In vitro disease modeling can be used both for understanding the development of pathology and for screening various therapies, such as gene therapies. This approach decreases costs, shortens research timelines, reduces animal testing, and may be more accurate in replicating the disease phenotype compared to animal models. This review focuses on the two types of stem cells: induced pluripotent stem cells (iPSCs) and mesenchymal stem cells (MSCs), which can be used for this purpose. Special attention is given to the impact of the isolation source and the variable expression of certain phenotypic markers on the differentiation capacity of these cells. Both similarities and critical differences between iPSCs and MSCs, as well as the outcomes of past and ongoing clinical trials, are discussed in order to gain insight and understanding as to which of these two cell types can be more suitable for the particular biomedical application.

Retinal pathologies are major causes of vision impairment and blindness in humans, and inherited retinal diseases (IRDs), such as retinitis pigmentosa, Leber congenital amaurosis, and Stargardt disease, greatly contribute to this problem. In vitro disease modeling can be used for understanding the development of pathology and for screening therapeutic pharmaceutical compounds. In the preclinical research phase, in vitro models complement in vivo models by reducing animal studies, decreasing costs, and shortening research timelines. Additionally, animal models may not always accurately replicate the human disease phenotype. This review examines the types of cells that can be used to create in vitro IRD models, including retina-specific cell lines, primary retinal cells, induced pluripotent stem cells (iPSCs), and more. Special attention is given to mesenchymal stem cells (MSCs), which are characterized by various isolation sources, relative ease of isolation, and straightforward differentiation. MSCs derived from bone marrow (BM), adipose tissue (AT), dental tissue (DT), umbilical cord (UC), and other sources can differentiate into retinal cells, including photoreceptor cells and retinal pigment epithelial (RPE) cells, dysfunction of which is most commonly associated with IRDs. Subsequent differentiation of MSCs into retinal cells can be carried out via various methods: culturing in induction media supplemented with certain growth factors, co-culturing with retinal cells or in their conditioned media, or regulating gene expression with viral vector-delivered transcription factors (TFs) or microRNAs (miRNAs). Compared to the popular iPSCs, for example, MSC-based models are significantly cheaper and faster to obtain, making them more feasible for large-scale drug screening. Nevertheless, the existing differentiation methods need further optimization for this promising platform to receive the success it deserves.

Time-lapse microscopy of mesenchymal stem cell (MSC) cultures allows for the quantitative observation of their self-renewal, proliferation, and differentiation. However, the rigorous comparison of two conditions, baseline (A) versus perturbation (B) (the addition of molecular factors, environmental shifts, genetic modification, etc.), remains difficult because morphology, division timing, and migratory behavior are highly heterogeneous at the single-cell scale. MSCs can be used as an in vitro model to study cell morphology and kinetics in order to assess the effect of, for example, gene therapy and prime editing in the near future. By combining static, frame-wise morphology with dynamic descriptors, we can obtain weight profiles that highlight which morphological and behavioral dimensions drive divergence. In this study, we present A/B Cells Policy: a modular, open-source Python package implementing a robust cell tracking pipeline. It integrates a YOLO-based architecture as a two-stage assignment framework with fallback and recovery passes, re-identification of lost tracks, and lineage reconstruction. The framework links descriptive statistics to a transferable system, opening up avenues for regenerative medicine, pharmacology, and early translational pipelines. It does this by providing an interpretable, measurement-based bridge between in vitro imaging and in silico intervention strategy planning.

Prostate cancer (PCa) remains a leading cause of cancer-related mortality in men, with resistance to androgen-deprivation therapy (ADT) being the major clinical challenge. A key driver of this resistance is transcriptional reprogramming, during which androgen receptor (AR) activity shifts from ligand-dependent signaling to reactivation via splice variants such as AR-V7 and eventually to AR-negative states. The oncogene c-MYC plays a pivotal role through context-dependent crosstalk with AR, suppressing canonical AR-dependent transcription while promoting its own oncogenic program. This reprogramming is sustained by dysregulation of RB1/E2F, NF-κB, PI3K/AKT/mTOR, WNT/β-catenin, and Hippo/YAP/TAZ pathways, alongside N-MYC and L-MYC activation, forming an interconnected network driving phenotypic plasticity. This review focuses on cyclin-dependent kinases 8 and 19 (CDK8/19), components of the Mediator complex kinase module, as potential regulators of epigenetic plasticity in PCa capable of modulating both AR-dependent and AR-independent transcription. Preclinical studies show that CDK8/19 inhibition suppresses castration-resistant prostate cancer (CRPC) xenograft growth, restores ADT sensitivity, and additively enhances enzalutamide even in AR-V7-expressing resistant models, though the mechanisms of CDK8/19-mediated AR regulation remain largely undefined. We analyze the signaling pathways driving AR activity changes during PCa progression, evaluate potential mechanisms of CDK8/19-mediated AR regulation, and assess the therapeutic potential of CDK8/19 inhibitors with ADT.