Biology subjects

Harvey, K.

Publications and source records attributed to Harvey, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Highly resolved tumor architecture via matched spatial and nucleus transcriptomics from a single tissue section

Spatial transcriptomics often relies on reference-based deconvolution to infer cell types in a tissue context; however, public single-cell datasets can miss patient-specific biology. Here we introduce SIMPlex, a method that generates matched spatial and single-nucleus gene-expression profiles from the same 5 um FFPE section. We demonstrate context-matched profiles across mouse brain, breast cancer and prostate cancer tissues, resolving fine-grained cell-states with distinct spatial signatures. By extracting both spatial and nuclear layers, SIMPlex maximises the information recovered from a single tissue section, an advantage for scarce archival and clinical specimens.

molecular biology↗

bioRxiv2026

The mechanosensitive protein Zyxin influences Hippo signalling and tissue growth via adherens junctions and basal spot junctions in Drosophila

Physical forces like tension and compression have a central role in the growth and morphogenesis of tissues. Cell-cell junctions and the actin cytoskeleton are key mediators of physical forces and influence activity of signalling networks like the Hippo pathway. Here, we show that the mechanosensitive proteins Zyxin and Ajuba work in concert to limit Hippo signalling and promote Drosophila epithelial tissue growth. Zyxin recruits both Ajuba and the central Hippo pathway kinase Warts to adherens junctions and basal spot junctions, and limit Warts activity by segregating it from Hippo pathway activator proteins. Zyxin also promotes the transmission of actomyosin tension to adherens junctions in growing epithelial tissues, indicating conservation of this function. Thus, we provide new insights into how Zyxin couples mechanical cues and Hippo pathway-dependent tissue growth and highlight the importance of basal spot junctions and their associated actomyosin network in epithelial tissue development.

developmental biology↗

bioRxiv2025

ROCK2 inhibition has a dual role in reducing ECM remodelling and cell growth, while impairing migration and invasion

The Rho-associated coiled-coil containing protein kinases 1/2 (ROCK1/2) are key signalling proteins involved in the regulation of the actin cytoskeleton and control a variety of cellular processes. This includes cell proliferation, stemness, cell migration and invasion as well as actomyosin contraction and extracellular matrix (ECM) remodelling. Due to a lack of ROCK2 specific inhibitors, previous pharmacological studies of ROCK function have relied on pan-ROCK1/2 inhibition. Here, we use the ROCK2 specific inhibitor, GV101, in the context of breast cancer (BC) models to uncouple the effects of ROCK2 pharmacological inhibition on both epithelial and stromal fibroblast cell populations. We demonstrate that ROCK2 inhibition with GV101 reduces fibroblast-mediated remodelling of pre-existing and de novo synthesised ECM resulting in a reduction in biomechanical stiffness, while also limiting epithelial cell growth in 2D and 3D settings. We also demonstrate that ROCK2 inhibition exposes epithelial cell vulnerability to fluid flow-induced shear stress. Furthermore, using 3D co-cultures we reveal that GV101 reduces single-cell migratory capacity, while the disruption of stromal ECM architecture is sufficient to impede collective cell migration and invasion. Finally, we assessed ROCK2 expression in human BC patient tumours revealing that ROCK2 expression is up-regulated during BC progression and that high ROCK2 expression correlates with poor patient outcome in the triple-negative subtype of BC. Together, these results demonstrate that ROCK2 specific inhibition disrupts key functions in both epithelial cell and stromal fibroblast compartments warranting further assessment of ROCK2 in highly proliferative, fibrotic or metastatic diseases, such as BC. HighlightsO_LIFibroblast-mediated remodelling of pre-existing and de novo synthesised extracellular matrix is reduced upon ROCK2 specific targeting. C_LIO_LIROCK2 inhibition impairs epithelial cancer cell growth and colony formation in 2D and 3D contexts, while also limiting single-cell migration and cell survival upon fluid flow-induced shear stress. C_LIO_LIROCK2 targeting during fibroblast-mediated ECM remodelling is sufficient to disrupt collective cell migration as well as 3D invasion into organotypic fibroblast-contracted collagen matrices. C_LIO_LIROCK2 expression is up-regulated during breast cancer progression and high expression correlates with poor patient outcome in triple-negative breast cancer. C_LI

cell biology↗

bioRxiv2025

Neuronal cell adhesion molecule (NRCAM) variant defined by microexon skipping is an essential, antigenically distinct, and targetable surface proteoform in high-grade glioma

To overcome the paucity of known tumor-specific surface antigens in pediatric high-grade glioma (pHGG), we contrasted splicing patterns in pHGGs and normal brain samples. Among alternative splicing events affecting extracellular protein domains, the most pervasive alteration was the skipping of [≤]30 nucleotide-long exons. Several of these skipped microexons mapped to L1-IgCAM family members, such as NRCAM. Bulk and single-nuclei short- and long-read RNA-seq revealed uniform skipping of NRCAM microexons 5 and 19 in virtually every pHGG sample. Importantly, the {Delta}ex5{Delta}ex19 (but not the full-length) NRCAM proteoform was essential for pHGG cell migration and invasion in vitro and tumor growth in vivo. We developed a monoclonal antibody selective for {Delta}ex5{Delta}ex19 NRCAM and demonstrated that "painting" of pHGG cells with this antibody enables killing by T cells armed with an FcRI-based universal immune receptor. Thus, pHGG-specific NRCAM and possibly other L1-IgCAM proteoforms are promising and highly selective targets for adoptive immunotherapies.

cancer biology↗

bioRxiv2024

Profiling of epithelial functional states and fibroblast phenotypes in hormone therapy-naive localised prostate cancer

Localised prostate cancers (PCa) are heterogeneous and multifocal, with diverse outcomes. Current prognostic methods are epithelium-centric, overlooking the complex cellular landscape within the tumour microenvironment (TME), which remains incompletely characterised. We performed a comprehensive analysis of cancerous and adjacent-benign cores from 24 patients with hormone therapy-naive localised PCa using single-cell RNA-sequencing. By integrating copy number variation and transcriptional signatures, we classified epithelial cells across a malignant spectrum, revealing widespread molecular perturbation. We found an expansion of Club cell phenotypes, suggestive of Luminal dedifferentiation. We also performed a detailed annotation of stromal phenotypes, focusing on fibroblasts, and identified a novel peri-neural fibroblast population. Spatial transcriptomics elucidated the precise anatomical distribution of CAFs within the PCa TME. This study provides a valuable foundation for advancing our understanding of PCa pathobiology and developing a comprehensive cellular model of the disease. Statement of SignificanceOur study leverages single-cell RNA-sequencing and spatial transcriptomics to provide a comprehensive cellular annotation of hormone therapy-naive localised PCa. We reveal widespread molecular perturbations in epithelial cells and map distinct fibroblast populations to specific anatomical niches. Notably, we identify a novel peri-neural phenotype associated with nerves, which merits further functional characterisation and exploration as a potential therapeutic target.

cancer biology↗

bioRxiv2024

Federated deep learning enables cancer subtyping by proteomics

Artificial intelligence applications in biomedicine face major challenges from data privacy requirements. To address this issue for clinically annotated tissue proteomic data, we developed a Federated Deep Learning (FDL) approach (ProCanFDL), training local models on simulated sites containing data from a pan-cancer cohort (n=1,260) and 29 cohorts held behind private firewalls (n=6,265), representing 19,930 replicate data-independent acquisition mass spectrometry (DIA-MS) runs. Local parameter updates were aggregated to build the global model, achieving a 43% performance gain on the hold-out test set (n=625) in 14 cancer subtyping tasks compared to local models, and matching centralized model performance. The approachs generalizability was demonstrated by retraining the global model with data from two external DIA-MS cohorts (n=55) and eight acquired by tandem mass tag (TMT) proteomics (n=832). ProCanFDL presents a solution for internationally collaborative machine learning initiatives using proteomic data, e.g., for discovering predictive biomarkers or treatment targets, while maintaining data privacy. Statement of SignificanceA federated deep learning approach applied to human proteomic data, acquired using two distinct proteomic technologies from 40 tumor cohorts from eight countries, enabled accurate cancer histopathological subtyping while preserving data privacy. This approach will enable privacy-compliant development of large-scale proteomic AI models, including foundation models, across institutions globally.

cancer biology↗

bioRxiv2024

Design of linked-domain protein inhibitors of UBE2D as tools to study cellular ubiquitination

Ubiquitin (Ub) is a post-translational modification that largely controls proteostasis through mechanisms spanning transcription, translation, and notably, protein degradation. Ub conjugation occurs through a hierarchical cascade of three enzyme classes (E1, E2, and E3s) involving >1000 proteins that regulate the ubiquitination of proteins. The E2 Ub-conjugating enzymes are the midpoint, yet their cellular roles remain under-characterized, partly due to a lack of inhibitors. For example, the cellular roles of the promiscuous E2 UBE2D/UBCH5 are not well described. Here, we develop a highly selective, multivalent, engineered protein inhibitor for the UBE2D family that simultaneously targets the RING- and backside-binding sites. In HeLa cells, these inhibitors phenocopy knockdown of UBE2D by reducing the IC50 to cisplatin and whole-cell proteomics reveal an increased abundance of [~]20% of the identified proteins, consistent with reduced Ub degradation and proteotoxic stress. These precision tools will enable new studies probing UBE2Ds central role in proteome management.

biochemistry↗

bioRxiv2024

The JNK and Hippo pathways control epithelial integrity and prevent tumour initiation by regulating an overlapping transcriptome

Epithelial organs maintain their integrity and prevent tumour initiation by actively removing defective cells, such as those that have lost apicobasal polarity. Here, we identify how transcription factors of two key signalling pathways - Jun-N-terminal kinase (JNK) and Hippo - regulate epithelial integrity by controlling transcription of an overlapping set of target genes. Targeted DamID experiments reveal that in proliferating cells of the Drosophila melanogaster eye, the AP-1 transcription factor Jun, and the Hippo pathway transcription regulators Yorkie and Scalloped bind to a common suite of target genes that regulate organ growth. In defective neoplastic cells, AP-1 transcription factors repress transcription of growth genes together with the CtBP co-repressor. If gene repression by AP-1/CtBP fails, neoplastic tumour growth ensues, driven by Yorkie/Scalloped. Thus, AP-1/CtBP eliminates defective cells and prevents tumour initiation by acting in parallel to Yorkie/Scalloped to repress expression of a shared transcriptome. These findings shed new light on the maintenance of epithelial integrity and tumour suppression.

developmental biology↗

bioRxiv2024

Damsel: Analysis and visualisation of DamID sequencing in R

SummaryDamID sequencing is a technique to map the genome-wide interaction of a protein with DNA. Damsel is the first Bioconductor package to provide an end to end analysis for DamID sequencing data within R. Damsel performs quantification and testing of significant binding sites along with exploratory and visual analysis. Damsel produces results consistent with previous analysis approaches. Availability and implementationThe R package Damsel is available for install through the Bioconductor project https://bioconductor.org/packages/release/bioc/html/Damsel.html and the code is available on GitHub https://github.com/Oshlack/Damsel/ Contactcaitlin.page@petermac.org Supplementary informationAvailable through the journal.

bioinformatics↗

bioRxiv2024

Interneurons that BiTE: Harnessing the migratory capacity of cortical inhibitory interneuron precursors to treat high-grade glioma

Glioblastoma has a poor prognosis with limited therapeutic options. To date, almost all therapeutic agents that showed promise in in vitro assays, preclinical trials, or even in early clinical trials have failed to make a substantial impact on the survival of patients with high-grade glioma. One major obstacle for small molecules, therapeutic proteins, or immune cells remains the blood brain barrier, which often prevents the efficient delivery of agents to the tumor. To address this delivery issue, we developed a cellular vector where implanted modified post-mitotic Migratory Cortical Inhibitory Interneuron Precursors (MCIPs) migrate to high-grade glioma by chemoattraction to locally secrete a therapeutic protein. The inhibitory interneurons of the cerebral cortex originate predominantly in the ventral/subcortical portion of the telencephalic neural tube. During fetal brain development, MCIP migration is guided over long distances by chemorepulsant and chemoattractant factors. Remarkably, several MCIP chemoattractant factors are also secreted by high-grade gliomas. Indeed, our in vitro and in vivo data show that MCIPs robustly migrate to the majority of glioblastoma cell lines evaluated. As a proof of principle, we modified the MCIPs to secrete bispecific T-cell engagers (BiTEs), linking the EGFR tumor antigen to CD3 on T-cells to create an adaptor molecule that induces an anti-tumor response of resident and supplied T-cells by bridging a tumor antigen and the T-cell receptor. We find that implanted BITE-secreting MCIPs significantly extended survival of mice injected with high-grade glioma. Therefore, we conclude that the use of MCIPs as a delivery vector for therapeutic agents could revolutionize the way we treat glioblastoma, as they allow for the local delivery of therapeutic agents in high concentrations, bypassing the need for these agents to cross the blood brain barrier while reducing the risk for systemic toxicities outside of the brain.

cancer biology↗

bioRxiv2024

Macropinocytosis mediates resistance to loss of glutamine transport in triple-negative breast cancer

Triple-negative breast cancer (TNBC) relies on glutamine uptake by the transporter ASCT2 to sustain their unique glutamine metabolism and growth. Despite previous data showing cell growth inhibition after ASCT2 knockdown, ASCT2 CRISPR knockout was well-tolerated by breast cancer cell lines. Despite the loss of a glutamine transporter and low rate of glutamine uptake, intracellular glutamine steady state levels were higher in ASCT2 knockout compared to control TNBC cells. Proteomics data revealed upregulation of macropinocytosis, reduction in glutamine efflux and glutamine synthesis in ASCT2 knockout cells. Loss of ASCT2 in TNBC cell line HCC1806 induced a 5-10-fold increase in macropinocytosis across 5 separate ASCT2 knockout clones, compared to a modest 2-fold increase in the shRNA ASCT2 knockdown. By comparison, ASCT2 knockout impaired cell proliferation in a non-macropinocytic breast cancer cell line, HCC1569. These data suggest that macropinocytosis provides a novel resistance mechanism to strategies targeting glutamine uptake alone. Despite this adaptation, TNBC cells continue to rely on glutamine metabolism for their growth, which suggests therapeutic targeting may need to focus on downstream glutamine metabolism pathways.

cancer biology↗

bioRxiv2023

snPATHO-seq: unlocking the pathology archives

Formalin-fixed paraffin-embedded (FFPE) samples are valuable but underutilized in single-cell omics research due to their low DNA and RNA quality. In this study, leveraging recent single-cell genomic technology advances, we introduce a versatile method to derive high-quality single-nucleus transcriptomic data from FFPE samples.

molecular biology↗

bioRxiv2023

Transcriptomics analyses of the LRRK2 protein interactome reveal distinct molecular signatures for sporadic and LRRK2 Parkinson's Disease

Mutations in the LRRK2 gene are the most common genetic cause for familial Parkinsons Disease (LRRK2-PD) and an important risk factor for sporadic PD (sPD). Multiple clinical trials are ongoing to evaluate the benefits associated with the therapeutical reduction of LRRK2 kinase activity. In this study, we described the changes on transcriptomic profiles (whole blood mRNA levels) of LRRK2 protein interactors in the sPD and LRRK2-PD cases as compared to healthy controls with the aim of comparing the two PD conditions. We went on to model the protein-protein interaction (PPI) network around LRRK2, which was weighted to reflect the transcriptomic changes in the network based on the expression and co-expression levels. Our results showed that LRRK2 interactors present both similar but also different alterations in expression levels and co-expression behaviours in the sPD and LRRK2-PD cases. The similar changes result in decreased connectivity within a topological cluster of the LRRK2 PPI network associated with ribosomal functions and DNA/RNA metabolism in both the sPD and LRRK2-PD scenario; while the connectivity within the autophagy/mitophagy/neurotransmitter-transport related cluster was increased exclusively in the LRRK2-PD condition as compared to the healthy controls. These results suggest that, albeit being classified as the same disease based on clinical features, LRRK2-PD and sPD show some significant differences from a molecular perspective.

neuroscience↗

bioRxiv2023

An experimental comparison of the Digital Spatial Profiling and Visium spatial transcriptomics technologies for cancer research

BackgroundSpatial transcriptomic technologies are powerful tools for resolving the spatial heterogeneity of gene expression in tissue samples. However, little evidence exists on relative strengths and weaknesses of the various available technologies for profiling human tumour tissue. In this study, we aimed to provide an objective assessment of two common spatial transcriptomics platforms, 10X Genomics Visium and Nanostrings GeoMx DSP. MethodThe abilities of the DSP and Visium platforms to profile transcriptomic features were compared using matching cell line and primary breast cancer tissue samples. A head-to-head comparison was conducted using data generated from matching samples and synthetic tissue references. Platform specific features were also assessed according to manufacturers recommendations to evaluate the optimal usage of the two technologies. ResultsWe identified substantial variations in assay design between the DSP and Visium assays such as transcriptomic coverage and composition of the transcripts detected. When the data was standardised according to manufacturers recommendations, the DSP platform was more sensitive in gene expression detection. However, its specificity was diminished by the presence of non-specific detection. Our results also confirmed the strength and weakness of each platform in characterising spatial transcriptomic features of tissue samples, in particular their application to hypothesis generation versus hypothesis testing. ConclusionIn this study, we share our experience on both DSP and Visium technologies as end users. We hope this can guide future users to choose the most suitable platform for their research. In addition, this dataset can be used as an important resource for the development of new analysis tools.

cancer biology↗

bioRxiv2023

Dysregulated Wnt and NFAT signaling in a Parkinson's disease LRRK2 G2019S knock-in model

BackgroundParkinsons disease (PD) is a progressive late-onset neurodegenerative disease leading to physical and cognitive decline. Mutations of leucine-rich repeat kinase 2 (LRRK2) are the most common genetic cause of PD. LRRK2 is a complex scaffolding protein with known regulatory roles in multiple molecular pathways. Two prominent examples of LRRK2-modulated pathways are Wingless/Int (Wnt) and nuclear factor of activated T-cells (NFAT) signaling. Both are well described key regulators of immune and nervous system development as well as maturation. The aim of this study was to establish the physiological and pathogenic role of LRRK2 in Wnt and NFAT signaling in the brain, as well as the potential contribution of the non-canonical Wnt/Calcium pathway. MethodsIn vivo cerebral Wnt and NFATc1 signaling activity was quantified in LRRK2 G2019S mutant knock-in (KI) and LRRK2 knockout (KO) male and female mice with repeated measures over 28 weeks, employing lentiviral luciferase biosensors, and analyzed using a mixed-effect model. To establish spatial resolution, we investigated tissues, and primary neuronal cell cultures from different brain regions combining luciferase signaling activity, immunohistochemistry, qPCR and western blot assays. Results were analyzed by unpaired t-test with Welchs correction or 2-way ANOVA with post hoc corrections. ResultsIn vivo Wnt signaling activity in LRRK2 KO and LRRK2 G2019S KI mice was increased significantly [~]3-fold, with a more pronounced effect in males ([~]4-fold) than females ([~]2-fold). NFATc1 signaling was reduced [~]0.5-fold in LRRK2 G2019S KI mice. Brain tissue analysis showed region-specific expression changes in Wnt and NFAT signaling components. These effects were predominantly observed at the protein level in the striatum and cerebral cortex of LRRK2 KI mice. Primary neuronal cell culture analysis showed significant genotype-dependent alterations in Wnt and NFATc1 signaling under basal and stimulated conditions. Wnt and NFATc1 signaling was primarily dysregulated in cortical and hippocampal neurons respectively. ConclusionsOur study further built on knowledge of LRRK2 as a Wnt and NFAT signaling protein. We identified complex changes in neuronal models of LRRK2 PD, suggesting a role for mutant LRRK2 in the dysregulation of NFAT, and canonical and non-canonical Wnt signaling.

neuroscience↗

bioRxiv2022

snPATHO-seq: unlocking the FFPE archives for single nucleus RNA profiling

FFPE (formalin-fixed, paraffin-embedded) tissue archives are the largest repository of clinically annotated human specimens. Despite numerous advances in technology, current methods for sequencing of FFPE-fixed single-cells are slow, labour intensive, insufficiently sensitive and have a low resolution, making it difficult to fully exploit their enormous research and clinical potential. Here we introduce single nuclei pathology sequencing (snPATHO-Seq), a sensitive and efficient high-throughput platform to profile the transcriptome of single nuclei extracted from formalin-fixed paraffin-embedded (FFPE) samples. snPATHO-Seq combines an optimised nuclei extraction protocol from archival samples with 10x Genomics probe-based technology targeting the whole transcriptome. We performed direct comparison of the Fixed RNA Profiling (FRP) and established 3 single cell RNA-Sequencing (scRNA-Seq) workflows through a comprehensive bioinformatics analysis of matched fresh and fixed samples derived from the LNCaP prostate cancer cell line. FRP detected 2.1 times more transcripts in the fixed sample than the 3 kit did in the fresh sample. Low mitochondrial genes detection using the FRP was translated into 99.9 percent of cells passing the QC filters, compared to 81.6 percent of cells using the v3.1 chemistry. We then optimized snPATHO-Seq and applied it to a human breast cancer metastasis to the liver collected at autopsy and preserved in FFPE, a particularly challenging sample type. Remarkably, at 28,000 reads/cell snPATHO-Seq was able to detect a median of 1850 genes/cell and 3,216 UMI counts/cell. Comparison of snPATHO-Seq with spatial transcriptomics data (10x Genomics Visium FFPE v1) derived from an adjacent section of the same sample revealed a strong correlation, validating the accuracy of the snPATHO-Seq data. Gene expression data from snPATHO-Seq was used to predict cell type composition within each spatial transcriptomic location via deconvolution. Overall, snPATHO-Seq enables high quality and sensitivity snRNA-Seq from preserved tissue samples, unlocking the vast archives of FFPE tissues and thereby allowing extensive retrospective clinical genomic studies.

cancer biology↗

bioRxiv2022

Tissue specific LRRK2 interactomes reveal a distinct functional unit within the striatum

Mutations in LRRK2 are the most common genetic cause of Parkinsons disease. Despite substantial research efforts, the physiological and pathological role of this multidomain protein remains poorly defined. In this study, we used a systematic approach to construct the general protein-protein interactome around LRRK2, which was then differentiated into 15 tissue-specific interactomes taking into consideration the differential expression patterns and the co-expression behaviours of the LRRK2 interactors in different healthy tissues. The LRRK2 interactors exhibited distinct expression features in the brain as compared to the peripheral tissues analysed. Moreover, a high degree of similarity was found for the LRRK2 interactors in putamen, caudate and nucleus accumbens, thus defining a potential LRRK2 functional cluster within the striatum. We also explored the functions highlighted by the "core LRRK2 interactors" within each tissue and illustrated how the LRRK2 interactomes can be used as a tool to trace the relationship between LRRK2 and specific interactors of interest, here exemplified with a study focused on the LRRK2 interactors belonging to the Rab protein family.

neuroscience↗

bioRxiv2022

Integration of single-cell RNA and protein data identifies novel clinically-relevant lymphocyte phenotypes in breast cancers

Immune cells are critical determinants of solid tumour aetiology, but the diverse phenotypes of intra-tumoural immune cells remain incompletely characterised. We applied integrated single cell RNA sequencing (scRNA-Seq) and highly multiplexed protein epitope analysis to a cohort of breast cancer samples to resolve cell states within the tumour microenvironment. We reveal novel protein markers for resting and activated tumour infiltrating lymphocytes, and show that high expression of CD103 primarily marks exhausted CD8 rather than tissue resident CD8 T-cells in human breast cancers. We identify two distinct states of activated CD4+ T follicular helper (Tfh) cells. A population resembling conventional Tfh (cTfh) cells were localised primarily to lymphoid aggregates by spatial transcriptomics. In contrast, cancer associated Tfh (caTfh) cells expressing markers of tissue residency and exhaustion co-localized with cancer foci and signalled to macrophages. Importantly, increased caTfh : cTfh ratio associated with improved disease outcome and response to checkpoint immunotherapy.

immunology↗