Biology subjects

Prehn, J. H. M.

Publications and source records attributed to Prehn, J. H. M..

14 recordsLinked to original sources

bioRxiv2026

Spatiotemporal transcriptomics reveals distinct responses of ALDH1A1-positive and ALDH1A1-negative midbrain dopaminergic neurons to alpha-synuclein overexpression

Parkinsons disease is characterized by the progressive and preferential degeneration of dopaminergic neurons in the substantia nigra pars compacta, and intraneuronal alpha-synuclein (Syn) accumulation. Dopaminergic neurons (DANs) are anatomically and molecularly heterogeneous, but the impact of Syn pathology on distinct subpopulations is not well defined. One midbrain DAN sub-population expresses Aldehyde Dehydrogenase 1A1 (ALDH1A1), an enzyme that detoxifies aldehyde by-products of dopamine metabolism, and has been associated with differential vulnerability. Here, we applied GeoMx spatial transcriptomics to profile ALDH1A1-positive (ALDH1A1+) and ALDH1A1-negative (ALDH1A1-) DAN subpopulations in the mouse midbrain in situ at 3- and 8-weeks following adeno-associated virus (AAV)-mediated Syn overexpression. Analyzing 10,532 genes, we identified robust transcriptional differences between ALDH1A1+ and ALDH1A1- DANs under control conditions, supporting their characterization as distinct molecular subpopulations. In AAV-Syn-injected mice, we observed increased Snca expression and a reduction in ALDH1A1- DANs in the ipsilateral substantia nigra. Syn overexpression induced subpopulation-specific and time-dependent transcriptional responses, with dysregulation in ALDH1A1- DANs characterized by early down-regulation of pathways related to synaptic function, neurotransmitter handling, and bioenergetics, including glycolysis. In contrast, ALDH1A1+ DANs displayed later up-regulation of genes enriched for Acetyl-CoA and cholesterol metabolism pathways, reflecting subpopulation-specific adaptations to Syn overexpression. Analysis of human single nucleus RNA-sequencing data revealed partial conservation of the metabolic dysregulation signature. Together, our findings show that murine midbrain ALDH1A1+ and ALDH1A1- DANs represent molecularly distinct subpopulations with divergent temporal responses to Syn overexpression, emphasizing the importance of cell-type and disease-stage context in studies of Parkinsons disease mechanisms.

neuroscience↗

bioRxiv2026

Biomimetic miR-133a inhibitor activated scaffolds optimised for spinal cord repair promote neurite outgrowth and angiogenesis via neuronal cytoskeletal remodelling

Significant challenges in spinal cord injury include the loss of neural tissue, disruption of local vasculature, and intrinsic suppression of actin mobilisation in neurons, together preventing axonal regrowth. Here, we develop an implantable biomimetic microRNA (miR) inhibitor-activated scaffold that combines optimised matrix cues with transcriptomically defined RNA-based modulation of intrinsic neuronal pathways as a platform to support neuronal cell delivery and promote neurovascular repair. First, hyaluronic acid macroporous scaffolds functionalized with collagen-IV and fibronectin supported iPSC-derived neuronal spheroid formation and neurite extension. To identify a neurotrophic target, we performed analysis of public miRNA-mRNA interaction datasets, revealing that miR-133a regulates pathways involved in neuronal actin cytoskeletal organisation. MiR-133a inhibitors were complexed with the cell-penetrating peptide RALA to form nanoparticles, demonstrated >95% scaffold loading efficiency, sustained localised release over 28 days and enhanced neurite outgrowth from motor neurons and iPSC neurons. Bulk RNA-sequencing and transcriptomic analysis of iPSC neurons within the scaffolds demonstrated coordinated upregulation of actin-remodelling, cell-matrix adhesion and metabolic pathways, indicative of a cytoskeletally adaptable neuron. When employed in an ex vivo dorsal root ganglia model, scaffold-mediated miR-133a inhibition promoted neurite extension and integration of delivered iPSC neurons with injured neural tissue. Finally, miR-133a-inhibitor-activated scaffolds upregulated neurovascular genes, increased endothelial cell migration and enhanced blood vessel formation in vivo in a chick embryo assay. These findings identify miR-133a as a neurotrophic target, elucidate the underlying mechanisms of action through transcriptomic analysis and demonstrate that biomimetic scaffold-mediated inhibition of miR-133a can enhance neuronal delivery for multifaceted spinal cord repair applications. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/719922v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@13fcb26org.highwire.dtl.DTLVardef@13239c3org.highwire.dtl.DTLVardef@6e6f5eorg.highwire.dtl.DTLVardef@51ad93_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2026

A neural network model delivers a highly prognostic protein signature in cancer stem cells that identifies relapse in stage III colorectal cancer patients.

BackgroundStage III colorectal cancer poses a significant threat of metastasis development, as tumour resection and adjuvant chemotherapy do not guarantee prolonged disease-free survival. ObjectiveThe spatial, quantitative, and qualitative characteristics of various cell types within tumour tissues could be key to developing accurate prognostic AI models. DesignTissue microarrays created from primary tumour tissues collected during surgical resection from a cohort of 493 stage III colorectal cancer (CRC) patients were analysed for 61 protein markers at the single-cell level using multiplexed immunofluorescence imaging via the Cell DIVE platform. Subsequent cell-type classification enabled quantitative cell-type analyses, co-localisation neighbourhood assessments, and cell-type-specific protein signature discoveries that distinguish between early and late/non-recurring patient samples. ResultsThis study identifies a stem cell protein profile that drives tumour relapse. A deep neural network (DNN) model, based on a stem cell protein signature composed of BAX, MLKL, FLIP, GLUT1, and CDX2, provided accurate prognosis for stage III CRC patients in both discovery and validation cohorts and in an independent validation cohort. Nodal count-based metric further increased prognosis accuracy. Our study also revealed distinct spatial arrangements of immune, endothelial, and stem cells that were linked to early tumour recurrence. ConclusionOur findings propose a clinically promising prognostic tool based on a five-protein stem cell signature. These markers not only predict chemotherapy resistance in cancer stem cells but also suggest potential therapeutic strategies such as combinatorial treatments incorporating small molecule inhibitors targeting FLIP and GLUT1. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIMore than 20% of stage III colorectal cancer patients will experience early tumour recurrence within the first 3 years post treatment that includes surgery and adjuvant 5-FU based chemotherapy treatment. C_LIO_LISeveral studies pointed towards involvements of number of cell type specific spatial neighbourhoods in tumour progression where some immune tumour microenvironment promoting angiogenesis and intravasation events, some may provide immunosuppression. C_LIO_LICancer stem cells could be responsible for metastatic tumour spread, early recurrence and chemoresistance. C_LI What this study addsO_LISpatial single cell quantitative multiplex profiling of 45 cancer hallmark proteins and 15 cell identity markers in 493 stage III CRC patients tissue samples demonstrated significant differences in cellular proximity neighbourhoods, cell type specific abundance and expression between the early and late recurrence samples. C_LIO_LIWe discover that macrophages show spatial association with the blood vessels in early recurrence samples. Moreover, we observed conglomeration of B cells and macrophages with Tregulatory, Thelper and Tcytotoxic cells in association with early recurrences. C_LIO_LIWe showed that stromal abundance of Tregulatory, Thelper, Tcytotoxic cells and monocytes are significantly in late, and no recurrence samples compared to early recurrence samples. C_LIO_LIThe most differential expression profile that differentiates late and no recurrence samples from the early recurrence samples is related to the stem cell population. Particularly, we found overexpression of GLUT1, FLIP and downregulation of BAX, BAK, MLKL and CDX2 proteins in the cancer stem cell of early recurrence samples. C_LIO_LIWe built a neural network based on the cancer stem cell protein signature (BAX, MLKL, FLIP, GLUT1 and CDX2 proteins) that delivers a high-performance prognostic classifier. C_LI How this study might affect research, practice or policyO_LIOur results propose a clinically promising prognostic tool based on a five-protein stem cell signature that outperforms existing clinical and proposed transcriptomic based signatures for separation between risk groups. C_LIO_LIMoreover, our five-protein signature markers not only predict stem cell chemotherapy resistance and therefore tumour recurrence but also suggest potential therapeutic strategies. For instance, this approach could guide combinatorial treatments at high risk of chemoresistance, such as incorporating small molecule inhibitors targeting FLIP (currently in discovery phase) and GLUT1 (already under preclinical trial evaluation). C_LI

cancer biology↗

bioRxiv2025

A multi-step filtering pipeline for human read removal enhances detection of Fusobacterium in WGS datasets with immunohistochemical confirmation in mucinous rectal cancer.

The study of tumour-associated microbiomes using whole-genome sequencing (WGS) has attracted considerable attention, but microbial signal detection remains controversial due to host contamination and methodological artefacts. As the necessity of human-read removal becomes increasingly evident, many groups now include this step in their data pre-processing workflows. In this work, we introduce an open-source tool designed for rigorous host-read removal and apply it to the reanalysis of WGS data from ten mucinous rectal adenocarcinoma cases originally published by Reynolds et al. The workflow integrates k-mer-based classification (Kraken2), quality and adapter trimming (Trim Galore), vector filtering (BBDuk/UniVec_Core), and duplicate-removal (FastUniq). After reducing data complexity, a multi-aligner, multi-reference approach (BWA-MEM/GRCh38, Bowtie2/T2T-CHM13, Minimap2/HPRC v1.1) removes remaining host sequences, collectively eliminating more than 99.9% of human-derived reads. Although the additional alignment steps eliminated only a small fraction of total reads, they consistently removed millions of residual sequences per sample, underscoring the importance of rigorous filtering in datasets where non-human reads are a small minority. Taxonomic profiling with PathSeq and MetaPhlAn revealed reproducible enrichment of Fusobacterium species in tumour versus matched normal tissues, with stricter filtering reducing overall microbial signal compared to prior results. Cross-validation with immunofluorescence analysis using pan-Fusobacterium (detecting both F. animalis and F. nucleatum) and F. nucleatum-specific antibodies showed a strong concordance with Fusobacterium subspecies detected by WGS. Compared to the unfiltered analysis, host depletion markedly reduced artificial microbial signals in normal samples while preserving tumour-associated Fusobacterium, resulting in a more reliable microbial profile. ImportanceWe developed an open-source tool that enables rapid removal of human-derived sequences and applied it to rectal cancer WGS data. This approach reduced false microbial signals while preserving true tumour-associated Fusobacterium, and we confirmed these findings in tissue using immunofluorescence staining. Our method provides a more reliable foundation for studying tumour-bacteria interactions.

bioinformatics↗

bioRxiv2025

DREAMER-S: Deep leaRning-Enabled Attention-based Multiple-instance approaches with Explainable Representations for Spatial Biology

Identifying image features that associate strongly with diagnostic or prognostic classes in large-scale, multi-channel spatial imaging is challenging without pixel-level annotations. We present DREAMER-S, an attention-based multiple-instance learning (MIL) framework that, using only image- or slide-level labels, learns spatial features within 3D imaging hypercubes that are most informative for downstream classification. We demonstrate DREAMER-S on Quantum Cascade Laser infrared (QCL-IR) tissue imaging, where attention weights are rendered spatially to highlight class-relevant spectral instances without manual annotation. Because the MIL attention layer assigns interpretable importances to spatial instances, the method is broadly transferable to spatial-biology applications that require instance-level filtering to focus towards salient regions of interest in high-content datasets. We further evaluate DREAMER-S on a chemotherapy-response task in a colorectal cancer patient-derived xenograft (PDX) model. After tuning, DREAMER-S separated spectral instances from a chemo-sensitive PDX (CRC0344) and a less responsive PDX (CRC0076) with an F1 score of [~]0.95. To validate explainability, we linked model saliency to cellular physiology, observing that, (i) unsupervised UMAP embeddings of high-attention spectra stratified samples by treatment (chemotherapy, apoptosis sensitizer, combination, vehicle), and (ii) selected spectral markers correlated with pro-apoptotic proteins measured independently in the same PDX system. Together, these results support a mechanistic link between spectral signals and apoptosis pathways and position DREAMER-S as an efficient, interpretable approach for analysing high-content spatial-biology imaging datasets.

bioinformatics↗

bioRxiv2024

Spatial Effects of Infiltrating T cells on Neighbouring Cancer Cells and Prognosis in Stage III CRC patients

Colorectal cancer (CRC) is one of the most frequently occurring cancers, but prognostic biomarkers identifying patients at risk of recurrence are still lacking. In this study, we aimed to investigate in more detail the spatial relationship between intratumoural T cells, cancer cells, and cancer cell hallmarks, as prognostic biomarkers in stage III colorectal cancer patients. We conducted multiplexed imaging of 56 protein markers at single cell resolution on resected fixed tissue from stage III CRC patients who received adjuvant 5-fluorouracil-based chemotherapy. Images underwent segmentation for tumour, stroma and immune cells, and cancer cell state protein marker expression was quantified at a cellular level. We developed a Python package for estimation of spatial proximity, nearest neighbour analysis focusing on cancer cell - T cell interactions at single-cell level. In our discovery cohort (MSK), we processed 462 core samples (total number of cells: 1,669,228) from 221 adjuvant 5FU-treated stage III patients. The validation cohort (HV) consisted of 272 samples (total number of cells: 853,398) from 98 stage III CRC patients. While there were trends for an association between percentage of cytotoxic T cells (across the whole cancer core), it did not reach significance (Discovery cohort: p = 0.07, Validation cohort: p = 0.19). We next utilized our region-based nearest neighbourhood approach to determine the spatial relationships between cytotoxic T cells, helper T cells and cancer cell clusters. In the both cohorts, we found that lower distance between cytotoxic T cells, T helper cells and cancer cells was significantly associated with increased disease-free survival. An unsupervised trained model that clustered patients based on the median distance between immune cells and cancer cells, as well as protein expression profiles, successfully classified patients into low-risk and high-risk groups (Discovery cohort: p = 0.01, Validation cohort: p = 0.003).

cancer biology↗

bioRxiv2023

Identification of inter- and intra-tumoral molecular phenotypes steering temozolomide resistance in patient-derived glioblastoma cells.

BackgroundRadiation therapy and chemotherapy using Temozolomide are the standard adjuvant treatments for patients with glioblastoma. Despite maximal treatment prognosis is still poor largely due to the emergence of Temozolomide resistance. This resistance is closely linked to the widely recognized inter- and intra-tumoral heterogeneity in glioblastoma, although the underlying mechanisms are not yet fully understood. This study aims to investigate the diverse molecular mechanisms involved in temozolomide resistance. MethodsTo induce temozolomide resistance, we subjected 21 patient-derived glioblastoma cell cultures to Temozolomide treatment for a period of up to 90 days. Prior to treatment, the cells molecular characteristics were analyzed using bulk RNA sequencing. Additionally, we performed single-cell sequencing on four of the cell cultures to track the evolution of temozolomide resistance. ResultsThe induced temozolomide resistance was associated with two distinct phenotypic behaviors, classified as "adaptive" (ADA) or "non-adaptive" (N-ADA) to temozolomide. The ADA phenotype displayed neurodevelopmental and metabolic gene signatures, whereas the N-ADA phenotype expressed genes related to cell cycle regulation, DNA repair, and protein synthesis. Single-cell RNA sequencing revealed that in ADA cell cultures, one or more subpopulations emerged as dominant in the resistant samples, whereas N-ADA cell cultures remained relatively stable. ConclusionsThe adaptability and heterogeneity of glioblastoma cells play pivotal roles in temozolomide treatment and contribute to the tumors ability to survive. Depending on the tumors adaptability potential, subpopulations with acquired resistance mechanisms may arise. Further research is necessary to deepen our understanding of these mechanisms and develop strategies to overcome them.

cancer biology↗

bioRxiv2022

Identification and characterization of four bacteriome- and mycobiome-derived subtypes in tumour and adjacent mucosa tissue of colorectal cancer patients

ObjectiveHere, we systematically investigated alterations in the bacteriome and mycobiome of CRC patients in tumours and matched adjacent mucosa resulting in the identification of microbiome-based subtypes associated with host clinico-pathological and molecular characteristics. DesignDiversity and composition of bacteriome and mycobiome of tumour and adjacent mucosa, resulting subtypes were computationally deconvoluted from RNA sequencing, using >10000 samples from in-house and publically available patient cohorts. ResultsThe bacteriome of tumours had higher dominance and lower -diversity compared to matched adjacent local and distant mucosa. Tumours were enriched with Proteobacteria (Gammaproteobacteria class), Fusobacteria (including Fusobacterium Nucleatum species) and Basidiomycota fungi (Malasseziaceae family). Tumours were depleted of Bacteroidetes (Bacteroidia class), Firmicutes (Clostridia class) and Ascomycota (Sordariomycetes and Saccharomycotina). Tumours and adjacent mucosa samples were classified into 4 microbial subtypes, termed C1 to C4, based on the bacteriome and mycobiome composition. The bacterial Propionibacteriaceae, Enterobacteriaceae, Fusobacteriaceae, Bacteroidaceae and Ruminococcaceae and the fungal Malasseziaceae, Saccharomycetaceae and Aspergillaceae were among the key families driving the microbial subtyping. Microbial subtypes were associated with distinct tumour histology and patient phenotypes and served as an independent prognostic marker for disease-free survival. Key associations between microbial subtypes and alterations in host immune response and signalling pathways were validated in the TCGA pan-cancer cohort. The microbial subtyping demonstrated stratification value in the pan-cancer settings beyond merely representing differences in survival by cancer type. ConclusionsThis study demonstrates the translational potential of microbial subtyping in CRC patient stratification, and provides avenues to design tailored microbiota modulation therapy to further precision oncology. Statement of significanceO_ST_ABSWhat is already known on this subject?C_ST_ABSO_LIThe microbiome has been implicated in the pathogenesis, progression and therapeutic response in patients diagnosed with CRC and other cancers. C_LIO_LIThe vast majority of studies to date has focussed on investigating the bacteriome while the critical role played by the mycobiome in shaping cancer has begun to be explored more recently. C_LIO_LIThe bacterial and fungal composition and diversity in on-tumour tissue compared to matched local and distal off-tumour mucosa is largely unexplored. C_LIO_LITumorigenesis may be promoted via alterations of the microbiome ecosystem that may be better recapitulated by a multi-kingdom microbial signature rather than by the abundance of individual bacterial or fungal microorganisms. C_LI What are the new findings?O_LIOn-tumour tissue was enriched with Fusobacteria, Proteobacteria, Basidyomicota and depleted of Bacteroidetes, Firmicutes, Ascomycota compared with adjacent off-tumour mucosa. C_LIO_LIWe stratified >600 CRC patients into four distinct microbial-based subtypes (C1-C4) according to their bacteriome and mycobiome composition. The microbial subtypes were associated with distinct prognosis, clinical phenotypes such as staging, tumour location, history, lymphovascular invasion, TP53 status and clinical outcome. C_LIO_LIFurthermore, the majority of matched adjacent mucosa samples were classified as C1 and paired tumour-matched normal samples demonstrated a robust shift towards the C1 subtype in off-tumour tissue, suggesting that the C1 subtype may recapitulate a healthier-like microbiome. This hypothesis was supported by the microbial subtyping of colon samples from healthy subjects that were categorised as C1 almost exclusively. C_LIO_LIThe identified microbial subtyping demonstrated stratification value in the pan-cancer settings (n=28 additional solid cancer indications spanning >9000 samples) beyond merely representing differences in survival by cancer type, providing the strongest stratification in liver cancer. C_LI How might it impact on clinical practise in the foreseeable future?O_LIThis study laids the foundation to develop a microbial signature as biomarker to clinically manage CRC and other solid cancers and potentially lead to microbiome-based companion diagnostics to design microbiota modulation therapy tailored to specific patients subgroups with distinct bacteriomes and mycobiomes. C_LI

cancer biology↗

bioRxiv2022

Bcl-xL is a key mediator of apoptosis following KRASG12C inhibition in KRASG12C mutant colorectal cancer.

PurposeNovel covalent inhibitors of KRASG12C have shown limited response rates in KRASG12C mutant (MT) colorectal cancer (CRC) patients. Thus, novel KRASG12C inhibitor combination strategies that can achieve deep and durable responses are needed. Experimental designSmall molecule KRASG12C inhibitors AZ1569 and AZ8037 were employed. To identify novel candidate combination strategies for AZ1569, we performed RNA sequencing, siRNA and high-throughput drug screening. Top hits were validated in a panel of KRASG12CMT CRC cells and in vivo. AZ1569-resistant CRC cells were generated and characterised. ResultsResponse to AZ1569 was heterogeneous across the KRASG12CMT models. AZ1569 was ineffective at inducing apoptosis when used as single-agent or combined with chemotherapy or agents targeting the EGFR/KRAS/AKT axis. Using a systems biology approach, we identified the anti-apoptotic BH3-family member BCL2L1/Bcl-xL as a top hit mediating resistance to AZ1569. Further analyses identified acute increases in the pro-apoptotic protein BIM following AZ1569 treatment. ABT-263 (Navitoclax), a pharmacological Bcl-2 family-inhibitor that blocks the ability of Bcl-xL to bind and inhibit BIM, led to dramatic and universal apoptosis when combined with AZ1569. Furthermore, this combination also resulted in dramatically attenuated tumour growth in KRASG12CMT xenografts. Finally, AZ1569-resistant cells showed amplification of KRASG12C, EphA2/c-MET activation, increased pro-inflammatory chemokine profile and cross-resistance to several targeted agents. Importantly, KRAS amplification and AZ1569-resistance were reversible upon drug withdrawal, arguing strongly for the use of drug holidays in the case of KRAS amplification. ConclusionsCombinatorial targeting of Bcl-xL and KRASG12C is highly effective, suggesting a novel therapeutic strategy for KRAS G12CMT CRC patients.

cancer biology↗

bioRxiv2021

Functional expression of the ATP-gated P2X7 receptor in human iPSC-derived neurons and astrocytes

The P2X7 receptor (P2X7R) is a cation membrane channel activated by extracellular adenosine 5'-triphosphate. Activation of this receptor results in numerous downstream events including the modulation of neurotransmission, release of pro-inflammatory mediators, cell proliferation or cell death. While the expression of P2X7Rs is well documented on microglia and oligodendrocytes, the presence of functional P2X7Rs on neurons and astrocytes remains debated. Furthermore, to date, functional studies on the P2X7R are mostly limited to studies in cells from rodents and immortalised cell lines expressing human P2X7Rs. To assess the functional expression of P2X7Rs in human neurons and astrocytes, we differentiated human-induced pluripotent stem cells (hiPSCs) into forebrain cortical neurons that co-express FOXG1 and {beta}III-tubulin as well as S100 {beta}-expressing astrocytes. Immunostaining revealed prominent punctate P2X7R staining on the soma and processes of hiPSC-derived neurons and astrocytes. In addition, our data show that stimulation with the potent nonselective P2X7R agonist BzATP induces robust calcium rises in hiPSC-derived neurons and astrocytes, which were blocked by the selective P2X7R antagonist AFC-5128. Together, our findings provide evidence for the functional expression of P2X7Rs in hiPSC-derived forebrain cortical neurons and astrocytes demonstrating that these cells offer the potential for investigating P2X7R-mediated pathophysiology and drug screening in vitro.

neuroscience↗

bioRxiv2021

Stratification Of Chemotherapy-Treated Stage III Colorectal Cancer Patients Using Multiplexed Imaging And Single Cell Analysis Of T Cell Populations

Colorectal cancer (CRC) has one of the highest cancer incidences and mortality rates. In stage III, postoperative chemotherapy benefits <20% of patients, while more than 50% will develop distant metastases. Predictive biomarkers for identification of patients with increased risk for disease recurrence are currently lacking, with progress in biomarker discovery hindered by the diseases inherent heterogeneity. The immune profile of colorectal tumors has previously been found to have prognostic value. The aims of this study were to evaluate immune signatures in the tumor microenvironment (TME) using an in situ multiplexed immunofluorescence imaging and single cell analysis technology (Cell DIVE). Tissue microarrays (TMAs) with up to three 1mm diameter cores per patient were prepared from 117 stage III CRC patients treated with adjuvant fluoropyrimidine/oxaliplatin chemotherapy. Single sections underwent multilplexed immunofluorescence with Cy3- and Cy5-conjugated antibodies for immune cell markers (CD45, CD3, CD4, CD8, FOXP3, PD1) and cell segmentation markers (DAPI, pan-cytokeratin, AE1, NaKATPase and S6). We applied a probabilistic multi-class, multi-label classification algorithm based on multi-parametric models to build statistical models of protein expression to classify immune cells. Expert annotations of immune cell markers were made on a range of images, and Support Vector Machines (SVM) were used to derive a statistical model for cell classification. Images were also manually scored independently by a Pathologist as high, moderate or low, for stromal and total immune cell content. Excellent agreement was found between manual and total automated scores (p<0.0001). Higher levels of multi-marker classified regulatory T cells (CD3+CD4+FOXP3+PD1-) were significantly associated with disease-free survival (DFS) and overall-survival (OS) (p=0.049 and 0.032), compared to FOXP3 alone. Our results also showed that PD1- Tregs rather than PD1+ Tregs were associated with improved survival. Overall, compared to single markers, multi-marker classification provided more accurate quantitation of immune cells with greater potential for predicting patient outcomes.

cancer biology↗

bioRxiv2020

Comparative profiling of N-respirasomes predicts aberrant mitochondrial bioenergetics at single-cell resolution

AO_SCPLOWBSTRACTC_SCPLOWMitochondria sustain the energy demand of the cell. The composition and functional state of the mitochondrial oxidative phosphorylation system are informative indicators of organelle homeostasis and bioenergetic capacity. Here we describe a highly sensitive and reproducible method for single-cell visualization and quantification of mitochondrial respiratory supercomplexes as a novel means of measuring mitochondrial respiratory chain integrity. We apply a proximity ligation assay (PLA) and perform comparative studies of mitochondrial CI, CIII and CIV-containing supercomplexes (or N-respirasomes) in fixed human and mouse brain tissues, tumorigenic cells, iPSCs and iPSC-derived NPCs and neurons. Our optimized approach enables a quantitative in-situ assessment of even subtle mitochondrial lesions associated with aberrant respiration. By combining quantitative proteomics with single cell imaging analysis, we also report the mechanistic contribution of the MICOS complex subunit CHCHD3 in regulating N-respirasomes. Overall, our PLA-based profiling of N-respirasomes establishes a sensitive and complementary technique for detecting cell-type specific mitochondrial perturbations in fixed materials.

cell biology↗

bioRxiv2020

TRAIL signalling promotes entosis in colorectal cancer

Entosis is a form of non-phagocytic cell-in-cell (CIC) interaction where a living cell enters into another. Tumours show evidence of entosis, however factors controlling entosis remain to be elucidated. Here we find that the death receptor ligand TRAIL is a potent activator of entosis in colon cancer cells. CLEM/3D confocal microscopy analysis revealed ultrastructural features of entosis and subsequent entotic cell death of inner cells upon TRAIL treatment. Induction of entosis and apoptosis by TRAIL were mutually exclusive events but both required the presence of caspase-8. Bax/Bak double knock-out or caspase inhibition altered the fate of inner cells from entotic cell death to survival and escape. Analysis of colorectal cancer tumours showed a significant association between expression levels of TRAIL and CICs. Notably, the presence of CICs in the invasive front regions of colorectal tumours was significantly correlated with adverse patient prognosis.

cancer biology↗

bioRxiv2017

Orexin/Hypocretin Immunoreactivity In The Lateral Hypothalamus Is Reduced In Genetically Obese But Not In Diet-Induced Obese Mice

The mechanisms that link diet and body weight are not fully understood. A diet high in fat often leads to obesity, and this in part is the consequence of diet-induced injury to specific hypothalamic nuclei. It has been suggested that a diet high in fat leads to cell loss in the lateral hypothalamus, which contains specific populations of neurones that are essential for regulating energy homoeostasis; however, we do not know which cell types are affected by the diet. We studied the possibility that high-fat diet leads to a reduction in orexin/hypocretin (O/H) and/or melanin-concentrating hormone (MCH) immunoreactivity in the lateral hypothalamus. We quantified immuno-labelled O/H and MCH cells in brain sections of mice fed a diet high in fat for up to 12 weeks starting at 4 weeks of age and found that this diet did not modify the number of O/H- or MCH-immunoreactive neurones. By contrast, there were fewer O/H- (but not MCH-) immunoreactive cells in geneticallyobese db/db mice compared to wild-type mice. Non-obese, heterozygous db/+ mice also had fewer O/H-immunoreactive cells. Differences in the number of O/H-immunoreactive cells were only a function of the db genotype but not of diet or body weight. Our findings show that the lateral hypothalamus is affected differently in genetic and in diet-induced obesity, and support the idea that hypothalamic neurones involved in energy balance regulation are not equally sensitive to the effects of diet.

neuroscience↗