Understanding patient-derived tumor organoid growth through an integrated imaging and mathematical modeling framework.

Patient-derived tumor organoids (PDTOs) are novel cellular models that maintain the genetic, phenotypic and structural features of patient tumor tissue and are useful for studying tumorigenesis and drug response. When integrated with advanced 3D imaging and analysis techniques, PDTOs can be used to establish physiologically relevant high-throughput and high-content drug screening platforms that support the development of patient-specific treatment strategies. However, in order to effectively leverage high-throughput PDTO observations for clinical predictions, it is critical to establish a quantitative understanding of the basic properties and variability of organoid growth dynamics. In this work, we introduced an innovative workflow for analyzing and understanding PDTO growth dynamics, by integrating a high-throughput imaging deep learning platform with mathematical modeling, incorporating flexible growth laws and variable dormancy times. We applied the workflow to colon cancer organoids and demonstrated that organoid growth is well-described by the Gompertz model of growth. Our analysis showed significant intrapatient heterogeneity in PDTO growth dynamics, with the initial exponential growth rate of an organoid following a lognormal distribution within each dataset. The level of intrapatient heterogeneity varied between patients, as did organoid growth rates and dormancy times of single seeded cells. Our work contributes to an emerging understanding of the basic growth characteristics of PDTOs, and it highlights the heterogeneity in organoid growth both within and between patients. These results pave the way for further modeling efforts aimed at predicting treatment response dynamics and drug resistance timing.

Pax6 isoforms shape eye development: Insights from developmental stages and organoid models.

Pax6 is a critical transcription factor involved in the development of the central nervous system. However, in humans, mutations in Pax6 predominantly result in iris deficiency rather than neurological phenotypes. This may be attributed to the distinct functions of Pax6 isoforms, Pax6a and Pax6b. In this study, we investigated the spatial and temporal expression patterns of Pax6 isoforms during different stages of mouse eye development. We observed a strong correlation between Pax6a expression and the neuroretina gene Sox2, while Pax6b showed a high correlation with iris-component genes, including the mesenchymal gene Foxc1. During early patterning from E10.5, Pax6b was expressed in the hinge of the optic cup and neighboring mesenchymal cells, whereas Pax6a was absent in these regions. At E14.5, both Pax6a and Pax6b were expressed in the future iris and ciliary body, coinciding with the integration of mesenchymal cells and Mitf-positive cells in the outer region. From E18.5, Pax6 isoforms exhibited distinct expression patterns as lineage genes became more restricted. To further validate these findings, we utilized ESC-derived eye organoids, which recapitulated the temporal and spatial expression patterns of lineage genes and Pax6 isoforms. Additionally, we found that the spatial expression patterns of Foxc1 and Mitf were impaired in Pax6b-mutant ESC-derived eye organoids. This in vitro eye organoids model suggested the involvement of Pax6b-positive local mesodermal cells in iris development. These results provide valuable insights into the regulatory roles of Pax6 isoforms during iris and neuroretina development and highlight the potential of ESC-derived eye organoids as a tool for studying normal and pathological eye development.