Biology subjects

Malik, S.

Publications and source records attributed to Malik, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Olfactory neuroepithelium biomarker platform: a proof from Alzheimer's disease

Unlike other diseases where target organs for biopsy are accessible, surrogate platforms are warranted for biomarkers of neuropsychiatric disorders due to the inaccessibility of the brain. We demonstrate a non-invasive platform combining a nasal soft-brush swab with single-cell Western blotting for neuron-specific protein analysis. Applied to Alzheimer's disease targeting phosphorylated tau, this demonstrated superior diagnostic capacity compared with blood-based approaches, indicating that the olfactory neuroepithelium is a sensitive biomarker platform.

biochemistry↗

bioRxiv2026

Integrative Bioinformatics Approach to Identify Prognostic Gene Signatures for Risk Stratification in Thyroid Carcinoma

Thyroid cancer is a heterogeneous malignancy with variable outcomes, highlighting the need for reliable biomarkers and effective risk stratification. In this study, we implemented a multi-step integrative framework to identify distinct prognostic biomarker sets using transcriptomic data from 572 thyroid cancer patients. Correlation analysis followed by false discovery rate (FDR) correction revealed significant associations of genes. Notably, MAFF (r = 0.25, p = 1.34x10-, FDR = 2.46x10-), NR4A3 (r = 0.24, p = 1.26x10-, FDR = 9.25x10-), and SRF showed strong positive correlations, whereas LOC728264 (r = -0.21, p = 7.39x10-, FDR = 6.36x10-) and VAMP1 (r = -0.20, p = 1.20x10-, FDR = 1.3x10-) exhibited negative correlations with OS. Univariate Cox regression identified several survival-associated genes, including TMEM90B (HR = 10.66, p = 2.88x10-) and PTH1R (HR = 9.88, p = 5.55x10-). LASSO regression further identified 31 key prognostic genes, including 13 potential drug targets predominantly functioning as inhibitors. Machine learning models based on seven independent 20-gene biomarker sets effectively predicted Class 0 (0-1 years), Class 1 (1-3 years), Class 2 (3-5 years), and Class 3 (>5 years), achieving AUC values of 0.91-0.94 and Kappa up to 0.76. An ensemble model further improved prediction (AUC = 0.95, Kappa = 0.72). Incorporating clinical variables (age, gender, stage) enhanced model performance (AUC = 0.96, Kappa = 0.80). Reduced 10- and 5-gene subsets demonstrated consistent yet slightly lower performance (AUC = 0.90 and 0.86, respectively). Collectively, the 20-gene set exhibited the strongest predictive and prognostic potential, highlighting the importance of integrating molecular and clinical features for risk stratification in thyroid cancer.All data and code are openly available (https://github.com/raghavagps/THCA_prognostic_biomarkers), supporting future research in thyroid cancer prediction.

bioinformatics↗

bioRxiv2026

Developmental regulation of progenitor aging shapes long-term intestinal homeostasis in Drosophila

Aging causes a progressive loss of tissue homeostasis, with stem cell exhaustion as a major hallmark. Age-associated decline in organ function is widely perceived as emanating from progressive accumulation of cellular damage in adult tissues. However, whether aging trajectories are established early on during development remains an open question. Here, we demonstrate that genetic modulation of cellular aging pathways in larval adult midgut progenitors (AMPs), which serve as the precursors of adult intestinal stem cells and differentiated epithelial cells, dictates the long-term trajectory of intestinal aging in Drosophila. Accelerated cellular aging by genetic perturbation employing Toll or Imd pathway overactivation or elevation of reactive oxygen species (ROS) using ND42 (mitochondrial complex I) knockdown in the AMPs results in aberrant progenitor proliferation, skewed lineage allocation, epithelial barrier dysfunction, and genomic instability. These alterations are accompanied by marked destabilization of AMP islet architecture and widespread changes in age-related molecular signatures, as revealed by bulk transcriptomic analysis. In contrast, decelerated cellular aging mediated by Foxo or Atg8a overexpression results in a decrease in enteroendocrine population and the intestinal barrier remained unaffected. Intriguingly, early-life activation of immune and oxidative stress signaling manifested later in the adult gut as elevated enteroendocrine differentiation, highlighting lasting effects on intestinal regenerative capacity and lineage balance. Together, our findings demonstrate that cellular aging is tightly regulated early on in development and its perturbation can cause developmental disruption hampering adult gut homeostasis, establishing AMPs as key developmental determinants that regulate the trajectory of intestinal aging in Drosophila.

developmental biology↗

bioRxiv2026

Intellectual disability risk gene RFX4 regulates cortical neurogenesis by restraining neuronal differentiation

Despite the recent identification of RFX4 as a neurodevelopmental disorder risk gene, its role in cortical development remained unclear. Here, we identified both shared and lineage-specific RFX4 requirements for human cortical development using new human stem cell models of deficiency and pathogenic mutation. We found that RFX4 restrains neurogenesis by acting cooperatively with NOTCH signaling, specifically repressing pro-neuronal and synaptic gene expression in neural progenitors. We also determined that genome-wide binding of RFX3, another neurodevelopmental disorder risk gene, depends upon RFX4 to regulate synaptic gene expression. Furthermore, we identified lineage-specific functions for RFX4 in regulating proliferation during cortical inhibitory neuron development. Ultimately, we demonstrated that RFX4 deficiency persistently dysregulates neuronal gene expression through neuronal differentiation and disrupts cortical neuron stratification in organoid models. These consequences were absent in neurons generated by direct differentiation, confirming that neuronal phenotypes resulted from unconstrained neurogenesis. Finally, we modeled pathogenic missense mutation of the RFX4 DNA-binding domain. While this mutation strongly reduced DNA binding, it dysregulated synaptic gene expression distinctly from our deficiency models, supporting pathogenic mechanisms distinct from haploinsufficiency. Together, this work identified both shared and lineage-specific requirements for RFX4 during cortical development, building a necessary foundation for elucidating the etiology of RFX4-associated disorders.

developmental biology↗

bioRxiv2025

Dynamic ASK1 proximity networks uncover SCF-dependent and noncanonical roles in ABA and drought adaptation

Plants rely on rapid proteome remodeling to withstand fluctuating environmental conditions, yet how the ubiquitin system dynamically coordinates these multilayered responses remains unclear. Here we define the in vivo proximity interactome of ARABIDOPSIS SKP1-LIKE 1 (ASK1), the core adaptor of SCF ubiquitin ligases, under acute abscisic acid (ABA) signaling and prolonged drought. TurboID-based proximity labeling coupled with quantitative proteomics revealed that ASK1 assembles highly condition-specific protein networks, distinguishing canonical SCF modules from broader noncanonical associations with transcriptional, chromatin, translational, vesicle-trafficking, and proteostasis machinery. Acute ABA exposure rapidly recruits F-box proteins and ABA-responsive transcription factors while engaging ribosomal and chromatin modules, whereas drought drives ASK1 into expanded proteostasis and stress-signaling assemblies, including chaperone-cochaperone systems, transcriptional repressors, and autophagy-endomembrane components. Global proteomics shows that ASK1 overexpression enhances accumulation of drought-protective and ABA-responsive proteins while repressing immune and ROS-scavenging pathways, indicating a shift in resource allocation. Together, these results describe ASK1 as a multifunctional proteostasis and signaling hub that integrates SCF-dependent and SCF-independent pathways to coordinate transcriptional, translational, and proteolytic reprogramming during plant adaptation to stress.

plant biology↗

bioRxiv2025

A Novel FNDC1-NAMPT-NAD axis is Implicated in Small and Large-vessel Arterial Disease and Drives Vascular Calcification

Vascular calcification represents a convergent pathological feature of diverse cardiovascular diseases, yet the upstream molecular programs orchestrating this process remain poorly defined. Here, we uncover fibronectin type III domain-containing 1 (FNDC1) as a previously unrecognized regulator of vascular calcification across both microvascular and macrovascular beds. Integrative transcriptomic profiling of human calciphylaxis lesions and atherosclerotic coronaries identified FNDC1 as one of the most significantly upregulated genes. In primary human vascular smooth muscle cells, FNDC1 drove osteogenic phenotype switch and vascular calcification through activation of PI3K/AKT signaling and metabolic reprogramming. Mechanistically, FNDC1 directly binds to nicotinamide phosphoribosyltransferase (NAMPT) resulting in elevated intracellular NAD levels, thus coupling vascular signaling to control of NAD biosynthesis. In murine models, genetic deletion of Fndc1 or pharmacologic inhibition of NAMPT suppressed arterial calcification and prolonged survival. Clinically, circulating FNDC1 levels were elevated in patients with both calciphylaxis and coronary artery disease and independently predicted cardiovascular risk in 42,687 UK Biobank participants. Together, these findings establish FNDC1 as a central mediator of vascular pathology and highlight the FNDC1- NAMPT-NAD+ axis as a promising target for therapeutic intervention.

cell biology↗

bioRxiv2025

IL4Pred2: Prediction of Interleukin-4 Inducing Peptides in Human and Mouse

In 2013, our group developed IL4pred, a host-independent method for predicting interleukin-4 (IL-4) inducing peptides, which has been widely used by the scientific community. In this study, we present a second-generation method, IL4Pred2, which is a host-specific approach designed to predict IL-4 inducing peptides separately for human and mouse hosts. All models were trained, tested, and benchmarked on experimentally validated data obtained from the IEDB. We employed a wide range of state-of-the-art techniques for prediction, including similarity-based approaches, machine learning, deep learning methods, and large language models. Our best model achieved highest AUC 0.80 with MCC 0.45 for human and AUC 0.82 with MCC 0.50 for mouse on independent set of main datasets. All models were trained, test and optimized on training dataset. We validate our final model on an independent dataset which is not used in training or hyperparameter optimization of models. In this study, we developed models on three types of datasets called Main, Alternate1 and Alternate2 for predicting IL-4 inducing peptides. This abstract show performance of our models on Main dataset, performance of models on other datasets have been discussed in manuscript. One of the major objectives of this study is to facilitate research community in the area of immunotherapy and vaccine development. Thus, we developed, a web server and standalone software IL4pred2 for predicting, designing and scanning IL-4 inducing peptides in proteins (https://webs.iiitd.edu.in/raghava/il4pred2/ and https://github.com/raghavagps/il4pred2).

bioinformatics↗

bioRxiv2025

Identification of Multiple Prognostic Biomarker Sets for Risk Stratification in SKCM

Most of the existing studies have identified a single profile of prognostic biomarkers for predicting high-risk cancer patients using transcriptomics data. In this study, we propose multiple distinct sets of prognostic biomarkers for predicting high-risk Skin Cutaneous Melanoma (SKCM) patients. Our primary analysis reveals that the expression of certain genes, such as CREG1, PCGF5, and VPS13C, strongly correlates with overall survival (OS) in SKCM patients. We developed machine learning-based prognostic models to predict 1-, 3-, and 5-year overall survival using gene expression profiles. State-of-the-art feature selection techniques were employed to identify the first prognostic biomarkers set consisting of 20 genes. Machine learning models built to predict high-risk patients using this set of biomarkers and achieved an AUC of 0.90 and a Kappa of 0.58 in distinguishing high-risk SKCM patients. Similarly, a second independent set of 20 prognostic genes was identified, with no overlap with the first set. The best model trained on this second set achieved an AUC of 0.89 with a Kappa of 0.56, while the fifth biomarker set achieved the highest performance with an AUC of 0.91 and a Kappa of 0.64. This process was repeated to obtain a total of seven distinct prognostic biomarker sets, each containing 20 unique genes. The predictive performance of these models varied between 0.84 and 0.91 for AUC and 0.48 to 0.64 for Kappa on the validation dataset. These findings demonstrate that it is possible to identify multiple independent sets of prognostic biomarkers, each capable of accurately predicting high-risk SKCM patients. HighlightsO_LIPrediction of high-risk SKCM patients from transcriptomics data C_LIO_LIIdentification of multiple set of prognostic biomarkers C_LIO_LIIdentification of set of biomarkers using feature selection technique C_LIO_LIDevelopment of machine learning based models for prediction C_LIO_LIPathway analysis of selected set of biomarker genes C_LI

bioinformatics↗

bioRxiv2025

Soil and water microbial communities: A source of novel antibiotics for sustainable plant disease control

Pathogenic microorganisms pose a significant threat to plant health and agricultural productivity worldwide. Herein, this study explores the potential of natural microbial communities as sources of biopesticides. We analyzed 20 soil and water samples from remote areas, isolating 121 colonies using nutrient agar. Antibacterial activity was assessed through agar diffusion, revealing that 12 colonies exhibited significant inhibitory effects against various pathogenic bacteria. Measurement of inhibition zones indicated that these colonies could produce antibiotics. Subsequently, molecular characterization with 16S rRNA and BLAST searches of 12 unidentified sequences highlighted substantial microbial diversity within the samples. This research underscores the promise of these natural microbial communities in developing biocontrol agents for managing plant diseases in greenhouse and field environments. Extraction and purification techniques could further refine these antibiotics, advancing sustainable agricultural practices.

microbiology↗

bioRxiv2025

E2F1 Suppresses EBV Lytic Reactivation through Cellular and Viral Transcriptional Networks

Latent EBV infection is causally associated with various B-cell malignancies, while periodic lytic-cycle replication is essential for sustaining viral progeny. Lytic cycle induction represents a promising therapeutic strategy for EBV-associated neoplasms. Therefore, uncovering the mechanisms that regulate EBV lytic-cycle reactivation is pivotal for understanding viral pathogenesis and advancing novel therapies. Our genome-wide transcriptomic analysis reveals that E2F1 expression is transcriptionally activated during EBV latent infection in B-lymphocytes but significantly suppressed during lytic cycle reactivation. While ectopic E2F1 expression suppresses lytic replication, E2F1 depletion markedly accelerates this process. Mechanistically, we establish that E2F1 and the lytic transactivator BZLF1 form a negative transcriptional feedback loop, tightly controlling viral lytic replication. Furthermore, E2F1 positively regulates c-Myc expression and together they repress the leaky BZLF1 expression during latency. Importantly, c-Myc does not influence E2F1 expression, nor does BZLF1 modulate c-Myc transcription, underlining a distinct regulatory hierarchy. In sum, our findings reveal that EBV tightly controls the latent-to-lytic switch through precise regulation of E2F1 expression, positioning E2F1 as a pivotal regulator of both cellular and viral gene expression. SynopsisEBV coordinates the latent-to-lytic switch by sensing E2F1 abundance, which acts as a crucial transcriptional regulator of both cellular and viral gene expressions. O_LIDuring EBV latent infection, E2F1 promotes c-Myc transcription, and together they suppress EBV lytic cycle transactivator BZLF1 expression. C_LIO_LIE2F1 and BZLF1 form a negative feedback loop in order to control each others transcriptions. C_LIO_LIBZLF1-driven controlled E2F1 expression successively inhibits c-Myc level, thereby stimulating EBV lytic cycle reactivation. C_LIO_LIBZLF1 does not regulate c-Myc, nor does c-Myc reciprocally regulate E2F1, emphasizing a unidirectional regulatory hierarchy. C_LI

cancer biology↗

bioRxiv2024

The farnesyl transferase inhibitor KO-2806 re-sensitizes relapsing tumors to RAS inhibition

Resistance remains a key issue limiting the clinical benefit from RAS-targeting therapeutic agents and necessitates combination approaches. We identify persistent mTORC1 activity in preclinical KRAS-mutant NSCLC and CRC models as a frequent, nongenetic driver of inherent and adaptive resistance to RAS inhibition. This vulnerability is targetable with the farnesyl transferase inhibitor KO-2806, which blocks mTORC1 activation via RHEB while sparing mTORC2 and its associated toxicities. The addition of KO-2806 to NSCLC or CRC tumors progressing on mutant-selective RAS inhibitors led to rapid and durable tumor regression. In contrast, switching from mutant-selective to pan-RAS inhibitor monotherapy resulted in only stasis of NSCLC tumors and had no effect on CRC tumor progression. Further, the addition of KO-2806 rescued sensitivity of progressing tumors to the pan-RAS inhibitor RMC-6236. Our results establish mTORC1 as an important mediator of escape from RAS inhibition and highlight KO-2806 as a promising RAS companion inhibitor in patients with prior RAS inhibitor exposure. SignificanceUtilizing in vivo models of tumor relapse, we define a subset of RAS inhibitor-resistant tumors in which vertical inhibition of MAPK is insufficient to restore sensitivity. By controlling parallel mTORC1 activity, KO-2806 may expand utility of RAS inhibitors in patients that have progressed on RAS-targeted therapy, regardless of inhibitor class.

cancer biology↗

bioRxiv2024

Verifying the concordance between motion corrected and conventional MPRAGE for pediatric morphometric analysis

PurposeTo validate a retrospective motion correction technique, Distributed and Incoherent Sample Orders for Reconstruction Deblurring using Encoding Redundancy (DISORDER), for pediatric brain morphometry. MethodsTwo T1-weighted MPRAGE 3D datasets were acquired at 3T in thirty-seven children, median age 7.75 years; one with conventional linear phase encoding and one using DISORDER. MPRAGE images were scored as motion-free or motion-corrupt. Cortical morphometry and regional brain volumes were measured with FreeSurfer, subcortical grey matter (GM) with FSL-FIRST, and hippocampal volumes with HippUnfold. Intraclass correlation coefficient (ICC) was used to determine agreement between the 2 MPRAGE acquisitions. Mann-Whitney U was used to test the difference between measures obtained using DISORDER and (i) motion-free and (ii) motion-corrupt conventional MPRAGE data. ResultsICC measures were good/excellent for most subcortical GM (motion-free, 0.75-0.96; motion-corrupt, 0.62-0.98) and regional brain volumes (motion-free 0.47-0.99; motion-corrupt, 0.54-0.99) between conventional MPRAGE and DISORDER data, except for the amygdala and nucleus accumbens (motion-free, 0.38-0.65; motion- corrupt, 0.1-0.42). However, these values were less consistent for motion-corrupt conventional MPRAGE data for hippocampal volumes (motion-free 0.65-0.99; motion-corrupt, 0.11-0.91) and cortical measures (motion-free 0.76-0.98; motion- corrupt, 0.09-0.74). Mann-Whitney U showed percentage differences in measures obtained with motion-corrupt conventional MPRAGE compared to DISORDER data were significantly greater than in those obtained using motion-free conventional MPRAGE data in 22/58 structures. ConclusionIn the absence of motion, morphometric measures obtained using DISORDER are largely consistent with those from conventional MPRAGE data, whereas improved reliability is obtained by DISORDER for motion-degraded scans. This study validates DISORDER for brain morphometric studies in children.

neuroscience↗

bioRxiv2024

Regulatory architecture of disease resistance in maize revealed by multi-omic systems genetics

Complex traits such as disease resistance have been traditionally studied using quantitative genetics. Here, we use systems genetics to integrate disease severity and multi-omic quantitate trait loci (QTL) to uncover biological networks underlying interaction with northern leaf blight (NLB), a yield-limiting disease of corn. Specifically, we integrated transcriptome, (phospho)proteome, and metabolome measurements to map molecular QTL and build predictive regulatory networks following NLB infection. These inferred networks identified a critical signaling module that was genetically validated comprised of a kinase termed NLB SUSCEPTIBLE KINASE 1, a bHLH transcription factor, and the lignin biosynthesis enzyme BROWN MIDRIB 2. Our results demonstrate the feasibility of high-throughput mapping of genetic determinants of gene- product levels and demonstrates the power of systems genetics to identify upstream regulatory genes that confer resistance to NLB that can inform future strategies for crop protection.

plant biology↗

bioRxiv2024

Identification of phenotypic and transcriptomic signatures underpinning maize crown root systems

Maize is pivotal in supporting global agriculture and addressing food security challenges. Crop root systems are critical for water uptake and nutrient acquisition, which impacts yield. Quantitative trait phenotyping is essential to understand better the genetic factors underpinning maize root growth and development. Root systems are challenging to phenotype given their below-ground, soil-bound nature. In addition, manual trait annotations of root images are tedious and can lead to inaccuracies and inconsistencies between individuals, resulting in data discrepancies. To address these issues, we have developed an automated phenotyping pipeline for field-grown maize crown roots by leveraging open-source software. Phenotypic variation of 20 maize genotypes from the Wisconsin Diversity panel was significant for numerous root traits, suggesting a genetic basis for the observed developmental deviations. In addition, juvenile root traits from controlled environment conditions exhibited inconsistent correlation with field-grown adult root traits, underscoring the developmental plasticity prevalent during maize root morphogenesis. Transcripts involved in hormone signaling and stress responses were among differentially expressed genes in roots from 20 maize genotypes, suggesting many molecular processes may underlie the observed phenotypic variance. This study furthers our understanding of genotype-phenotype relationships, which is relevant for informing agricultural strategies to improve maize root physiology.

plant biology↗

bioRxiv2024

Functional investigation of a putative calcium-binding site involved in the inhibition of inositol 1,4,5-trisphosphate receptor activity

A wide variety of factors influence inositol 1,4,5-trisphosphate (IP3) receptor (IP3R) activity resulting in modulation of intracellular Ca2+ release. This regulation is thought to define the spatio-temporal patterns of Ca2+ signals necessary for the appropriate activation of downstream effectors. The binding of both IP3 and Ca2+ are obligatory for IP3R channel opening, however, Ca2+ regulates IP3R activity in a biphasic manner. Mutational studies have revealed that Ca2+ binding to a high-affinity pocket formed by the ARM3 domain and linker domain promotes IP3R channel opening without altering the Ca2+ dependency for channel inactivation. These data suggest a distinct low-affinity Ca2+ binding site is responsible for the reduction in IP3R activity at higher [Ca2+]. We determined the consequences of mutating a cluster of acidic residues in the ARM2 and central linker domain reported to coordinate Ca2+ in cryo-EM structures of the IP3R type 3. This site is termed the "CD Ca2+ binding site" and is well-conserved in all IP3R sub-types. We show that the CD site Ca2+ binding mutants where the negatively charged glutamic acid residues are mutated to alanine exhibited enhanced sensitivity to IP3-generating agonists. Ca2+ binding mutants displayed spontaneous elemental Ca2+ events (Ca2+ puffs) and the number of IP3-induced Ca2+ puffs was significantly augmented in cells stably expressing Ca2+ binding site mutants. When measured with "on-nucleus" patch clamp, the inhibitory effect of high [Ca2+] on single channel-open probability (Po) was reduced in mutant channels and this effect was dependent on [ATP]. These results indicate that Ca2+ binding to the putative CD Ca2+ inhibitory site facilitates the reduction in IP3R channel activation when cytosolic [ATP] is reduced and suggest that at higher [ATP], additional Ca2+ binding motifs may contribute to the biphasic regulation of IP3-induced Ca2+ release.

biochemistry↗

bioRxiv2024

Longitudinal proteomic analysis of T cell differentiation in vivo reveals dynamic changes of the interactome

CD8 T cell exhaustion impedes immune responses to cancer and chronic infections, and a biochemical understanding of exhaustion is essential to improving immunotherapy. Here, we present the first longitudinal protein abundance and phosphoproteomic analysis of antigen-specific CD8 T cells undergoing differentiation in vivo during acute (LCMV-Armstrong) and chronic (LCMV-Clone 13) infection. Comparing protein abundance across the two infection conditions identified over 180 known and novel exhaustion-associated proteins, including proteins missed by transcriptional analyses. Phosphoproteomic analysis identified >900 differentially regulated phosphosites on >400 proteins, including known inhibitory phosphosites on PD1, PAG1, SHP-1/PTPN6, SLAMF1/CD150. We also calculated phosphosite conservation across mammals, to direct follow-up studies towards sites with likely essential function. Lastly, our analysis uncovers exhaustion-associated kinases with clinical-stage inhibitors, underscoring the translational utility of our dataset to guide immunotherapy development. Together, our datasets define a biochemical atlas of T cell exhaustion in vivo, shedding light on the molecular mechanisms of T cell dysfunction.

immunology↗

bioRxiv2024

A unique subset of pericystic endothelium associates with aberrant microvascular remodelling and impaired blood perfusion early in polycystic kidney disease

Hallmarks of autosomal dominant polycystic kidney disease (ADPKD), the most common hereditary kidney anomaly, include expanding fluid-filled epithelial cysts, inflammation, and fibrosis. Despite previous work showing the potential of vascular-based therapies, renal microvascular alterations in ADPKD, and their timing, are poorly understood. Using single-cell transcriptomics of human kidney microvasculature, we identify a population of endothelial cells adjacent to cysts in ADPKD. This pericystic endothelium, distinguishable by its expression of osteopontin (SPP1), has a distinct molecular profile compared to the common endothelial cell injury signature in other kidney diseases. SPP1+ pericystic endothelium was also present in an orthologous mouse model of ADPKD before overt kidney functional decline. By interrogating geometric, topological and fractal properties from three-dimensional imaging of early ADPKD mouse kidneys, we show that pericystic endothelium associates with disorganisation and non-uniformity of the renal cortical microvasculature. Concurrently, we detected region-specific reductions in cortical blood flow within ADPKD murine kidneys using arterial spin labelling. We conclude that ADPKD kidneys contain a unique subset of endothelium manifesting with aberrant remodelling and impaired blood perfusion. Its detection, prior to renal functional decline, advocates the vasculature as a therapeutic target to modulate or preserve renal function in early ADPKD.

pathology↗

bioRxiv2024

PRMT5 inhibition preferentially targets MYCN-amplified neuroblastoma via altered transcriptional and splicing programmes regulating key cancer cell fitness pathways.

About 50% of poor prognosis neuroblastoma arises due to MYCN over-expression. We previously demonstrated that MYCN and PRMT5 proteins interact and PRMT5 knockdown led to apoptosis of MYCN amplified (MNA) neuroblastoma. Here we evaluate PRMT5 inhibitors GSK3203591/GSK3326593 as targeted therapeutics for MNA neuroblastoma and show MYCN-dependent growth inhibition and apoptosis. RNAseq revealed dysregulated MYCN transcriptional programmes and altered mRNA splicing, converging on key regulatory pathways such as DNA damage response, epitranscriptomics and cellular metabolism. Metabolic tracing showed glutamine metabolism was impeded following GSK3203591 treatment, which disrupted the MLX/Mondo nutrient sensors via intron retention of MLX mRNA. Glutaminase (GLS) protein was decreased by GSK3203591 despite unchanged transcript levels, suggesting post-transcriptional regulation. We demonstrate the RNA methyltransferase METTL3 and cognate reader YTHDF3 proteins are lowered following splicing alterations; accordingly, we observed hypomethylation of GLS mRNA and decreased GLS following YTHDF3 knockdown. In vivo efficacy of GSK3326593 was confirmed by increased survival of Th-MYCN mice together with splicing events and protein decreases consistent with in vitro data. Our study supports the spliceosome as a key vulnerability of MNA neuroblastoma and rationalises PRMT5 inhibition as a targeted therapy. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/582087v2_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@1ac6b5org.highwire.dtl.DTLVardef@1eb9520org.highwire.dtl.DTLVardef@18b980corg.highwire.dtl.DTLVardef@1ab46e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗