Biology subjects

Khan, T.

Publications and source records attributed to Khan, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Host specificity, seasonality, and urbanicity shape the gut microbiome of a synanthropic insect

The soapberry bug Jadera haematoloma is a classic model of rapid adaptive evolution, with a well-documented host shift from native herbaceous sapinds to the introduced goldenrain tree (Koelreuteria spp.). This host shift has facilitated the insect's spread into novel anthropogenic urban habitats. Microbial associations are often critical to insect environmental adaptation. Here, we characterize the gut microbiota of J. haematoloma across native and introduced host plants, seasonal transitions, and a gradient of urbanicity. Our findings indicate that the soapberry bug gut microbiome is highly specialized, with a small number of core bacterial amplicon sequence variants (ASVs) primarily from the families Rhizobiaceae, Streptococcaceae, Enterobacteriaceae, and Lactobacillaceae. While traits such as sex and wing morph do not correlate with microbiome structure, the host plant acts as the primary determinant of community composition. Bugs feeding on the ancestral host plant maintain a more diverse and even microbial community featuring Enterobacteriaceae, whereas the gut environment of bugs on the introduced host is overwhelmingly dominated by a single unclassified Rhizobiaceae ASV. Furthermore, seasonal transitions drive significant turnover among accessory microbial taxa. Finally, we demonstrate that urbanization introduces a distinct ecological effect on the insect's microbiome. While the degree of local green space does not systematically alter within-host taxonomic richness, it is associated with modest change in mean community composition and significantly disrupts microbial community variance. Increased urbanization correlates with significantly higher beta dispersion, indicating that anthropogenic environments lead to more stochastic microbiomes, which may be an indicator of environmental stress. Together, these results illustrate how rapid dietary host shifts and the ecological pressures of urbanization interact to shape the microbiome of a synanthropic insect.

ecology↗

bioRxiv2026

History of opioid use disorder correlates with altered neuroimmune signatures in the human dorsal root ganglia

Understanding mechanisms for the negative reinforcing effects of opioids are fundamental to improving patient care. Using human dorsal root ganglia (DRG) from donors with and without opioid use disorder (OUD), we set out to examine functional and molecular correlates of chronic opioid use. At a molecular level, we detected disrupted immune signatures throughout cells in the peripheral nervous system (PNS), spanning glial-neuroimmune interactions to changes in non-neuronal senescence. At the physiological level these changes are paired with sensitization of DRG sensory neurons. Our findings reveal a neuro-inflammatory state in the PNS of individuals with OUD. Targeting therapeutics towards these PNS-based mechanisms could be an approach to alleviating the negative reinforcing effects of opioids.

neuroscience↗

bioRxiv2026

MAPK signaling links BRD2 chromatin occupancy to PI3K/AKT inhibitor sensitivity

Bromodomain and extra-terminal (BET) proteins, BRD2, BRD3, BRD4, and BRDT, couple histone acetylation to transcription by recruiting elongation and transcription factor complexes to chromatin. Although BET proteins are promising therapeutic targets, the functions of individual family members remain incompletely understood. We identify BRD2 as a co-targetable vulnerability with PI3K/AKT inhibition in breast cancer. Pan-BET inhibition and BRD2 knockout synergized with PI3K pathway inhibitors in breast cancer cell lines, patient-derived organoids, and in vivo models. BRD2 knockout impaired proliferation of triple-negative breast cancer cells and upregulated signaling and stress-response pathways, including the DNA damage response. Mechanistically, BRD2 is phosphorylated at Ser37 by the mitogen- and stress-activated kinases MSK and RSK, and Ser37 phosphorylation is required for chromatin binding and reader function. Finally, mechanistic digital twin modeling identified BETi-PI3Ki regimens that maintained efficacy while reducing drug exposure. Together, these findings identify BRD2 as a phosphorylation-dependent, co-targetable vulnerability in PI3K-inhibited breast cancer.

cancer biology↗

bioRxiv2026

Chronic lower limb pain is not associated with a loss of inhibitory neurons in the human lumbar spinal dorsal horn

The spinal dorsal horn is the primary processing site of nociceptive sensory input from the periphery. Excitatory spinal interneurons releasing glutamate can amplify this information before it is sent to the brain, whereas inhibitory neurons releasing GABA and/or glycine can suppress the outflow of nociceptive signals. An imbalance favoring excitation is thought to underlie certain aspects of chronic pain. Although rodent studies have identified spinal mechanisms underlying hyperalgesia and allodynia, little is known about the anatomical changes associated with chronic pain in the human spinal cord, a gap in knowledge we sought to address in this study. Using immunohistochemistry and in situ hybridization on lumbar spinal cord tissue recovered from organ donors, we characterized neuronal size and density across the human dorsal horn and confirmed the presence of the human equivalent of the lateral spinal nucleus in many individuals. Chronic lower limb pain was not associated with changes in neuronal density in the dorsal horn. Likewise, the ratio of excitatory (SLC17A6+) to inhibitory (PAX2+) neurons remained consistent across laminae for age, sex and chronic pain state, providing no evidence for selective loss of inhibitory neurons with chronic pain in humans. We found no differences in the size or density of the postsynaptic markers Homer1 and gephyrin between groups, suggesting glutamatergic and GABAergic postsynaptic sites remain structurally stable. These findings provide a thorough evaluation of cellular anatomy of the human dorsal horn and form a foundation for future studies investigating neuronal changes that may contribute to chronic pain in humans.

neuroscience↗

bioRxiv2026

Polystyrene microplastics uptake drives Inflammatory, Epitranscriptomic, and Metabolic Reprogramming in Human aortic endothelial cells

Microplastics (MPLs) are pervasive environmental pollutants increasingly linked to adverse human health outcomes, including atherosclerosis. However, the underlying mechanisms remain poorly understood. Human aortic endothelial cells (HAECs), which line the inner surface of blood vessels, play a critical role in maintaining vascular homeostasis and in the development of atherosclerosis. This study demonstrates that polystyrene microplastics enter HAECs through clathrin-mediated endocytosis and macropinocytosis and subsequently co-localize with mitochondria and lysosomes. Exposure to MPLs induced coordinated transcriptional, epitranscriptomic, and metabolomic reprogramming in HAECs. Transcriptomic analysis revealed disruption of mitochondrial genes and activation of inflammatory pathways with the response of the NF-{kappa}B pathway being particularly prominent. Mass spectrometry analysis of RNA modification further identified significant remodeling of the epitranscriptomic landscape, highlighted by increased 1-methyladenosine (m1A) modification and reciprocal regulation of its associated enzymes (TRMT61A upregulation and ALKBH3 suppression), along with alterations in other RNA modifications such as m3C, pseudouridine ({Psi}), m5C, and m7G. Comparative analysis of transcriptomic profiles from human atherosclerotic plaques revealed shared dysregulated pathways in vascular regulation and cellular signaling. Metabolomic profiling further showed extensive remodeling of lipid metabolic networks associated with oxidative stress and inflammation. Together, these findings suggest that MPLs exposure may disrupt endothelial function and pose a potential risk to human cardiovascular health. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/737624v2_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@2ad601org.highwire.dtl.DTLVardef@47f041org.highwire.dtl.DTLVardef@ee45cdorg.highwire.dtl.DTLVardef@128d6d5_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2026

Human Gut Phageome Analysis Uncovers Thousands of Highly Modular Endolysins

The escalating threat of antimicrobial resistance has renewed global interest in bacteriophages as precise and powerful tools for controlling bacterial populations in the human gut. These viruses owe much of their antibacterial potential to phage-encoded endolysins, enzymes capable of rapidly degrading bacterial cell walls with high specificity and low potential for resistance development. Despite their therapeutic promise, the overall composition of the gut phageome and the structural modularity of its endolysins remain poorly understood. In this study, we performed a large-scale analysis of 9,141 human gut metagenomic samples from 34 independent studies. Using standardized workflows for assembly, genome clustering, host prediction, and protein domain annotation, we reconstructed 15,267 phage genomes and identified 3,794 corresponding endolysins. The recovered genomes showed substantial variation in size and coding density, with an average GC content of 43%. Host prediction indicated that most phages targeted bacterial members of the phyla Bacillota (41%) and Bacteroidota (23%). Endolysin sequences grouped into 296 protein families and displayed striking domain modularity. Catalytic domains such as Amidase_2 and Glyco_hydro_25 frequently co-occurred with cell wall-binding motifs including LysM and CW_7. Remarkably, one endolysin contained 15 distinct domains, the highest natural domain diversity reported to date. Collectively, this study represents the most comprehensive characterization of the human gut phageome and its encoded endolysins to date. The exceptional modular diversity uncovered highlights the gut phageome as a rich reservoir of endolysin variants, providing a strong foundation for developing next-generation therapeutics against multidrug-resistant bacterial pathogens.

genomics↗

bioRxiv2026

Nav1.8 mediates peripheral-to-central nociceptive transmission independently of central presynaptic mechanisms in human DRG-spinal cord circuits

Suzetrigine, a selective Nav1.8 blocker, despite its significant role as a non-opioid analgesic, exhibits modest efficacy. The potential enhancement of Nav1.8 blocker efficacy through engagement of Nav1.8 at central terminals remains uncertain. We established a donor-derived human organotypic nociceptive circuit to determine where and how clinically relevant analgesics suppress pain signaling. Using ELISA and immunohistochemistry, we quantified calcitonin gene-related peptide (CGRP) release from acute explants of adult human spinal cord, dorsal root ganglia (DRG), and an intact DRG-spinal cord preparation preserving primary afferent anatomy and directional signaling. In isolated spinal cords, capsaicin evoked concentration-dependent spinal CGRP release without compromising viability, and clinically used analgesics inhibited it, validating the assay. In the intact circuit, the application of capsaicin to the DRG cell bodies triggered CGRP release exclusively in the spinal cord, consistent with compartmentalized neuropeptide release at central terminals. Selective Nav1.8 inhibition with suzetrigine reduced spinal CGRP release only when applied to the DRG or nerve root, not the spinal cord, indicating that Nav1.8 regulates peripheral action potential propagation rather than presynaptic transmitter release. These findings establish the first intact human pain circuit-based assay to study analgesics and demonstrate that the analgesic efficacy of Nav1.8 inhibitors is unlikely to increase with improved CNS penetration.

neuroscience↗

bioRxiv2026

Progressive neurodegeneration in human dorsal root ganglion from diabetes to painful neuropathy

Diabetic painful neuropathy (DPN) is characterized by neuropathic pain accompanied by loss of sensory function. We hypothesized that neurodegeneration in the dorsal root ganglion (DRG) could underlie DPN progression. To address this question, we performed multi-omic evaluation on DRGs from otherwise healthy organ donors, donors with diabetes but no neuropathy, and donors with clinically diagnosed DPN. We discovered that the first stages of neurodegeneration begin early in diabetes before the onset of DPN, with Nageotte nodule formation accompanied by apoptotic gene expression and decreased proportion of specific populations of A-fibers in DPN with remodeling of non-neuronal cells. Our findings define DPN as a neurodegenerative disorder of the DRG, identify molecular markers of disease stage, and highlight the need for early intervention to prevent irreversible neurodegeneration.

neuroscience↗

bioRxiv2025

Distinct Virome and Bacteriome Profiles of Term and Preterm Placentas from African, Asian and European Women

While the human placental microbiome has been extensively studied, information regarding the virome remains limited. The association between subclinical placental viral infections and spontaneous preterm birth (PTB) is poorly understood. Hence, we examined fresh placenta samples from women in the UK, Bangladesh, and South Africa to elucidate the virome profiles and association with spontaneous PTB. We employed shotgun metagenomics, real-time PCR, and Gram staining, complemented by bioinformatics, to detect both viruses and bacteria in the decidua and chorionic villous tissues. We did not identify any known pathogenic viruses in 236 placental samples, except for one preterm placenta from the Bangladeshi cohort, where human herpesvirus 6 was detected. The majority of the viruses were bacteriophages present at very low abundance and low frequencies across the three cohorts. Lambdavirus lambda was detected in 14% of UK and 11% of Bangladeshi samples but was absent in South African samples. Papiine betaherpesvirus 3 was identified in 62.5% of South African placentas. Punavirus (29.1%) and Streptococcus phages (16.67%) were also prevalent in South African samples. A variety of bacterial species including Moraxella osloensis, Delftia lacustris, Cutibacterium acnes, Escherichia coli and Staphylococcus epidermidis were detected in samples across the three cohorts in variable frequencies but without any notable tissue immune responses. None of the viruses or bacteria exhibited associations with PTB, except D. lacustris, which was significantly more abundant in preterm compared to term placentas in the Bangladeshi cohort. We conclude that the human placenta harbours a virome predominated by bacteriophages and that subclinical viral infection in spontaneous PTB is rare.

microbiology↗

bioRxiv2025

A molecular map of the human spinal dorsal and ventral horn defines arrangement of neuronal types and glial sex differences

The spinal cord is the gateway for somatosensory and nociceptive information to the brain and a key locus for sensory-motor integration. Studies in mice have advanced our understanding of spinal cord circuitry, and transcriptomic studies have begun to characterize the human spinal cord; however, major gaps in knowledge persist. We conducted single-nucleus sequencing of lumbar spinal cord tissue from 11 adult organ donors and annotated spinal cord cell types with high resolution spatial transcriptomics. We identified 34 spatially and transcriptionally defined neuronal classes and detected sex-specific cell types and states across multiple glial populations. Electrophysiological recordings from dorsal horn neurons revealed firing patterns for neuronal subtypes and group I mGluR-dependent plasticity. Our work defines previously unknown aspects of human spinal cord molecular anatomy and physiology.

neuroscience↗

bioRxiv2025

Deep multiplexed 50-marker imaging of circulating tumor cells expands actionable biomarker profiling for precision oncology

Liquid biopsy-derived circulating tumor cells (CTCs) offer a minimally invasive avenue for precision oncology by enabling longitudinal monitoring of actionable molecular and cell-phenotypic biomarkers. However, conventional immunofluorescence imaging-based CTC profiling captures just 4-5 markers per cell, restricting crucial insights into oncogenic and resistance drivers, as well as tumor cell heterogeneity. Here we present an integrated pipeline employing deep multiplexed imaging to profile up to 50 molecular markers per CTC, capturing expression, phosphorylation, and subcellular localization of diverse biomarkers. Validated in a multi-stage prostate cancer resistance model and applied to prostate cancer patient-derived CTCs, this approach enhances CTC classification and reveals inter- and intra-patient heterogeneity correlating with therapy response. Machine learning identified therapeutically actionable signatures, suggesting patient-specific treatment strategies. This deep multiplexed imaging pipeline advances the utility of CTCs in guiding personalized cancer therapy by providing comprehensive molecular and phenotypic insights through minimally invasive liquid biopsies. Highlights- Multiplexed immunofluorescence imaging of circulating tumor cells captures up to 50 molecular markers per cell with subcellular localisation. - Single-cell and subcellular analyses identify quantitative signatures correlating with patient outcome, as well as therapeutically actionable biomarkers. - This method transforms the utility of CTCs for future use in patient stratification and for guiding personalised therapies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=181 SRC="FIGDIR/small/684075v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@a36ff4org.highwire.dtl.DTLVardef@b06c1org.highwire.dtl.DTLVardef@1e8a572org.highwire.dtl.DTLVardef@c60753_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

cancer biology↗

bioRxiv2025

Automating Candidate Gene Prioritization with Large Language Models: From Naive Scoring to Literature-Grounded Validation

BackgroundIdentifying promising therapeutic targets from thousands of genes in transcriptomic studies remains a major bottleneck in biomedical research. While large language models (LLMs) show potential for gene prioritization, they suffer from hallucination and lack systematic validation against expert knowledge. MethodsWe developed a two-stage computational framework that combines LLM-based screening with literature validation for systematic gene prioritization. Starting with 10,824 genes from the BloodGen3 repertoire, we applied multi-criteria evaluation for sepsis relevance, followed by retrieval-augmented generation (RAG) using 6,346 curated sepsis publications. A novel faithfulness evaluation system verified that LLM predictions aligned with retrieved literature evidence. ResultsThe framework identified 609 sepsis-relevant genes with >94% filtering efficiency, demonstrating strong enrichment for inflammatory pathways including TNF- signaling, complement activation, and interferon responses. Literature validation yielded 30 ultra-high confidence therapeutic candidates, including both established sepsis genes (IL10, TREM1, S100A9, NLRP3) and novel targets warranting investigation. Benchmark validation against expert-curated databases achieved 71.2% recall, with systematic correlation between computational confidence and evidence quality. The final candidate set balanced discovery (11 novel genes) with validation (19 known genes), maintaining biological coherence throughout the filtering process. ConclusionsThis framework demonstrates that rigorous methodology can transform unreliable LLM outputs into systematically validated biological insights. By combining computational efficiency with literature grounding, the approach provides a practical tool for prioritizing experimental validation efforts. The modular design enables adaptation to other diseases through knowledge base substitution, offering a systematic approach to literature-guided biomarker discovery. AvailabilitySource code and implementation details are available at https://github.com/taushifkhan/llm-geneprioritization-framework, vector database at https://doi.org/10.5281/zenodo.15802241 and Interactive demonstration at https://llm-geneprioritization.streamlit.app/

bioinformatics↗

bioRxiv2025

Uncovering the role of laminin (laminin α5 ) in maintenance of epithelial identity and polarity in bilayer zebrafish epidermis during development

Polarity is one of the fundamental properties of cells. It is characterised by the asymmetric distribution of lipids and proteins in the cell membrane and cortex, and organelles in the cell. Cell polarisation drives essential processes such as morphogenesis, cell migration, asymmetric cell division, directional transport of molecules across epithelium, nerve impulse transmission etc. Although, the importance of polarity proteins such as atypical protein kinase C (aPKC) and Lgl2 (lethal giant larvae 2) has been relatively well understood in the developing zebrafish epidermis, whether basal lamina components are important for polarity maintenance has remained unclear. I analysed the role of Laminin5 (basal lamina component) in the establishment and maintenance of apicobasal polarity, in developing bi layered zebrafish epidermis. I found that the loss of laminin 5 function results in reduced E cadherin localization and increased cell spreading along with dynamic cell boundaries and increased cell proliferation indicating acquisition of mesenchymal traits. A similar phenotype was observed in integrin 6b mutant, which did not exacerbate in the double mutant embryos indicating that laminin 5 and integrin 6b function in the same pathway. Interestingly, periderm, the cell layer above basal epidermis, maintains its apicobasal polarity and epithelial integrity presumably via reinforcing the localization of aPKC and Lgl. My work unravels the importance of Laminin 5 and Integrin 6b interaction in the maintenance of epithelial characteristics in the basal layer of the developing zebrafish epidermis.

cell biology↗

bioRxiv2025

Liver Kinome Profiling Identifies PS1145 as a Potential Therapeutic molecule for amelioration of Systemic Inflammation in Alcohol-related Liver Disease

Background and aimsAlcohol-related liver disease (ALD) has high mortality due to systemic inflammation. We analysed liver and monocyte kinome profiles in a chronic ethanol-fed pre-clinical rat model to identify therapeutic targets that could mitigate inflammation in ALD. MethodKinome profile was performed in liver and circulating monocytes at baseline, and after 8,12,16,20 and 24-weeks of 40% ethanol administration. Pathway-specific inhibitors, including PS1145 (IKK-phosphorylation inhibitor), PH-797804 (MAPK14 inhibitor), resveratrol and prednisolone were tested for their anti-inflammatory effects in ALD-rats, PBMC from patients and NIAAA mouse model. ResultsKinome profiling identified 497 liver and 345 monocyte kinases in ALD rats (FDR<0.01). A time-dependent increase in MAPK14-associated kinases was observed in both tissues (FC>1.5, p<0.05). By 24 weeks, 172 liver and 48 monocyte kinases were significantly upregulated, particularly those linked to MyD88-TLR4, PI3K-Akt, TNF, TGF{beta}, and cellular senescence pathways. Key contributors included TGF{beta}R1, ROS-generating kinases, and IL-1-driven MAPK14 and IKK phosphorylation. Targeting this axis, PS1145 (an IKK inhibitor) suppressed NF{kappa}B activation and inflammation in THP1 and HepG2 cells, as well as PBMCs from healthy and SAH patients, outperforming PH797804, resveratrol, and prednisolone (p<0.05, FC>1.5). PS1145 significantly reduced IL-6, TNF, and NF{kappa}B, while increasing IL-10. In vivo, PS1145 treatment in the NIAAA mouse model markedly reduced hepatic steatosis, cellular stress and inflammatory pathways (cytokine signalling, IL-36 signalling and others) more effectively than standard therapies, Notably, it also downregulated IL36R, impairing TLR receptor dimerization, suggesting a dual mechanism of action (p<0.05) highlighting its therapeutic potential in ameliorating systemic inflammation in ALD. ConclusionOur study highlights the key role of MAPK14 and MYD88-TLR4 pathway kinases in driving systemic inflammation in SAH. The IKK inhibitor PS1145, by blocking both IKK phosphorylation and TLR dimerization, effectively suppresses inflammatory signalling and improves liver pathology, positioning it as a promising targeted therapy for ALD.

pharmacology and toxicology↗

bioRxiv2025

Spatial transcriptomic profiling of human paravertebral sympathetic chain ganglia reveals diabetes-induced neuroplasticity

The paravertebral sympathetic chain ganglia (SCG) are autonomic ganglia critical for regulating the "fight-or-flight" response. Symptoms of sympathetic dysfunction are prevalent in diabetes, affecting up to 90% of patients. The molecular and cellular composition of the human SCG and its alteration in diabetes remains poorly defined. To address this gap, we performed spatial transcriptomic profiling of lumbar SCGs from diabetic and non-diabetic organ donors. We identified 3 three distinct neuronal populations, two noradrenergic (NA1 and NA2) and one cholinergic (CHO), based on tyrosine hydroxylase (TH) and SLC18A3 expression, respectively. We also characterized 9 non-neuronal populations consisting of Schwann cells, immune cells, fibroblasts, adipocytes, and endothelial cells. In diabetic SCGs, we observed a significant loss of myelinating Schwann cells and a phenotypic shift of cholinergic neurons toward a noradrenergic identity. Additionally, diabetes was associated with a significant reduction in the transcripts of vasodilatory neuropeptides, such as VIP and CALCA, suggesting a mechanism for impaired vascular control. Upstream regulator analysis highlighted altered neurotrophic signaling in diabetes, with enhanced NGF/TRKA and diminished BDNF/TRKB activity, potentially driven by target-derived cues. Comparison between SCG and dorsal root ganglia (DRG) neurons revealed ganglia-specific genes, like SCN3A and NPY (SCG) versus SCN10A and GPX1 (DRG), offering specific therapeutic targets for autonomic dysfunction or pain. Our findings provide a transcriptomic characterization of human SCG, revealing molecular signatures that underlie diabetic autonomic dysfunction. This work lays a foundation for the development of therapies to restore sympathetic function and avoid unintended autonomic effects in the development of analgesics. Significance StatementAutonomic dysfunction affects up to 90% of people with diabetes, yet the human sympathetic nervous system remains poorly molecularly defined. To address this gap, we present a spatial transcriptomic profile of the human sympathetic chain ganglia (SCG), revealing how diabetes affects the human autonomic nervous system. We show that diabetes shifts the cholinergic neuronal population to a noradrenergic phenotype and reduces vasodilation neuropeptide expression, potentially explaining impaired vascular control and thermoregulation. Comparative analysis of sympathetic and sensory ganglia reveals distinct gene profiles that may inform novel therapeutic strategies. These findings offer critical insight into the molecular drivers of diabetic autonomic neuropathy and lay the groundwork for safer, more precise treatments that selectively modulate autonomic or sensory function in chronic disease.

neuroscience↗

bioRxiv2025

A potent and selective TNKS2 inhibitor for tumor-selective WNT suppression

Hyperactive WNT signaling is a potent cancer driver, but clinical translation of WNT inhibitors has been hampered by on-target toxicities. WNT signaling can be constrained through inhibition of the PARP family enzymes Tankyrase 1 (TNKS1) and Tankyrase 2 (TNKS2), however, existing TNKS inhibitors suppress WNT signaling in both tumor and healthy tissues. In this study, we show that the loss of chromosome 8p that occurs in approximately half of advanced epithelial malignancies, creates a collateral vulnerability that enables tumor-selective inhibition of Tankyrase activity. 8p loss depletes expression of TNKS1 and creates a tumor-specific dependency on the functionally redundant TNKS2 protein. Through structure-guided drug design, we identify a first-in-class TNKS2-selective inhibitor that can drive selective WNT inhibition in TNKS1-deficient oncogenic cell and organoid models. This work demonstrates a targetable vulnerability in multiple cancer types, providing a new approach to potent and selective WNT-targeted therapies.

cancer biology↗

bioRxiv2025

Decreased KCC2 expression in the human spinal dorsal horn associated with chronic pain and long-term opioid use

Loss of GABAergic and glycinergic inhibitory efficacy in the spinal dorsal horn is associated with neuropathic pain and opioid-induced hyperalgesia in rodent models. Downregulation of the KCC2 chloride extrusion transporter is a key mechanism underlying this decreased inhibitory efficacy, but to-date there is no evidence supporting or opposing this hypothesis in humans. Here we demonstrate that KCC2 expression is decreased in superficial dorsal horn neurons of organ donors who died with a documented history of pain, or of long-term opioid use. We show profoundly decreased KCC2 dorsal horn membrane expression in a primary cohort associated with either chronic pain or opioid use, and in a replication cohort of mixed chronic pain and opioid use history. These results show that decreased dorsal horn inhibitory efficacy likely promotes chronic pain in humans and support the development of therapeutics augmenting KCC2 function as a treatment for chronic pain and opioid use disorders.

neuroscience↗

bioRxiv2024

Tackling the Complexity of Spatial Transcriptomics Data Interpretation with Large Language Models

Spatial transcriptomics offers unprecedented insights into the complex cellular landscapes of tissues, particularly in cancer research where understanding the tumor microenvironment is crucial. However, interpreting the vast and intricate data generated by this technology remains a significant challenge. This study explores the potential of Large Language Models (LLMs) to assist in the analysis and interpretation of spatial transcriptomic data from a murine melanoma tumor model. We first evaluated the performance of multiple LLM models in describing and quantifying spatial gene expression patterns. Our benchmarking revealed that spatial transcriptomics data interpretation proved challenging for most models, with only a few demonstrating sufficient capability for this complex task. Using Claude 3.5 Sonnet, which showed the highest accuracy in spot quantification and pattern recognition, we developed a systematic workflow for analyzing the tumor immune landscape. The model first assisted in identifying and prioritizing panels of M1 and M2 macrophage-associated markers through knowledge-driven scoring. It then demonstrated remarkable ability to integrate spatial expression data with extensive immunological knowledge, providing sophisticated interpretation of local immune organization. When analyzing individual tumor regions, the model identified coordinated immunosuppressive mechanisms including metabolic barriers and disrupted pro-inflammatory signaling cascades, findings that both aligned with and extended current understanding of tumor immunology. This study highlights the potential of LLMs as powerful assistive tools in spatial transcriptomics analysis, capable of combining advanced pattern recognition with extensive knowledge integration to enhance data interpretation. While significant development work remains to make such workflows scalable, our proof of concept demonstrates that LLMs can help accelerate the translation of spatial transcriptomics data into biological insights.

cancer biology↗