Biology subjects

Wynne, K.

Publications and source records attributed to Wynne, K..

At least 19 recordsLinked to original sources

bioRxiv2026

SMAD3-driven cell state transitions underpin immunoresistance in bladder cancer

Despite the clinical success of anti-PD-1/PD-L1 immunotherapy in a subset of patients with high-risk bladder cancer (BLCA), most tumors remain refractory to treatment. We hypothesized that immunotherapy resistance is encoded within the intrinsic signaling state of BLCA cells and arises through specific cell-state transitions that precede therapeutic exposure. To test this hypothesis, we applied a cell State Transition Assessment and Regulation (cSTAR) framework to identify key signaling modules and aberrant causal network connections that (i) drive oncogenic progression and acquisition of aggressive phenotypes and (ii) govern BLCA cell susceptibility to T cell-mediated cytotoxicity. cSTAR analysis identified TGF{beta}/SMAD3 signaling as the principal driver of both oncogenic transformation and immunoresistance in BLCA cells. Inhibiting SMAD3 sensitized BLCA cells to PD-1-expressing Jurkat cells and primary human CD4+ T cell-mediated cytotoxicity through suppression of autophagy and activation of multiple cell death pathways. By integrating cell state transition analysis with functional immune co-culture assays, our work demonstrates that tumor cell state transitions control sensitivity to T cell killing, complementing established immune-intrinsic mechanisms of immunotherapy response.

systems biology↗

bioRxiv2026

Barcoding biology: Chemotype predicts variation in genotype, physiology, and stress response

Predicting biological responses to perturbations such as stress, nutrition, or pharmaceuticals could transform healthcare and biosciences. The task is challenging because complex interactions among many factors interactively drive biological variation, and thereby alter responses. However, metabolism integrates these drivers of variation, suggesting that emergent biological states may be reflected in aggregate chemical states. We define such states as chemotypes and test their predictive utility. Using Fourier-transform infrared (FTIR) spectroscopy coupled with machine learning in Drosophila melanogaster, we show that chemotypes serve as proxies for biological variation driven by sex, genotype, nutrition and age, and - critically - predict among-population variation in stress response. These findings indicate that chemotypes provide a computable and integrative representation of organismal biology, predicting genotype, phenotype, and response to perturbation.

systems biology↗

bioRxiv2026

SS18-SSX co-opts P300 to sustain oncogenic transcription independent of SWI/SNF activity

Synovial sarcoma is driven by the SS18-SSX fusion oncoprotein, which has been assumed to promote tumorigenesis through its incorporation into the SWI/SNF chromatin remodeling complexes. Accordingly, therapeutic efforts have focused on targeting SS18-SSX containing SWI/SNF assemblies, yet these approaches have produced limited clinical benefit. Here, we demonstrate that SS18-SSX sustains oncogenic transcription independent of SWI/SNF activity. Despite efficient degradation and dismantling of SWI/SNF complexes, fusion occupancy at target loci and associated gene expression programs remain largely intact. Instead, we identify the acetyltransferase P300 as an essential co-factor supporting SS18-SSX chromatin binding and transcriptional activation. Targeting P300 displaces the fusion from chromatin, suppresses its transcriptional output, compromising synovial sarcoma viability. Notably, dual PROTAC mediated degradation of P300 and SWI/SNF produces strong synergistic effects, broadly disrupting SS18-SSX localization and function. These findings redefine the mechanistic basis of synovial sarcoma and reveal a mechanistically anchored therapeutic strategy for targeting its core oncogenic driver.

cancer biology↗

bioRxiv2026

Peptidomics Mapping of Proteolysis Highlights Triple Activation of Sprouted Seeds by Germination, Homogenisation and Species Mixture.

We investigated how seed proteolysis was enhanced by germination, by subsequent homogenisation (disrupting sprout compartments), and by co-incubation of homogenates from different species. Mass spectrometry of released peptides tracked proteolytic signatures from chickpea, lentil, mung and broccoli proteins, in soaked seeds, in sprouted seeds, and after sprout homogenisation followed by incubation alone or in mixture with other sprouts. The proteolytic signatures differed markedly among the four species, and in the different treatment conditions. After homogenisation, legumain-like cleavage (after asparagine) increased in lentil, and proline-rich peptides increased in broccoli. For co-incubated homogenised sprouts, each species homogenate significantly contributed 6 to 57% of proteolytic patterns in peptides of other species, with chickpea and broccoli homogenates notably releasing metabolic protein peptides from mung and lentil. Thus, germination, homogenisation and homogenate species mixtures can each contribute to proteolysis of seed peptides, potentially increasing digestibility and reducing allergenicity. HIGHLIGHTSO_LIProteolysis motifs in soaked seeds and sprouts very diverse among species C_LIO_LISeed germination proteolysis altered by homogenisation C_LIO_LISeed germination proteolysis altered by co-incubation of different species C_LIO_LIFoods based on homogenised sprout mixtures may release more digestible peptides C_LI

bioinformatics↗

bioRxiv2025

A structure-based modelling approach identifies effective drug combinations for RAS-mutant acute myeloid leukemia

Mutations activating RAS/RAF/MEK/ERK signaling are associated with poor outcome in acute myeloid leukemia (AML), but therapeutic targeting of this pathway is challenging. Here, we employ a structure-based, dynamic RAS pathway model to successfully predict RAF inhibitor (RAFi) combinations which synergistically suppress ERK signaling in RAS-mutant AML. Our in silico models predicted therapeutic synergy of two iterations of conformation-specific RAF inhibitors: Type I[1/2] + Type II and Type I + Type II. Predictions were validated in vitro in AML cell lines and patient samples, with synergy verified by the Loewe Additivity model. Lifirafenib (Type II) + encorafenib (Type I[1/2]) was highly synergistic against both NRAS- and KRAS-mutant lines, while synergy of lifirafenib + SB590885 (Type I) was specific to NRAS-mutants. Immunoblotting confirmed that combination efficacy correlated strongly with decreased RAS pathway activation. Leveraging the pharmacokinetic predictions of our in silico model, both combinations were then assessed in a pre-clinical NRAS-mutant AML patient-derived xenograft (PDX) model, showing significantly improved leukaemia growth delay and event-free survival compared with single agent approaches. Assessment of leukemia burden in bone marrow and spleen during treatment further showed site-specific efficacy against circulating and spleen-resident blasts for both combinations. In summary, we report that our structure based-modelling approach can effectively identify novel, non-obvious, and well-tolerated RAFi combinations that are highly effective against in vitro and in vivo models, thereby suggesting alternative potential therapeutic strategies for high-risk RAS-mutant AML.

cancer biology↗

bioRxiv2024

Diphenyleneiodonium chloride inhibits MYCN-amplified neuroblastoma by targeting MYCN induced mitochondrial alterations

High-risk neuroblastoma is one of the most lethal childhood cancers. Half of these tumors are driven by MYCN gene amplification (MNA). Despite intensive chemo- and radiotherapy, only 40% of patients survive, and they often suffer from severe long-term side effects of these genotoxic treatments. Thus, new therapies are needed that are less toxic and more efficacious. Here, we identified diphenyleneiodonium (DPI) as a tool compound that preferentially targets MNA neuroblastoma. Using proteomic assays we investigated the DPI mode of action, finding that DPI induces the proteasomal degradation of MYCN and could reverse some alterations induced by high levels of MYCN. These include profound changes in the expression of proteins participating in the mitochondrial electron transport chain. Metabolic and biological assays suggested that alterations in mitochondrial function and the associated production of reactive oxygen species (ROS) are critical DPI targets in the context of MNA. DPI reduced the survival, and malignant transformation of neuroblastoma across a panel of cell lines at clinically achievable concentrations. DPI also shrank tumors and prevented metastatic spread in zebrafish models of MYCN-driven neuroblastoma. These findings suggest that processes impacted by complex I inhibitors could be valuable new targets for the development of non-genotoxic drugs against high-risk MNA neuroblastoma. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/619268v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@167e953org.highwire.dtl.DTLVardef@10749e4org.highwire.dtl.DTLVardef@1842598org.highwire.dtl.DTLVardef@c05d82_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Paralog protein compensation preserves protein-protein interaction networks following gene loss in cancer

Proteins operate within dense interconnected networks, where interactions are necessary both for stabilising proteins and for enabling them to execute their molecular functions. Remarkably, protein-protein interaction networks operating within tumour cells continue to function despite widespread genetic perturbations. Previous work has demonstrated that tumour cells tolerate perturbations of paralogs better than perturbations of singleton genes, but the mechanisms behind this genetic robustness remains poorly understood. Here, we systematically profile the proteomic response of tumours and tumour cell lines to gene loss. We find many examples of active compensation, where deletion of one paralog results in increased abundance of another, and collateral loss, where deletion of one paralog results in reduced abundance of another. Compensation is enriched among sequence-similar paralog pairs that are central in the protein-protein interaction network and widely conserved across evolution. Compensation is also significantly more likely to be observed for gene pairs with a known synthetic lethal relationship. Our results support a model whereby loss of one gene results in increased protein abundance of its paralog, stabilising the protein-protein interaction network. Consequently, tumour cells may become dependent on the paralog for survival, creating potentially targetable vulnerabilities.

systems biology↗

bioRxiv2024

MYCN inhibits TrkC-mediated differentiation in neuroblastoma cells via disruption of the PKA signalling pathway

Neuroblastoma is a complex paediatric cancer with a spectrum of clinical outcomes ranging from spontaneous regression to aggressive metastatic disease. Low-risk patients achieve over 90% survival with no or minimal treatment, while high-risk patients face less than 50% survival despite intensive multimodal therapy. Half of the high-risk cases harbour amplification of the MYCN oncogene. In addition to MYCN status, Trk receptors have also been linked to prognosis. TrkA expression is seen with low-risk cases while TrkB expression often occurs in high-risk MYCN-amplified NB. While TrkA and TrkB are well studied in NB, the role of TrkC in neuroblastoma genesis is not clear. Therefore, this study investigates the interplay between MYCN status and NT-3/TrkC signalling in neuroblastoma. Using a panel of neuroblastoma cell lines with varying MYCN levels, we found that TrkC activation leads to neuronal differentiation of MYCN non-amplified cells, whereas it promotes proliferation of MYCN-amplified cells. Temporal phosphoproteomics revealed differential activation of the PKA pathway, which was crucial for TrkC-mediated differentiation. Manipulating the PKA pathway altered cell fate outcomes, underscoring its role. In MYCN-amplified cells, MYCN knockdown increased PKA and CREB activity, shifting the phenotype towards differentiation. Analysis of neuroblastoma patient data showed lower expression of PKA pathway genes in MYCN-amplified tumours. Additionally, miR-221, upregulated by MYCN, was identified as a suppressor of the PKA/CREB pathway. These findings highlight the context-dependent nature of NT-3/TrkC signalling influenced by MYCN; and suggest therapeutic potential in targeting the PKA pathway to induce differentiation of high-risk MYCN-amplified neuroblastoma.

cancer biology↗

bioRxiv2024

OXPHOS TARGETING OF MYCN-AMPLIFIED NEUROBLASTOMA

SummaryHigh risk - neuroblastoma (HR-NB) is a pediatric solid tumor with high lethality. Half of HR-NB are driven by MYCN gene amplification (MNA). These HR-NBs require high dosage chemotherapy and often relapse. Moreover, current therapies can cause severe long-term side effects and new therapies are urgently needed. This study investigates a novel therapeutic approach targeting the metabolic vulnerabilities of MNA NB cells. We discovered that Diphenyleneiodonium chloride (DPI), an inhibitor of flavoprotein enzymes and mitochondrial complex I, synergizes with mitoquinone mesylate (MitoQ), a mitochondria-targeted antioxidant in 2D and 3D in vitro models of NB. Similarly to DPI, MitoQ affects MNA cells in a MYCN-dependent fashion, being more toxic when MYCN levels are high. Furthermore, low nanomolar concentrations of MitoQ significantly decrease MYCN protein expression and induce differentiation of MNA cells. The DPI and MitoQ combination further synergizes with vincristine, a chemotherapeutic agent used in NB treatment. Phosphoproteomics and proteomics analysis suggests that the drug combination induces MNA NB cell death by arresting the cell cycle and inhibiting oxidative phosphorylation (OXPHOS) in the mitochondria. Thus, interference with mitochondrial metabolism may represent an effective strategy to enhance the activity of chemotherapeutic drugs in MNA-NB.

cancer biology↗

bioRxiv2023

Specific cPRC1 complexes are co-opted to mediate oncogenic gene repression in diffuse midline glioma

Diffuse midline glioma (DMG) is a fatal childhood brain tumour characterised primarily by mutant histone H3 (H3K27M). H3K27M causes a global reduction in Polycomb Repressive Complex 2 (PRC2)-mediated H3K27me3 by inhibiting PRC2 enzymatic activity. Paradoxically, PRC2 is essential in DMG tumour cells where residual complex activity is required for oncogenic gene repression, although the molecular mechanisms acting downstream of PRC2 in this context are poorly understood. Here, weve discovered this oncogenic gene repression is mediated by specific canonical PRC1 (cPRC1) formations. By combining CRISPR screening, biochemical and chromatin mapping approaches with functional perturbations we show that cPRC1 complexes containing CBX4 and PCGF4 drive oncogenic gene repression downstream of H3K27me3 in DMG cells. Remarkably, the altered H3K27me3 modification landscape characteristic of these tumours rewires the distribution of cPRC1 complexes on chromatin. CBX4 and PCGF4 containing cPRC1 accumulate at sites of H3K27me3 while other cPRC1 formations are displaced. Despite accounting for <5% of cPRC1 complexes in DMG, CBX4/PCGF4-containing complexes predominate as gene repressors. Our findings link the altered distribution of H3K27me3 with imbalanced cPRC1 function, promoting oncogenic gene repression in DMG cells, revealing new disease mechanisms and highlighting potential therapeutic opportunities in this incurable childhood brain tumour.

cancer biology↗

bioRxiv2023

Loss of Polycomb Repressive Complex 2 function causes asparaginase resistance in T-acute lymphoblastic leukemia through decreased WNT pathway activity

Loss-of-function mutations and deletions in core components of the epigenetic Polycomb Repressive Complex 2 (PRC2) are associated with poor prognosis and treatment resistance in T-acute lymphoblastic leukemia (T-ALL). We leveraged clinical mutational and transcriptional data to identify a functional link between PRC2 alterations and changes in WNT signaling pathway activity in leukemia cells. Computational integration of transcriptomic, proteomic and phosphoproteomic data from an isogenic T-ALL cellular model revealed reduced activity of the WNT-dependent stabilization of proteins (WNT/STOP) pathway in cells lacking core PRC2 factor EZH2. We discovered that PRC2 loss significantly reduced sensitivity to key T-ALL treatment asparaginase, and that this was mechanistically linked to increased cellular ubiquitination levels that bolstered leukemia cell asparagine reserves. We further found that asparaginase resistance in PRC2-depleted leukemic blasts could be mitigated by pharmaceutical proteasome inhibition, thereby providing a novel and clinically tractable means to tackle induction treatment failure in high-risk T-ALL.

cancer biology↗

bioRxiv2022

Kinase Suppressor of RAS 1 (KSR1) maintains the transformed phenotype of BRAFV600E mutant human melanoma cells

KSR1 is a scaffolding protein for the RAS-RAF-MEK-ERK pathway, which is one of the most frequently altered pathways in human cancers. Previous results have shown that KSR1 has a critical role in mutant RAS mediated transformation. Here, we examined the role of KSR1 in mutant BRAF transformation. We used CRISPR/Cas9 to knock out KSR1 in a BRAFV600E transformed melanoma cell line. KSR1 loss produced a complex phenotype characterized by impaired proliferation, cell cycle defects, decreased transformation, decreased invasive migration, increased cellular senescence, and increased apoptosis. To decipher this phenotype, we used a combination of proteomic ERK substrate profiling, global protein expression profiling, and biochemical validation assays. The results suggest that KSR1 directs ERK to phosphorylate substrates that have a critical role in ensuring cell survival. The results further indicate that KSR1 loss induces the activation of p38 Mitogen-Activated Protein Kinase (MAPK) and subsequent cell cycle aberrations and senescence. In summary, KSR1 function plays a key role in oncogenic BRAF transformation.

cancer biology↗

bioRxiv2022

Analysis of context-specific KRAS-effectors (sub)complexes in Caco-2 cells

Ras is a key switch controlling cell behavior. In the GTP-bound form, Ras interacts with numerous effectors in a mutually exclusive manner, where individual Ras-effectors are likely part of larger cellular (sub)complexes. The molecular details of these (sub)complexes and their alteration in specific contexts is not understood. Focusing on KRAS, we performed affinity purification (AP)-mass spectrometry (MS) experiments of exogenous expressed FLAG-KRAS WT and three oncogenic mutants ( genetic contexts) in the human Caco-2 cell line, each exposed to 11 different culture media ( culture contexts) that mimic conditions relevant in the colon and colorectal cancer. We identified four effectors present in complex with KRAS in all genetic and growth contexts ( context-general effectors). Seven effectors are found in KRAS complexes in only some contexts ( context-specific effectors). Analyzing all interactors in complex with KRAS per condition, we find that the culture contexts had a larger impact on interaction rewiring than genetic contexts. We investigated how changes in the interactome impact functional outcomes and created a shiny app for interactive visualization. We validated some of the functional differences in metabolism and proliferation. Finally, we used networks to evaluate how KRAS effectors are involved in the modulation of functions by random walk analyses of effector-mediated (sub)complexes. Altogether, our work shows the impact of environmental contexts on network rewiring, which provides insights into tissue-specific signaling mechanisms. This may also explain why KRAS oncogenic mutants may be causing cancer only in specific tissues despite KRAS being expressed in most cells and tissues.

systems biology↗

bioRxiv2022

Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra

Accurate prediction of mosquito population age structures can improve the evaluation of mosquito-targeted interventions since old mosquitoes are more likely to transmit malaria than young ones. Mid-infrared spectroscopy (MIRS) reveals age-associated variation in the biochemical composition of the mosquito cuticle, which can then be used to train machine learning (ML) models to predict mosquito ages. However, these MIRS-ML models are not always generalisable across different mosquito populations. Here, we investigated whether dimensionality reduction applied to the MIRS input data and transfer learning could improve the generalisability of MIRS-ML predictions for mosquito ages. We reared adults of the malaria vector, Anopheles arabiensis, in two insectaries (Ifakara, Tanzania and Glasgow, UK). The heads and thoraces of female mosquitoes of two age classes (1-9 day-olds and 10-17 day-olds) were scanned using an attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectrometer (4000 cm-1 to 400 cm-1). The dimensionality of the spectra data was reduced using unsupervised principal component analysis (PCA) or t-distributed stochastic neighbour embedding (t-SNE), and then the spectra were used to train deep learning (DL) and standard machine learning (ML) classifiers. Transfer learning was also evaluated for improving the computational cost of the models when predicting mosquito age classes from new populations. Model accuracies for predicting the age of test mosquitoes from the same insectary as the training samples reached 99% for DL and 92% for ML, but did not generalise to a different insectary, achieving only 46% and 48% for ML for DL, respectively. Dimensionality reduction did not improve the model generalisability between locations but reduced computational time up to 5-fold. However, transfer learning by updating pre-trained models with 2% of mosquitoes from the alternate location brought both DL and standard ML model performance to ~98% accuracy for predicting mosquito age classes in the alternative insectary. Combining dimensionality reduction and transfer learning can reduce computational costs and improve the transferability of both deep learning and standard machine learning models for predicting the age of mosquitoes. Future studies could investigate the optimal quantities and diversity of training data necessary for transfer learning, and implications for broader generalisability to unseen datasets.

bioinformatics↗

bioRxiv2022

Interplay between Polycomb PCGF protein interactomes revealed by screening under endogenous conditions

The six PCGF proteins (PCGF1-6) define the biochemical identity of Polycomb Repressor Complex 1 (PRC1) subcomplexes. While structural and functional studies of PRC1 subcomplexes have revealed specialized roles in distinct aspects of epigenetic regulation, our understanding of variation in protein interaction networks between the PCGF subunits is incomplete. We carried out an affinity purification mass spectrometry (AP-MS) screen of subunits PCGF1 (NSPC1), PCGF2 (MEL18), and PCGF4 (BMI1), using an immunoprecipitation approach that replicated endogenous cellular conditions in a cell line capable of differentiation programs. Over 200 interactions were found, including 83 that had not been described previously. Bioinformatic analysis found that these interacting proteins covered a range of functional pathways, often focused on cell biology and chromatin regulation. We found evidence of mutual regulation (at mRNA and protein level) between distinct PCGF subunits. Furthermore, we confirmed that disruption of each subunit using shRNA results in reduced proliferation ability. Overall, our work adds to understanding of the role of PCGF proteins within the wider cellular network.

cancer biology↗

bioRxiv2020

Rapid ageing and species identification of natural mosquitoes for malaria surveillance

The malaria parasite, which is transmitted by several Anopheles mosquito species, requires more time to reach its human-transmissible stage than the average lifespan of a mosquito. Monitoring the species-specific age structure of mosquito populations is critical to evaluating the impact of vector control interventions on malaria risk. We developed a rapid, cost-effective surveillance method based on deep learning of mid-infrared spectra of mosquitoes cuticle that simultaneously identifies the species and the age of three main malaria vectors, in natural populations. Using over 40,000 ecologically and genetically diverse females, we could speciate and age grade An. gambiae, An. arabiensis, and An. coluzzii with up to 95% accuracy. Further, our model learned the age of new populations with minimal sampling effort and detected the impact of control interventions on simulated mosquito populations, measured as a shift in their age structures. We anticipate our method to be applied to other arthropod vector-borne diseases.

zoology↗

bioRxiv2020

Low-frequency vibrational modes in G-quadruplexes reveal the mechanical properties of nucleic acids

Low-frequency vibrations play an essential role in biomolecular processes involving DNA such as gene expression, charge transfer, drug intercalation, and DNA-protein recognition. However, understanding of the vibrational basis of these mechanisms relies on theoretical models due to the lack of experimental evidence. Here we present the low-frequency vibrational spectra of G-quadruplexes (structures formed by four strands of DNA) and B-DNA characterized using femtosecond optical Kerr-effect spectroscopy. Contrary to expectation, we found that G-quadruplexes show several strongly underdamped delocalized phonon-like modes that have the potential to contribute to the biology of the DNA at the atomic level. In addition, G-quadruplexes present modes at a higher frequency than B-DNA demonstrating that changes in the stiffness of the molecule alter its gigahertz to terahertz vibrational profile. These results demonstrate that current theoretical models fail to predict basic properties of the vibrational modes of DNA. Statement of significanceA number of recent studies have identified thermally excited low-frequency vibrational modes as a key deciding factor in the biological function of DNA. However, the nature of these vibrational modes has never been established. Here, vibrational spectroscopy with unrivalled signal-to-noise in the gigahertz to terahertz range is used to determine the low-frequency Raman spectra of nucleotides and oligomeric DNAs carefully chosen to form G-quadruplexes, structures formed by four strands of DNA common in the genome. These G-quadruplexes exhibit an unusual group of highly-underdamped delocalized vibrational modes--not reproduced by any of the theoretical models in use--which are expected to be the thermally excited. This provides a new perspective on the role of low-frequency vibrational modes in protein interactions and allostery.

biophysics↗

bioRxiv2019

Human bone marrow mesenchymal stem/stromal cell behaviour is coordinated via mechanically activated osteocyte-derived extracellular vesicles

Osteocytes are mechanosensitive cells that are believed to play a fundamental role in coordinating bone mechanoadaptation via the secretion of paracrine factors. However, the exact mechanisms by which osteocytes relay mechanical signals to effector cells is poorly understood. In this study, we demonstrated that osteocytes subjected to a physiologic fluid shear secrete a distinct collection of factors that significantly enhance human MSC recruitment and osteogenesis. Utilising proteomics we generated an extensive map of proteins within the mechanically activated osteocyte secretome, identifying numerous paracrine factors that are modified by mechanical stimulation. Moreover, we identified the presence of extracellular vesicles (EVs) and further demonstrated that these mechanically activated osteocyte derived EVs (MAEVs) coordinate human MSCs recruitment and osteogenesis. This indicates that mechanical conditioning of parent cells can modify EVs and demonstrates the pro-osteogenic potential of MAEVs as a cell-free therapy to enhance bone regeneration and repair in diseases such as osteoporosis.

physiology↗