human material was stable in the mouse once the original mouse tissues were removed. This new model allows for further experimental analysis of this system, which is not only useful for basic science, but also for regenerative medicine approaches (e.g., replacing human colon that had to be removed for medical reasons). Abstract:
Genetic lineage tracing has revealed that Lgr5+ murine colon stem cells (CoSCs) rapidly proliferate at the crypt bottom. However, the spatiotemporal dynamics of human CoSCs in vivo have remained experimentally intractable. Here we established an orthotopic xenograft system for normal human colon organoids, enabling stable reconstruction of the human colon epithelium in vivo. Xenografted organoids were prone to displacement by the remaining murine crypts, and this could be overcome by complete removal of the mouse epithelium. Xenografted organoids formed crypt structures distinctively different from surrounding mouse crypts, reflecting their human origin. Lineage tracing using CRISPR-Cas9 to engineer an LGR5-CreER knockin allele demonstrated self-renewal and multipotency of LGR5+ CoSCs. In contrast to the rapidly cycling properties of mouse Lgr5+ CoSCs, human LGR5+ CoSCs were slow-cycling in vivo. This organoid-based orthotopic xenograft model enables investigation of the functional behaviors of human CoSCs in vivo, with potential therapeutic applications in regenerative medicine.
Patient-derived xenografts (PDXs) – where human tumors are transplanted into immunodeficient mice to test for therapeutic approaches – are popular research models in cancer research. The underlying premise is that the transplanted tissue will “faithfully represent” the original human tumor, but here is a paper suggesting otherwise, showing significant genetic changes that occur. This of course puts into question how effective the model system is. It is important to know the limitations of a model system and strive for improvement; it is also important to use the tools at hand. There is currently no perfect model system for human cancer. Human cancer cells in culture are a very useful model, but cells in culture are not a human tumor, and the cells of course change over time, so they are not “faithfully representing” the original tumor; various 3-D cell culture models, organoids, etc. are useful but also come with caveats; animal models (transgenics, xenografts, dietary or chemical challenges on wild-type mice) are also useful, but we remember that mice are not humans, and as we see in this paper, transplanted human tissue can change over time. There is always a hurdle going from therapies tested in model systems to their efficacy in actual human patients, and the variability between models and humans is one major cause for this. But we must do the best we can with the tools we currently have at hand. With all their faults, PDXs can yield valuable data; we just need to be careful with the interpretation – and always look toward developing a better model system. Abstract:
Patient-derived xenografts (PDXs) have become a prominent cancer model system, as they are presumed to faithfully represent the genomic features of primary tumors. Here we monitored the dynamics of copy number alterations (CNAs) in 1,110 PDX samples across 24 cancer types. We observed rapid accumulation of CNAs during PDX passaging, often due to selection of preexisting minor clones. CNA acquisition in PDXs was correlated with the tissue-specific levels of aneuploidy and genetic heterogeneity observed in primary tumors. However, the particular CNAs acquired during PDX passaging differed from those acquired during tumor evolution in patients. Several CNAs recurrently observed in primary tumors gradually disappeared in PDXs, indicating that events undergoing positive selection in humans can become dispensable during propagation in mice. Notably, the genomic stability of PDXs was associated with their response to chemotherapy and targeted drugs. These findings have major implications for PDX-based modeling of human cancer.
