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Young, L.

Publications and source records attributed to Young, L..

At least 19 recordsLinked to original sources

A 4,000-year genomic history of Bantu speakers from the Congo rainforest

The Congo rainforest was the heartland of the Bantu Expansion, yet its demographic history remains partially understood. We inferred past population dynamics using genomes from 960 sub-Saharan Africans, including four newly sequenced ancient individuals from Iroungou cave and 176 present-day individuals from Gabon. Bantu-speaking populations began differentiating ~4,000 years ago, preceding explosive population growth by a millennium. Distinct southward dispersals contributed to the ancestry of Bantu speakers in Gabon and elsewhere in sub-Saharan Africa, with the ~700-year-old Iroungou individuals providing the closest genetic proxies for the latter. Both Bantu speakers and hunter-gatherers from the Congo rainforest experienced a major demographic crisis ~1,500 years ago, coinciding with an archaeological hiatus. These findings illuminate early Bantu dispersals and the subsequent, unexplained collapse of rainforest populations.

genomics↗

Weak interactions drive selective proteome demixing and tune the differential response to environmental perturbations

The intracellular space is a crowded environment where macromolecules perform distinct tasks despite pervasive "non-specific" interactions. Whether these interactions are functionally relevant and how they influence cellular organization remains unclear. Here, we developed QuPID-MS, which measures the propensity of proteins to phase separate in native cell extracts proteome-wide. We find that weak interactions drive condensation of half of the proteome in a crowding- and temperature-dependent manner and we present evidence that this proteome demixing occurs in cells. Importantly, protein condensation properties are conserved and broadly change when cells adapt to new environments, demonstrating that weak interactions are regulated and linked to function. Indeed, condensation of the growth regulator TORC1 coincides with its rapid inactivation, while high solubility of the stress-activated Hog1 ensures its activity across conditions. We thus uncover a fundamental organizing principle that allows tuning of cell growth to environmental fluctuations while ensuring other processes function robustly despite perturbations.

cell biology↗

IL-1-activated cancer-associated fibroblasts promote STAT1-driven transcriptional reprogramming of pancreatic tumour cells

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers, with limited treatment options and poor survival rates. It is characterised by strong driver mutations, epigenetic reprogramming, and a dense tumour microenvironment (TME). A defining feature of the PDAC TME is its fibrotic stroma, which is largely composed of cancer-associated fibroblasts (CAFs). Distinct CAF populations have been implicated in PDAC progression, but the mechanisms that govern their crosstalk with the cancer cells are poorly understood. We generated genetically engineered pancreatic stellate cells (PSCs) modelling interleukin-1 (IL-1)-dependent inflammatory CAFs (iCAFs) and transforming growth factor-{beta} (TGF-{beta})-dependent myofibroblastic CAFs (myCAFs) to investigate how distinct stromal populations shape the epigenetic landscape of pancreatic ductal adenocarcinoma (PDAC). We found that iCAFs, but not myCAFs, promoted gemcitabine resistance in epithelial tumour cells and identified STAT1 as a critical mediator of iCAF-tumour cell crosstalk. Mechanistically, STAT1 drove the induction of interferon (IFN)-responsive genes, while blockade of IFN-{beta} attenuated iCAF-mediated transcriptional reprogramming. Genetic ablation of STAT1 in tumour cells abolished iCAF-induced chemoresistance and associated transcriptional changes. In an orthotopic in vivo model, STAT1 knockout significantly prolonged survival following gemcitabine treatment, supporting a central role for STAT1 signalling in stromal-driven therapy resistance. We provide a comprehensive analysis on how IL-1-dependent iCAFs contribute to epigenetic reprogramming in PDAC and uncover a previously undescribed role for STAT1 in stromal-epithelial interactions. These findings reveal distinct, non-overlapping mechanisms by which CAF subtypes modulate tumour behaviour and identify STAT1 as a therapeutic vulnerability that can be exploited to sensitise PDAC to standard chemotherapy. Significance statementThis study establishes that the epigenetic landscape of PDAC is differentially shaped by iCAF- and myCAF-like PSCs and defines STAT1 as a mediator of iCAF-induced chemoresistance and transcriptional reprogramming. We demonstrate that genetic ablation of STAT1 sensitises tumours to gemcitabine in vivo, extending survival and positioning STAT1 as an actionable target to overcome stromal-mediated therapy resistance in PDAC.

cancer biology↗

Cell-matrix mechanosensing and cellular metabolic demand are linked through SKT and mTORC2

Integrin-based adhesion complexes mediate cell adhesion to the extracellular matrix and enable the cell to interpret and respond to both biochemical and mechanical cues. Such cues can affect a cells metabolic rate; however, how mechanical signals are converted into metabolic rate changes is not clear. We identified an uncharacterised protein; Sickle Tail Protein Homolog (KIAA1217), SKT to be enriched in cell-matrix adhesion complexes in stiff microenvironments. Low SKT expression correlates with an improved prognosis in pancreatic ductal adenocarcinoma (PDAC), suggesting an important role for SKT in extracellular matrix dependent tumour progression. Here, we show that SKT interacts with the mechanistic target of rapamycin complex 2 (mTORC2), a pivotal signalling complex in glucose metabolism, cell growth, and survival. SKT recruits mTORC2 to cell-matrix adhesions in a mechanoresponsive manner. SKT mediated mTORC2 signalling from adhesions is required for maintaining glycolytic flux and control of adhesion dynamics. Our findings show that SKT serves as a rheostat that controls metabolic adaptation of cells to their matrix microenvironment. Collectively, our research provides insights into the molecular mechanisms and interplay between cell adhesion and metabolic signalling in complex and stiff tumour microenvironments. The novel functions identified for SKT in cell-matrix adhesions, mTORC2 signalling and glycolysis unveils a signalling axis between the tumour microenvironment and cellular metabolism that are required for PDAC growth and invasion.

cell biology↗

Non-overlapping social and food reward representations in the basolateral amygdala

The ability to consider and appraise positively valenced stimuli in the environment, such as food and social interaction, to guide appropriate action is important for survival of most animals. Several studies have compared how food and social rewards are represented in different regions involved in reward processing and found either overlapping or distinct representations. In the basolateral amygdala (BLA) there seems to be opposing evidence for both shared and unique encoding of social and nonsocial stimuli. In our recent work, we found that the medial prefrontal cortex (mPFC), a region reciprocally connected to the BLA, has distinct social and food representations using a novel self-paced two-choice assay. Given the BLA and mPFCs differing roles in reward processing, it is important to understand how these two nodes may differ in their encoding reward types within the same assay. To resolve how the BLA encodes social and food information, we recorded the activity of individual BLA neurons in female and male mice during a two-choice social-sucrose operant task. We found that BLA neurons robustly and distinctly respond to social and food reward. In contrast to the mPFC, BLA neurons did not show a bias towards social reward responsiveness and instead showed equal social/sucrose representation, in males, or a sucrose reward bias, in females. BLA neurons were sensitive to internal state - water deprivation increased the proportion of sucrose reward responsive neurons. Additionally, sucrose reward responsive BLA neurons were differentially sensitive to reward omissions, such that neurons that were excited by sucrose reward were more sensitive to reward omissions compared to those inhibited by reward. Together, these findings demonstrate distinct, heterogeneous response profiles within the BLA to social and food rewards, in a manner different from the mPFC.

neuroscience↗

MIF-induced CD74+ microglia/macrophages are clinically relevant disease-associated subpopulations in brain metastasis and other CNS disorders

The upregulation of CD74, a chaperone involved in MHC-II antigen processing 1,2, has been broadly reported in virtually all brain disorders analyzed by single-cell RNA sequencing 3-6. However, its expression is usually interpreted as indicative of antigen presentation. In parallel, CD74 expression has also been described in cancer cells across multiple tumor types, but interestingly in glioma its expression has been mainly identified in the microenvironment. However, the functional contribution of CD74 to disease progression in the brain, and specifically in secondary brain tumors, has not been directly addressed. Here we described that, in contrast to what it has been assumed, the presence of CD74+ microglia/macrophages, which is induced by increased levels of interferon gamma in the brain affected by metastases, does not relate to its canonical pathway. Instead, CD74s alternative function as cytokine receptor is pivotal. Rewired by increasing levels of its ligand MIF, produced by proliferating cancer cells, the CD74 receptor, upon binding to this ligand, translocates to the nucleus activating a NF-{kappa}B-dependent program promoting metastasis progression. A brain metastasis-associated CD74 signature involves a more aggressive progression of the local disease in patients, while it has no clinical correlation with the matched primary tumor. Furthermore, we identified the CD74+ myeloid population in additional brain disorders including Alzheimers disease and multiple sclerosis, which shared a pan-disease non-canonical signature with clinical relevance. The brain-penetrant drug ibudilast, which prevents the binding of MIF to CD74, decreases brain metastases in experimental models in vivo and in patient-derived organotypic cultures ex vivo in a primary tumor-agnostic manner. Our findings suggest that MIF/CD74-induced reprogramming of myeloid cells in brain disorders is a novel vulnerability that could be exploited therapeutically against brain metastases, and possibly other brain disorders, guided by a non-invasive molecular strategy.

cancer biology↗

ALG13 loss-of-function alters glycosylation, impairs neuronal maturation, and drives network hypoactivity in a cortical organoid model of CDG

BackgroundCongenital disorders of glycosylation (CDGs) are a group of rare metabolic diseases recognized for their neurological presentations, including developmental delay and seizures. However, the link between glycosylation defects and cortical brain network pathology remains elusive. MethodsTo address this unmet need, we generated iPSC derived human cortical organoids (hCOs) for ALG13-CDG, which is the second most common CDG that is also X-linked. To comprehensively understand the impact of glycosylation defects on cortical pathology in CDG, we combined electrophysiological recordings using multi-electrode arrays (MEA) with comprehensive molecular profiling via multiomics, including scRNA-seq, proteomics, glycoproteomics, N-glycan imaging, lipidomics, and metabolomics. X-inactivation status was also evaluated in both iPSCs and organoids. ResultsALG13-CDG hCOs revealed reduced glycosylation of proteins critical for extracellular matrix (ECM), neuronal migration, lipid metabolism, calcium ion homeostasis, and neuronal excitability. Dysregulation in related pathways was corroborated by proteomics and scRNA-seq, which also showed altered communication patterns in these pathways. Trajectory analysis revealed an inversion in neuronal development, with early inhibitory and delayed excitatory development, indicating an excitatory and inhibitory (E/I) imbalance. MEA recordings demonstrated early network hypoactivity with reduced firing rates, immature burst dynamics, and shorter axonal extensions. Despite this, transcriptomic and proteomic data revealed upregulation of excitatory receptors suggesting latent hyperexcitability. Altered lipid and sugar (GlcNAc) metabolism and skewed X-inactivation were also observed. ConclusionsOur study provides the first evidence of glycosylation defects in an ALG13-CDG human cortical organoid (hCO) model and links these defects to disrupted neuronal developmental trajectories and dysregulation of key pathways essential for brain function. We identify mistimed neuronal maturation and an excitatory/inhibitory (E/I) imbalance as early drivers of network hypoactivity and immature burst dynamics, with downstream compensatory hyperexcitability that may contribute to seizure susceptibility. While specific to ALG13-CDG, these mechanisms likely extend to other glycosylation disorders with overlapping neurological features. This work offers new mechanistic insight into cortical dysfunction associated with impaired protein glycosylation and highlights potential targets for therapeutic intervention.

neuroscience↗

CRISPR-mediated knockdown of oxytocin receptor in extended amygdala reduces stress-induced social avoidance and vigilance

Oxytocin receptors (OTRs) within the extended amygdala and nucleus accumbens (NAc) have been implicated in modulating social behaviors, particularly following stress. The effects of OTR could be mediated by modulating the activity of pre-synaptic axon terminals or via receptors in post-synaptic neurons or glia. Using a viral-mediated CRISPR/Cas9 gene editing system in female California mice (Peromyscus californicus), we selectively knocked down OTR in the anteromedial bed nucleus of the stria terminalis (BNST) or NAc to examine their roles modulating social approach and vigilance behaviors. Knockdown of OTR in the BNST attenuated stress-induced decreases of social approach and had less robust effects on vigilance when interacting with a target mouse behind a wire barrier. In this large arena, where mice could control their proximity to a target mouse, BNST OTR knockdown also increased investigation of a non-social stimulus (empty cage). Behavioral effects of BNST OTR knockdown were weaker in the small arena where focal mice physically interacted with target mice. Interestingly, OTR knockdown in the NAc, reduced stress-induced social vigilance without affecting social approach. These effects could mediated altered encoding of socially aversive experiences, as knockdown manipulations were performed before stress exposure. Together, these results highlight effects of local OTR on social behavior are region-specific.

neuroscience↗

Early Radiation Therapy Response Assessment using Multi-scale Photoacoustic Imaging

There is a critical unmet clinical need to identify biomarkers that predict and detect radiotherapy response in cancer. Using the unique capabilities of multi-scale photoacoustic imaging (PAI) for depicting tumour oxygenation and vasculature in vivo, we identified surrogate biomarkers of radiation response in two human breast cancer models (MCF7 and MDA-MB-231), comparing hypofractionated delivery with an ablative single dose scheme. Ex vivo immunohistochemistry results underpinned findings from mesoscopic and multispectral tomographic PAI, performed 24h pre-RT, 24h post-RT, and at endpoint. A denser and more mature vasculature of the MCF7 xenografts afforded an improved response to both RT schemes compared to MDA-MB-231, in terms of overall tumour oxygenation, tumour volume and proliferation. Increased intratumoural blood oxygen saturation and oxygen diffusion pre-RT were associated with improved outcomes and decreased proliferation, expected given the oxygen-enhancement effect in RT. In vivo PAI revealed the differential effect between ablative courses of RT in both models, with the ablative scheme altering the tumour vasculature as early as 24h post-RT, and pruning the looping vessels and total blood volume at endpoint in the more radiosensitive MCF-7 xenografts. An increase in blood oxygen saturation at endpoint was observed only in the MCF7 xenografts treated with hypofractionated RT, confirming the reduced oxygen consumption of damaged tumour cells, indicative of response. Thus, we showed that PAI could capture early RT response and inform on radioresistance, thus demonstrating promise of PAI as an in vivo and future clinical tool to monitor the tumour vascular response to RT.

cancer biology↗

Androgen receptor interactions provide insight into steroid mediated metabolic shifts in endocrine resistant breast cancer.

PurposeAromatase Inhibitors (AI) are standard therapy for hormone receptor positive breast cancers in post-menopausal patients. Disease recurrence is common and previous studies suggest that the altered steroid environment may be a driver of resistance. Using label-free mass-spectrometry we explored the unique androgen receptor (AR) interactome that supervenes in AI resistant breast cancer and the associated hyperandrogenic environment. Experimental DesignAR expression was evaluated in a primary breast cancer tissue-microarray (n=875) with nuclear and cytoplasmic localization quantified. Liquid-chromatography tandem mass-spectrometry (LC-MS/MS) analysis was utilized to identify proteins interacting with the AR in models of AI-resistance. Validation was carried out by co-immunoprecipitation and co-localisation studies. Live-cell imaging, Seahorse MitoStress Assays and flow cytometry were used to quantify changes in mitochondria and cell metabolism arising in models of AI-resistance. ResultsUtilising digital pathology we detected that abundant cytoplasmic AR protein was associated with poor survival only in the post-menopausal cohort, and most significantly, in the therapy-refractory Luminal B subtype (p=0.0085). Models of AI-resistance and androgen excess highlight diffuse AR localisation throughout the cytoplasm and nucleus accompanied by increased mitochondrial mass and membrane potential, and increased oxidative phosphorylation and glycolysis. Exploration of the AR protein interactome identified G3BP1, SLIRP, and IGFBP5 as AR protein partners which are associated with stress, adaptive metabolic response and estrogen receptor repression. ConclusionsThe findings of this study highlight the prognostic potential of cytoplasmic AR immunoreactivity in specific breast cancer subtypes and uncover novel extra-nuclear AR protein interactions that may mediate metabolic adaptations during the development of endocrine-resistance.

cancer biology↗

A Deep Learning Framework for Predicting Prognostically Relevant Consensus Molecular Subtypes in HPV-Positive Cervical Squamous Cell Carcinoma from Routine Histology Images

Despite efforts in human papillomavirus (HPV) prevention and screening, cervical cancer remains the fourth most prevalent cancer among women globally. In this study, we propose an end-to-end deep learning framework to investigate histological correlates of the two consensus molecu-lar subtype (CMS) of HPV-positive cervical squamous cell carcinoma (CSCC) patients. Analysing three international CSCC cohorts (n=545 patients), we demonstrate that the genomically determined CMS can be predicted from routine haematoxylin and eosin (H&E)-stained histology slides, with our Digital-CMS scores achieving significant patient stratifications in terms of disease-specific survival (TCGA p=0.0022, Oslo p=0.0495) and disease-free survival (TCGA p=0.0495, Oslo p=0.0282). In addition, our extensive analyses reveal distinct tumour microenvironment (TME) differences between the two CMS subtypes of the CSCC cohorts. Notably, CMS-C1 CSCC subgroup has markedly increased lymphocyte presence, whereas CMS-C2 subgroup has high nuclear pleomor-phism, an elevated neutrophil-to-lymphocyte ratio, and increased neutrophil density. Analysis of representative histological regions reveals higher degree of malignancy in CMS-C2 patients, as-sociated with poor prognosis. This study introduces a potentially clinically advantageous Digital-CMS score derived from digitised WSIs of routine H&E-stained tissue sections, offers new insights into TME differences impacting patient prognosis and potential therapeutic targets, and identifies histological patterns serving as potential surrogate markers of the two CMS subtypes for clinical application.

pathology↗

Estrogen Receptor alpha/14-3-3 molecular glues as alternative treatment strategy for endocrine resistant breast cancer

Endocrine resistance in breast cancer treatment is a major clinical hurdle, causing an urgent need for alternative treatment modalities. The suppressive protein-protein interaction (PPI) between Estrogen Receptor alpha (ER) and the adaptor protein 14-3-3 offers such a strategy. Here, we report the biological impact of small-molecule molecular glues of this ER/14-3-3 PPI by using both fusicoccin-derived semi-synthetic natural products and fully synthetic covalent drug-like molecules. We show that the ER/14-3-3 PPI is stabilized by both the natural- and synthetic glues, resulting in a suppression of ER transcriptional activity and a blockade of breast cancer cell proliferation, both in cell lines and in organoids derived from endocrine therapy resistant breast cancer patients. Importantly, the molecular glues effectively blocked ER action even in case of constitutively active clinical ER mutations, providing the foundations for developing alternative classes of ER targeting compounds to improve treatment of patients with endocrine-therapy resistant breast cancer. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/591105v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@173545corg.highwire.dtl.DTLVardef@a78ab7org.highwire.dtl.DTLVardef@183f4b6org.highwire.dtl.DTLVardef@371606_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Cancer drug sensitivity prediction from routine histology images

Drug sensitivity prediction models can aid in personalising cancer therapy, biomarker discovery, and drug design. Such models require survival data from randomized controlled trials which can be time consuming and expensive. In this proof-of-concept study, we demonstrate for the first time that deep learning can link histological patterns in whole slide images (WSIs) of Haematoxylin & Eosin (H&E) stained breast cancer sections with drug sensitivities inferred from cell lines. We employ patient-wise drug sensitivities imputed from gene expression based mapping of drug effects on cancer cell lines to train a deep learning model that predicts sensitivity to multiple drugs from WSIs. We show that it is possible to use routine WSIs to predict the drug sensitivity profile of a cancer patient for a number of approved and experimental drugs. We also show that the proposed approach can identify cellular and histological patterns associated with drug sensitivity profiles of cancer patients. HighlightsO_LIPredicting drug sensitivity from routine histology images and cell lines C_LIO_LIDiscovery of histology image patterns linked to drug sensitivity C_LIO_LIA novel deep learning pipeline for analysing drug sensitivity profiles C_LI

cancer biology↗

Data-Driven Modelling of Gene Expression States in Breast Cancer and their Prediction from Routine Whole Slide Images

Identification of gene expression state of a cancer patient from routine pathology imaging and characterization of its phenotypic effects have significant clinical and therapeutic implications. However, prediction of expression of individual genes from whole slide images (WSIs) is challenging due to co-dependent or correlated expression of multiple genes. Here, we use a purely data-driven approach to first identify groups of genes with co-dependent expression and then predict their status from (WSIs) using a bespoke graph neural network. These gene groups allow us to capture the gene expression state of a patient with a small number of binary variables that are biologically meaningful and carry histopathological insights for clinically and therapeutic use cases. Prediction of gene expression state based on these gene groups allows associating histological phenotypes (cellular composition, mitotic counts, grading, etc.) with underlying gene expression patterns and opens avenues for gaining significant biological insights from routine pathology imaging directly. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/536756v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@74d0dcorg.highwire.dtl.DTLVardef@13c2708org.highwire.dtl.DTLVardef@26a6dborg.highwire.dtl.DTLVardef@194b076_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIData-driven discovery of co-expressing gene groups in breast caner C_LIO_LIHistological imaging based prediction of gene groups via deep learning C_LIO_LIIdentification of phenotypic correlates of gene-expression in histological imaging C_LIO_LIClinical and therapeutic impact of gene groups and their visual patterns identified C_LI

pathology↗

Biodiversity shows unique responses to land-use change across regional biomes

Biogeography has a critical influence on how ecological communities respond to threats and how effective conservation interventions are designed. For example, the resilience of ecological communities is linked to environmental and climatic features, and the nature of threats impacting ecosystems also varies geographically. Understanding community-level threat responses may be most accurate at fine spatial scales, however collecting detailed ecological data at such a high resolution would be prohibitively resource intensive. In this study, we aim to find the spatial scale that could best capture variation in community-level threat responses whilst keeping data collection requirements feasible. Using a database of biodiversity records with extensive global coverage, we modelled species richness and total abundance (the responses) across land-use types (reflecting threats), considering three different spatial scales: biomes, biogeographical realms, and regional biomes (the interaction between realm and biome). We then modelled data from three highly sampled biomes separately to ask how responses to threat differ between regional biomes and taxonomic group. We found strong support for regional biomes in explaining variation in species richness and total abundance compared to biomes or realms alone. Our biome case studies demonstrate that there is a high variation in magnitude and direction of threat responses across both regional biomes and taxonomic group, but all groups in tropical forest showed a consistently negative response, whilst many taxon-regional biome groups showed no clear response to threat in temperate forest and tropical grassland. Our results suggest that the taxon-regional biome unit has potential as a reasonable spatial and ecological scale for understanding how ecological communities respond to threats and designing effective conservation interventions to bend the curve on biodiversity loss.

ecology↗

LDL Receptor-Related Protein 5 is a Selective Transporter for Unesterified Polyunsaturated Fatty Acids

Polyunsaturated fatty acids (PUFAs), which cannot be synthesized by animals and must be supplied from the diet, have been strongly associated with human health. However, the mechanisms for their accretion and actions remain poorly understood. Here, we show that LDL receptor-related protein 5 (LRP5), but not its homolog LRP6, selectively transports unesterified PUFAs into a number of cell types. The LDLa ligand-binding repeats of LRP5 directly bind to PUFAs and are required for PUFA transport. LRP5 transports PUFAs via internalization to intracellular compartments including lysosomes, and n-3 PUFAs depends on this transport mechanism to inhibit mTORC1. This LRP5-mediated PUFA transport mechanism suppresses neutrophil extracellular trap formation in neutrophils and protects mice from myocardial injury during ischemia-reperfusion. Thus, this study reveals a previously unknown and biologically important mechanism for PUFA transport and mTORC1 regulation.

cell biology↗

Modelling drug responses and evolutionary dynamics using triple negative breast cancer patient-derived xenografts

Triple negative breast cancers (TNBC) exhibit inter- and intra-tumour heterogeneity, which is reflected in diverse drug responses and interplays with tumour evolution. Here, we use TNBC patient-derived tumour xenografts (PDTX) as a platform for co-clinical trials to test their predictive value and explore the molecular features of drug response and resistance. Patients and their matched PDTX exhibited mirrored drug responses to neoadjuvant therapy in a clinical trial. In parallel, additional clinically-relevant treatments were tested in PDTXs in vivo to identify alternative effective therapies for each PDTX model. This framework establishes the foundation for anticipatory personalised therapies for those patients with resistant or relapsed tumours. The PDTXs were further explored to model PDTX- and treatment-specific behaviours. The dynamics of drug response were characterised at single-cell resolution revealing a novel mechanism of response to olaparib. Upon olaparib treatment PDTXs showed phenotypic plasticity, including transient activation of the immediate-early response and irreversible sequential phenotypic switches: from epithelial to epithelial-mesenchymal-hybrid states, and then to mesenchymal states. This molecular mechanism was exploited ex vivo by combining olaparib and salinomycin (an inhibitor of mesenchymal-transduced cells) to reveal synergistic effects. In summary, TNBC PDTXs have the potential to help design individualised treatment strategies derived from model-specific evolutionary insights.

cancer biology↗

CRF neurons of the BNST promote resilience by blunting the internal experience of aversion.

The Bed Nucleus of the Stria Terminalis (BNST) has been studied extensively for its coordination of opposing adaptive behaviors. Previously, we uncovered a critical role for Corticotropin-Releasing Factor (CRF)-expressing neurons of the oval nucleus of the BNST (BNSTovCRF) in maintaining resilience to social defeat through stress-dependent self-sustaining neuronal activity.1 However, as mice develop resilience, it is not well-understood how affect and motivation are altered to achieve adaptive behavior in the face of ongoing threat. Here, we explore how this neuronal population exerts a powerful influence over internal state in various stress contexts to promote adaptive social responding. Using cell-type-selective optogenetics, a suite of behavioral paradigms, and transgenic Crf-ChR2 mice, we show that BNSTovCRF neurons induce resiliency by altering the encoding of psychosocial stress, enhancing the appetitiveness of social interaction, and enhancing tolerability to physical stress. Adaptive responses to stress typically emanate as a response to negative internal states by external stimuli; here, we show that in resilient mice, stressful environments are less aversive than susceptible mice, suggesting a different motivational capacity to endure stress in this group. Thus, we describe a novel role for BNSTovCRF neurons in resisting the emotional effects of cumulative stress by reducing the internal experience of aversion

neuroscience↗