Signal transducer and activation of transcription 5 (STAT5) is a key transcription factor that regulates various biological processes in mammalian development. Aberrant regulation of STAT5 has also been causally linked to many diseases, including cancers and immune-related diseases. Although persistent activation of STAT5 due to dysregulation of the signaling cascade has been reported to be associated with the progression of solid tumors and leukemia, various genomic mutations of STAT5 have also been found to cause a wide range of diseases. The present review comprehensively summarizes results of recent studies evaluating the intrinsic function of STAT5 and the link between STAT5 mutations and human diseases. This review also describes the types of disease models useful for investigating the mechanism underlying STAT5-driven disease progression. These findings provide basic knowledge for understanding the regulatory mechanisms of STAT5 and the progression of various diseases resulting from aberrant regulation of STAT5. Moreover, this review may provide insights needed to create optimal disease models that reflect human disease associated STAT5 mutations and to design gene therapies to correct STAT5 mutations.

Non-alcoholic fatty liver disease (NAFLD), which affects both adults and children, is the most common liver disorder worldwide. NAFLD is characterized by excess fat accumulation in the liver in the absence of significant alcohol use. NAFLD is strongly associated with obesity, insulin resistance, metabolic syndrome, as well as specific genetic polymorphisms. Severe NAFLD cases can further progress to cirrhosis, hepatocellular carcinoma (HCC), or cardiovascular complications. Here, we describe the pathophysiological features and critical genetic variants associated with NAFLD. Recent advances in genome-engineering technology have provided a new opportunity to generate in vitro and in vivo models that reflect the genetic abnormalities of NAFLD. We review the currently developed NAFLD models generated using clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) genome editing. We further discuss unique features of CRISPR/Cas9 and Cas9 variants, including base editors and prime editor, that are useful for replicating genetic features specific to NAFLD. We also compare advantages and limitations of currently available methods for delivering genome-editing tools necessary for optimal genome editing. This review should provide helpful guidance for selecting “good fit” genome-editing tools and appropriate gene-delivery methods for the successful development of NAFLD models and clinical therapeutics.

Zika virus (ZIKV), transmitted by Aedes mosquitoes, has been a global health concern since 2007. It primarily causes fetal microcephaly and neuronal defects through maternal transmission and induces neurological complications in adults. Recent studies report elevated proinflammatory cytokines and persistent neurological alterations post recovery, but the in vivo mechanisms remain unclear. In our study, viral RNA loads in the brains of mice infected with ZIKV peaked at 7 days post infection and returned to baseline by day 21, indicating recovery. RNA sequencing of the cerebral cortex at 7 and 21 days revealed upregulated genes related to neuroinflammation and microglial activation. Histological analyses indicated neuronal cell death and altered neurite morphology owing to severe neuroinflammation. Additionally, sustained microglial activation was associated with increased phospho-Tau levels, constituting a marker of neurodegeneration. These findings highlight how persistent microglial activation leads to neuronal dysfunction post ZIKV recovery, providing insights into the molecular pathogenesis of ZIKV-induced brain abnormalities.

Super-enhancers are large clusters of enhancers critical for cell-type-specific development. In a previous study, 440 mammary-specific super-enhancers, highly enriched for an active enhancer mark H3K27ac; a mediator MED1; and the mammary-enriched transcription factors ELF5, NFIB, STAT5A, and GR, were identified in the genome of the mammary epithelium of lactating mice. However, the triggering mechanism for mammary-specific super-enhancers and the molecular interactions between key transcription factors have not been clearly elucidated. In this study, we investigated in vivo protein–protein interactions between major transcription factors that activate mammary-specific super-enhancers. In mammary epithelial cells, ELF5 strongly interacted with NFIB while weakly interacting with STAT5A, and it showed modest interactions with MED1 and GR, a pattern unlike that in non-mammary cells. We further investigated the role of key transcription factors in the initial activation of the mammary-specific Wap super-enhancer, using CRISPR-Cas9 genome editing to introduce single or combined mutations at transcription factor binding sites in the pioneer enhancer of the Wap super-enhancer in mice. ELF5 and STAT5A played key roles in igniting Wap super-enhancer activity, but an intact transcription factor complex was required for the full function of the super-enhancer. Our study demonstrates that mammary-enriched transcription factors within a protein complex interact with different intensities and synergize to activate the Wap super-enhancer. These findings provide an important framework for understanding the regulation of cell-type-specific development.

Advances in organoid technology have transformed how gliomas are modeled and studied. Recent FDA and NIH initiatives further promote human-relevant organoid platforms for preclinical research. Glioma organoids can be broadly categorized into 3 main classes: Engineered organoids, which enable controlled modeling of gliomagenesis driven by specific mutations; patient-derived organoids, which preserve key molecular and histopathological features of the original tumors; and assembloids, which are designed to model tumor-microenvironment interactions. Together, these systems provide a human cell-relevant framework for investigating glioma biology, tumor-microenvironment crosstalk, and therapeutic responses and resistance. In this review, we provide a comprehensive overview of the spectrum of glioma organoid models, recognizing that different systems offer distinct and complementary strengths, and we offer practical guidance for selecting appropriate models and analytical readouts based on specific basic and translational research objectives. To address increasing methodological heterogeneity and fragmented terminology, we propose a foundational nomenclature framework for glioma organoid models to improve clarity and communication within the field. We highlight applications in technically challenging subtypes, including isocitrate dehydrogenase (IDH)-mutant gliomas and diffuse midline gliomas (DMGs). We also discuss key challenges—including scalability, standardization, microenvironment fidelity, and vascularization—and emerging innovations addressing these limitations. Finally, we call for greater collaboration and standardization within the glioma organoid community to accelerate the integration of organoid models into translational pipelines to redefine and refine preclinical modeling in neuro-oncology.

The tumor microenvironment (TME) is a dynamic and heterogeneous ecosystem in which cancer, stromal, immune, and physicochemical components collectively regulate disease progression and therapeutic response. Recent evidence further indicates that intratumoral bacteria are active contributors to tumor metabolism, immune modulation, and treatment outcomes, revealing a previously underexplored multi-kingdom dimension of solid tumors. However, mechanistic understanding of tumor–microbe interactions remain limited by the absence of experimental platforms that integrate microbial components into physiologically relevant and controllable tumor models. Here, we propose bacteria-integrated tumor microenvironments as an emerging bioengineering framework for modeling cancer as a multi-kingdom system with biomaterials. We first lay out the existence of bacteria in our body and outline key design principles for these systems, including control of microbial localization, nutrient and oxygen gradients, and interkingdom signaling within engineered matrices. We further discuss applications in studying microbial contributions to therapeutic resistance, evaluating engineered bacterial therapies, and developing patient-specific tumor–microbiome models for precision oncology. Finally, we highlight challenges in standardizing multi-kingdom tumor platforms and integrating them with advanced imaging, sequencing, and computational tools. Collectively, bacteria-integrated TME establish a new paradigm for engineering cancer as a multi-kingdom system with translational potential in oncology.