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At least 19 recordsLinked to original sources
PubMed2026

Vitamin D Pathway Activation Reduces Cardiomyocyte DNA Damage and Improves Cardiac Contractility in Preclinical Models.

BACKGROUND: In heart failure (HF), DNA damage caused by various external stressors contributes to cardiac dysfunction through the activation of DNA damage response pathways. To date, no clinical strategies have been established to restore cardiac function by reducing accumulated DNA damage. We previously found that vitamin D improved contractility in lamin A/C (LMNA) p.Q353R-mutant induced pluripotent stem (iPS) cell-derived cardiomyocytes (iPSCMs), but whether this effect extends to other LMNA variants and in vivo models remained uncertain. OBJECTIVES: The objective of the study was to evaluate the association of vitamin D pathway activation with cardiomyocyte phosphorylated histone H2AX (γH2AX) foci and contractile phenotypes in patient-derived iPSCMs and mouse models of HF. METHODS: iPS cell lines were generated from dilated cardiomyopathy patients carrying the LMNA p.R225X mutation, and the effects of vitamin D treatment on γH2AX foci and cardiomyocyte contractility were evaluated. In addition, the effects of the vitamin D analog paricalcitol were evaluated in Lmna p.R225X mice and in a pressure overload mouse model of HF. RESULTS: Consistent with previous findings, vitamin D treatment reduced γH2AX foci in cardiomyocytes derived from LMNA p.R225X mutant iPS cells through upregulating the expression of DNA repair factors, and improved contractility in these iPSCMs. Furthermore, paricalcitol reduced γH2AX foci and attenuated cardiac dysfunction in both Lmna p.R225X mice and pressure overload HF model mice. CONCLUSIONS: Vitamin D pathway activation improved contractile phenotypes across complementary preclinical models and was accompanied by reduced γH2AX foci or related transcriptional changes. These findings support further mechanistic and preclinical investigation.

DNA damage↗
PubMed2026

Efficacy of pharmacological and microbiota-based therapies in preclinical models of autism spectrum disorder: a systematic review.

BACKGROUND: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition in which pharmacological and microbiota-targeted interventions are emerging as promising therapeutic avenues. Animal models are the main tool to investigate etiology, molecular mechanisms and screening for pharmacological therapies. Methodological differences, outcome measure variability, incomplete reporting, biological confounders, and overgeneralization of the results made evaluating innovative pharmacological agents challenging. These limitations in the field highlight a need for systematic and standardized research to reliably assess and translate pharmacological interventions from ASD animal models to human clinical relevance. SUBJECTS: This systematic review synthesized efficacy evidence for pharmacological and microbiota-based therapies across established ASD animal models. RESULTS: We identified 52 recent (2010-2025) studies that reported key ASD behavioral outcomes after pharmacological or microbiota-focused treatments. Interventions were grouped into therapeutic classes - including oxytocinergic agents, E/I balance therapeutic targets, metabolic drugs, cannabinoids, purine-based interventions and emerging targets - alongside microbiota-directed strategies such as probiotics, prebiotics, and fecal microbiota transplantation. By integrating effect directions and robustness across models, we identified most potential drug candidates, evaluated the efficacy of novel strategies, and recognized critical translational gaps. The reviewed studies demonstrate that ASD-like behavioral deficits in preclinical models can be modulated through interventions targeting diverse biological systems, including neurotransmission, neuroinflammation, metabolism, and the gut-brain axis. CONCLUSIONS: These findings support the multifactorial nature of ASD pathophysiology which arises from a network of interacting systemic processes rather than a single molecular defect. It could explain the limited success of traditionally narrowly targeted interventions and suggest a paradigm shift into a more systemic approach.

Animals↗
PubMed2025

A First-in-Class Chemical-Induced Proximity System Achieves Dose-Dependent Control of Tumor Protein P53 Gene Activation in Preclinical Models of Gastric Cancer.

The tumor protein P53 (TP53) gene has long been studied in cancer research with genomic and epigenetic aberrations playing a driving role in cancer pathology, yet even after decades of work, only a few methods have been developed to specifically target TP53 therapeutically. Some cancers are driven by loss-of-function TP53 mutations, while others have wild-type TP53 in a transcriptionally repressed state; the latter is exploitable by advances in epigenome editing. In our previous work, we demonstrated that deactivated CRISPR/Cas9 systems (dCas9), combined with an FK-506-binding protein (FKBP) recruitment protein tag and chemical epigenetic modifier (CEM) small molecules, can elicit gene-specific changes in expression in a dose-dependent manner. Here, we describe the development, application, and characterization of the dCas9-FKBP-CEM technology to increase TP53 expression. We demonstrate that catalyzing increased TP53 expression via dCas9-FKBP-CEM87 induced apoptosis, cell cycle arrest, and tumor growth inhibition in a dose-dependent manner in preclinical models of gastric cancer.

CRISPR↗
PubMed2026

Are there any common effects in preclinical models of micro- and nanoplastic (MNP) exposure? A systematic review.

Micro- and nanoplastics (MNPs) are emerging contaminants detected in food sources and the marine food chain, raising concerns about human health. Although no causal relationship has been established between MNP exposure and specific diseases, growing evidence suggests adverse developmental, behavioral, cognitive and biochemical effects. This systematic review synthesized evidence from common preclinical neurotoxicology models, including C. elegans, D. rerio, D. melanogaster, in vitro systems and rodents, to identify convergent developmental, behavioral and biochemical outcomes. The protocol was preregistered in OSF, followed PRISMA-P guidelines, applied PICOS criteria, and assessed methodological quality using the European Commission's ToxRTool. Overall, 185 studies were included. Consistent findings showed impaired survival and disrupted development across all models. Behavioral alterations affecting anxiety, memory, learning, sociability and locomotor activity were also consistently reported. In addition, numerous studies identified disruptions in the serotonergic (5-HT) system, including changes in neurotransmitter levels, transporters and metabolic enzymes. Despite methodological heterogeneity, these findings indicate that MNP exposure produces reproducible neurodevelopmental and neurochemical alterations across experimental models. Future studies should improve methodological harmonization, strengthen cross-model comparability and identify robust biomarkers and key mechanisms underlying MNP-induced neurotoxicity, facilitating translation to human health risk assessment frameworks.

Animals↗
PubMed2026

Evaluation of metabolic, reproductive, and gut microbiota alterations in a comparative study of different preclinical models of polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a multifaceted, complex metabolic and endocrine disease where gut flora is considered an important factor in causing PCOS. This study aimed to identify a suitable PCOS model that contributes to gut microbial dysbiosis and metabolic and hormonal disturbances. Prepubertal SD rats were administered with normal control (NC), dihydrotestosterone (DHT), DHT with fructose (F), DHT+ high fat diet (HFD) for 91 days, dehydroepiandrosterone (DHEA), DHEA with fructose, DHEA with HFD for 30 days, sodium valproate (SV), sodium valproate with fructose, and sodium valproate with HFD for 21 days. The estrous cycles were assessed over this timeframe. At the end of the experiment, superoxide dismutase and uterine and ovarian morphology were evaluated, along with hormone levels, lipid profiles, and 16S rRNA genomic sequencing. All models exhibited PCOS characteristics, including hormonal imbalances, insulin resistance (p ≤ .001), multiple follicular cysts on ultrasonography, and histological alterations. Gut microbial dysbiosis was observed across all PCOS-induced groups; however, the DHT alone group showed more pronounced alterations in microbial composition than the other experimental groups. Specifically, the DHT alone group exhibited reduced abundance of Firmicutes and increased abundance of Proteobacteria. Among the evaluated models, the DHT-only model showed more pronounced metabolic, hormonal, reproductive, and gut microbial alterations and may serve as a suitable model for PCOS research.

Animals↗
PubMed2026

Losartan shows limited benefit in preclinical models of Geleophysic dysplasia.

Geleophysic dysplasia (GD) is a rare genetic disorder characterized by short stature, joint contractures, and cardiopulmonary complications, with early mortality, and linked to mutations in ADAMTSL2 (GD1), FBN1 (GD2), or LTBP3 (GD3) genes. These mutations are hypothesized to disrupt extracellular matrix (ECM) organization and enhance transforming growth factor beta (TGF-β) signaling. Losartan, an angiotensin II receptor blocker, has been proposed to mitigate TGF-β-mediated pathologies. In this study we tested the efficacy of losartan as a therapeutic drug for GD. We evaluated losartan's therapeutic potential using Adamtsl2 p.A165T mutant mice and patient-derived fibroblasts. Survival, growth, TGF-β signaling, and ECM protein expression were assessed. Losartan did not improve survival or growth in our mutant mice. Compared with control fibroblasts, patient-derived fibroblasts showed reduced basal TGF-β1 secretion. Consistent with this finding, transcriptomic analyses did not reveal activation of the TGF-β signaling pathway, and no differences in SMAD phosphorylation were observed between patient and control cells. Losartan treatment failed to modulate TGF-β signaling or ECM protein incorporation. These results suggest limited benefits of losartan in GD and challenge the notion of TGF-β dysregulation in GD pathogenesis, indicating a need for alternative targeted therapies.

Losartan↗
PubMed2025

Tumor Signatures of Physical Fitness: Insights from a Preclinical Model.

PURPOSE: Cardiorespiratory fitness (CRF) and muscle strength are associated with cancer risk/mortality in adults. However, there is yet no evidence for pediatric tumors. This study investigated the association of CRF and muscle strength with several tumor-related phenotypes in an aggressive childhood malignancy, high-risk neuroblastoma. METHODS: Twelve mice-bearing orthotopic high-risk neuroblastomas were studied. CRF and muscle strength were assessed using treadmill and grip strength testing, respectively. The following tumor-related outcomes were studied: survival, clinical severity, tumor weight/volume, metastasis, and intratumor immune infiltrates. In addition, tumor samples underwent quantitative proteomic analysis via liquid chromatography-tandem mass spectrometry. Spearman correlations (or logistic regression) were performed between CRF/muscle strength and the abovementioned variables. Proteins that were significantly correlated with CRF or muscle strength were mapped into protein-protein interaction (PPI) networks using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. RESULTS: CRF was inversely correlated with clinical severity score ( r = -0.657, P = 0.020). Of 6840 identified tumor proteins, 76 correlated significantly with CRF (19 positively, 57 negatively), whereas 194 correlated with muscle strength (97 positively, 97 negatively). Proteins correlated with CRF were primarily involved in metabolic and structural pathways, including angiotensinogen and elastin. In turn, muscle strength-associated proteins were more abundant and included keratin family proteins (e.g., keratin, type I cytoskeletal 14, and type II cytoskeletal 5), proteins involved in cell adhesion (e.g., desmoglein-1-alpha), and translational regulators (e.g., eukaryotic initiation factor 4A). Network analysis revealed significant enrichment in structural organization and cellular adhesion pathways. CONCLUSIONS: Besides the association of CRF with clinical severity of the tumor, distinct novel tumor proteomic signatures associated with CRF and muscle strength were identified, highlighting potential mechanisms linking physical fitness with childhood cancer biology.

Muscle Strength↗
PubMed2026

The molecular similarity landscape of preclinical cancer models to patient tumors.

Selecting appropriate preclinical models is fundamental for translational oncology, yet a large-scale, multi-omic quantitative comparison of their similarity to primary human tumors is lacking. To address this, we integrated transcriptomic, proteomic, and genomic profiles from over 10,000 primary tumors from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC), alongside 4,000 preclinical models. Using a robust computational framework, we revealed a clear hierarchy of transcriptomic and proteomic similarity to patient tumors: with patient-dervied xenografts (PDXs) having greater transcriptomic and proteomic similarity to patient tumors (>) compared with patient-derived organoids (PDOs), which are equal in hierarchy to that of PDX-dervied organoids (PDXOs) > cell lines. We also quantified high molecular conservation (Pearson correlation coefficient = 0.96) across paired in vitro to in vivo platform (organoids to PDX) transitions. Furthermore, genomic analysis demonstrated that whole-exome sequencing (WES) outperforms RNA-seq in detecting DNA variants, and it identified a clonal complexity hierarchy (cell lines > PDXOs > PDXs > PDOs) reflecting the effect of passaging history on intratumor heterogeneity. Ultimately, this study delivers a comprehensive quantitative benchmark, establishing a population-level hierarchy of molecular similarity between preclinical models and primary tumors and providing a data-driven reference for model selection. These findings offer a data-driven framework for selecting models that balance biological representativeness with experimental practicality.

Humans↗
PubMed2026

Standardized Xenograft Models for Preclinical Cancer Research.

Xenograft models are the principal in vivo platform of preclinical oncology and the most established experimental link between cell culture and clinical investigation. From the carcinogen-exposed rabbit models of the early twentieth century through the current generation of humanized patient-derived xenograft (PDX) systems, these platforms have evolved in response to the demands of translational cancer research. This review critically examines the biological principles, methodological standards, and translational applications of the principal xenograft platforms in current use. Cell line-derived xenograft (CDX) models remain the most widely used and most cost-effective modality for preclinical efficacy testing, offering the reproducibility, scalability, and accessibility that have sustained their role across oncology drug development pipelines for decades. PDX models have emerged as the preferred platform for co-clinical trial design, predictive biomarker discovery, and personalized oncology applications, preserving the genomic landscape, intratumor heterogeneity, and histological architecture of the donor tumor across serial passages. The engraftment biology of PDX systems, including immunodeficient host strain selection, implantation site, tumor source, and passage biology, is reviewed, together with humanized and autologous humanized configurations that extend the platform to immune checkpoint inhibitors, bispecific T-cell engagers, and chimeric antigen receptor T (CAR-T) cell therapy evaluation. This review addresses preclinical-to-clinical translation as a function of immunological divergence, incomplete tumor microenvironment recapitulation, and standardization. Formal frameworks, including the PDX Model Minimal Information (PDX-MI) standard and the Minimal Information for Standardization of Humanized Mice (MISHUM), are examined alongside global biobank infrastructure and emerging AI-driven translational modeling approaches.

Animals↗
PubMed2020

Battling Neurodegenerative Diseases with Adeno-Associated Virus-Based Approaches.

Neurodegenerative diseases (NDDs) are most commonly found in adults and remain essentially incurable. Gene therapy using AAV vectors is a rapidly-growing field of experimental medicine that holds promise for the treatment of NDDs. To date, the delivery of a therapeutic gene into target cells via AAV represents a major obstacle in the field. Ideally, transgenes should be delivered into the target cells specifically and efficiently, while promiscuous or off-target gene delivery should be minimized to avoid toxicity. In the pursuit of an ideal vehicle for NDD gene therapy, a broad variety of vector systems have been explored. Here we specifically outline the advantages of adeno-associated virus (AAV)-based vector systems for NDD therapy application. In contrast to many reviews on NDDs that can be found in the literature, this review is rather focused on AAV vector selection and their preclinical testing in experimental and preclinical NDD models. Preclinical and in vitro data reveal the strong potential of AAV for NDD-related diagnostics and therapeutic strategies.

Animals↗
PubMed2026

Combined high-fat, high-sucrose diet and streptozotocin treatment induces cardiometabolic heart failure with preserved ejection fraction in mice.

Diabetes is associated with an increased incidence of heart failure with preserved ejection fraction (HFpEF), but the underlying mechanisms are poorly understood. A shortage of mouse models reflecting the diverse HFpEF pathophysiology contributes to this inadequate understanding of disease mechanisms. We conducted a comprehensive analysis of a nongenetic, inducible type 2 diabetes mellitus (T2DM) mouse model about its suitability as a preclinical model of cardiometabolic, diabetes-induced HFpEF. T2DM was induced in C57Bl/6 mice by a high-fat/high-sucrose diet and a low-dose streptozotocin (DIO-STZ). Cardiac function was assessed in vivo by echocardiography and left ventricular catheterization and in vitro using the isolated perfused heart. Structural, molecular, and bioenergetic disturbances were analyzed by immunohistochemistry, RNA-seq, qPCR, Western blot, and extracellular flux analysis of myocardial tissue. Blood glucose, fatty acids, and ketone body levels were elevated, and insulin levels were reduced in DIO-STZ compared with chow. DIO-STZ mice showed an HFpEF phenotype with reduced cardiac output, end-diastolic volume, and increased filling pressure. No differences in myocardial fibrosis or in vitro stiffness were detected between DIO-STZ and chow. RNA-Seq pointed toward disturbances in lipid and ketone metabolism. Extracellular flux analysis revealed increased fatty acid oxidation capacity without differences in glucose metabolism. No general mitochondrial dysfunction was observed, but a reduced capacity for β-hydroxybutyrate oxidation. The diabetic DIO-STZ mouse model showed a pronounced functional HFpEF phenotype with underlying mechanisms that remarkably differ from other HFpEF models, making the DIO-STZ model a relevant extension of the range of HFpEF mouse models, especially for investigating molecular mechanisms or therapeutic interventions in diabetes-associated HFpEF.NEW & NOTEWORTHY Heart failure with preserved ejection fraction (HFpEF) is a clinical syndrome whose pathophysiological mechanisms are incompletely understood, potentially due to a lack of preclinical models reflecting the broad range of pathophysiological aspects. We describe a diabetic DIO-STZ mouse model showing a pronounced HFpEF with underlying mechanisms that remarkably differ from other HFpEF models, making this model a relevant extension of the range of HFpEF models, especially for investigating molecular mechanisms or therapeutical interventions in diabetes.

Animals↗
PubMed2026

Patient-derived models of prostate cancer: Capturing tumour complexity from initiation to metastasis.

Prostate cancer is a growing global health challenge. To identify new ways to improve patient care, researchers need a variety of preclinical models that faithfully recapitulate human tumours across the disease continuum, from initiation to metastasis. These complementary models include primary cultures of prostate epithelial cells (PrECs), co-cultures, patient-derived explants (PDEs), patient-derived organoids (PDOs) and patient-derived xenografts (PDXs). Collectively, these models enable researchers to study tumour biology and therapeutic responses in clinically relevant contexts. Yet, there is still a need to improve the fidelity of preclinical models to human tumours by integrating diverse cell types from the tumour microenvironment and mimicking biomechanical features. By improving culture methods with matrix components that resemble the tumour microenvironment and new formulations of media that imitate human plasma, in vitro models will more accurately reflect human physiology, nutrient availability, and metabolism. In time this may reduce the reliance on animal testing through organ-on-chip and related techniques. These more complex models are suited to more detailed experimental readouts, including single-cell and spatial analyses. Intravital imaging also enables dynamic visualisation of cell-cell interactions and treatment responses in vivo. Collectively, these approaches are facilitating a shift towards sophisticated models that capture patients' tumour heterogeneity, different cellular niches, and provide opportunities to carefully study tumorigenesis, metastasis, lineage plasticity, and therapy resistance. In this review, we discuss the current progress and future directions for patient-derived models of prostate cancer, highlighting how they can be generated, refined, characterised and shared to accelerate the worldwide effort in translational research.

Humans↗
PubMed2026

Deep learning-assisted, pathogenesis-informed lung histopathology scoring in preclinical mouse models of SARS-CoV-2 and influenza A infection.

INTRODUCTION: SARS-CoV-2 and influenza A virus (IAV) cause viral pneumonia, yet their lung lesions evolve with distinct spatial organization and resolution-phase architecture. In preclinical murine studies, H&E histopathology is a primary endpoint, but burden-focused semiquantitative scoring can miss pathogen- and phase-specific differences in lesion topology, compartmental involvement, inflammatory organization, and repair. We aimed to define virus- and phase-specific morphologic signatures and translate them into a practical, pathogenesis-informed scoring guide, supported by whole-slide convolutional neural network (CNN) analysis with class activation mapping (CAM). METHODS: Mice were infected under standardized conditions and evaluated during the early, peak-injury, and late phases of infection, corresponding to 2~3, 5~8, and 14 days post-infection (dpi), respectively. Lungs were assessed by H&E with semiquantitative scoring and by immunostaining to map viral antigen distribution and epithelial tropism. Whole-slide CNN models were trained for virus- and phase-specific classification, and CAM localized discriminative regions. RESULTS: Dose titration established reproducible lethal and sublethal infection conditions for both viruses. Viral antigen kinetics diverged, with SARS-CoV-2 peaking early and declining toward clearance by the resolution phase, whereas IAV peaked later and declined by the resolution phase, paralleling distinct injury-repair trajectories. CNN/CAM analysis distinguished virus- and phase-specific histologic patterns across the early, peak-injury, and resolution phases of infection and highlighted spatial signatures consistent with expert review. At the peak-injury phase, SARS-CoV-2 lungs showed broad alveolar/interstitial involvement, whereas IAV exhibited bronchocentric inflammatory organization. During the resolution phase, IAV showed prominent epithelial regeneration with remodeling-forward architecture, while SARS-CoV-2 more often retained localized residual inflammatory foci. Across both infections, tissue inflammatory composition shifted over time, with higher neutrophil representation during the peak-injury phase and a relative increase in lymphocytic representation during the resolution phase. Integrating lesion topology/distribution, edema, epithelial injury-regeneration, remodeling features, and lymphocyte predominance, we proposed a pathogen-resolved, phase-informed histopathology scoring guide with recommended evaluation windows for each model. CONCLUSION: Together, these findings define virus- and phase-specific morphologic programs that inform respiratory virus pathogenesis in mice and can be translated into practical scoring criteria for preclinical respiratory virus studies.

Animals↗
PubMed2025

Individualized patient tumor organoids faithfully preserve human brain tumor ecosystems and predict patient response to therapy.

Tumor organoids are important tools for cancer research, but current models have drawbacks that limit their applications for predicting response to therapy. Here, we developed a fast, efficient, and complex culture system (IPTO, individualized patient tumor organoid) that accurately recapitulates the cellular and molecular pathology of human brain tumors. Patient-derived tumor explants were cultured in induced pluripotent stem cell (iPSC)-derived cerebral organoids, thus enabling culture of a wide range of human tumors in the central nervous system (CNS), including adult, pediatric, and metastatic brain cancers. Histopathological, genomic, epigenomic, and single-cell RNA sequencing (scRNA-seq) analyses demonstrated that the IPTO model recapitulates cellular heterogeneity and molecular features of original tumors. Crucially, we showed that the IPTO model predicts patient-specific drug responses, including resistance mechanisms, in a prospective patient cohort. Collectively, the IPTO model represents a major breakthrough in preclinical modeling of human cancers, which provides a path toward personalized cancer therapy.

Humans↗
PubMed2026

Kinesins in Cancer Drug Resistance: Mechanisms, Therapeutic Targeting, and Translational Potential.

Drug resistance in cancer remains a major barrier to durable therapeutic benefits and limits the effectiveness of chemotherapy, targeted therapy, and combination treatment in multiple malignancies. Increasing evidence indicates that specific kinesin superfamily proteins contribute to tumor adaptation and therapeutic response in a context-dependent manner through their roles in mitotic regulation, intracellular transport, and stress-response pathways. Aberrant expression of multiple kinesin family members has been documented across diverse cancers and is frequently associated with aggressive clinicopathological features, poor prognosis, and resistance to treatment. However, expression alterations alone do not establish functional dependency, and mechanistic validation is required to distinguish true resistance drivers from adaptive tumor states. In this review, we summarize the classification, biological functions, and abnormal expression patterns of kinesins in cancer; discuss the major mechanisms through which they contribute to drug resistance; and examine strategies for targeting kinesins, including natural-product-derived direct inhibitors, small-molecule inhibitor development, rational combination approaches, and structure-guided and computational optimization strategies. We also evaluate the biomarker potential of kinesin dysregulation and the value of advanced preclinical models for mechanistic and translational investigations. Finally, we highlight the major challenges that hinder clinical translation, including target specificity, compensatory resistance, insufficient biomarker validation, and tumor heterogeneity. Future progress will require integration of functional genomics, multiomics profiling, and mechanism-guided therapeutic strategies to determine when kinesin inhibition represents a clinically actionable approach for resistant malignancies.

biomarker potential↗
PubMed2026

Deciphering mitochondrial metabolic vulnerabilities in ovarian clear cell carcinoma with mass spectrometry-based clinical proteomics.

INTRODUCTION: Ovarian clear cell carcinoma (OCCC) is a rare gynecologic malignancy with a high mortality rate and a lack of response to standard chemotherapy. Despite the functional association between the loss of ARID1A and mitochondrial dependency, the clinical translation of mitochondria-targeted therapies in OCCC has been hindered by a substantial disconnect between biological insight and therapeutic application. There is an urgent, unmet need to identify novel, more specific and effective therapies targeting the mitochondria-related molecular vulnerabilities of ARID1A-mutant OCCC. AREAS COVERED: This critical perspective is informed by results from PubMed literature searches and recent webinars and presentations providing insight into opportunities for mass spectrometry (MS)-based proteomic approaches to enhance and accelerate the clinical translation of mitochondria-targeted therapies in OCCC. EXPERT OPINION: The MS-based proteomic analysis of clinically-relevant experimental models of OCCC will provide a unique opportunity to progress beyond simplified preclinical models and incorporate the full spectrum of patient-specific systemic and microenvironmental factors that may influence therapeutic response, including the adipocyte-related metabolic dependencies of OCCC. Targeted MS is a precise and robust approach that can be applied to verify these novel, mechanistic insights into how mitochondria-targeted therapies intersect with tumor metabolism in OCCC.

Humans↗
PubMed2026

LCM-Enriched Proteomic Characterization of Antibody-Mediated Glomerular Damage and Complement Activation in Pre-Clinical Models.

Biologics, lipid nanoparticles, and other therapeutic modalities can result in adverse events, often detected as lesions during preclinical pathology assessments. Characterization of these lesions provides valuable information during drug development to contextualize mechanisms of injury and assess species translatability. Here, we investigated the utility of a laser capture microdissection (LCM)-enriched mass spectrometry proteomics approach to analyze two well-characterized preclinical models of regional (glomerular) injury: Passive Heyman Nephritis in rats and bovine gamma globulin-induced glomerular injury in nonhuman primates (NHPs). Using LCM-enriched proteomics, glomeruli were isolated from formalin-fixed paraffin-embedded kidney tissue in the rat model, enabling identification of 4,661 proteins and quantification of 3,410. Proteinuria measurements were compared with digital pathology metrics of glomerular morphology and proteomics results, with all modalities yielding concordant evidence of glomerular injury and proteomics confirming the role of complement activation. The same LCM- enriched proteomics workflow was applied to an NHP model of induced glomerular damage, identifying 4,623 proteins, quantifying 3,000, and confirming qualitative concordance with established features of complement-mediated glomerular injury. Together, these findings illustrate the applicability of LCM-enriched proteomics for region-specific characterization of antibody-mediated tissue injury and support its use as a hypothesis-generating platform in translational toxicologic pathology.

Animals↗
PubMed2022

Organoids and microphysiological systems: Promising models for accelerating AAV gene therapy studies.

The FDA has predicted that at least 10-20 gene therapy products will be approved by 2025. The surge in the development of such therapies can be attributed to the advent of safe and effective gene delivery vectors such as adeno-associated virus (AAV). The enormous potential of AAV has been demonstrated by its use in over 100 clinical trials and the FDA's approval of two AAV-based gene therapy products. Despite its demonstrated success in some clinical settings, AAV-based gene therapy is still plagued by issues related to host immunity, and recent studies have suggested that AAV vectors may actually integrate into the host cell genome, raising concerns over the potential for genotoxicity. To better understand these issues and develop means to overcome them, preclinical model systems that accurately recapitulate human physiology are needed. The objective of this review is to provide a brief overview of AAV gene therapy and its current hurdles, to discuss how 3D organoids, microphysiological systems, and body-on-a-chip platforms could serve as powerful models that could be adopted in the preclinical stage, and to provide some examples of the successful application of these models to answer critical questions regarding AAV biology and toxicity that could not have been answered using current animal models. Finally, technical considerations while adopting these models to study AAV gene therapy are also discussed.

Animals↗