Biology subjects

Harrison, D. J.

Publications and source records attributed to Harrison, D. J..

8 recordsLinked to original sources

bioRxiv2026

Allosteric modulation of β1 integrin through the hybrid domain reverses articular cartilage injury and functional impairment in a murine model of inflammatory arthritis

Rheumatoid arthritis is a chronic inflammatory joint disease in which progressive destruction of cartilage and bone drives long-term disability. Current disease-modifying therapies target the immune and cytokine networks that sustain synovial inflammation, but none is directed at the chondrocyte, the resident cell responsible for maintaining cartilage matrix. Chondrocyte survival and matrix homeostasis depend on {beta}1-integrin-mediated adhesion to the extracellular matrix, and dysregulated integrin signalling has been implicated in cartilage injury. Here we test the hypothesis that allosteric modulation of {beta}1 integrin, rather than simple adhesion blockade, is chondroprotective. Using the monoclonal antibody JB1a, which binds an epitope in the hybrid domain of {beta}1 integrin and stabilises the receptor in a low-affinity conformation, we show that intra-articular administration produces both functional and structural amelioration of Freunds complete adjuvant (FCA)-induced arthritis in mice. JB1a abolished the FCA-induced increase in joint diameter and hyperalgesia and markedly reduced synovial inflammation, pannus formation and cartilage erosion, with no effect on the contralateral joint and no observed adverse effects. These changes were accompanied by a reduction in chondrocyte apoptosis in vivo. In primary human articular chondrocytes, JB1a abolished interleukin-1{beta} (IL-1{beta})-induced caspase 3/7 activation, reduced IL-8 secretion, and restored the sinusoidal oscillation of intracellular ATP that was otherwise abrogated by IL-1{beta}. In contrast, the adhesion-blocking, integrin-clustering antibody 6S6 activated caspase 3/7 and amplified IL-1{beta}-induced IL-8 secretion, indicating that the therapeutic effect is a property of the specific mode of receptor engagement rather than of adhesion blockade per se. These findings identify {beta}1-integrin conformational state as a determinant of chondrocyte energy homeostasis and survival, and nominate allosteric {beta}1-integrin modulation as a mechanistically distinct, chondrocyte-directed therapeutic strategy in inflammatory arthritis.

pharmacology and toxicology↗

bioRxiv2025

Dimerization and Threonine-Dependent Stabilization Govern Human YRDC Catalysis

Addition of N6-threonylcarbamoyladenosine occurs at position 37 (tA37) of five mitochondrial tRNA species, influencing translation fidelity and efficiency. Mutations in YRDC, the enzyme catalyzing the first step in tA37 synthesis, cause severe neurological and renal diseases in humans, including in Galloway-Mowatt disease (GAMOS). YRDC generates threonylcarbamoyl-AMP (TC-AMP) using ATP, threonine and bicarbonate as substrates, yet their binding order, residues involved in amino-acid selectivity, and precisely how mutations contribute to disease remain unclear. Here, we combine protein biophysics, mass spectrometry, NMR, mutagenesis and kinetics to define how the human enzyme operates. Differential scanning fluorimetry and circular dichroism identify L-threonine as the gatekeeper ligand. It binds with millimolar affinity, stabilizing YRDC and enhancing ATP binding nearly fortyfold, enabling bicarbonate association. Several amino acids can form aminoacylcarbamoyl-AMP adducts in vitro, but threonine yields superior protein stabilization and product formation. Native mass spectrometry and single-molecule mass photometry corroborate YRDCs dimeric state. GAMOS-linked mutations destabilize folding, disrupting dimerization and uncoupling substrate binding from catalysis, explaining functional losses. Supported by kinetic data and NMR, we propose a chemical mechanism for the reaction and identify dimerization and conformational stability as control points for activity. This work provides a foundation for designing selective YRDC inhibitors or enhancers.

biochemistry↗

bioRxiv2024

Long-read Spatial Transcriptomic Profiling of Patient-derived ccRCC Tumoroids Reveals Heterogeneity in Isoform and Gene Expression

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of kidney cancer characterized by its diverse tumor composition featuring various subclonal populations that hinder effective treatment responses. Tumoroids present an avenue for modelling this diversity and replicating the intricate tumor heterogeneity. Spatial transcriptomics preserves the spatial context of gene expression enabling us to study distinct tumor areas and the influence on overall diversity. Our spatial transcriptomics analysis uncovered tumor clusters with distinct genetic profiles that showcase various functional areas in depth and offer valuable understandings into the diversity of ccRCC types. Some of these tumor clusters exhibited activity in genes responsible for protein catabolism and reduced abundance of genes related to mitochondrial respiration processes. We also show isoform expression within tumoroids, in particular glutaminase (GLS) especially with the prevalence of the highly metabolically active GAC isoform that is expressed in regions where mitochondrial gene abundance is lower; whereas the KGA isoform displayed a more focal expression pattern. Combining long-read spatial transcriptomics with organoid models presents a novel strategy for unravelling gene and transcript level complexity.

cancer biology↗

bioRxiv2024

Knock out of the intracellular calcium conducting ion channel Mitsugumin 23 (MG23) protects against pressure overload induced left ventricular hypertrophy and cardiac dysfunction.

BackgroundIn cardiac dysfunction, intracellular Ca2+-dynamics are disrupted leading to leakage of Ca2+ from the sarcoplasmic reticulum (SR). This results in diminished cardiac contractility and impaired cardiac function. In cardiac tissue, the underlying molecular mechanisms responsible for RyR2-independent Ca2+ leak are poorly understood. Mitsugumin 23 (MG23) is an intracellular Ca2+-conducting ion channel located on ER/SR and nuclear membranes. We propose that MG23 contributes to regulation of intracellular Ca2+-homeostasis, and that altered MG23 function may drive progression of cardiac dysfunction. The aim of this research was to investigate the role of MG23 in SR Ca2+ leak, and whether knock out of Mg23 protects the heart against pressure-overload induced left ventricular hypertrophy. MethodsCardiac pressure-overload was induced in wild type (WT) and Mg23-knock out (KO) mice through subcutaneous Angiotensin II (AngII, 1.1 mg/kg/day) infusion via osmotic pump. After 10-days infusion, in vivo pressure-volume dynamics were measured by insertion of a pressure-volume catheter into the left ventricle. MG23 protein expression was assessed through Western blot analysis. Ventricular fibrosis and cardiomyocyte size were measured using histological and immunofluorescence approaches. Cardiomyocytes were isolated from WT and Mg23-KO hearts and intracellular Ca2+ dynamics assessed through live cell imaging using the Ca2+ indicator Fluo-4. ResultsAngII-induced cardiac pressure-overload increased expression of MG23 in WT mouse hearts. Knock out of Mg23 protected hearts against AngII-induced cardiac hypertrophy. Compared to WT animals, AngII treated Mg23-KO mice displayed a significant reduction in left ventricular fibrosis and displayed normal cardiac functioning. In Mg23-KO hearts, no alteration in expression of key Ca2+ handling proteins was identified, but cardiomyocytes displayed altered Ca2+ spark profiles consistent with a role for MG23 in SR Ca2+ leak. ConclusionMG23 plays a key role in driving Ca2+ dysregulation observed in the early pathological stages of pressure-overload induced heart failure.

physiology↗

bioRxiv2023

Spatial Metabolomics co-registered with Multiplex Phenotyping for the Evaluation of Human Kidney Tissue

A workflow has been evaluated that utilises a single tissue section to obtain spatially co-registered, molecular, and phenotypical information suitable for AI-enabled analysis. The impact of varying DESI-MSI conditions (e.g., temperature, scan rate, acquisition time) on the detection of small molecules and on tissue quality for integration into typical clinical pathology workflows assessed in human kidney.

systems biology↗

bioRxiv2023

Microenvironment of metastatic site reveals key predictors of PD-1 blockade response in renal cell carcinoma

Immune checkpoint blockade (ICB) therapies have improved the overall survival (OS) of many patients with advanced cancers. However, the response rate to ICB varies widely among patients, exposing non-responders to potentially severe immune-related adverse events. The discovery of new biomarkers to identify patients responding to ICB is now a critical need in the clinic. We therefore investigated the tumor microenvironment (TME) of advanced clear cell renal cell carcinoma (ccRCC) samples from primary and metastatic sites to identify molecular and cellular markers of response to ICB. We revealed a significant discrepancy in treatment response between subgroups based on cell fractions inferred from metastatic sites. One of the subgroups was enriched in non-responders and harbored a lower fraction of CD8+ T cells and plasma cells, as well as a decreased expression of immunoglobulin genes. In addition, we developed the Tumor-Immunity Differential (TID) score which combines features from tumor cells and the TME to accurately predict response to anti-PD-1 immunotherapy (AUC-ROC=0.88, log-rank tests for PFS P < 0.0001, OS P = 0.01). Finally, we also defined TID-related genes (YWHAE, CXCR6 and BTF3), among which YWHAE was validated as a robust predictive marker of ICB response in independent cohorts of pre- or on-treatment biopsies of melanoma and lung cancers. Overall, these results provide a rationale to further explore variations in the cell composition of metastatic sites, and underlying gene signatures, to predict patient response to ICB treatments. One Sentence SummaryTumor microenvironment balance of metastasis and associated genes are key predictors of immunotherapy patient response in kidney cancer.

bioinformatics↗

bioRxiv2022

A comprehensive library of canonical and non-canonical MHC class I antigens for cancer vaccine development.

A longstanding disconnect between the growing number of MHC Class I immunopeptidomic studies and genomic medicine hinders cancer vaccine design. We develop COD-dipp to genomically map the full spectrum of detected canonical and non-canonical (non-exonic) MHC Class I antigens from 26 cancer studies. We demonstrate that patient mutations in regions overlapping physically identified antigens better predict immunotherapy response when compared to neoantigen predictions. We suggest a vaccine design approach using 140,966 highly immune-visible regions of the genome annotated by their expression and haplotype frequency in the human population. These regions tend to be highly conserved, mutated in cancer and harbor 7.8 times more immunogenicity. Intersecting pan-cancer mutations with these immune surveilled regions revealed a potential to create off-the-shelf multi-epitope vaccines against public neoantigens. Here we release COD-dipp, a cancer vaccine toolkit as a web-application (https://www.proteogenomics.ca/COD-dipp) and open-source high-throughput resource.

bioinformatics↗

bioRxiv2020

Identification of immunological features enables survival prediction of muscle-invasive bladder cancer patients using machine learning

AO_SCPLOWBSTRACTC_SCPLOWClinical staging and prognosis of muscle-invasive bladder cancer (MIBC) routinely includes assessment of patient tissue samples by a pathologist. Recent studies corroborate the importance of image analysis in identifying and quantifying immunological markers from tissue samples that can provide further insights into patient prognosis. In this paper, we apply multiplex immunofluorescence on MIBC tissue sections to capture whole slide images and quantify potential prognostic markers related to lymphocytes, macrophages, tumour buds, and PD-L1. We propose a machine learning based approach for the prediction of 5 year prognosis with different combinations of image, clinical, and spatial features. An ensemble model comprising several functionally different models successfully stratifies MIBC patients into two risk groups with high statistical significance (p value < 1e - 05). Critical to improving MIBC survival rates, our method classifies correctly 71.4% of the patients who succumb to MIBC within 5 years, significantly higher than the 28.6% of the current clinical gold standard, the TNM staging system.

cancer biology↗