Transcription factor NFE2L1 decreases in glomerulonephropathies after podocyte damage

Funding: This work was supported by NHS Lothian. This project received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 101017453 as part of the KATY project, and from NuCana plc.Podocyte cellular injury and detachment from glomerular capillaries constitute a critical factor contributing to kidney disease. Notably, transcription factors are instrumental in maintaining podocyte differentiation and homeostasis. This study explores the hitherto uninvestigated expression of Nuclear Factor Erythroid 2-related Factor 1 (NFE2L1) in podocytes. We evaluated the podocyte expression of NFE2L1, Nuclear Factor Erythroid 2-related Factor 2 (NFE2L2), and NAD(P)H:quinone Oxidoreductase (NQO1) in 127 human glomerular disease biopsies using multiplexed immunofluorescence and image analysis. We found that both NFE2L1 and NQO1 expressions were significantly diminished across all observed renal diseases. Furthermore, we exposed human immortalized podocytes and ex vivo kidney slices to Puromycin Aminonucleoside (PAN) and characterized the NFE2L1 protein isoform expression. PAN treatment led to a reduction in the nuclear expression of NFE2L1 in ex vivo kidney slices and podocytes.Publisher PDFPeer reviewe

Dynamic modulation of phosphoprotein expression in ovarian cancer xenograft models

The authors thank Medical Research Scotland and the Scottish Funding Council. This work was su pported by Medical Research Scotland [FRG353 to V.A.S.]; the FP7 -­‐ Directorate -­‐ General for Research and Innovation of the European Commission [EU HEALTH -­‐ F4 -­‐ 2012 -­‐ 305033 to Coordinating Action Systems Medicine -­‐ D.J.H.]; the Chief Scientist Office of Scotland [D.J.H.], the Scottish Funding Council [D.J.H. and S.P.L.]. Health Canada Scholarship (Indspire) [KEF], Scottish Overseas Research Student Award Scheme (University of Edinburgh)[KEF] and the Three Fires Award (Wikwemikong Board of Education)[KEF].Background: The dynamic changes that occur in protein expression after treatment of a cancer in vivo are poorly described. In this study we measure the effect of chemotherapy over time on the expression of a panel of proteins in ovarian cancer xenograft models. The objective was to identify phosphoprotein and other protein changes indicative of pathway activation that might link with drug response. Methods: Two xenograft models, platinum-responsive OV1002 and platinum-unresponsive HOX424, were used. Treatments were carboplatin and carboplatin-paclitaxel. Expression of 49 proteins over 14 days post treatment was measured by quantitative immunofluorescence and analysed by AQUA . Results: Carboplatin treatment in the platinum-sensitive OV1002 model triggered up-regulation of cell cycle, mTOR and DDR pathways, while at late time points WNT, invasion , EMT and MAPK pathways were modulated. Estrogen receptor-alpha (ESR1) and ERBB pathways were down-regulated early, within 24h from treatment administration. Combined carboplatin-paclitaxel treatment triggered a more extensive response in the OV1002 model modulating expression of 23 of 49 proteins. Therefore the cell cycle and DDR pathways showed similar or more pronounced changes than with carboplatin alone . In addition to expression of pS6 and pERK increasing, components of the AKT pathway were modulated with pAKT increasing while its regulator PTEN was down-regulated early. WNT signaling, EMT and invasion markers were modulated at later time points. Additional pathways were also observed with the NFκB and JAK/STAT pathways being up-regulated. ESR1 was down-regulated as was HER4, while further protein members of the ERB B pathway were upregulated late. By contrast, in the carboplatin-unresponsive HOX 424 xenograft, carboplatin only modulated expression of MLH1 while carboplatin-paclitaxel treatment modulated ESR1 and pMET.Publisher PDFPeer reviewe

YAP translocation precedes cytoskeletal rearrangement in podocyte stress response : a podometric investigation of diabetic nephropathy

KH was funded by a University of St Andrews 600th Anniversary Ph.D. scholarship. ME and DH were supported by NHS Lothian.Podocyte loss plays a pivotal role in the pathogenesis of glomerular disease. However, the mechanisms underlying podocyte damage and loss remain poorly understood. Although detachment of viable cells has been documented in experimental Diabetic Nephropathy, correlations between reduced podocyte density and disease severity have not yet been established. YAP, a mechanosensing protein, has recently been shown to correlate with glomerular disease progression, however, the underlying mechanism has yet to be fully elucidated. In this study, we sought to document podocyte density in Diabetic Nephropathy using an amended podometric methodology, and to investigate the interplay between YAP and cytoskeletal integrity during podocyte injury. Podocyte density was quantified using TLE4 and GLEPP1 multiplexed immunofluorescence. Fourteen Diabetic Nephropathy cases were analyzed for both podocyte density and cytoplasmic translocation of YAP via automated image analysis. We demonstrate a significant decrease in podocyte density in Grade III/IV cases (124.5 per 106 μm3) relative to Grade I/II cases (226 per 106 μm3) (Student’s t-test, p<0.001), and further show that YAP translocation precedes cytoskeletal rearrangement following injury. Based on these findings we hypothesize that a significant decrease in podocyte density in late grade Diabetic Nephropathy may be explained by early cytoplasmic translocation of YAP.Publisher PDFPeer reviewe

Use of high-plex data reveals novel insights into the tumour microenvironment of clear cell renal cell carcinoma

This work was supported by Medical Research Scotland (MRS), NHS Lothian, NanoStringTechnologies, and the Industrial Centre for AI Research in Digital Diagnostics (iCAIRD) which is funded by Innovate UK on behalf of UK Research and Innovation (UKRI) [project number: 104690].Although Immune Checkpoint Inhibitors (ICIs) have significantly improved the oncological outcomes, about one third of patients affected by Clear Cell Renal Cell Carcinoma (ccRCC) still experience recurrence. Current prognostic algorithms like the Leibovich Score (LS) rely on morphological features manually assessed by pathologists, and are therefore subject to bias. Moreover, these tools do not consider the heterogeneous molecular milieu present in the Tumour Microenvironment (TME), which may have prognostic value. We systematically developed a semi-automated method to investigate 62 markers and their combinations in 150 primary ccRCCs using multiplex Immunofluorescence (mIF), NanoString GeoMx® Digital Spatial Profiling (DSP) and Artificial Intelligence (AI)-assisted image analysis in order to find novel prognostic signatures and investigate their spatial relationship. We found that coexpression of Cancer Stem Cell (CSC) and Epithelial-to-Mesenchymal Transition (EMT) markers such as OCT4 and ZEB1 are indicative of poor outcome. OCT4 and the immune markers CD8, CD34 and CD163 significantly stratified patients at intermediate LS. Furthermore, augmenting the LS with OCT4 and CD34 improved patient stratification by outcome. Our results support the hypothesis that combining molecular markers has prognostic value and can be integrated with morphological features to improve risk stratification and personalised therapy. To conclude, GeoMx® DSP and AI image analysis are complementary tools providing high multiplexing capability required to investigate the TME of ccRCC, while reducing observer bias.Publisher PDFPeer reviewe

Genome-scale CRISPR/Cas9 screen determines factors modulating sensitivity to ProTide NUC-1031

A.S. is the recipient of a Medical Research Scotland PhD Studentship awarded to P.A.R. Edinburgh Genomics is partly supported through core grants from Natural Environment Research Council (R8/H10/56), Medical Research Council (MR/K001744/1) and Biotechnological and Biological Research Council (BB/J004243/1). Publication of this article was funded in part by the University of St Andrews Open Access Publishing Fund.Gemcitabine is a fluoropyrimidine analogue that is used as a mainstay of chemotherapy treatment for pancreatic and ovarian cancers, amongst others. Despite its widespread use, gemcitabine achieves responses in less than 10% of patients with metastatic pancreatic cancer and has a very limited impact on overall survival due to intrinsic and acquired resistance. NUC-1031 (Acelarin), a phosphoramidate transformation of gemcitabine, was the first anti-cancer ProTide to enter the clinic. We find it displays important in vitro cytotoxicity differences to gemcitabine, and a genome-wide CRISPR/Cas9 genetic screening approach identified only the pyrimidine metabolism pathway as modifying cancer cell sensitivity to NUC-1031. Low deoxycytidine kinase expression in tumour biopsies from patients treated with gemcitabine, assessed by immunostaining and image analysis, correlates with a poor prognosis, but there is no such correlation in tumour biopsies from a Phase I cohort treated with NUC-1031.Publisher PDFPeer reviewe

Tissue-specific immunopathology in fatal COVID-19

Funding: Inflammation in COVID-19: Exploration of Critical Aspects of Pathogenesis (ICECAP) receives funding and support from the Chief Scientist Office (RapidResearch in COVID-19 programme [RARC-19] funding call, “Inflammation in Covid-19: Exploration of Critical Aspects of Pathogenesis; COV/EDI/20/10” to D.A.D., C.D.L., C.D.R., J.K.B., and D.J.H.), LifeArc (through the University of Edinburgh STOPCOVID funding award to K.D., D.A.D., and C.D.L.), UK Research and Innovation (UKRI) (Coronavirus Disease [COVID-19] Rapid Response Initiative; MR/V028790/1 to C.D.L., D.A.D., and J.A.H.), and Medical Research Scotland (CVG-1722-2020 to D.A.D., C.D.L., C.D.R., J.K.B., and D.J.H.). C.D.L. is funded by a Wellcome Trust Clinical Career Development Fellowship(206566/Z/17/Z). J.K.B. and C.D.R. are supported by the Medical Research Council (grant MC_PC_19059) as part of the International Severe AcuteRespiratory Infection Consortium Coronavirus Clinical Characterisation Consortium (ISARIC-4C). D.J.H., I.H.U., and M.E. are supported by the Industrial Centre for Artificial Intelligence Research in Digital Diagnostics. S.P. is supported by Kidney Research UK, and G.T. is supported by the Melville Trust for the Cure and Care of Cancer. Identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and sequencing work was supported by theU.S. Food and Drug Administration grant HHSF223201510104C (“Ebola Virus Disease: correlates of protection, determinants of outcome and clinicalmanagement”; amended to incorporate urgent COVID-19 studies) and contract 75F40120C00085 (“Characterization of severe coronavirus infection inhumans and model systems for medical countermeasure development and evaluation”; awarded to J.A.H.). J.A.H. is also funded by the Centre of Excellence in Infectious Diseases Research and the Alder Hey Charity. R.P.-R. is directly supported by the Medical Research Council Discovery Medicine North Doctoral Training Partnership. The group of J.A.H. is supported by the National Institute for Health Research Health Protection Research Unit in Emerging and Zoonotic Infections at the University of Liverpool in partnership with Public Health England and in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.Rationale: In life-threatening Covid-19, corticosteroids reduce mortality, suggesting that immune responses have a causal role in death. Whether this deleterious inflammation is primarily a direct reaction to the presence of SARS-CoV-2 or an independent immunopathologic process is unknown. Objectives: To determine SARS-CoV-2 organotropism and organ-specific inflammatory responses, and the relationships between viral presence, inflammation, and organ injury. Methods: Tissue was acquired from eleven detailed post-mortem examinations. SARS-CoV-2 organotropism was mapped by multiplex PCR and sequencing, with cellular resolution achieved by in situ viral spike protein detection. Histological evidence of inflammation was quantified from 37 anatomical sites, and the pulmonary immune response characterized by multiplex immunofluorescence. Measurements and main results: Multiple aberrant immune responses in fatal Covid-19 were found, principally involving the lung and reticuloendothelial system, and these were not clearly topologically associated with the virus. Inflammation and organ dysfunction did not map to the tissue and cellular distribution of SARS-CoV-2 RNA and protein, both between and within tissues. An arteritis was identified in the lung, which was further characterised as a monocyte/myeloid-rich vasculitis, and occurred along with an influx of macrophage/monocyte-lineage cells into the pulmonary parenchyma. In addition, stereotyped abnormal reticulo-endothelial responses, including excessive reactive plasmacytosis and iron-laden macrophages, were present and dissociated from viral presence in lymphoid tissues. Conclusions: Tissue-specific immunopathology occurs in Covid-19, implicating a significant component of immune-mediated, virus-independent immunopathology as a primary mechanism in severe disease. Our data highlight novel immunopathological mechanisms, and validate ongoing and future efforts to therapeutically target aberrant macrophage and plasma cell responses as well as promoting pathogen tolerance in Covid-19.Publisher PDFPeer reviewe

Interpreting lymphocyte classification from Hoechst stained slides with deep learning

Funding: This work is supported by the Industrial Centre for AI Research in Digital Diagnostics (iCAIRD) which is funded by Innovate UK on behalf of UK Research and Innovation (UKRI) [project number: 104690].Multiplex immunofluorescence and immunohistochemistry benefit patients by allowing cancer pathologists to identify proteins expressed on the surface of cells. This enables cell classification, better understanding of the tumour microenvironment, and more accurate diagnoses, prognoses, and tailored immunotherapy based on the immune status of individual patients. However, these techniques are expensive. They are time consuming processes which require complex staining and imaging techniques by expert technicians. Hoechst staining is far cheaper and easier to perform, but is not typically used as it binds to DNA rather than to the proteins targeted by immunofluorescence techniques. In this work we show that through the use of deep learning it is possible to identify an immune cell subtype without immunofluorescence. We train a deep convolutional neural network to identify cells expressing the T lymphocyte marker CD3 from Hoechst 33342 stained tissue only. CD3 expressing cells are often used in key prognostic metrics such as assessment of immune cell infiltration, and by identifying them without the need for costly immunofluorescence, we present a promising new approach to cheaper prediction and improvement of patient outcomes. We also show that by using deep learning interpretability techniques, we can gain insight into the previously unknown morphological features which make this possible.Publisher PDFPeer reviewe

HoechstGAN:virtual lymphocyte staining using generative adversarial networks

The presence and density of specific types of immune cells are important to understand a patient’s immune response to cancer. However, immunofluorescence staining required to identify T cell subtypes is expensive, time-consuming, and rarely performed in clinical settings. We present a framework to virtually stain Hoechst images (which are cheap and widespread) with both CD3 and CD8 to identify T cell subtypes in clear cell renal cell carcinoma using generative adversarial networks. Our proposed method jointly learns both staining tasks, incentivising the network to incorporate mutually beneficial information from each task. We devise a novel metric to quantify the virtual staining quality, and use it to evaluate our method

Spatial analysis of NQO1 in non-small cell lung cancer shows its expression is independent of NRF1 and NRF2 in the tumor microenvironment

This work was funded in part by NuCana plc, Lothian NHS and the Industrial Centre for AI Research in Digital Diagnostics (iCAIRD), which is funded by Innovate UK on behalf of UK Research and Innovation (UKRI) [project number: 104690].Nuclear factor erythroid 2-related factor 1 (NFE2L1, NRF1) and nuclear factor erythroid 2-related factor 2 (NFE2L2, NRF2) are distinct oxidative stress response transcription factors, both of which have been shown to perform cytoprotective functions, modulating cell stress response and homeostasis. NAD(P)H:quinone oxidoreductase (NQO1) is a mutual downstream antioxidant gene target that catalyzes the two-electron reduction of an array of substrates, protecting against reactive oxygen species (ROS) generation. NQO1 is upregulated in non-small cell lung cancer (NSCLC) and is proposed as a predictive biomarker and therapeutic target. Antioxidant protein expression of immune cells within the NSCLC tumor microenvironment (TME) remains undetermined and may affect immune cell effector functions and survival outcomes. Multiplex immunofluorescence was performed to examine the co-localization of NQO1, NRF1 and NRF2 within the tumor and TME of 162 chemotherapy-naïve, early-stage NSCLC patients treated by primary surgical resection. This study demonstrates that NQO1 protein expression is high in normal, tumor-adjacent tissue and that NQO1 expression varies depending on the cell type. Inter and intra-patient heterogenous NQO1 expression was observed in lung cancer. Co-expression analysis showed NQO1 is independent of NRF1 and NRF2 in tumors. Density-based co-expression analysis demonstrated NRF1 and NRF2 double-positive expression in cancer cells is associated with improved overall survival.Publisher PDFPeer reviewe