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The lack of understanding of the molecular and cellular characteristics of human retinal progenitor cells (RPCs) has hindered their application in cell therapy for retinal degenerative diseases. This study aims to employ retinal organoids (ROs) derived from a VSX2-enhanced green fluorescent protein (eGFP) reporter human induced pluripotent stem cell (hiPSC) line for positive selection of human RPCs, investigate their features, and facilitate their applications. Methods: hiPSCs were differentiated into three-dimensional ROs following established protocols. The fidelity of the VSX2-eGFP reporter was confirmed through immunostaining. Fluorescence-activated cell sorting was employed to select VSX2-eGFP-positive (+) cells at distinct developmental stages, followed by bulk RNA sequencing (RNA-seq) analysis to assess their transcriptome profile. Immunostaining and flow cytometry were utilized to validate the identity of VSX2-eGFP+ cells and potential cluster of differentiation (CD) biomarkers for identifying human RPCs. Results: hiPSCs were successfully differentiated into ROs containing abundant RPCs. The spatiotemporal activity of the VSX2-eGFP reporter recapitulated the dynamic expression of endogenous VSX2 protein. Compared to VSX2-eGFP-negative (-) cells, VSX2-eGFP+ cells mainly exhibited characteristics of RPCs at early stages of retinal development and of bipolar cells at late stages. RNA-seq analysis revealed transcriptional heterogeneity within VSX2-eGFP+ cells across four distinct developmental stages. Moreover, the dynamic expression of 394 known CD biomarkers in VSX2-eGFP+ cells at distinct developmental stages was analyzed herein for the first time. One CD biomarker, TNFRSF1B, which has never been reported to be expressed in RPCs, was found to be highly expressed in RPCs at the early stages and might serve as a candidate CD biomarker for sorting RPCs. Conclusions: This study provides valuable insights into the molecular and cellular characteristics of human RPCs, especially their expression profiles of CD biomarkers, laying a foundation for research on retinal development and the clinical translation of hiPSC-derived RPCs.

Prader-Willi syndrome (PWS) is a genomic imprinting disorder caused by the loss of function of the paternal chromosome 15q11-13, resulting in a spectrum of symptoms associated with hypothalamic dysfunction. PWS patients lack the expression of paternally expressed genes (PEGs) in the 15q11-13 locus but possess an epigenetically silenced set of these genes in the maternal allele. Thus, activation of these silenced genes can serve as a therapeutic target for PWS. Here, we leverage CRISPR-based epigenome editing system to modulate the DNA methylation status of the PWS imprinting control region (PWS-ICR) in induced pluripotent stem cells (iPSCs) derived from PWS patients. Successful demethylation in the PWS-ICR restores the PEG expression from the maternal allele and reorganizes the methylation patterns in other PWS-associated imprinted regions beyond the PWS-ICR. Remarkably, these corrected epigenomic patterns and PEG expression are maintained following the differentiation of these cells into hypothalamic organoids. Finally, the single-cell transcriptomic analysis of epigenome-edited organoids demonstrates a partial restoration of the transcriptomic dysregulation observed in PWS. This study highlights the utility of epigenome editing technology as a therapeutic approach in addressing PWS and potentially other imprinting disorders. The authors develop CRISPR-based epigenome editing strategy to reactivate silenced maternally inherited genes for Prader-Willi syndrome in human iPSC and hypothalamic organoid models, highlighting its potential for treating imprinting disorders.

Bispecific T cell-engagers (BTEs) are engineered antibodies that redirect T cells to target antigen-expressing tumors. BTEs targeting tumor-specific antigens such as interleukin 13 receptor alpha 2 (IL13RA2) and epidermal growth factor receptor variant III (EGFRvIII) have been developed for glioblastoma (GBM). However, there is limited mechanistic understanding of the action of BTE since prior studies were mostly conducted in immunocompromised animal models. To close this gap, the function of BTEs was assessed in the immunosuppressive tumor microenvironment (TME) of orthotopic and genetically engineered mouse models (GEMM) with intact immune systems. Method: sA BTE that bridges CD3 epsilon on murine T cells to IL13RA2-positive GBM cells was developed, and the therapeutic mechanism was investigated in immunocompetent mouse models of GBM. Multicolor flow cytometry, single-cell RNA sequencing (scRNA-seq), multiplex immunofluorescence, and multiparametric MRI across multiple preclinical models of GBM were used to evaluate the mechanism of action and response. Results: BTE-mediated interactions between murine T cells and GBM cells triggered T cell activation and antigen-dependent killing of GBM cells. BTE treatment significantly extended the survival of mice bearing IL13RA2-expressing orthotopic glioma and de novo forming GBM in the GEMM. Quantified parametric MRI validated the survival data, showing a reduction in glioma volume and decreased glioma viability. Flow cytometric and scRNA-seq analyses of the TME revealed robust increases in activated and memory T cells and decreases in immunosuppressive myeloid cells within the brains of mice following BTE treatment. Conclusions: Our data demonstrate that the survival benefits of BTEs in preclinical models of glioma are due to the ability to engage the host immune system in direct killing, induction of immunological memory, and modulation of the TME. These findings provide a deeper insight into the mechanism of BTE actions in GBM.

We examined the role of SLFN12, a member of the Schlafen (SLFN) family of interferon-regulated genes and proteins in leukemogenesis, and its potential as a therapeutic target in acute myeloid leukemia (AML). We explored the effects of velcrins, a class of small molecules able to modulate SLFN12 biological activity, on AML cells. Velcrin treatment of AML cells stabilized SLFN12 and promoted SLFN12 complex formation with phosphodiesterase 3A or phosphodiesterase 3B. Such effects were associated with growth-inhibitory and proapoptotic responses, as well as potent suppressive effects on leukemic cell growth. In addition, velcrin treatment suppressed clonogenic capacity of primitive leukemic progenitors and significantly extended survival in a mouse AML xenograft model. Taken together, these findings establish an important role of SLFN12 in leukemogenesis and raise the potential for the use of velcrins as a therapeutic strategy for AML. Significance: Our studies identify SLFN12 as a potential target in AML with important clinical–translational implications.

Alzheimer’s disease (AD) involves cognitive decline, amyloid-beta (Aβ) accumulation, tau hyperphosphorylation, and neuroinflammation. CREB1, a key transcription factor for memory, is downregulated in AD, contributing to disease progression. Phosphodiesterases 4 and 10 (PDE4 and PDE10) are key enzymes that degrade cAMP, a second messenger involved in CREB signaling, synaptic plasticity, and neuroprotection. Dysregulation of PDE activity has been implicated in AD and other neurodegenerative disorders. Methods: We used human iPSC-derived cortical neurons and microglia, along with the APP/PS1 mouse model, to investigate the role of CREB1 and assess the therapeutic potential of dual PDE4/10A inhibition in AD. Results: CREB1 deficiency in neurons increased Aβ and p-tau231 accumulation. Dual inhibition of PDE4 and PDE10A activated the cAMP-PKA-CREB pathway, restoring CREB1 activity, reducing Aβ and p-tau231, and mitigating neuroinflammation. This intervention improved synaptic plasticity and cognitive performance in vivo. Conclusions: Our findings demonstrate that dual PDE4/10A inhibition synergistically enhances the cAMP-PKA-CREB signaling, promoting neuroprotection and synaptic remodeling. This approach offers a promising therapeutic strategy for modifying AD pathology and restoring cognitive function.

A growing body of evidence implicates inflammation as a key hallmark in the pathophysiology of Parkinson’s disease (PD), with microglia playing a central role in mediating neuroinflammatory signaling in the brain. However, the molecular mechanisms linking microglial activation to dopaminergic neuron degeneration remain poorly understood. In this study, we investigated the contribution of the PD-associated LRRK2-G2019S mutation to microglial neurotoxicity using patient-derived induced pluripotent stem cell (iPSC) models. We found that LRRK2-G2019S mutant microglia exhibited elevated activation markers, enhanced phagocytic capacity, and increased secretion of pro-inflammatory cytokines such as TNF-α. These changes were associated with metabolic dysregulation, including upregulated glycolysis and impaired serine biosynthesis. In 3D midbrain organoids, these overactivated microglia resulted in dopaminergic neuron degeneration. Notably, treating LRRK2-G2019S microglia with oxamic acid, a glycolysis inhibitor, attenuated microglial inflammation and reduced neuronal loss. Our findings underscore the link between metabolic targeting in microglia and dopaminergic neuronal loss in LRRK2-G2019S mutation, and highlight a potential strategy that warrants further preclinical evaluation.

Pluripotent cancer stem cells play a pivotal role in inducing phenotypic plasticity across various cancer types, including bladder cancer. This plasticity, crucial for cancer progression, is largely regulated by epigenetic modifications including N6-methyladenosine (m6A) in RNAs. However, the role of the m6A reader protein YTHDC2 in this process remains poorly understood. In this study, we uncovered that the depletion of YTHDC2 significantly increased the pool of bladder cancer stem cells (BCSCs), resulting in a phenotypic shift towards a more invasive subtype of bladder cancer. This shift was characterized by enhanced proliferation, migration, invasion, and self-renewal capabilities of cancer cells, highlighting YTHDC2’s function as a tumor suppressor. Mechanistically, YTHDC2 recognized and bound to m6A-modified SOX2 mRNA, resulting in translational inhibition of SOX2. In conclusion, our study identifies YTHDC2 as a tumor suppressor in bladder cancer through inhibiting SOX2-mediated cell pluripotency and underscores the therapeutic potential of targeting the YTHDC2-SOX2 axis in bladder cancer.

Respiratory organoids have emerged as a powerful in vitro model for studying respiratory diseases and drug discovery. However, the high-throughput analysis of organoid images remains a challenge due to the lack of automated and accurate segmentation tools. This study presents a semi-automatic algorithm for image analysis of respiratory organoids (nasal and lung organoids), employing the U-Net architecture and CellProfiler for organoids segmentation. The algorithm processes bright-field images acquired through z-stack fusion and stitching. The model demonstrated a high level of accuracy, as evidenced by an intersection-over-union metric (IoU) of 0.8856, F1-score = 0.937 and an accuracy of 0.9953. Applied to forskolin-induced swelling assays of lung organoids, the algorithm successfully quantified functional differences in Cystic Fibrosis Transmembrane conductance Regulator (CFTR)-channel activity between healthy donor and cystic fibrosis patient-derived organoids, without fluorescent dyes. Additionally, an open-source dataset of 827 annotated respiratory organoid images was provided to facilitate further research. Our results demonstrate the potential of deep learning to enhance the efficiency and accuracy of high-throughput respiratory organoid analysis for future therapeutic screening applications. Author summaryIn this study, we developed a semi-automated tool to analyze images of respiratory organoids—3D cell structures that mimic the human respiratory system. These organoids are vital for studying diseases like cystic fibrosis and testing potential drugs, but manually analyzing their images is time-consuming and prone to errors. Our tool uses artificial intelligence (AI) to quickly and accurately measure organoid size and shape from bright-field microscope images, eliminating the need for fluorescent dyes that can harm cells. We trained our AI model on a publicly shared dataset of 827 annotated organoid images, achieving high accuracy in detecting and quantifying organoids. When applied to cystic fibrosis research, the tool successfully measured differences in organoid swelling (forskolin-induced swelling - a key test for drug response) between healthy and patient-derived samples. By making our dataset and method openly available, we hope to support further research into respiratory diseases. Our work bridges the gap between complex lab techniques and practical applications, offering a faster, more reliable way to study human health and disease.