Biology subjects

Patel, J.

Publications and source records attributed to Patel, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Restoring DSCAM expression rescues neuronal morphology and axon guidance deficits in Down syndrome

Down syndrome (DS) results from the triplication of human chromosome 21 (HSA21) and is the leading cause of intellectual disability. Down syndrome cell adhesion molecule (DSCAM) is located on HSA21 and is overproduced in DS. DSCAM is a receptor for netrin-1 and important for neural wiring in the developing brain. Using a Dscam gain-of-function mouse model and human induced pluripotent stem cell (hiPSC)-derived cortical neurons, in combination with cellular, molecular, and behavioral approaches, this study aims to understand how DSCAM triplication and its subsequent excessive production contribute to changes in neural development and intellectual disability in DS. Analysis of morphological parameters revealed impaired neuronal development and loss of netrin-1-mediated axon guidance in mouse hippocampal pyramidal neurons overexpressing DSCAM. Furthermore, DSCAM overexpression reduces interhemispheric connectivity in vivo, and hippocampal- dependent learning in adult mice. DS hiPSC-derived excitatory pyramidal neurons exhibit a similar phenotype: impaired morphological development and loss of netrin-1-mediated axon guidance. Remarkably, normalization of DSCAM in DS hiPSC-derived neurons rescues many of these neuronal phenotypes, including reduced axon length and deficits in axon guidance. These results suggest that DSCAM plays an essential role in the development of neurons and neuronal networks, and its overproduction contributes to intellectual disability in DS.

neuroscience↗

bioRxiv2025

Deep neural networks trained for estimating albedo and illumination achieve lightness constancy differently than human observers.

Lightness constancy, the ability to create perceptual representations that are strongly correlated with surface albedo despite variations in lighting and context, is a challenging computational problem. Indeed, it has proven difficult to develop image-computable models of how human vision achieves a substantial degree of lightness constancy in complex scenes. Recently, convolutional neural networks (CNNs) have been developed that are proficient at estimating albedo, but little is known about how they achieve this, or whether they are good models of human vision. We examined this question by training a CNN to estimate albedo and illumination in a computer-rendered virtual world, and evaluating both the CNN and human observers in a lightness matching task. In several conditions, we eliminated cues potentially supporting lightness constancy: local contrast, shading, shadows, and all contextual cues. We found that the network achieved a high degree of lightness constancy, outperforming three classic models, and substantially outperforming human observers as well. However, we also found that eliminating cues affected the CNN and humans very differently. Humans had much worse constancy when local contrast cues were made uninformative, but were minimally affected by elimination of shading or shadows. The CNN was unaffected by local contrast, but relied on shading and shadows. These results suggest that the CNN followed an effective strategy of integrating global image cues, whereas humans used a more local strategy. In a follow-up experiment, we found that the CNN could learn to exploit noise artifacts that were correlated with illuminance in ray-traced scenes, whereas humans did not. We conclude that CNNs can learn an effective, global strategy of estimating lightness, which is closer to an optimal strategy for the ensemble of scenes we studied than the computation used by human vision.

neuroscience↗

bioRxiv2025

Molecular mechanisms regulating PDE11A4 age-related liquid-liquid phase separation (LLPS) and its reversal by selective, potent and orally-available PDE11A4 small molecule inhibitors both in vitro and in vivo

PDE11A is a little-studied phosphodiesterase family that breaks down cAMP and cGMP, with the PDE11A4 isoform enriched in the memory-related hippocampus. Age-related increases in hippocampal PDE11A expression occur in human and rodents, causing age-related cognitive decline of social memories. Interestingly, this age-related increase triggers PDE11A4 liquid-liquid phase separation (LLPS), causing the enzyme to accumulate in the brain in filamentous structures termed "ghost axons". Here we sought to identify molecular mechanisms regulating PDE11A4 LLPS and therapeutic approaches capable of reversing it. PDE11A4 LLPS was reduced by phosphorylation of PDE11A4-S163 or-S239 and the D355A mutation that blocks the effect of cGMP binding the PDE11A4 GAF-A domain. PDE11A4 LLPS was increased by inhibiting kinases with staurosporine or stimulating packaging/repacking via the trans-Golgi network by overexpressing TGN38 or RhoB. 8 PDE11 inhibitors (MLG-122, MLG-185, MLG-199, SMQ-02-57, SMQ-03-30, SMQ-03-20, tadalafil, and BC11-38) across 3 scaffolds reverse overexpression-related PDE11A4 LLPS in HT22 mouse hippocampal neuronal cells. This effect of PDE11A4 inhibitors occurs within minutes, is reversed upon washout of lower but not higher concentrations, and occurs in part by reducing PDE11A4 homodimerization. PDE11A4 inhibitors also rescued exacerbated PDE11A4 LLPS triggered by aging-like S117D/S124D phosphomimic mutations, staurosporine, or TGN38/RhoB overexpression. In vivo, orally-administered 30mg/kg SMQ-03-20 reversed age-related increases in PDE11A4 ghost axons and neuroinflammation in old mice. Thus, PDE11A inhibitors that reverse age-related PDE11A4 LLPS in HT22 hippocampal cells also reduce PDE11A4 ghost axons and neuroinflammation in the aged mouse brain, indicating therapeutical potential.

neuroscience↗

bioRxiv2025

Redirecting cytomegalovirus immunity against pancreas cancer for immunotherapy

Immunotherapy shows limited success in pancreatic cancer, largely due to a low mutational burden and immunosuppressive microenvironment. Here we hypothesized that pre-existing antiviral immunity can be redirected to control pancreatic tumors. Cytomegalovirus (CMV, a {beta}-herpesvirus) was chosen, as the majority of the population is infected and it induces an extremely large/broad memory T cell response. Mice latently infected with murine CMV (MCMV) were orthotopically implanted with pancreatic cancer cells and treated with systemic injections of MCMV T-cell epitopes. The therapy promoted preferential accumulation of MCMV-specific T cells within pancreatic tumors, delaying tumor growth and increasing survival. Immunophenotyping and scRNAseq analyses showed these T cells were highly activated and cytotoxic, leading to increased tumor necrosis and caspase-3 activation. Finally, therapy was enhanced when combined with subtherapeutic doses of gemcitabine chemotherapy. Together, these results show that CMV-specific T cells can be repurposed to combat pancreatic cancer. SignificanceOur studies reveal that CMV-specific viral memory T cells can be re-directed to control a solid tumor normally refractory to immunotherapy via a simple, intravenous injection of T cell peptide epitopes. This mutation agnostic approach has significant potential for the development of "off-the-shelf" therapeutics by stimulating pre-existing antiviral memory and it is widely applicable due to the high prevalence of CMV.

cancer biology↗

bioRxiv2025

A high-throughput platform for biophysical antibody developability assessment to enable AI/ML model training

Antibodies must bind their targets with high affinity and specificity to achieve useful therapeutic activity. They must also possess suitable developability properties (e.g., thermostability, solubility, viscosity, polyreactivity) to ensure favorable manufacturing, formulation, and in vivo performance. Both binding and developability properties are inherent to a given antibody amino acid sequence. Identification or selection of antibodies possessing suitable binding characteristics is now routine, and de novo computational design models, trained on extensive complementarity-determining region sequence and structural data, are rapidly improving. Developability properties, however, remain difficult to predict largely due to insufficient training data, with empirical testing being heavily used to avoid challenges in late-stage antibody development. To fill this gap, we built a high-throughput antibody developability assay platform designed to generate the large datasets needed to train improved machine learning (ML) models. We optimized and automated known developability assays [Jain et al., 2017], and developed a robust integrated data analytics pipeline. Here we report data on 246 antibodies--representing 106 approved, 135 clinical-stage, and 5 preregistration/withdrawn molecules--across a panel of 10 developability assays, in a "tidy data" format suitable for AI/ML modeling. We used these data to develop an XGBoost [Chen et al., 2016] ML model that better predicts similarity to approved antibodies compared to conventional use of developability warning thresholds. Additionally, we confirm that preliminary predictive models do improve with more training data. Our high-throughput PROPHET-Ab platform enables data generation at the scale needed to develop improved ML models to predict antibody developability. SignificanceSuccessful antibody drugs exhibit important "developability" properties, beyond tight and specific binding to their target, including high expressibility, high stability and solubility, low aggregation propensity, low viscosity, low polyreactivity, and long in vivo half-life. Collectively, developability properties predict favorable manufacturing, storage, administration, and safety, and deficiencies in these properties increase risk for clinical failure. Despite progress in developing machine learning models to predict structure and binding, antibody developability models lag, largely due to a lack of sufficiently large training datasets. We have built a high-throughput platform, PROPHET-Ab, that enables data generation at the scale needed to train improved AI/ML models to predict antibody developability.

biophysics↗

bioRxiv2025

RNA Transcripts Serve as a Template for Double-Strand Break Repair in Human Cells

Double-strand breaks (DSBs) are toxic lesions that lead to genome instability. While canonical DSB repair pathways typically operate independently of RNA, emerging evidence suggests that RNA:DNA hybrids and transcripts near damaged sites can influence repair outcomes. However, a direct role for transcript RNA as a template during DSB repair in human cells is yet to be established. In this study, we designed fluorescent- and sequencing-based assays, which demonstrated that RNA-containing oligonucleotides and messenger RNA serve as templates to promote DSB repair. We conducted a CRISPR/Cas9-based genetic screen to identify factors that promote RNA-templated DSB repair (RT-DSBR), and of the candidate polymerases, we identified DNA polymerase-zeta (Pol{zeta}) as the potential reverse transcriptase that facilitates RT-DSBR. Furthermore, by analyzing sequencing data from cancer genomes, we identified the presence of whole intron deletions, a unique genomic scar reflective of RT-DSBR activity generated when spliced mRNA serves as the repair template. These findings highlight RT-DSBR as an alternative pathway for repairing DSBs in transcribed genes, with potential mutagenic consequences.

molecular biology↗

bioRxiv2025

Dynamic Reprogramming of Stromal Pdgfra-expressing cells during WNT-Mediated Transformation of the Intestinal Epithelium

Stromal fibroblasts regulate critical signaling gradients along the intestinal crypt-villus axis1 and provide a niche that supports adjacent epithelial stem cells. Here we report that Pdgfra-expressing fibroblasts secrete ligands that promote a regenerative-like state in the intestinal mucosa during early WNT-mediated tumorigenesis. Using a mouse model of WNT-driven oncogenesis and single-cell RNA sequencing (RNA-seq) of mesenchyme cell populations, we revealed a dynamic reprogramming of Pdgfra+ fibroblasts that facilitates WNT-mediated tissue transformation. Functional assays of potential mediators of cell-to-cell communication between these fibroblasts and the oncogenic epithelium revealed that TGFB signaling is notably induced in Pdgfra+ fibroblasts in the presence of oncogenic epithelium, and TGFB was essential to sustain regenerative-like growth of organoids ex vivo. Genetic reduction of Cdx2 in the {beta}-catenin mutant epithelium elevated the fetal-like/regenerative transcriptome and accelerated WNT-dependent onset of oncogenic transformation of the tissue in vivo. These results demonstrate that Pdgfra+ fibroblasts are activated during WNT-driven oncogenesis to promote a regenerative state in the epithelium that precedes and facilitates formation of tumors.

cancer biology↗

bioRxiv2025

Cancer associated fibroblasts drive epithelial to mesenchymal transition and classical to basal change in pancreatic ductal adenocarcinoma cells with loss of IL-8 expression

Pancreatic ductal adenocarcinoma (PDAC) carries an extremely poor prognosis, in part resulting from cellular heterogeneity that supports overall tumorigenicity. Cancer associated fibroblasts (CAF) are key determinants of PDAC biology and response to systemic therapy. While CAF subtypes have been defined, the effects of patient-specific CAF heterogeneity and plasticity on tumor cell behavior remain unclear. Here, multi-omics was used to characterize the tumor microenvironment (TME) in tumors from patients undergoing curative-intent surgery for PDAC. In these same patients, matched tumor organoid and CAF lines were established to functionally validate the impact of CAFs on the tumor cells. CAFs were found to drive epithelial-mesenchymal transition (EMT) and a switch in tumor cell classificiaton from classical to basal subtype. Furthermore, we identified CAF-specific interleukin 8 (IL-8) as an important modulator of tumor cell subtype. Finally, we defined neighborhood relationships between tumor cell and T cell subsets. Statement of SignificanceThis multidimensional analysis highlights the diverse role CAFs have in influencing other cell types in the TME, including epithelial-derived tumor and infiltrating immune cells. Our methods provide a platform for evaluating emerging therapeutic approaches and for studying mechanisms that dictate tumor behavior in a manner that reflects patient-specific heterogeneity.

cancer biology↗

bioRxiv2024

SUMO Inhibition Plus CD40 Agonism Increases Anti-Tumor Immunogenicity Through Interferon Mediated Macrophage Activation

Resistance to immunotherapy is a cardinal feature of pancreatic ductal adenocarcinoma (PDAC). Inhibition of Small Ubiquitin-like MOdifier (SUMO), a post-translational modification with important immune regulatory functions, augments responsiveness to immunotherapy in non-PDAC models via pro-immunogenic effects on myeloid cells, cancer cells, and T-cells. Recently, it has been reported that SUMO inhibition has direct immunogenic effects on PDAC. Here, we report that the novel combination of SUMO inhibition with a small molecule, TAK-981, plus antibody-mediated CD40 agonism improves survival in an aggressive orthotopic mouse model of PDAC by enhancing anti-tumoral immunogenicity. This combination amplifies CD8+ T-cell tumor infiltration and induces significant changes among macrophages. TAK-981 also leads to enhanced cancer specific MHC-I expression both in vitro and in vivo by augmenting interferon signaling. We show that the improvement in survival is mediated by macrophages. Our findings show that SUMO inhibition complements CD40 agonism to enhance immune activity in PDAC via interferon signaling, improving survival in an aggressive pre-clinical model of PDAC and translating previous findings to a characteristically immunosuppressive and highly aggressive solid malignancy.

cancer biology↗

bioRxiv2024

Age-related increases in PDE11A4 protein expression trigger liquid:liquid phase separation (LLPS) of the enzyme that can be reversed by PDE11A4 small molecules inhibitors

PDE11A is a little-studied phosphodiesterase sub-family that breaks down cAMP/cGMP, with the PDE11A4 isoform being enriched in the memory-related brain region called the hippocampus. Age-related increases in PDE11A expression occur in human and rodent hippocampus and cause age-related cognitive decline of social memories. Interestingly, the age-related increase in PDE11A4 protein ectopically accumulates in spherical clusters that group together in the brain to form linear filamentous patterns termed "ghost axons." The biophysical/physiochemical mechanisms underlying this age-related clustering of PDE11A4 are not yet known. As such, we determine here if age-related clustering of PDE11A4 may reflect liquid:liquid phase separation (LLPS), and if PDE11A inhibitors being developed for age-related cognitive decline can reverse this biomolecular condensation. We found that human and mouse PDE11A4 exhibit several LLPS-promoting sequence features including intrinsically disordered regions, non-covalent pi-pi interactions, and prion-like domains, with multiple bioinformatic tools predicting PDE11A4 undergoes LLPS. Consistent with these predictions, age-related PDE11A4 clusters were non-membrane bound spherical droplets that progressively fuse over time in a concentration-dependent manner. 5 different PDE11 inhibitors (tadalafil, BC11-38, SMQ-02-57, SMQ-03-30 and SMQ-03-20) across 3 scaffolds reversed PDE11A4 LLPS (a.k.a. remixing) in hippocampal HT22 cells, with PDE11A4 droplets reforming (a.k.a. de-mixing) following a 5-hour washout of low but not high concentrations of these compounds. Strikingly, a single oral administration of 30 mg/kg SMQ-03-20 substantially reduced the presence of PDE11A4 ghost axon in the aged mouse brain. Thus, PDE11A4 exhibits 4 defining criteria of LLPS, and PDE11A small molecule inhibitors reverse this age-related phenotype both in vitro and in vivo.

neuroscience↗

bioRxiv2024

A novel role for Neurog2 in MYCN driven neuroendocrine plasticity of prostate cancer

Neuroendocrine prostate cancer (NEPC) presents a formidable clinical challenge owing to its aggressive progression and resistance to conventional therapies. A key driver of NEPC is the overexpression of MYCN, a well-established oncogene associated with neuroendocrine tumors. However, efforts to directly inhibit the N-Myc protein encoded by this gene have resulted in limited success, thereby hindering therapeutic advancements. To overcome this obstacle, we conducted unbiased genome-wide screening using isogenic prostate cancer cell lines to identify the synthetic vulnerabilities of MYCN. Among the identified candidates, NEUROG2 emerged as a significant candidate. Neurog2 is a proneural transcription factor (PTF) known for its role in developmental processes and trans-differentiation of adult cells. Our findings demonstrate that Neurog2 depletion does not affect non-malignant cells, but significantly suppresses the growth of MYCN-overexpressing cells and tumors in orthotopic NEPC models. Furthermore, our observations indicate that the Neurog2-mediated regulation of PTFs can facilitate NEPC development. Thus, targeting Neurog2 holds promise as an effective therapeutic strategy for MYCN-overexpressing NEPC.

cancer biology↗

bioRxiv2024

SGLT2 inhibitors activate pantothenate kinase in the human heart

Inhibitors of sodium glucose cotransporter-2 (SGLT2i) demonstrate strong symptomatic and mortality benefits in the treatment of heart failure but appear to do so independently of SGLT2. The relevant pharmacologic target of SGLT2i remains unclear. We show here that SGLT2i directly activate pantothenate kinase 1 (PANK1), the rate-limiting enzyme that initiates the conversion of pantothenate (vitamin B5) to coenzyme-A (CoA), an obligate co-factor for all major pathways of fuel use in the heart. Using stable-isotope infusion studies, we show that SGLT2i promote pantothenate consumption, activate CoA synthesis, rescue decreased levels of CoA in human failing hearts, and broadly stimulate fuel use in ex vivo perfused human cardiac blocks from patients with heart failure. Furthermore, we show that SGLT2i bind to PANK1 directly at physiological concentrations and promote PANK1 enzymatic activity in assays with purified components. Novel in silico dynamic modeling identified the site of SGLT2i binding on PANK1 and indicated a mechanism of activation involving prevention of allosteric inhibition of PANK1 by acyl-CoA species. Finally, we show that inhibition of PANK1 prevents SGLT2i-mediated increased contractility of isolated adult human cardiomyocytes. In summary, we demonstrate robust and specific off-target activation of PANK1 by SGLT2i, promoting CoA synthesis and efficient fuel use in human hearts, providing a likely explanation for the remarkable clinical benefits of SGLT2i.

biochemistry↗

bioRxiv2024

Multi-Model Machine Learning for Automated Identification of Rice Diseases Using Leaf Image Data

PurposeRice is grown almost everywhere in the world but is notably prevalent in Asian nations where it serves as the main food source for nearly half of the worlds population. Yet, enduring agricultural problems like various rice diseases have been a problem for farmers and planting specialists for ages. A fast, efficient, less expensive, and reliable approach to detecting rice diseases is urgently required in agricultural information since severe rice infections could result in no harvest of grains. Automated disease monitoring of rice plants using leaf images is critical for transitioning from labor-intensive, experience-based decision-making to an automated, data-driven strategy in agricultural production. In the modern era, Artificial Intelligence (AI) is being widely investigated in various areas of the medical and plant sciences to assess and diagnose the types of diseases. MethodsThis work proposes a hybrid deep-machine learning system for the automated detection of rice plant diseases using a leaf image dataset. Benchmarked MobileNetV2 architecture is employed to extract the deep features from the input images. Obtained features are fed as input to various machine learning classifiers with different kernel functions using a 10-fold validation strategy. ResultsThe developed hybrid system attained the highest classification accuracy of 98.6%, specificity of 98.85%, and sensitivity of 97.25% using a medium neural network. The results demonstrate that the established system is computationally faster and more efficient. The proposed system is ready for testing with more databases. ConclusionsThe suggested technology accurately diagnoses various rice plant illnesses, reducing manual labor and allowing farmers to receive prompt treatment. Future research topics include incorporating cloud-based monitoring for leaf image capture in non-connected farms, as well as building mobile IoT platforms for continuous screening.

plant biology↗

bioRxiv2024

MICAL2 Is a Super Enhancer Associated Gene that Promotes Pancreatic Cancer Growth and Metastasis

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest solid cancers and thus identifying more effective therapies is a major unmet need. In this study we characterized the super enhancer (SE) landscape of human PDAC to identify novel, potentially targetable, drivers of the disease. Our analysis revealed that MICAL2 is a super enhancer-associated gene in human PDAC. MICAL2 is a flavin monooxygenase that induces actin depolymerization and indirectly promotes SRF transcription by modulating the availability of serum response factor coactivators myocardin related transcription factors (MRTF-A and MRTF-B). We found that MICAL2 is overexpressed in PDAC and correlates with poor patient prognosis. Transcriptional analysis revealed that MICAL2 upregulates KRAS and EMT signaling pathways, contributing to tumor growth and metastasis. In loss and gain of function experiments in human and mouse PDAC cells, we observed that MICAL2 promotes both ERK1/2 and AKT activation. Consistent with its role in actin depolymerization and KRAS signaling, loss of MICAL2 expression also inhibited macropinocytosis. Through in vitro phenotypic analyses, we show that MICAL2, MRTF-A and MRTF-B influence PDAC cell proliferation, migration and promote cell cycle progression. Importantly, we demonstrate that MICAL2 is essential for in vivo tumor growth and metastasis. Interestingly, we find that MRTF-B, but not MRTF-A, phenocopies MICAL2-driven phenotypes in vivo. This study highlights the multiple ways in which MICAL2 impacts PDAC biology and suggests that its inhibition may impede PDAC progression. Our results provide a foundation for future investigations into the role of MICAL2 in PDAC and its potential as a target for therapeutic intervention.

cancer biology↗

bioRxiv2024

Two-hit mouse model of heart failure with preserved ejection fraction combining diet-induced obesity and renin-mediated hypertension

Heart failure with preserved ejection fraction (HFpEF) is increasingly common but its pathogenesis is poorly understood. The ability to assess genetic and pharmacologic interventions is hampered by the lack of robust preclinical mouse models of HFpEF. We have developed a novel "2-hit" model, which combines obesity and insulin resistance with chronic pressure overload to recapitulate clinical features of HFpEF. C57BL6/NJ mice fed a high fat diet for >10 weeks were administered an AAV8-driven vector resulting in constitutive overexpression of mouse Renin1d. Control mice, HFD only, Renin only and HFD-Renin (aka "HFpEF") littermates underwent a battery of cardiac and extracardiac phenotyping. HFD-Renin mice demonstrated obesity and insulin resistance, a 2-3-fold increase in circulating renin levels that resulted in 30-40% increase in left ventricular hypertrophy, preserved systolic function, and diastolic dysfunction indicated by altered E/e, IVRT, and strain measurements; increased left atrial mass; elevated natriuretic peptides; and exercise intolerance. Transcriptomic and metabolomic profiling of HFD-Renin myocardium demonstrated upregulation of pro-fibrotic pathways and downregulation of metabolic pathways, in particular branched chain amino acid catabolism, similar to findings in human HFpEF. Treatment of these mice with the sodium-glucose cotransporter 2 inhibitor empagliflozin, an effective but incompletely understood HFpEF therapy, improved exercise tolerance, left heart enlargement, and insulin homeostasis. The HFD-Renin mouse model recapitulates key features of human HFpEF and will enable studies dissecting the contribution of individual pathogenic drivers to this complex syndrome. Addition of HFD-Renin mice to the preclinical HFpEF model platform allows for orthogonal studies to increase validity in assessment of interventions. NEW & NOTEWORTHYHeart failure with preserved ejection fraction (HFpEF) is a complex disease to study due to limited preclinical models. We rigorously characterize a new two-hit HFpEF mouse model, which allows for dissecting individual contributions and synergy of major pathogenic drivers, hypertension and diet-induced obesity. The results are consistent and reproducible in two independent laboratories. This high-fidelity pre-clinical model increases the available, orthogonal models needed to improve our understanding of the causes and assessment treatments for HFpEF.

physiology↗

bioRxiv2024

Identification of Fasnall as a therapeutically effective Complex I inhibitor

Proliferating cancer cells actively utilize anabolic processes for biomass production, including de novo biosynthesis of amino acids, nucleotides, and fatty acids. The key enzyme of the fatty acid biosynthesis pathway, fatty acid synthase (FASN), is widely recognized as a promising therapeutic target in cancer and other health conditions1,2. Here, we establish a metabolic signature of FASN inhibition using a panel of pharmacological inhibitors (GSK2194069, TVB-2640, TVB-3166, C75, cerulenin, and Fasnall). We find that the activity of commonly used FASN inhibitors is inconsistent with the metabolic signature of FASN inhibition (accumulation of malonate, succinate, malonyl coenzyme A, succinyl coenzyme A, and other metabolic perturbations). Moreover, we show that one of these putative FASN inhibitors, Fasnall, is a respiratory Complex I inhibitor that mimics FASN inhibition through NADH accumulation and consequent depletion of the tricarboxylic acid cycle metabolites. We demonstrate that Fasnall impairs tumor growth in several oxidative phosphorylation-dependent cancer models, including combination therapy-resistant melanoma patient-derived xenografts. Fasnall administration does not reproduce neurological side effects in mice reported for other Complex I inhibitors3,4. Our results have significant implications for understanding the FASN role in human health and disease and provide evidence of therapeutic potential for Complex I inhibitors with fast systemic clearance. Our findings also highlight the continuing need for validation of small molecule inhibitors to distinguish high-quality chemical probes and to expand the understanding of their application.

cancer biology↗

bioRxiv2024

Sodium-glucose co-transporter 2 Inhibitors Act Independently of SGLT2 to Confer Benefit for Heart Failure with Reduced Ejection Fraction in Mice

Sodium-glucose co-transporter 2 inhibitors (SGLT2i) are novel, potent heart failure medications with an unknown mechanism of action. We sought to determine if the beneficial actions of SGLT2i in heart failure were on- or off-target, and related to metabolic reprogramming, including increased lipolysis and ketogenesis. The phenotype of mice treated with empagliflozin and genetically engineered mice constitutively lacking SGLT2 mirrored metabolic changes seen in human clinical trials (including reduced blood glucose, increased ketogenesis, and profound glucosuria). In a mouse heart failure model, SGLT2i treatment, but not generalized SGLT2 knockout, resulted in improved systolic function and reduced pathologic cardiac remodeling. SGLT2i treatment of the SGLT2 knockout mice sustained the cardiac benefits, demonstrating an off-target role for these drugs. This benefit is independent of metabolic changes, including ketosis. The mechanism of action and target of SGLT2i in HF remain elusive.

physiology↗

bioRxiv2024

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer1-7, however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naive hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

cancer biology↗