Reduction of nuclear Y654-p-β-catenin expression through SH3GL2-meditated downregulation of EGFR in chemotolerance TNBC: Clinical and prognostic importance

Triple negative breast cancer (TNBC) originates from a less differentiated ductal cell of breast, which is less sensitive to chemotherapy. The chemotolerance mechanism of TNBC has not yet been studied in detail. For this reason, molecular profiles (expression/genetic/epigenetic) of Y654-p-β-catenin (active) and its kinase epidermal growth factor receptor (EGFR) along with SH3GL2 (regulator of EGFR homeostasis) were compared between neoadjuvant chemotherapy treated (NACT) and pretherapeutic TNBC samples. Reduced nuclear expression of Y654-p-β-catenin protein with low proliferation index and CD44 prevalence showed concordance with reduced expression of EGFR/Y1045-p-EGFR proteins in the NACT samples than the pretherapeutic TNBC samples. Infrequent messenger RNA expression, gene amplification (10–32.5%), and mutation (1%) of EGFR were seen in the TNBC samples irrespective of therapy, suggesting the importance of EGFR protein stabilization in this tumor. The upregulation of SH3GL2 seen in the NACT samples in contrast to the pretherapeutic samples might be due to its promoter hypomethylation, as seen in the quantitative methylation assay. A similar trend of upregulation of SH3GL2 and downregulation of EGFR, Y1045-p-EGFR, Y654-p-β-catenin were seen in the MDA-MB-231 cell line using antharacycline antitumor drugs (doxorubicin/nogalamycin). The NACT patients with reduced expression of Y654-p-β-catenin and/or EGFR and high expression of SH3GL2 showed comparatively better prognosis than the pretherapeutic patients. Thus, our study showed that reduced nuclear expression of Y654-p-β-catenin in NACT samples due to downregulation of EGFR protein through promoter hypomethylation-mediated upregulation of SH3GL2, resulting in low proliferation index/CD44 prevalence with better prognosis of the NACT patients, might have an important role in the chemotolerance of TNBC.     

Binding of FAD and tryptophan to the tryptophan 6‐halogenase Thal is negatively coupled

Flavin‐dependent halogenases require reduced flavin adenine dinucleotide (FADH₂), O₂, and halide salts to halogenate their substrates. We describe the crystal structures of the tryptophan 6‐halogenase Thal in complex with FAD or with both tryptophan and FAD. If tryptophan and FAD were soaked simultaneously, both ligands showed impaired binding and in some cases only the adenosine monophosphate or the adenosine moiety of FAD was resolved, suggesting that tryptophan binding increases the mobility mainly of the flavin mononucleotide moiety. This confirms a negative cooperativity between the binding of substrate and cofactor that was previously described for other tryptophan halogenases. Binding of substrate to tryptophan halogenases reduces the affinity for the oxidized cofactor FAD presumably to facilitate the regeneration of FADH₂ by flavin reductases.     

Large scale maximum average power multiple inference on time-course count data with application to RNA-seq analysis

Experiments that longitudinally collect RNA sequencing (RNA-seq) data can provide transformative insights in biology research by revealing the dynamic patterns of genes. Such experiments create a great demand for new analytic approaches to identify differentially expressed (DE) genes based on large-scale time-course count data. Existing methods, however, are suboptimal with respect to power and may lack theoretical justification. Furthermore, most existing tests are designed to distinguish among conditions based on overall differential patterns across time, though in practice, a variety of composite hypotheses are of more scientific interest. Finally, some current methods may fail to control the false discovery rate. In this paper, we propose a new model and testing procedure to address the above issues simultaneously. Specifically, conditional on a latent Gaussian mixture with evolving means, we model the data by negative binomial distributions. Motivated by Storey (2007) and Hwang and Liu (2010), we introduce a general testing framework based on the proposed model and show that the proposed test enjoys the optimality property of maximum average power. The test allows not only identification of traditional DE genes but also testing of a variety of composite hypotheses of biological interest. We establish the identifiability of the proposed model, implement the proposed method via efficient algorithms, and demonstrate its good performance via simulation studies. The procedure reveals interesting biological insights, when applied to data from an experiment that examines the effect of varying light environments on the fundamental physiology of the marine diatom Phaeodactylum tricornutum.     

An analytical framework for estimating aquatic species density from environmental DNA

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross‐validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.     

Diagnosis of light leaf spot (Pyrenopeziza brassicae) on winter oilseed rape (Brassica napus) in the UK

Light leaf spot lesions were generally first observed as light green areas on leaves of UK winter oilseed rape crops in January or February and later became brittle and bleached. Elongated lesions, which were brown with indistinct edges, developed on stems in the spring and summer, when lesions were also observed on flower buds, pedicels and pods. Development of diagnostic white pustules (spore masses of Pyrenopeziza brassicae, which erupt through surfaces of infected tissues) for confirmation of light leaf spot infection on symptomless plants or plants with indistinct or ambiguous symptoms in the autumn, winter or spring was enhanced by incubating plants in polyethylene bags. In experiments with artificially inoculated plants, glasshouse-grown plants exposed in infected crops and plants sampled from crops, white pustules developed at all incubation temperatures from 2^oC to 20^oC on infected leaves of different cultivars. The period of incubation required before the appearance of pustules decreased as the time that had already elapsed since the initial infection increased. The longest periods of incubation were required at the lowest temperatures (2^oC or 5^oC) but leaves senesced and abscised from plants most quickly at the highest temperatures (15^oC or 20^oC), suggesting that the optimal incubation temperature was between 10^oC and 15^oC.     

Prognostic factors for early relapse in non-metastatic triple negative breast cancer — real world data

BackgroundTriple negative breast cancer (TNBC) has the worst prognosis amongst all subtypes. Studies have shown that the achievement of pathologic complete response in the breast and axilla correlates with improved survival. The aim of this study was to identify clinical or pathological features of real-life TNBC patients with a higher risk of early relapse.Materials and methodsSingle-centre retrospective analysis of 127 women with TNBC, stage II–III, submitted to neoadjuvant treatment and surgery between January 2016 and 2020. Multivariate Cox regression analysis for disease free survival (DFS) at 2 years was performed and statistically significant variables were computed into a prognostic model for early relapse.ResultsAfter 29 months of median follow-up, 105 patients (82.7%) were alive and, in total, 38 patients (29.9%) experienced recurrence. The 2-year DFS was 73% (95% CI: 21.3–22.7). In multivariate analysis, being submitted to neoadjuvant radiotherapy [HR 2.8 (95% CI: 1.2–6.4), p = 0.017] and not achieving pathologic complete response [HR 0.3 (95% CI: 0.1–1.7), p = 0.011] were associated with higher risk of recurrence. In our prognostic model, the presence of at least one of these variables defined a subgroup of patients with a worse 2-year DFS than those without these features (59% vs. 90%, p < 0.001, respectively).ConclusionsIn this real-life non-metastatic TNBC cohort, neoadjuvant radiotherapy (performed due to insufficient clinical response to neoadjuvant chemotherapy or significant toxicity) impacted as an independent prognostic factor for relapse along with the absence of pathologic complete response identifying a subgroup of higher risk patients for early relapse that might merit a closer follow-up.     

MIG‐6 is essential for promoting glucose metabolic reprogramming and tumor growth in triple‐negative breast cancer

Treatment of triple‐negative breast cancer (TNBC) remains challenging due to a lack of effective targeted therapies. Dysregulated glucose uptake and metabolism are essential for TNBC growth. Identifying the molecular drivers and mechanisms underlying the metabolic vulnerability of TNBC is key to exploiting dysregulated cancer metabolism for therapeutic applications. Mitogen‐inducible gene‐6 (MIG‐6) has long been thought of as a feedback inhibitor that targets activated EGFR and suppresses the growth of tumors driven by constitutive activated mutant EGFR. Here, our bioinformatics and histological analyses uncover that MIG‐6 is upregulated in TNBC and that MIG‐6 upregulation is positively correlated with poorer clinical outcomes in TNBC. Metabolic arrays and functional assays reveal that MIG‐6 drives glucose metabolism reprogramming toward glycolysis. Mechanistically, MIG‐6 recruits HAUSP deubiquitinase for stabilizing HIF1α protein expression and the subsequent upregulation of GLUT1 and other HIF1α‐regulated glycolytic genes, substantiating the comprehensive regulation of MIG‐6 in glucose metabolism. Moreover, our mouse studies demonstrate that MIG‐6 regulates GLUT1 expression in tumors and subsequent tumor growth in vivo. Collectively, this work reveals that MIG‐6 is a novel prognosis biomarker, metabolism regulator, and molecular driver of TNBC.     

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

The process by which cerebral perfusion is maintained constant over a wide range of systemic pressures is known as “cerebral autoregulation.” Effective dampening of flow against pressure changes occurs over periods as short as ~15 sec and becomes progressively greater over longer time periods. Thus, slower changes in blood pressure are effectively blunted and faster changes or fluctuations pass through to cerebral blood flow relatively unaffected. The primary difficulty in characterizing the frequency dependence of cerebral autoregulation is the lack of prominent spontaneous fluctuations in arterial pressure around the frequencies of interest (less than ~0.07 Hz or ~15 sec). Oscillatory lower body negative pressure (OLBNP) can be employed to generate oscillations in central venous return that result in arterial pressure fluctuations at the frequency of OLBNP. Moreover, Projection Pursuit Regression (PPR) provides a nonparametric method to characterize nonlinear relations inherent in the system without a priori assumptions and reveals the characteristic non-linearity of cerebral autoregulation. OLBNP generates larger fluctuations in arterial pressure as the frequency of negative pressure oscillations become slower; however, fluctuations in cerebral blood flow become progressively lesser. Hence, the PPR shows an increasingly more prominent autoregulatory region at OLBNP frequencies of 0.05 Hz and below (20 sec cycles). The goal of this approach it to allow laboratory-based determination of the characteristic nonlinear relationship between pressure and cerebral flow and could provide unique insight to integrated cerebrovascular control as well as to physiological alterations underlying impaired cerebral autoregulation (e.g., after traumatic brain injury, stroke, etc.).     

Allosterism and Na++-d-glucose cotransport kinetics in rabbit jejunal vesicles: Compatibility with mixed positive and negative cooperativities in a homo- dimeric or tetrameric structure and experimental evidence for only one transport protein involved

Summary We first present two simple dimeric models of cotransport that may account for all of the kinetics of Na⁺⁺-d-glucose cotransport published so far in the small intestine. Both the sigmoidicity in the Na⁺⁺ activation of transport (positive cooperativity) and the upward deviations from linearity in the Eadie-Hofstee plots relative to glucose concentrations (negative cooperativity) can be rationalized within the concept of allosteric kinetic mechanisms corresponding to either of two models involving sequential or mixed concerted and sequential conformational changes. Such models also allow for 2 Na⁺⁺ 1 S and 1 Na⁺⁺ 1 S stoichiometries of cotransport at low and high substrate concentrations, respectively, and for partial inhibition by inhibitors or substrate analogues. Moreover, it is shown that the dimeric models may present physiological advantages over the seemingly admitted hypothesis of two different cotransporters in that tissue. We next address the reevaluation of Na⁺⁺-d-glucose cotransport kinetics in rabbit intestinal brush border membrane vesicles using stable membrane preparations, a dynamic approach with the Fast Sampling Rapid Filtration Apparatus (FSRFA), and both nonlinear regression and statistical analyses. Under different conditions of temperatures, Na⁺⁺ concentrations, and membrane potentials clamped using two different techniques, we demonstrate that our data can be fully accounted for by the presence of only one carrier in rabbit jejunal brush border membranes since transport kinetics relative to glucose concentrations satisfy simple Michaelis-Menten kinetics. Although supporting a monomeric structure of the cotransporter, such a conclusion would conflict with previous kinetic data and more recent studies implying a polymeric structure of the carrier protein. We thus consider a number of alternatives trying to reconcile the observation of Michaelis-Menten kinetics with allosteric mechanisms of cotransport associated with both positive and negative cooperativities for Na⁺⁺ and glucose binding, respectively. Such models, implying energy storage and release steps through conformational changes associated with ligand binding to an allosteric protein, provide a rational hypothesis to understand the long-time debated question of energy transduction from the Na⁺⁺ electrochemical gradient to the transporter.This research was supported by grant MT-7607 from the Medical Research Council of Canada. One of the authors (A.B.) was supported by a scholarship from the Fonds de la Recherche en Santé du Québec and C. C. was supported by a fellowship from the GRTM. The technical assistance of Mrs. C. Leroy has been greatly appreciated. The authors also thank D.D. Maenz and C. Malo for insightful discussions and C. Gauthier for the art work.     

Coumarin-3-carboxylic acid derivatives as potentiators and inhibitors of recombinant and native N-methyl-d-aspartate receptors

N-Methyl-d-aspartate receptors (NMDARs) are known to be involved in a range of neurological and neurodegenerative disorders and consequently the development of compounds that modulate the function of these receptors has been the subject of intense interest. We have recently reported that 6-bromocoumarin-3-carboxylic acid (UBP608) is a negative allosteric modulator with weak selectivity for GluN2A-containing NMDARs. In the present study, a series of commercially available and newly synthesized coumarin derivatives have been evaluated in a structure-activity relationship (SAR) study as modulators of recombinant NMDAR activity. The main conclusions from this SAR study were that substituents as large as iodo were accommodated at the 6-position and that 6,8-dibromo or 6,8-diiodo substitution of the coumarin ring enhanced the inhibitory activity at NMDARs. These coumarin derivatives are therefore excellent starting points for the development of more potent and GluN2 subunit selective inhibitors, which may have application in the treatment of a range of neurological disorders such as neuropathic pain, epilepsy and depression. Surprisingly, 4-methyl substitution of UBP608 to give UBP714, led to conversion of the inhibitory activity of UBP608 into potentiating activity at recombinant GluN1/GluN2 receptors. UBP714 also enhanced NMDAR mediated field EPSPs in the CA1 region of the hippocampus. UBP714 is therefore a novel template for the development of potent and subunit selective NMDAR potentiators that may have therapeutic applicability in the treatment of patients with cognitive deficits or schizophrenia.