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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to present with pulmonary and extra-pulmonary organ complications. In comparison with the 2009 pandemic (pH1N1), SARS-CoV-2 infection is likely to lead to more severe disease, with multi-organ effects, including cardiovascular disease. SARS-CoV-2 has been associated with acute and long-term cardiovascular disease, but the molecular changes govern this remain unknown.In this study, we investigated the landscape of cardiac tissues collected at rapid autopsy from SARS-CoV-2, pH1N1, and control patients using targeted spatial transcriptomics approaches. Although SARS-CoV-2 was not detected in cardiac tissue, host transcriptomics showed upregulation of genes associated with DNA damage and repair, heat shock, and M1-like macrophage infiltration in the cardiac tissues of COVID-19 patients. The DNA damage present in the SARS-CoV-2 patient samples, were further confirmed by γ−H2Ax immunohistochemistry. In comparison, pH1N1 showed upregulation of Interferon-stimulated genes (ISGs), in particular interferon and complement pathways, when compared with COVID-19 patients.These data demonstrate the emergence of distinct transcriptomic profiles in cardiac tissues of SARS-CoV-2 and pH1N1 influenza infection supporting the need for a greater understanding of the effects on extra-pulmonary organs, including the cardiovascular system of COVID-19 patients, to delineate the immunopathobiology of SARS-CoV-2 infection, and long term impact on health.

Gene-set analysis (GSA) dominates the functional interpretation of omics data and downstream hypothesis generation. Despite its ability to summarise thousands of measurements into semantically interpretable components, GSA often results in hundreds of significantly enriched gene-sets. However, summarisation and effective visualisation of GSA results to facilitate hypothesis generation is still lacking. While some webservers provide gene-set visualization tools, there is still a need for tools that can effectively summarize and guide exploration of GSA results. To enable versatility, webservers accept gene lists as input, however, none provide end-to-end solutions for emerging data types such as single-cell and spatial omics. Here, we present vissE.Cloud, a webserver for end-to-end gene-set analysis, offering gene-set summarisation and highly interactive visualisation. vissE.Cloud uses algorithms from our earlier R package vissE to summarise GSA results by identifying biological themes. We maintain versatility by allowing analysis of gene lists, as well as, analysis of raw single-cell and spatial omics data, including CosMx and Xenium data, making vissE.Cloud the first webserver to provide end-to-end gene-set analysis of sub-cellular localised spatial data. Structuring the results hierarchically allows swift interactive investigations of results at the gene, gene-set, and clusters level. vissE.Cloud is freely available at https://www.vissE.Cloud.

To gain a better understanding of the complexity of gene expression in normal and diseased tissues it is important to account for the spatial context and identity of cellin situ. State-of-the-art spatial profiling technologies, such as the Nanostring GeoMx Digital Spatial Profiler (DSP), now allow quantitative spatially resolved measurement of the transcriptome in tissues. However, the bioinformatics pipelines currently used to analyse GeoMx data often fail to successfully account for the technical variability within the data and the complexity of experimental designs, thus limiting the accuracy and reliability of subsequent analysis. Carefully designed quality control workflows, that include in-depth experiment-specific investigations into technical variation and appropriate adjustment for such variation can address this issue. Here we presentstandR, a R/Bioconductor package that enables an end-to-end analysis of GeoMx DSP data. With four case studies from previously published experiments, we demonstrate how the standR workflow can enhance the statistical power of GeoMx DSP data analysis and how application of standR enables scientists to develop in-depth insights into the biology of interest.

Antibodies targeting “immune checkpoints” have revolutionized cancer therapy by reactivating tumor-resident cytotoxic lymphocytes, primarily CD8+ T cells. Interest in targeting analogous pathways in other cytotoxic lymphocytes is growing. Natural killer (NK) cells are key to cancer immunosurveillance by eradicating metastases and driving solid tumor inflammation. NK-cell antitumor function is dependent on the cytokine IL15. Ablation of the IL15 signaling inhibitor CIS (Cish) enhances NK-cell antitumor immunity by increasing NK-cell metabolism and persistence within the tumor microenvironment (TME). The TME has also been shown to impair NK-cell fitness via the production of immunosuppressive transforming growth factor β (TGFβ), a suppression which occurs even in the presence of high IL15 signaling. Here, we identified an unexpected interaction between CIS and the TGFβ signaling pathway in NK cells. Independently, Cish- and Tgfbr2-deficient NK cells are both hyperresponsive to IL15 and hyporesponsive to TGFβ, with dramatically enhanced antitumor immunity. Remarkably, when both these immunosuppressive genes are simultaneously deleted in NK cells, mice are largely resistant to tumor development, suggesting that combining suppression of these two pathways might represent a novel therapeutic strategy to enhance innate anticancer immunity.

Official gene symbols (HGNC) for our 20 NK signature genes and a subset of the results leading to their inclusion during curation, in particular bulk RNA-seq differential expression results and comparison to T cells for single-cell RNA-seq data from Tirosh et al (2016). For further details please refer to the Materials and Methods. LM22: CIBERSORT LM22 lists; LM7: Tosolini et al LM7 list.

Supplementary Figures 1-9, & Supplementary Table 2.

Natural killer (NK) cell activity is essential for initiating antitumor responses and may be linked to immunotherapy success. NK cells and other innate immune components could be exploitable for cancer treatment, which drives the need for tools and methods that identify therapeutic avenues. Here, we extend our gene-set scoring method singscore to investigate NK cell infiltration by applying RNA-seq analysis to samples from bulk tumors. Computational methods have been developed for the deconvolution of immune cell types within solid tumors. We have taken the NK cell gene signatures from several such tools, then curated the gene list using a comparative analysis of tumors and immune cell types. Using a gene-set scoring method to investigate RNA-seq data from The Cancer Genome Atlas (TCGA), we show that patients with metastatic cutaneous melanoma have an improved survival rate if their tumor shows evidence of NK cell infiltration. Furthermore, these survival effects are enhanced in tumors that show higher expression of genes that encode NK cell stimuli such as the cytokine IL15. Using this signature, we then examine transcriptomic data to identify tumor and stromal components that may influence the penetrance of NK cells into solid tumors. Our results provide evidence that NK cells play a role in the regulation of human tumors and highlight potential survival effects associated with increased NK cell activity. Our computational analysis identifies putative gene targets that may be of therapeutic value for boosting NK cell antitumor immunity.

Supplementary Figure from TGFβ and CIS Inhibition Overcomes NK-cell Suppression to Restore Antitumor Immunity

Sox9 immunostaining pattern in a variety of Shh-MB genetic mouse models

S1. Sox 9 and Sox 2 immunoreactivity in the developing cerebellum

Medulloblastoma is the most common malignant pediatric brain tumor and there is an urgent need for molecularly targeted and subgroup-specific therapies. The stem cell factor SOX9, has been proposed as a potential therapeutic target for the treatment of Sonic Hedgehog medulloblastoma (SHH-MB) subgroup tumors, given its role as a downstream target of Hedgehog signaling and in functionally promoting SHH-MB metastasis and treatment resistance. However, the functional requirement for SOX9 in the genesis of medulloblastoma remains to be determined. Here we report a previously undocumented level of SOX9 expression exclusively in proliferating granule cell precursors (GCP) of the postnatal mouse cerebellum, which function as the medulloblastoma-initiating cells of SHH-MBs. Wild-type GCPs express comparatively lower levels of SOX9 than neural stem cells and mature astroglia and SOX9low GCP-like tumor cells constitute the bulk of both infant (Math1Cre:Ptch1lox/lox) and adult (Ptch1LacZ/+) SHH-MB mouse models. Human medulloblastoma single-cell RNA data analyses reveal three distinct SOX9 populations present in SHH-MB and noticeably absent in other medulloblastoma subgroups: SOX9+MATH1+ (GCP), SOX9+GFAP+ (astrocytes) and SOX9+MATH1+GFAP+ (potential tumor-derived astrocytes). To functionally address whether SOX9 is required as a downstream effector of Hedgehog signaling in medulloblastoma tumor cells, we ablated Sox9 using a Math1Cre model system. Surprisingly, targeted ablation of Sox9 in GCPs (Math1Cre:Sox9lox/lox) revealed no overt phenotype and loss of Sox9 in SHH-MB (Math1Cre:Ptch1lox/lox;Sox9lox/lox) does not affect tumor formation.Implications:Despite preclinical data indicating SOX9 plays a key role in SHH-MB biology, our data argue against SOX9 as a viable therapeutic target.

Most cancer deaths are due to metastasis, and epithelial-to-mesenchymal transition (EMT) plays a central role in driving cancer cell metastasis. EMT is induced by different stimuli, leading to different signaling patterns and therapeutic responses. TGFβ is one of the best-studied drivers of EMT, and many drugs are available to target this signaling pathway. A comprehensive bioinformatics approach was employed to derive a signature for TGFβ-induced EMT which can be used to score TGFβ-driven EMT in cells and clinical specimens. Considering this signature in pan-cancer cell and tumor datasets, a number of cell lines (including basal B breast cancer and cancers of the central nervous system) show evidence for TGFβ-driven EMT and carry a low mutational burden across the TGFβ signaling pathway. Furthermore, significant variation is observed in the response of high scoring cell lines to some common cancer drugs. Finally, this signature was applied to pan-cancer data from The Cancer Genome Atlas to identify tumor types with evidence of TGFβ-induced EMT. Tumor types with high scores showed significantly lower survival rates than those with low scores and also carry a lower mutational burden in the TGFβ pathway. The current transcriptomic signature demonstrates reproducible results across independent cell line and cancer datasets and identifies samples with strong mesenchymal phenotypes likely to be driven by TGFβ.Implications: The TGFβ-induced EMT signature may be useful to identify patients with mesenchymal-like tumors who could benefit from targeted therapeutics to inhibit promesenchymal TGFβ signaling and disrupt the metastatic cascade. Mol Cancer Res; 15(5); 619–31. ©2017 AACR.

Medulloblastoma and granule cell precursor Gli1 target genes

S3. Sox9 expression quantification

GFAPCre:Sox9lox/lox mice are not viable

Expanded and additional figures supporting this manuscript.

Detailed description of computational methods used in this manuscript.

Expanded and additional tables supporting this manuscript.

S4. Single cell sequencing data analysis

This table presents the Top 10 most enriched KEGG pathways identified from the panel of miRNAs regulated by claudin-2, along with their enrichment score and p-value.

Figure S1 shows the delineation of the tumor in MRI images.

Supplementary Methods and Data- Changes are unmarked

The recognition of the immune system as a key component of the tumor microenvironment (TME) led to promising therapeutics. Because such therapies benefit only subsets of patients, understanding the activities of immune cells in the TME is required. Eosinophils are an integral part of the TME especially in mucosal tumors. Nonetheless, their role in the TME and the environmental cues that direct their activities are largely unknown. We report that breast cancer lung metastases are characterized by resident and recruited eosinophils. Eosinophil recruitment to the metastatic sites in the lung was regulated by G protein–coupled receptor signaling but independent of CCR3. Functionally, eosinophils promoted lymphocyte-mediated antitumor immunity. Transcriptome and proteomic analyses identified the TME rather than intrinsic differences between eosinophil subsets as a key instructing factor directing antitumorigenic eosinophil activities. Specifically, TNFα/IFNγ–activated eosinophils facilitated CD4+ and CD8+ T-cell infiltration and promoted antitumor immunity. Collectively, we identify a mechanism by which the TME trains eosinophils to adopt antitumorigenic properties, which may lead to the development of eosinophil-targeted therapeutics.Significance:These findings demonstrate antitumor activities of eosinophils in the metastatic tumor microenvironment, suggesting that harnessing eosinophil activity may be a viable clinical strategy in patients with cancer.

Legends describing the supplementary figures

This file contains all supplemental Figures, as well as legends for both Supplemental Figures and Supplemental Tables, as well as Supplemental methods and associated references

Purpose: Bioinformatics analysis followed by in vivo studies in patient-derived xenograft (PDX) models were used to identify and validate CDK 4/6 inhibition as an effective therapeutic strategy for medulloblastoma, particularly group 3 MYC-amplified tumors that have the worst clinical prognosis.Experimental Design: A protein interaction network derived from a Sleeping Beauty mutagenesis model of medulloblastoma was used to identify potential novel therapeutic targets. The top hit from this analysis was validated in vivo using PDX models of medulloblastoma implanted subcutaneously in the flank and orthotopically in the cerebellum of mice.Results: Informatics analysis identified the CDK4/6/CYCLIN D/RB pathway as a novel “druggable” pathway for multiple subgroups of medulloblastoma. Palbociclib, a highly specific inhibitor of CDK4/6, was found to inhibit RB phosphorylation and cause G1 arrest in PDX models of medulloblastoma. The drug caused rapid regression of Sonic hedgehog (SHH) and MYC-amplified group 3 medulloblastoma subcutaneous tumors and provided a highly significant survival advantage to mice bearing MYC-amplified intracranial tumors.Conclusions: Inhibition of CDK4/6 is potentially a highly effective strategy for the treatment of SHH and MYC-amplified group 3 medulloblastoma. Clin Cancer Res; 23(19); 5802–13. ©2017 AACR.

Posttreatment recurrence of colorectal cancer, the third most lethal cancer worldwide, is often driven by a subpopulation of cancer stem cells (CSC). The tight junction (TJ) protein claudin-2 is overexpressed in human colorectal cancer, where it enhances cell proliferation, colony formation, and chemoresistance in vitro. While several of these biological processes are features of the CSC phenotype, a role for claudin-2 in the regulation of these has not been identified. Here, we report that elevated claudin-2 expression in stage II/III colorectal tumors is associated with poor recurrence-free survival following 5-fluorouracil–based chemotherapy, an outcome in which CSCs play an instrumental role. In patient-derived organoids, primary cells, and cell lines, claudin-2 promoted colorectal cancer self-renewal in vitro and in multiple mouse xenograft models. Claudin-2 enhanced self-renewal of ALDHHigh CSCs and increased their proportion in colorectal cancer cell populations, limiting their differentiation and promoting the phenotypic transition of non-CSCs toward the ALDHHigh phenotype. Next-generation sequencing in ALDHHigh cells revealed that claudin-2 regulated expression of nine miRNAs known to control stem cell signaling. Among these, miR-222-3p was instrumental for the regulation of self-renewal by claudin-2, and enhancement of this self-renewal required activation of YAP, most likely upstream from miR-222-3p. Taken together, our results indicate that overexpression of claudin-2 promotes self-renewal within colorectal cancer stem-like cells, suggesting a potential role for this protein as a therapeutic target in colorectal cancer.Significance: Claudin-2-mediated regulation of YAP activity and miR-222-3p expression drives CSC renewal in colorectal cancer, making it a potential target for therapy. Cancer Res; 78(11); 2925–38. ©2018 AACR.

Spatial molecular technologies have revolutionised the study of disease microenvironments by providing spatial context to tissue heterogeneity. Recent spatial technologies are increasing the throughput and spatial resolution of measurements, resulting in larger datasets. The added spatial dimension and volume of measurements poses an analytics challenge that has, in the short-term, been addressed by adopting methods designed for the analysis of single-cell RNA-seq data. Though these methods work well in some cases, not all necessarily translate appropriately to spatial technologies. A common assumption is that total sequencing depth, also known as library size, represents technical variation in single-cell RNA-seq technologies, and this is often normalised out during analysis. Through analysis of several different spatial datasets, we noted that this assumption does not necessarily hold in spatial molecular data. To formally assess this, we explore the relationship between library size and independently annotated spatial regions, across 23 samples from 4 different spatial technologies with varying throughput and spatial resolution. We found that library size confounded biology across all technologies, regardless of the tissue being investigated. Statistical modelling of binned total transcripts shows that tissue region is strongly associated with library size across all technologies, even after accounting for cell density of the bins. Through a benchmarking experiment, we show that normalising out library size leads to sub-optimal spatial domain identification using common graph-based clustering algorithms. On average, better clustering was achieved when library size effects were not normalised out explicitly, especially with data from the newer sub-cellular localised technologies. Taking these results into consideration, we recommend that spatial data should not be specifically corrected for library size prior to analysis unless strongly motivated. We also emphasise that spatial data are different to single-cell RNA-seq and care should be taken when adopting algorithms designed for single cell data.

Mutations in genes encoding general transcription factors cause neurological disorders. Despite clinical prominence, the consequences of defects in the basal transcription machinery during brain development are unclear. We found that loss of the TATA-box binding protein-associated factor TAF8, a component of the general transcription factor TFIID, in the developing central nervous system affected the expression of many, but notably not all genes. Taf8 deletion caused apoptosis, unexpectedly restricted to forebrain regions. Nuclear levels of the transcription factor p53 were elevated in the absence of TAF8, as were the mRNAs of the pro-apoptotic p53 target genes Noxa, Puma and Bax. The cell death in Taf8 forebrain regions was completely rescued by additional loss of p53, but Taf8 and p53 brains failed to initiate a neuronal expression program. Taf8 deletion caused aberrant transcription of promoter regions and splicing anomalies. We propose that TAF8 supports the directionality of transcription and co-transcriptional splicing, and that failure of these processes causes p53-induced apoptosis of neuronal cells in the developing mouse embryo. [Image: see text]

Background Medulloblastoma (MB) is a malignant tumour of the cerebellum which can be classified into four major subgroups based on gene expression and genomic features. Single-cell transcriptome studies have defined the cellular states underlying each MB subgroup; however, the spatial organisation of these diverse cell states and how this impacts response to therapy remains to be determined. Methods Here, we used spatially resolved transcriptomics to define the cellular diversity within a sonic hedgehog (SHH) patient-derived model of MB and show that cells specific to a transcriptional state or spatial location are pivotal for CDK4/6 inhibitor, Palbociclib, treatment response. We integrated spatial gene expression with histological annotation and single-cell gene expression data from MB, developing an analysis strategy to spatially map cell type responses within the hybrid system of human and mouse cells and their interface within an intact brain tumour section. Results We distinguish neoplastic and non-neoplastic cells within tumours and from the surrounding cerebellar tissue, further refining pathological annotation. We identify a regional response to Palbociclib, with reduced proliferation and induced neuronal differentiation in both treated tumours. Additionally, we resolve at a cellular resolution a distinct tumour interface where the tumour contacts neighbouring mouse brain tissue consisting of abundant astrocytes and microglia and continues to proliferate despite Palbociclib treatment. Conclusions Our data highlight the power of using spatial transcriptomics to characterise the response of a tumour to a targeted therapy and provide further insights into the molecular and cellular basis underlying the response and resistance to CDK4/6 inhibitors in SHH MB.

PurposeRobust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness.MethodsWe conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients.ResultsWe show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients.ConclusionThese data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.

Hairy cell leukaemia (HCL) is a rare CD20+ B cell malignancy characterised by rare “hairy” B cells and extensive bone marrow (BM) infiltration. Frontline treatment with the purine analogue cladribine (CDA) results in a highly variable response duration. We hypothesised that analysis of the BM tumour microenvironment would identify prognostic biomarkers of response to CDA. HCL BM immunology pre and post CDA treatment and healthy controls were analysed using Digital Spatial Profiling to assess the expression of 57 proteins using an immunology panel. A bioinformatics pipeline was developed to accommodate the more complex experimental design of a spatially resolved study. Treatment with CDA was associated with the reduction in expression of HCL tumour markers (CD20, CD11c) and increased expression of myeloid markers (CD14, CD68, CD66b, ARG1). Expression of HLA-DR, STING, CTLA4, VISTA, OX40L were dysregulated pre- and post-CDA. Duration of response to treatment was associated with greater reduction in tumour burden and infiltration by CD8 T cells into the BM post-CDA. This is the first study to provide a high multiplex analysis of HCL BM microenvironment demonstrating significant immune dysregulation and identify biomarkers of response to CDA. With validation in future studies, prospective application of these biomarkers could allow early identification and increased monitoring in patients at increased relapse risk post CDA.

The recognition of the immune system as a key component of the tumor microenvironment (TME) led to promising therapeutics. Because such therapies benefit only subsets of patients, understanding the activities of immune cells in the TME is required. Eosinophils are an integral part of the TME especially in mucosal tumors. Nonetheless, their role in the TME and the environmental cues that direct their activities are largely unknown. We report that breast cancer lung metastases are characterized by resident and recruited eosinophils. Eosinophil recruitment to the metastatic sites in the lung was regulated by G protein–coupled receptor signaling but independent of CCR3. Functionally, eosinophils promoted lymphocyte-mediated antitumor immunity. Transcriptome and proteomic analyses identified the TME rather than intrinsic differences between eosinophil subsets as a key instructing factor directing antitumorigenic eosinophil activities. Specifically, TNFα/IFNγ–activated eosinophils facilitated CD4+ and CD8+ T-cell infiltration and promoted antitumor immunity. Collectively, we identify a mechanism by which the TME trains eosinophils to adopt antitumorigenic properties, which may lead to the development of eosinophil-targeted therapeutics. Significance: These findings demonstrate antitumor activities of eosinophils in the metastatic tumor microenvironment, suggesting that harnessing eosinophil activity may be a viable clinical strategy in patients with cancer.

Background Medulloblastoma (MB) is the most common malignant paediatric brain tumour and a leading cause of cancer-related mortality and morbidity. Existing treatment protocols are aggressive in nature resulting in significant neurological, intellectual and physical disabilities for the children undergoing treatment. Thus, there is an urgent need for improved, targeted therapies that minimize these harmful side effects. Methods We identified candidate drugs for MB using a network-based systems-pharmacogenomics approach: based on results from a functional genomics screen, we identified a network of interactions implicated in human MB growth regulation. We then integrated drugs and their known mechanisms of action, along with gene expression data from a large collection of medulloblastoma patients to identify drugs with potential to treat MB. Results Our analyses identified drugs targeting CDK4, CDK6 and AURKA as strong candidates for MB; all of these genes are well validated as drug targets in other tumour types. We also identified non-WNT MB as a novel indication for drugs targeting TUBB, CAD, SNRPA, SLC1A5, PTPRS, P4HB and CHEK2. Based upon these analyses, we subsequently demonstrated that one of these drugs, the new microtubule stabilizing agent, ixabepilone, blocked tumour growth in vivo in mice bearing patient-derived xenograft tumours of the Sonic Hedgehog and Group 3 subtype, providing the first demonstration of its efficacy in MB. Conclusions Our findings confirm that this data-driven systems pharmacogenomics strategy is a powerful approach for the discovery and validation of novel therapeutic candidates relevant to MB treatment, and along with data validating ixabepilone in PDX models of the two most aggressive subtypes of medulloblastoma, we present the network analysis framework as a resource for the field.

Intellectual disability (ID) and autism spectrum disorder (ASD) are the most common neurodevelopmental disorders and are characterized by substantial impairment in intellectual and adaptive functioning, with their genetic and molecular basis remaining largely unknown. Here, we identify biallelic variants in the gene encoding one of the Elongator complex subunits, ELP2, in patients with ID and ASD. Modelling the variants in mice recapitulates the patient features, with brain imaging and tractography analysis revealing microcephaly, loss of white matter tract integrity and an aberrant functional connectome. We show that the Elp2 mutations negatively impact the activity of the complex and its function in translation via tRNA modification. Further, we elucidate that the mutations perturb protein homeostasis leading to impaired neurogenesis, myelin loss and neurodegeneration. Collectively, our data demonstrate an unexpected role for tRNA modification in the pathogenesis of monogenic ID and ASD and define Elp2 as a key regulator of brain development.

Plant proteins that are secreted without a classical signal peptide leader sequence are termed leaderless secretory proteins (LSPs) and are implicated in both plant development and (a)biotic stress responses. In plant proteomics experimental workflows, identification of LSPs is hindered by the possibility of contamination from other subcellar compartments upon purification of the secretome. Applying machine learning algorithms to predict LSPs in plants is also challenging due to the rarity of experimentally validated examples for training purposes. This work attempts to address this issue by establishing criteria for identifying potential plant LSPs based on experimental observations and training random forest classifiers on the putative datasets. The resultant plant protein database LSPDB and bioinformatic prediction tools LSPpred and SPLpred are available at lsppred.lspdb.org. The LSPpred and SPLpred modules are internally validated on the training dataset, with false positives controlled at 5%, and are also able to classify the limited number of established plant LSPs (SPLpred (3/4, LSPpred 4/4). Until such time as a larger set of bona fide (independently experimentally validated) LSPs is established using imaging technologies (light/fluorescence/electron microscopy) to confirm sub-cellular location, these tools represent a bridging method for predicting and identifying plant putative LSPs for subsequent experimental validation.

Cancer cells invoke phenotypic plasticity programs to drive disease progression and evade chemotherapeutic insults, yet until now there have been no validated clinical therapies targeting this process. Here, we identify a phenotypic plasticity signature associated with poor survival in basal/triple-negative breast cancer, in which androgen signalling is prominent. We establish that anti-androgen therapies block cancer stem cell function and prevent chemotherapy-induced emergence of new cancer stem cells. In particular, the anti-androgen agent seviteronel synergizes with chemotherapy to improve chemotherapeutic inhibition of primary and metastatic tumour growth and prevent the emergence of chemotherapy-resistant disease. We validate cytoplasmic AR expression as a clinical phenotypic plasticity biomarker that predicts poor survival and poor response to chemotherapy, and positive response to seviteronel plus chemotherapy. This new targeted combination therapy validates modulating phenotypic plasticity as an effective strategy to prevent and treat chemotherapy-resistant cancers with transformative clinical potential.STATEMENT OF SIGNIFICANCEThere are currently no curative therapies for patients with chemotherapy-resistant cancer. We demonstrate that modulating phenotypic plasticity prevents the emergence of chemotherapy-resistant disease in triple-negative breast cancer. This represents the first known validated clinical therapy leveraging phenotypic plasticity. Moreover, we identify a highly effective anti-androgen drug and a biomarker to select and treat patients best-suited to this new therapy. A clinical trial is underway (NCT04947189).SUMMARY SENTENCEBlocking phenotypic plasticity is an effective targeted therapeutic strategy to treat cance

Patients withIn this study, we characterized the treatment-naive immune context in patients withIn single-cell data,In conclusion, treatment-naive

Functional analysis of high throughput experiments using pathway analysis is now ubiquitous. Though powerful, these methods often produce thousands of redundant results owing to knowledgebase redundancies upstream. This scale of results hinders extensive exploration by biologists and often leads to investigator biases due to previous knowledge and expectations. To address this issue, we present vissE, a flexible network-based analysis method that summarises redundancies into biological themes and provides various analytical modules to characterise and visualise them with respect to the underlying data, thus providing a comprehensive view of the biological system. We demonstrate vissE’s versatility by applying it to three different technologies: bulk, single-cell and spatial transcriptomics. Applying vissE to a factor analysis of a breast cancer spatial transcriptomic data, we identified stromal phenotypes that support tumour dissemination. Its adaptability allows vissE to enhance all existing gene-set enrichment and pathway analysis workflows, removing investigator bias from molecular discovery.Abstract Figure

B lymphoid development is initiated by the differentiation of hematopoietic stem cells into lineage committed progenitors, ultimately generating mature B cells. This highly regulated process generates clonal immunological diversity via recombination of immunoglobulin V, D and J gene segments. While several transcription factors that control B cell development and V(D)J recombination have been defined, how these processes are initiated and coordinated into a precise regulatory network remains poorly understood. Here, we show that the transcription factor ETS Related Gene (Erg) is essential for early B lymphoid differentiation. Erg initiates a transcriptional network involving the B cell lineage defining genes, Ebf1 and Pax5, which directly promotes expression of key genes involved in V(D)J recombination and formation of the B cell receptor. Complementation of Erg deficiency with a productively rearranged immunoglobulin gene rescued B lineage development, demonstrating that Erg is an essential and stage-specific regulator of the gene regulatory network controlling B lymphopoiesis., B cell development is tightly regulated in a stepwise manner to ensure proper generation of repertoire diversity via somatic gene rearrangements. Here, the authors show that a transcription factor, Erg, functions at the earliest stage to critically control two downstream factors, Ebf1 and Pax5, for modulating this gene rearrangement process.

Antibodies targeting “immune checkpoints” have revolutionized cancer therapy by reactivating tumor-resident cytotoxic lymphocytes, primarily CD8+ T cells. Interest in targeting analogous pathways in other cytotoxic lymphocytes is growing. Natural killer (NK) cells are key to cancer immunosurveillance by eradicating metastases and driving solid tumor inflammation. NK-cell antitumor function is dependent on the cytokine IL15. Ablation of the IL15 signaling inhibitor CIS (Cish) enhances NK-cell antitumor immunity by increasing NK-cell metabolism and persistence within the tumor microenvironment (TME). The TME has also been shown to impair NK-cell fitness via the production of immunosuppressive transforming growth factor β (TGFβ), a suppression which occurs even in the presence of high IL15 signaling. Here, we identified an unexpected interaction between CIS and the TGFβ signaling pathway in NK cells. Independently, Cish- and Tgfbr2-deficient NK cells are both hyperresponsive to IL15 and hyporesponsive to TGFβ, with dramatically enhanced antitumor immunity. Remarkably, when both these immunosuppressive genes are simultaneously deleted in NK cells, mice are largely resistant to tumor development, suggesting that combining suppression of these two pathways might represent a novel therapeutic strategy to enhance innate anticancer immunity.