Simultaneous profiling of multiple chromatin proteins in the same cells.

Methods derived from CUT&RUN and CUT&Tag enable genome-wide mapping of the localization of proteins on chromatin from as few as one cell. These and other mapping approaches focus on one protein at a time, preventing direct measurements of co-localization of different chromatin proteins in the same cells and requiring prioritization of targets where samples are limiting. Here, we describe multi-CUT&Tag, an adaptation of CUT&Tag that overcomes these hurdles by using antibody-specific barcodes to simultaneously map multiple proteins in the same cells. Highly specific multi-CUT&Tag maps of histone marks and RNA Polymerase II uncovered sites of co-localization in the same cells, active and repressed genes, and candidate cis-regulatory elements. Single-cell multi-CUT&Tag profiling facilitated identification of distinct cell types from a mixed population and characterization of cell-type-specific chromatin architecture. In sum, multi-CUT&Tag increases the information content per cell of epigenomic maps, facilitating direct analysis of the interplay of different chromatin proteins.

Functional genomic screens with death rate analyses reveal mechanisms of drug action.

A common approach for understanding how drugs induce their therapeutic effects is to identify the genetic determinants of drug sensitivity. Because 'chemo-genetic profiles' are performed in a pooled format, inference of gene function is subject to several confounding influences related to variation in growth rates between clones. In this study, we developed Method for Evaluating Death Using a Simulation-assisted Approach (MEDUSA), which uses time-resolved measurements, along with model-driven constraints, to reveal the combination of growth and death rates that generated the observed drug response. MEDUSA is uniquely effective at identifying death regulatory genes. We apply MEDUSA to characterize DNA damage-induced lethality in the presence and absence of p53. Loss of p53 switches the mechanism of DNA damage-induced death from apoptosis to a non-apoptotic death that requires high respiration. These findings demonstrate the utility of MEDUSA both for determining the genetic dependencies of lethality and for revealing opportunities to potentiate chemo-efficacy in a cancer-specific manner.

Acinetobacter baumannii transformants expressing oxacillinases and metallo-ß-lactamases that confer resistance to meropenem: new tools for anti-Acinetobacter drug development and AMR preparedness.

Antimicrobial resistance (AMR) in Acinetobacter baumannii is an unmet medical need. Multiple drug-resistant/extremely drug-resistant strains of A. baumannii do not display growth well in in vivo models, and consequently, their response to antibacterial therapy is inconsistent. We addressed this issue by engineering carbapenem resistance motifs into the highly virulent genetic background of A. baumannii AB5075. This strain has a chromosomally encoded oxa-23 that was deleted (Δoxa-23), then plasmids expressing oxa-23, oxa-24/40, oxa-58, imp-1, vim-2, and ndm-1 were introduced to create the mutant strains. Each transformant was used as a challenge strain in a neutropenic murine thigh infection model and assessed for the extent of growth and response to meropenem 200 mg/kg subcutaneously every 6 h (q6h). Pharmacodynamic analyses were performed by transforming drug exposure from dose (mg/kg) to the fraction of the dosing interval; free meropenem concentrations were >minimum inhibitory concentration (MIC) (fT > MIC). AB5075 and the AB5075Δoxa-23 mutant had a MICs of 32 and 4 mg/L, respectively. The transformants harboring oxacillinases oxa-24/40 and oxa-58 had an MIC of 64 mg/L. The metallo-ß-lactamases imp-1, vim-2, and ndm-1 had MICs of 128, 64, and 64 mg/L, respectively. All vehicle-treated transformants displayed in vivo growth in the range of 0.75-1.4 log. The response to meropenem was consistent with the varying fT > MIC of the transformants and was readily described by an inhibitory sigmoid Emax relationship. Stasis was achieved with a fT > MIC of 0.36. These A. baumannii transformants are invaluable new tools for the assessment of anti-Acinetobacter compounds and provide a new pathway for AMR preparedness.

Development of neonatal brain functional centrality and alterations associated with preterm birth.

Formation of the functional connectome in early life underpins future learning and behavior. However, our understanding of how the functional organization of brain regions into interconnected hubs (centrality) matures in the early postnatal period is limited, especially in response to factors associated with adverse neurodevelopmental outcomes such as preterm birth. We characterized voxel-wise functional centrality (weighted degree) in 366 neonates from the Developing Human Connectome Project. We tested the hypothesis that functional centrality matures with age at scan in term-born babies and is disrupted by preterm birth. Finally, we asked whether neonatal functional centrality predicts general neurodevelopmental outcomes at 18 months. We report an age-related increase in functional centrality predominantly within visual regions and a decrease within the motor and auditory regions in term-born infants. Preterm-born infants scanned at term equivalent age had higher functional centrality predominantly within visual regions and lower measures in motor regions. Functional centrality was not related to outcome at 18 months old. Thus, preterm birth appears to affect functional centrality in regions undergoing substantial development during the perinatal period. Our work raises the question of whether these alterations are adaptive or disruptive and whether they predict neurodevelopmental characteristics that are more subtle or emerge later in life.

Predicting age and clinical risk from the neonatal connectome.

The development of perinatal brain connectivity underpins motor, cognitive and behavioural abilities in later life. Diffusion MRI allows the characterisation of subtle inter-individual differences in structural brain connectivity. Individual brain connectivity maps (connectomes) are by nature high in dimensionality and complex to interpret. Machine learning methods are a powerful tool to uncover properties of the connectome which are not readily visible and can give us clues as to how and why individual developmental trajectories differ. In this manuscript we used Deep Neural Networks and Random Forests to predict demographic and neurodevelopmental characteristics from neonatal structural connectomes in a large sample of babies (n = 524) from the developing Human Connectome Project. We achieved an accurate prediction of post menstrual age (PMA) at scan in term-born infants (mean absolute error (MAE) = 0.72 weeks, r = 0.83 and p < 0.001). We also achieved good accuracy when predicting gestational age at birth in a cohort of term and preterm babies scanned at term equivalent age (MAE = 2.21 weeks, r = 0.82, p < 0.001). We subsequently used sensitivity analysis to obtain feature relevance from our prediction models, with the most important connections for prediction of PMA and GA found to predominantly involve frontal and temporal regions, thalami, and basal ganglia. From our models of PMA at scan for infants born at term, we computed a brain maturation index (predicted age minus actual age) of individual preterm neonates and found a significant correlation between this index and motor outcome at 18 months corrected age. Our results demonstrate the applicability of machine learning techniques in analyses of the neonatal connectome and suggest that a neural substrate of brain maturation with implications for future neurodevelopment is detectable at term equivalent age from the neonatal connectome.

Effects of gestational age at birth on perinatal structural brain development in healthy term-born babies.

Infants born in early term (37-38 weeks gestation) experience slower neurodevelopment than those born at full term (40-41 weeks gestation). While this could be due to higher perinatal morbidity, gestational age at birth may also have a direct effect on the brain. Here we characterise brain volume and white matter correlates of gestational age at birth in healthy term-born neonates and their relationship to later neurodevelopmental outcome using T2 and diffusion weighted MRI acquired in the neonatal period from a cohort (n = 454) of healthy babies born at term age (>37 weeks gestation) and scanned between 1 and 41 days after birth. Images were analysed using tensor-based morphometry and tract-based spatial statistics. Neurodevelopment was assessed at age 18 months using the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III). Infants born earlier had higher relative ventricular volume and lower relative brain volume in the deep grey matter, cerebellum and brainstem. Earlier birth was also associated with lower fractional anisotropy, higher mean, axial, and radial diffusivity in major white matter tracts. Gestational age at birth was positively associated with all Bayley-III subscales at age 18 months. Regression models predicting outcome from gestational age at birth were significantly improved after adding neuroimaging features associated with gestational age at birth. This work adds to the body of evidence of the impact of early term birth and highlights the importance of considering the effect of gestational age at birth in future neuroimaging studies including term-born babies.

Deletion of Cdkn1b in ACI rats leads to increased proliferation and pregnancy-associated changes in the mammary gland due to perturbed systemic endocrine environment.

Mammary epithelial progenitors are the normal cell-of-origin of breast cancer. We previously defined a population of p27+ quiescent hormone-responsive progenitor cells in the normal human breast whose frequency associates with breast cancer risk. Here, we describe that deletion of the Cdkn1b gene encoding the p27 cyclin-dependent kinase inhibitor in the estrogen-induced mammary tumor-susceptible ACI rat strain leads to a decrease in the relative frequencies of Cd49b+ mammary luminal epithelial progenitors and pregnancy-related differentiation. We show by comprehensive gene expression profiling of purified progenitor and differentiated mammary epithelial cell populations that p27 deletion has the most pronounced effects on luminal progenitors. Cdkn1b-/- females have decreased fertility, but rats that are able to get pregnant had normal litter size and were able to nurse their pups implying that loss of p27 in ACI rats does not completely abrogate ovarian function and lactation. Reciprocal mammary gland transplantation experiments indicate that the p27-loss-induced changes in mammary epithelial cells are not only caused by alterations in their intrinsic properties, but are likely due to altered hormonal signaling triggered by the perturbed systemic endocrine environment observed in Cdkn1b-/- females. We also observed a decrease in the frequency of mammary epithelial cells positive for progesterone receptor (Pr) and FoxA1, known direct transcriptional targets of the estrogen receptor (Erα), and an increase in phospho-Stat5 positive cells commonly induced by prolactin (Prl). Characterization of genome-wide Pr chromatin binding revealed distinct binding patterns in mammary epithelial cells of Cdkn1b+/+ and Cdkn1b-/- females and enrichment in genes with known roles in Notch, ErbB, leptin, and Erα signaling and regulation of G1-S transition. Our data support a role for p27 in regulating the pool size of hormone-responsive luminal progenitors that could impact breast cancer risk.

Characteristics of free air carbon dioxide enrichment of a northern temperate mature forest.

In 2017, the Birmingham Institute of Forest Research (BIFoR) began to conduct Free Air Carbon Dioxide Enrichment (FACE) within a mature broadleaf deciduous forest situated in the United Kingdom. BIFoR FACE employs large-scale infrastructure, in the form of lattice towers, forming 'arrays' which encircle a forest plot of ~30 m diameter. BIFoR FACE consists of three treatment arrays to elevate local CO2 concentrations (e[CO2 ]) by +150 µmol/mol. In practice, acceptable operational enrichment (ambient [CO2 ] + e[CO2 ]) is ±20% of the set point 1-min average target. There are a further three arrays that replicate the infrastructure and deliver ambient air as paired controls for the treatment arrays. For the first growing season with e[CO2 ] (April to November 2017), [CO2 ] measurements in treatment and control arrays show that the target concentration was successfully delivered, that is: +147 ± 21 µmol/mol (mean ± SD) or 98 ± 14% of set point enrichment target. e[CO2 ] treatment was accomplished for 97.7% of the scheduled operation time, with the remaining time lost due to engineering faults (0.6% of the time), CO2 supply issues (0.6%) or adverse weather conditions (1.1%). CO2 demand in the facility was driven predominantly by wind speed and the formation of the deciduous canopy. Deviations greater than 10% from the ambient baseline CO2 occurred <1% of the time in control arrays. Incidences of cross-contamination >80 µmol/mol (i.e. >53% of the treatment increment) into control arrays accounted for <0.1% of the enrichment period. The median [CO2 ] values in reconstructed three-dimensional [CO2 ] fields show enrichment somewhat lower than the target but still well above ambient. The data presented here provide confidence in the facility setup and can be used to guide future next-generation forest FACE facilities built into tall and complex forest stands.

Multimodal image analysis of clinical influences on preterm brain development.

OBJECTIVE: Premature birth is associated with numerous complex abnormalities of white and gray matter and a high incidence of long-term neurocognitive impairment. An integrated understanding of these abnormalities and their association with clinical events is lacking. The aim of this study was to identify specific patterns of abnormal cerebral development and their antenatal and postnatal antecedents. METHODS: In a prospective cohort of 449 infants (226 male), we performed a multivariate and data-driven analysis combining multiple imaging modalities. Using canonical correlation analysis, we sought separable multimodal imaging markers associated with specific clinical and environmental factors and correlated to neurodevelopmental outcome at 2 years. RESULTS: We found five independent patterns of neuroanatomical variation that related to clinical factors including age, prematurity, sex, intrauterine complications, and postnatal adversity. We also confirmed the association between imaging markers of neuroanatomical abnormality and poor cognitive and motor outcomes at 2 years. INTERPRETATION: This data-driven approach defined novel and clinically relevant imaging markers of cerebral maldevelopment, which offer new insights into the nature of preterm brain injury. Ann Neurol 2017;82:233-246.

Reconstitution of the death-inducing signaling complex reveals a substrate switch that determines CD95-mediated death or survival.

The death-inducing signaling complex (DISC) is critical for initiation of death-receptor-mediated apoptosis; however, paradoxically, CD95 also signals for cell survival. Here, we reconstitute a functional DISC using only purified CD95, FADD, and procaspase-8 and unveil a two-step activation mechanism involving both dimerization and proteolytic cleavage of procaspase-8 that is obligatory for death-receptor-induced apoptosis. Initially, dimerization yields active procaspase-8 with a very restricted substrate repertoire, limited to itself or c-FLIP. Proteolytic cleavage is then required to fully activate caspase-8, thereby permitting DISC-mediated cleavage of the critical exogenous apoptotic substrates, caspase-3 and Bid. This switch in catalytic activity and substrate range is a key determinant of DISC signaling, as cellular expression of noncleavable procaspase-8 mutants, which undergo DISC-mediated oligomerization, but not cleavage, fails to initiate CD95-induced apoptosis. Thus, using the reconstituted DISC, we have delineated a crucial two-step activation mechanism whereby activated death receptor complexes can trigger death or survival.

Determination of minimum inhibitory concentrations using machine-learning-assisted agar dilution.

Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional methods for measuring minimum inhibitory concentration (MIC) are resource intensive, subject to human error, and require considerable infrastructure. AIgarMIC streamlines and standardizes MIC measurement and is especially valuable for large-scale surveillance activities. MICs were measured using agar dilution for n = 10 antibiotics against clinical Enterobacterales isolates (n = 1,086) obtained from a large tertiary hospital microbiology laboratory. Escherichia coli (n = 827, 76%) was the most common organism. Photographs of agar plates were divided into smaller images covering one inoculation site. A labeled data set of colony images was created and used to train a convolutional neural network to classify images based on whether a bacterial colony was present (first-step model). If growth was present, a second-step model determined whether colony morphology suggested antimicrobial growth inhibition. The ability of the AI to determine MIC was then compared with standard visual determination. The first-step model classified bacterial growth as present/absent with 94.3% accuracy. The second-step model classified colonies as "inhibited" or "good growth" with 88.6% accuracy. For the determination of MIC, the rate of essential agreement was 98.9% (644/651), with a bias of -7.8%, compared with manual annotation. AIgarMIC uses artificial intelligence to automate endpoint assessments for agar dilution and potentially increases throughput without bespoke equipment. AIgarMIC reduces laboratory barriers to generating high-quality MIC data that can be used for large-scale surveillance programs. IMPORTANCE: This research uses modern artificial intelligence and machine-learning approaches to standardize and automate the interpretation of agar dilution minimum inhibitory concentration testing. Artificial intelligence is currently of significant topical interest to researchers and clinicians. In our manuscript, we demonstrate a use-case in the microbiology laboratory and present validation data for the model's performance against manual interpretation.

Calcineurin promotes adaptation to chronic stress through two distinct mechanisms.

Adaptation to environmental stress requires coordination between stress-defense programs and cell cycle progression. The immediate response to many stressors has been well characterized, but how cells survive in challenging environments long-term is unknown. Here, we investigate the role of the stress-activated phosphatase calcineurin (CN) in adaptation to chronic CaCl2 stress in Saccharomyces cerevisiae. We find that prolonged exposure to CaCl2 impairs mitochondrial function and demonstrate that cells respond to this stressor using two CN-dependent mechanisms - one that requires the downstream transcription factor Crz1 and another that is Crz1-independent. Our data indicate that CN maintains cellular fitness by promoting cell cycle progression and preventing CaCl2-induced cell death. When Crz1 is present, transient CN activation suppresses cell death and promotes adaptation despite high levels of mitochondrial loss. However, in the absence of Crz1, prolonged activation of CN prevents mitochondrial loss and further cell death by upregulating glutathione (GSH) biosynthesis genes thereby mitigating damage from reactive oxygen species. These findings illustrate how cells maintain long-term fitness during chronic stress and suggest that CN promotes adaptation in challenging environments by multiple mechanisms.

Calcineurin promotes adaptation to chronic stress through two distinct mechanisms.

Adaptation to environmental stress requires coordination between stress-defense programs and cell cycle progression. The immediate response to many stressors has been well characterized, but how cells survive in challenging environments long term is unknown. Here, we investigate the role of the stress-activated phosphatase calcineurin (CN) in adaptation to chronic CaCl2 stress in Saccharomyces cerevisiae. We find that prolonged exposure to CaCl2 impairs mitochondrial function and demonstrate that cells respond to this stressor using two CN-dependent mechanisms-one that requires the downstream transcription factor Crz1 and another that is Crz1 independent. Our data indicate that CN maintains cellular fitness by promoting cell cycle progression and preventing CaCl2-induced cell death. When Crz1 is present, transient CN activation suppresses cell death and promotes adaptation despite high levels of mitochondrial loss. However, in the absence of Crz1, prolonged activation of CN prevents mitochondrial loss and further cell death by upregulating glutathione biosynthesis genes thereby mitigating damage from reactive oxygen species. These findings illustrate how cells maintain long-term fitness during chronic stress and suggest that CN promotes adaptation in challenging environments by multiple mechanisms.

Clinical, socio-demographic, and parental correlates of early autism traits in a community cohort of toddlers.

Identifying factors linked to autism traits in the general population may improve our understanding of the mechanisms underlying divergent neurodevelopment. In this study we assess whether factors increasing the likelihood of childhood autism are related to early autistic trait emergence, or if other exposures are more important. We used data from 536 toddlers from London (UK), collected at birth (gestational age at birth, sex, maternal body mass index, age, parental education, parental language, parental history of neurodevelopmental conditions) and at 18 months (parents cohabiting, measures of socio-economic deprivation, measures of maternal parenting style, and a measure of maternal depression). Autism traits were assessed using the Quantitative Checklist for Autism in Toddlers (Q-CHAT) at 18 months. A multivariable model explained 20% of Q-CHAT variance, with four individually significant variables (two measures of parenting style and two measures of socio-economic deprivation). In order to address variable collinearity we used principal component analysis, finding that a component which was positively correlated with Q-CHAT was also correlated to measures of parenting style and socio-economic deprivation. Our results show that parenting style and socio-economic deprivation correlate with the emergence of autism traits at age 18 months as measured with the Q-CHAT in a community sample.

p53 controls choice between apoptotic and non-apoptotic death following DNA damage.

DNA damage can activate apoptotic and non-apoptotic forms of cell death; however, it remains unclear what features dictate which type of cell death is activated. We report that p53 controls the choice between apoptotic and non-apoptotic death following exposure to DNA damage. In contrast to the conventional model, which suggests that p53-deficient cells should be resistant to DNA damage-induced cell death, we find that p53-deficient cells die at high rates following DNA damage, but exclusively using non-apoptotic mechanisms. Our experimental data and computational modeling reveal that non-apoptotic death in p53-deficient cells has not been observed due to use of assays that are either insensitive to cell death, or that specifically score apoptotic cells. Using functional genetic screening - with an analysis that enables computational inference of the drug-induced death rate - we find in p53-deficient cells that DNA damage activates a mitochondrial respiration-dependent form of cell death, called MPT-driven necrosis. Cells deficient for p53 have high basal respiration, which primes MPT-driven necrosis. Finally, using metabolite profiling, we identified mitochondrial activity-dependent metabolic vulnerabilities that can be targeted to potentiate the lethality of DNA damage specifically in p53-deficient cells. Our findings reveal how the dual functions of p53 in regulating mitochondrial activity and the DNA damage response combine to facilitate the choice between apoptotic and non-apoptotic death.

In Vivo Tumorigenicity of the 20q11.21 Amplicon in an Engraftment Model of hPSCs and Differentiated Liver Cells.

Human pluripotent stem cells (hPSCs) are a promising source of somatic cells for clinical applications and disease modelling. However, during culture they accumulate genetic aberrations such as amplification of 20q11.21 which occurs in approximately 20% of extensively cultured hPSC lines and confers a BCL2L1-mediated survival advantage. During the production of the large number of cells required for transplantation and therapy these aberrations may become unavoidable which has important safety implications for therapies and may also impact upon disease modelling. Presently, these risks are poorly understood; whilst it is apparent that large-scale genetic aberrations can pose an oncogenic risk, the risks associated with smaller, more insidious changes have not been fully explored. In this report, the effects of engraftment of human embryonic stem cells (hESCs) and hESC-derived hepatocyte-like cells (HLCs) with and without amplification of the 20q11.21 minimal amplicon and isochromosome 20q (i20q) in SCID-beige mice are presented. The cells were tracked in vivo using a luminescent reporter over a period of approximately four months. Intrasplenic injection of hESCs showed greater engraftment potential and the formation of more severely disruptive lesions in the liver and spleen of animals injected with cells containing 20q11.21 compared with i20q and wild type. HLCs with 20q11.21 engrafted more successfully and formed more severely disruptive lesions than wild type cells or cells with i20q. These results reinforce the notion that karyotyping of therapeutic hPSC is required for transplant, and suggest that screening for known common aberrations is necessary. Further work to identify commonly arising genetic aberrations should be performed and routine screening for hPSCs intended for therapeutic use should be used.

JAK-STAT Signaling in Inflammatory Breast Cancer Enables Chemotherapy-Resistant Cell States.

Inflammatory breast cancer (IBC) is a difficult-to-treat disease with poor clinical outcomes due to high risk of metastasis and resistance to treatment. In breast cancer, CD44+CD24- cells possess stem cell-like features and contribute to disease progression, and we previously described a CD44+CD24-pSTAT3+ breast cancer cell subpopulation that is dependent on JAK2/STAT3 signaling. Here we report that CD44+CD24- cells are the most frequent cell type in IBC and are commonly pSTAT3+. Combination of JAK2/STAT3 inhibition with paclitaxel decreased IBC xenograft growth more than either agent alone. IBC cell lines resistant to paclitaxel and doxorubicin were developed and characterized to mimic therapeutic resistance in patients. Multi-omic profiling of parental and resistant cells revealed enrichment of genes associated with lineage identity and inflammation in chemotherapy-resistant derivatives. Integrated pSTAT3 chromatin immunoprecipitation sequencing and RNA sequencing (RNA-seq) analyses showed pSTAT3 regulates genes related to inflammation and epithelial-to-mesenchymal transition (EMT) in resistant cells, as well as PDE4A, a cAMP-specific phosphodiesterase. Metabolomic characterization identified elevated cAMP signaling and CREB as a candidate therapeutic target in IBC. Investigation of cellular dynamics and heterogeneity at the single cell level during chemotherapy and acquired resistance by CyTOF and single cell RNA-seq identified mechanisms of resistance including a shift from luminal to basal/mesenchymal cell states through selection for rare preexisting subpopulations or an acquired change. Finally, combination treatment with paclitaxel and JAK2/STAT3 inhibition prevented the emergence of the mesenchymal chemo-resistant subpopulation. These results provide mechanistic rational for combination of chemotherapy with inhibition of JAK2/STAT3 signaling as a more effective therapeutic strategy in IBC. SIGNIFICANCE: Chemotherapy resistance in inflammatory breast cancer is driven by the JAK2/STAT3 pathway, in part via cAMP/PKA signaling and a cell state switch, which can be overcome using paclitaxel combined with JAK2 inhibitors.

Heterogeneity and transcriptional drivers of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a heterogeneous disease with limited treatment options. To characterize TNBC heterogeneity, we defined transcriptional, epigenetic, and metabolic subtypes and subtype-driving super-enhancers and transcription factors by combining functional and molecular profiling with computational analyses. Single-cell RNA sequencing revealed relative homogeneity of the major transcriptional subtypes (luminal, basal, and mesenchymal) within samples. We found that mesenchymal TNBCs share features with mesenchymal neuroblastoma and rhabdoid tumors and that the PRRX1 transcription factor is a key driver of these tumors. PRRX1 is sufficient for inducing mesenchymal features in basal but not in luminal TNBC cells via reprogramming super-enhancer landscapes, but it is not required for mesenchymal state maintenance or for cellular viability. Our comprehensive, large-scale, multiplatform, multiomics study of both experimental and clinical TNBC is an important resource for the scientific and clinical research communities and opens venues for future investigation.

Breast cancer prevention by short-term inhibition of TGFß signaling.

Cancer prevention has a profound impact on cancer-associated mortality and morbidity. We previously identified TGFß signaling as a candidate regulator of mammary epithelial cells associated with breast cancer risk. Here, we show that short-term TGFBR inhibitor (TGFBRi) treatment of peripubertal ACI inbred and Sprague Dawley outbred rats induces lasting changes and prevents estrogen- and carcinogen-induced mammary tumors, respectively. We identify TGFBRi-responsive cell populations by single cell RNA-sequencing, including a unique epithelial subpopulation designated secretory basal cells (SBCs) with progenitor features. We detect SBCs in normal human breast tissues and find them to be associated with breast cancer risk. Interactome analysis identifies SBCs as the most interactive cell population and the main source of insulin-IGF signaling. Accordingly, inhibition of TGFBR and IGF1R decrease proliferation of organoid cultures. Our results reveal a critical role for TGFß in regulating mammary epithelial cells relevant to breast cancer and serve as a proof-of-principle cancer prevention strategy.

Insights into Immune Escape During Tumor Evolution and Response to Immunotherapy Using a Rat Model of Breast Cancer.

Animal models are critical for the preclinical validation of cancer immunotherapies. Unfortunately, mouse breast cancer models do not faithfully reproduce the molecular subtypes and immune environment of the human disease. In particular, there are no good murine models of estrogen receptor-positive (ER+) breast cancer, the predominant subtype in patients. Here, we show that Nitroso-N-methylurea-induced mammary tumors in outbred Sprague-Dawley rats recapitulate the heterogeneity for mutational profiles, ER expression, and immune evasive mechanisms observed in human breast cancer. We demonstrate the utility of this model for preclinical studies by dissecting mechanisms of response to immunotherapy using combination TGFBR inhibition and PD-L1 blockade. Short-term treatment of early-stage tumors induced durable responses. Gene expression profiling and spatial mapping classified tumors as inflammatory and noninflammatory, and identified IFNγ, T-cell receptor (TCR), and B-cell receptor (BCR) signaling, CD74/MHC II, and epithelium-interacting CD8+ T cells as markers of response, whereas the complement system, M2 macrophage phenotype, and translation in mitochondria were associated with resistance. We found that the expression of CD74 correlated with leukocyte fraction and TCR diversity in human breast cancer. We identified a subset of rat ER+ tumors marked by expression of antigen-processing genes that had an active immune environment and responded to treatment. A gene signature characteristic of these tumors predicted disease-free survival in patients with ER+ Luminal A breast cancer and overall survival in patients with metastatic breast cancer receiving anti-PD-L1 therapy. We demonstrate the usefulness of this preclinical model for immunotherapy and suggest examination to expand immunotherapy to a subset of patients with ER+ disease. See related Spotlight by Roussos Torres, p. 672.