The FDA Modernization Act and the subsequent federal policy changes in 2025 have signaled a shift towards the use of non-animal, human-centered models for preclinical drug development and toxicity screening, emphasizing 3D cell-based, organ-on-chip, and organoid platforms as alternatives to animal models. While animal models have been instrumental in improving our understanding of disease mechanisms, they do not allow decoupling of biomechanical and biochemical effects during pathogenesis. Standard in vitro systems offer improved accessibility but often lack physiologically relevant microenvironments. In this review, we discuss how kidney-on-chip and iPSC-derived kidney organoid models serve as physiologically relevant platforms for modeling nephrotoxicity, kidney development, and pathophysiology. Kidney-on-chip models can recapitulate in vivo mechanical forces, such as fluid shear stress and mechanical strain, experienced by cells, enabling real-time functional readouts of glomerular filtration, tubular reabsorption, and potential nephrotoxic response. Integrating on-chip platforms with patient-derived iPSCs and differentiated kidney cell types allows human-relevant responses unavailable in static culture. iPSC-derived kidney organoids recapitulate the 3D architecture of nephron segments and ureteric bud branching patterns, demonstrating selective transport, toxicity responses, and structural stability over months in culture. We detail how bioengineering approaches, including organoid-on-chip models, bioprinting, and multi-organ-on-chip integration, could address the current limitations of these systems, like maturity, scalability and vascularization. We further discuss how integrating publicly available clinical databases and machine learning approaches with on-chip validation can improve translational relevance. We conclude that interdisciplinary collaboration between engineers, biologists, and physician scientists will be essential to translate bioengineered kidney models into clinical and therapeutic applications.

The FDA Modernization Act and the subsequent federal policy changes in 2025 have signaled a shift towards the use of non-animal, human-centered models for preclinical drug development and toxicity screening, emphasizing 3D cell-based, organ-on-chip, and organoid platforms as alternatives to animal models. While animal models have been instrumental in improving our understanding of disease mechanisms, they do not allow decoupling of biomechanical and biochemical effects during pathogenesis. Standard in vitro systems offer improved accessibility but often lack physiologically relevant microenvironments. In this review, we discuss how kidney-on-chip and iPSC-derived kidney organoid models serve as physiologically relevant platforms for modeling nephrotoxicity, kidney development, and pathophysiology. Kidney-on-chip models can recapitulate in vivo mechanical forces, such as fluid shear stress and mechanical strain, experienced by cells, enabling real-time functional readouts of glomerular filtration, tubular reabsorption, and potential nephrotoxic response. Integrating on-chip platforms with patient-derived iPSCs and differentiated kidney cell types allows human-relevant responses unavailable in static culture. iPSC-derived kidney organoids recapitulate the 3D architecture of nephron segments and ureteric bud branching patterns, demonstrating selective transport, toxicity responses, and structural stability over months in culture. We detail how bioengineering approaches, including organoid-on-chip models, bioprinting, and multi-organ-on-chip integration, could address the current limitations of these systems, like maturity, scalability and vascularization. We further discuss how integrating publicly available clinical databases and machine learning approaches with on-chip validation can improve translational relevance. We conclude that interdisciplinary collaboration between engineers, biologists, and physician scientists will be essential to translate bioengineered kidney models into clinical and therapeutic applications.

INTRODUCTION:Increased endothelin-1 (ET1) and endothelin receptor A (ETA) signaling have been implicated in the pathogenesis of focal segmental glomerulosclerosis (FSGS). Previous studies have suggested that crosstalk between activated podocytes and glomerular endothelial cells (GECs) could contribute to the pathogenesis of FSGS. METHODS:To examine this, we developed mouse lines with endothelial cell-targeted and conditional deletion of ETA using the Cre-LoxP system (Scl:Cre-ETAfl/fl), as well as targeted deletion of ET1 in podocytes (Nphs2:Cre-ET1fl/fl). RESULTS:The absence of endothelial ETA in mice was protective in adriamycin-induced glomerular injury, as evidenced by decreased albuminuria and reduced podocyte depletion. RNA-seq of ET1-treated mouse glomerular endothelial cells showed activation of cellular signaling pathways and alteration of matrix component deposition programs via ETA. Endothelin-1 expression was detected in glomerular cells in patient biopsy samples and mice with FSGS. Compared to adriamycin-treated mice, podocyte-specific ET1 knockout mice treated with adriamycin had reduced glomerular injury, albuminuria, and podocyte depletion. Furthermore, canonical transforming growth factor (TGF)β signaling mediates ET1 release by podocytes, and Edn1 knockout in podocytes with inducible TGFβ receptor-1 signaling (Nphs2:Cre-ET1-Nphs1:TgfbrI) abrogated glomerular injury and albuminuria upon TGFβ receptor-1 activation. Ultrastructural changes and podocyte depletion were completely prevented in these mice, and there was no increase in GEC-associated ETA expression. Mathematical modelling supports rapid bidirectional diffusion of ET1 across the glomerular basement membrane. CONCLUSIONS:Our studies provide in vivo evidence that crosstalk of podocyte-derived ET1 with activation of GEC ETA contributes to glomerular injury in FSGS.

Introduction:Severe acute kidney injury (AKI) is strongly associated with the risk of developing chronic kidney disease; however, little is known about the cell type-specific mechanisms driving kidney injury severity. Methods:In this multicenter observational study, we used clinically obtained liquid biopsy proteomics and machine learning (ML) to predict severe outcomes in patients with COVID-associated and non-COVID AKI. Further, we orthogonally combined 169 urine proteomics with 437 plasma proteomics samples and 40 urine sediment single-cell transcriptomics samples to identify complementary dysregulated mechanisms. Results:Using a 10-fold cross-validated random forest algorithm, we identified a set of urinary proteins that demonstrate predictive power for both discovery and validation set with AUC of 87% and 76%, respectively. These predictive proteomics features obtained demonstrate that cell adhesion and autophagy-associated pathways are uniquely impacted in severe AKI. Differentially abundant proteins (DAPSs) associated with these pathways are highly expressed in cells of the juxtamedullary nephron, endothelial cells (ECs), and podocytes, indicating that these kidney cell types could be potential targets. Single-cell transcriptomic analysis in the in vitro model of kidney organoids infected with SARS-CoV-2 reveal dysregulation of extracellular matrix (ECM) organization in multiple nephron segments, recapitulating the clinically observed fibrotic response across multiomics datasets. Ligand-receptor interaction analysis of the podocyte and tubule organoid clusters shows significant reduction and loss of interaction between integrins and basement membrane receptors in the infected kidney organoids. Conclusion:Collectively, these data suggest that ECM degradation and adhesion-associated mechanisms could be the main driver of severe kidney injury.

Atomic force microscope (AFM) indentation allows high-resolution spatial characterization of biomechanical properties of cells and tissues. Rapid, reproducible, and quantitative analysis of AFM force curves has been challenging due to several technical limitations, such as excessive noise and uncertainty associated with contact-point determination. Here, we propose a novel machine-learning algorithm composed of convolutional bidirectional long short-term memory neural networks called Convolutional Bidirectional Recurrent Architecture (COBRA) that can reliably process raw AFM elastography data, triage poor-quality curves, and accurately identify the contact point without any a priori knowledge of underlying material properties. Using over 5000 manually curated force curves on seven different healthy and diseased cell types, we trained several regression and classification algorithms to compare their utility. In contrast to classical analytical or semi-quantitative techniques and other machine-learning methods, the COBRA approach identified low-quality or anomalous indentation events better, with an area under the curve of 0.92, and it estimated the contact point with the minimal absolute error of 28 ± 3 nm and pointwise elastic modulus with mean absolute percentage error of 5.3% ± 0.7%. The method was also successful in identifying the contact point in independently acquired AFM data from the literature with divergent probes and substrates. In conclusion, our method can rapidly filter low-quality AFM force curves and automatically process raw indentation data with the lowest error levels, allowing high-throughput analyses with increased precision and reproducibility.

The Library of Integrated Network-based Cellular Signatures (LINCS), an NIH Common Fund program, has cataloged and analyzed cellular function and molecular activity profiles in response to >80,000 perturbing agents that are potentially disruptive to cells. Because of the importance of proteins and their modifications to the response of specific cellular perturbations, four of the six LINCS centers have included significant proteomics efforts in the characterization of the resulting phenotype. This manuscript aims to describe this effort and the data harmonization and integration of the LINCS proteomics data discussed in recent LINCS papers.

Drug-induced gene expression profiles can identify potential mechanisms of toxicity. We focus on obtaining signatures for cardiotoxicity of FDA-approved tyrosine kinase inhibitors (TKIs) in human induced-pluripotent-stem-cell-derived cardiomyocytes, using bulk transcriptomic profiles. We use singular value decomposition to identify drug-selective patterns across cell lines obtained from multiple healthy human subjects. Cellular pathways affected by cardiotoxic TKIs include energy metabolism, contractile, and extracellular matrix dynamics. Projecting these pathways to published single cell expression profiles indicates that TKI responses can be evoked in both cardiomyocytes and fibroblasts. Integration of transcriptomic outlier analysis with whole genomic sequencing of our six cell lines enables us to correctly reidentify a genomic variant causally linked to anthracycline-induced cardiotoxicity and predict genomic variants potentially associated with TKI-induced cardiotoxicity. We conclude that mRNA expression profiles when integrated with publicly available genomic, pathway, and single cell transcriptomic datasets, provide multiscale signatures for cardiotoxicity that could be used for drug development and patient stratification. Using a new computational pipeline for identification of drug-selective transcriptomic responses and FAERS data, the authors identified potential pathways and genomic variants indicative of cancer drug cardiotoxicity in iPSC-derived cardiomyocytes.

Background African American (AA) kidney transplant recipients exhibit a higher rate of graft loss compared to other racial and ethnic populations, highlighting the need to identify causative factors underlying this disparity. Method We analyzed RNA sequences of pretransplant whole blood from subjects followed in three kidney transplant cohorts to identify single nucleotide polymorphisms (SNPs) associated with death censored graft loss (DCGL). We employed a meta-analysis to uncover key transcriptional signatures and pathways associated with the identified SNPs and used single cell RNA to define cellular specificity. We characterized SNP functions using in vitro immunological and survival assays and tested for associations between the identified SNPs and other immune-related diseases using a ∼30,100 subject, electronic health record (EHR)-linked database. Results We uncovered a cluster of four consecutive missense SNPs in the Leukocyte Immunoglobulin-Like Receptor B3 ( LILRB3 , a negative immune response regulator) gene that strongly associated with DCGL. This LILRB3 -4SNPs cluster encodes missense mutations at amino acids 617-618 proximal to a SHP-1/2 phosphatase-binding ITIM motif. LILRB3 -4SNPs is specifically enriched within subjects of AA ancestry (8.6% prevalence vs 2.3% in Hispanic and 0.1% in European populations), is not linked to APOL1 G1/G2 alleles, and exhibited a strong association with DCGL. Analysis of PBMC and transplant biopsies from recipients with LILRB3 -4SNPs showed evidence of enhanced adaptive immune responsiveness and ferroptosis-associated death in monocytes. Overexpression of the variant allele in THP-1 cells (macrophage line) induced augmented inflammation and ferroptosis, which were attenuated by a ferroptosis inhibitor, verifying a causal link. The LILRB3 -4SNPs also associated with multiple systemic and organ-specific immune-related diseases in AAs, consistent with conferring a broadly relevant immune function. Conclusion the LILRB3 -4SNPs represent a functionally important, distinct genetic risk factor for kidney transplant outcome and development/severity of other immune-related diseases in patients of AA ancestry. Pharmacological targeting of ferroptosis should be tested to prevent or treat these disease processes in AA recipients carrying LILRB3 -4SNPs. ### Competing Interest Statement Dr. Zhang reports personal fees from VericiDx and reports the patents (1. Patents US Provisional Patent Application F&R ref 27527-0134P01, Serial No. 61/951,651, filled March 2014. Method for identifying kidney allograft recipients at risk for chronic injury; 2. US Provisional Patent Application: Methods for Diagnosing Risk of Renal Allograft Fibrosis and Rejection (miRNA); 3. US Provisional Patent Application: Method for Diagnosing Subclinical Acute Rejection by RNA sequencing Analysis of a Predictive Gene Set; 4. US Provisional Patent Application: Pretransplant prediction of post-transplant acute rejection.); Dr Menon receives research support from Natera. Dr. Cravedi is a consultant for Chinook therapeutics. Dr. Lorenzo Gallon is the non-executive Director and Chair of the science advisory board for Verici. Other investigators have no financial interest to declare. The genomic data of pre- and post-transplant specimen in this study were posted to NCBI Gene Expression Omnibus database (GSE252274). The RNAseq data from VericiDx Inc. is available upon request.

COVID-19 has been a significant public health concern for the last four years; however, little is known about the mechanisms that lead to severe COVID-associated kidney injury. In this multicenter study, we combined quantitative deep urinary proteomics and machine learning to predict severe acute outcomes in hospitalized COVID-19 patients. Using a 10-fold cross-validated random forest algorithm, we identified a set of urinary proteins that demonstrated predictive power for both discovery and validation set with 87% and 79% accuracy, respectively. These predictive urinary biomarkers were recapitulated in non-COVID acute kidney injury revealing overlapping injury mechanisms. We further combined orthogonal multiomics datasets to understand the mechanisms that drive severe COVID-associated kidney injury. Functional overlap and network analysis of urinary proteomics, plasma proteomics and urine sediment single-cell RNA sequencing showed that extracellular matrix and autophagy-associated pathways were uniquely impacted in severe COVID-19. Differentially abundant proteins associated with these pathways exhibited high expression in cells in the juxtamedullary nephron, endothelial cells, and podocytes, indicating that these kidney cell types could be potential targets. Further, single-cell transcriptomic analysis of kidney organoids infected with SARS-CoV-2 revealed dysregulation of extracellular matrix organization in multiple nephron segments, recapitulating the clinically observed fibrotic response across multiomics datasets. Ligand-receptor interaction analysis of the podocyte and tubule organoid clusters showed significant reduction and loss of interaction between integrins and basement membrane receptors in the infected kidney organoids. Collectively, these data suggest that extracellular matrix degradation and adhesion-associated mechanisms could be a main driver of COVID-associated kidney injury and severe outcomes.

Assays that measure morphology, proliferation, motility, deformability, and migration are used to study the invasiveness of cancer cells. However, native invasive potential of cells may be hidden from these contextual metrics because they depend on culture conditions. We created a micropatterned chip that mimics the native environmental conditions, quantifies the invasive potential of tumor cells, and improves our understanding of the malignancy signatures. Unlike conventional assays, which rely on indirect measurements of metastatic potential, our method uses three-dimensional microchannels to measure the basal native invasiveness without chemoattractants or microfluidics. No change in cell death or proliferation is observed on our chips. Using six cancer cell lines, we show that our system is more sensitive than other motility-based assays, measures of nuclear deformability, or cell morphometrics. In addition to quantifying metastatic potential, our platform can distinguish between motility and invasiveness, help study molecular mechanisms of invasion, and screen for targeted therapeutics.

SIGNIFICANCE STATEMENT:The renal immune infiltrate observed in autosomal polycystic kidney disease contributes to the evolution of the disease. Elucidating the cellular mechanisms underlying the inflammatory response could help devise new therapeutic strategies. Here, we provide evidence for a mechanistic link between the deficiency polycystin-1 and mitochondrial homeostasis and the activation of the cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS)/stimulator of the interferon genes (STING) pathway. Our data identify cGAS as an important mediator of renal cystogenesis and suggest that its inhibition may be useful to slow down the disease progression. BACKGROUND:Immune cells significantly contribute to the progression of autosomal dominant polycystic kidney disease (ADPKD), the most common genetic disorder of the kidney caused by the dysregulation of the Pkd1 or Pkd2 genes. However, the mechanisms triggering the immune cells recruitment and activation are undefined. METHODS:Immortalized murine collecting duct cell lines were used to dissect the molecular mechanism of cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS) activation in the context of genotoxic stress induced by Pkd1 ablation. We used conditional Pkd1 and knockout cGas-/- genetic mouse models to confirm the role of cGAS/stimulator of the interferon genes (STING) pathway activation on the course of renal cystogenesis. RESULTS:We show that Pkd1 -deficient renal tubular cells express high levels of cGAS, the main cellular sensor of cytosolic nucleic acid and a potent stimulator of proinflammatory cytokines. Loss of Pkd1 directly affects cGAS expression and nuclear translocation, as well as activation of the cGAS/STING pathway, which is reversed by cGAS knockdown or functional pharmacological inhibition. These events are tightly linked to the loss of mitochondrial structure integrity and genotoxic stress caused by Pkd1 depletion because they can be reverted by the potent antioxidant mitoquinone or by the re-expression of the polycystin-1 carboxyl terminal tail. The genetic inactivation of cGAS in a rapidly progressing ADPKD mouse model significantly reduces cystogenesis and preserves normal organ function. CONCLUSIONS:Our findings indicate that the activation of the cGAS/STING pathway contributes to ADPKD cystogenesis through the control of the immune response associated with the loss of Pkd1 and suggest that targeting this pathway may slow disease progression.

Podocytes form the backbone of the glomerular filtration barrier and are exposed to various mechanical forces throughout the lifetime of an individual. The highly dynamic biomechanical environment of the glomerular capillaries greatly influences the cell biology of podocytes and their pathophysiology. Throughout the past two decades, a holistic picture of podocyte cell biology has emerged, highlighting mechanobiological signalling pathways, cytoskeletal dynamics and cellular adhesion as key determinants of biomechanical resilience in podocytes. This biomechanical resilience is essential for the physiological function of podocytes, including the formation and maintenance of the glomerular filtration barrier. Podocytes integrate diverse biomechanical stimuli from their environment and adapt their biophysical properties accordingly. However, perturbations in biomechanical cues or the underlying podocyte mechanobiology can lead to glomerular dysfunction with severe clinical consequences, including proteinuria and glomerulosclerosis. As our mechanistic understanding of podocyte mechanobiology and its role in the pathogenesis of glomerular disease increases, new targets for podocyte-specific therapeutics will emerge. Treating glomerular diseases by targeting podocyte mechanobiology might improve therapeutic precision and efficacy, with potential to reduce the burden of chronic kidney disease on individuals and health-care systems alike.

Despite recent progress in the identification of mediators of podocyte injury, mechanisms underlying podocyte loss remain poorly understood, and cell-specific therapy is lacking. We previously reported that kidney and brain expressed protein (KIBRA), encoded by WWC1, promotes podocyte injury in vitro through activation of the Hippo signaling pathway. KIBRA expression is increased in the glomeruli of patients with focal segmental glomerulosclerosis, and KIBRA depletion in vivo is protective against acute podocyte injury. Here, we tested the consequences of transgenic podocyte-specific WWC1 expression in immortalized human podocytes and in mice, and we explored the association between glomerular WWC1 expression and glomerular disease progression. We found that KIBRA overexpression in immortalized human podocytes promoted cytoplasmic localization of Yes-associated protein (YAP), induced actin cytoskeletal reorganization, and altered focal adhesion expression and morphology. WWC1-transgenic (KIBRA-overexpressing) mice were more susceptible to acute and chronic glomerular injury, with evidence of YAP inhibition in vivo. Of clinical relevance, glomerular WWC1 expression negatively correlated with renal survival among patients with primary glomerular diseases. These findings highlight the importance of KIBRA/YAP signaling to the regulation of podocyte structural integrity and identify KIBRA-mediated injury as a potential target for podocyte-specific therapy in glomerular disease.