Signal Signature Research Articles

Investigation of the motif activity of transcription regulators in pancreatic β-like cell subpopulations differentiated from human induced pluripotent stem cells.

Pancreatic β-cells are composed of different subtypes that play a key role in the control of insulin secretion and thereby control glucose homeostasis. In vitro differentiation of human induced pluripotent stem cells (hiPSCs) into 3D spheroids leads to the generation of β-cell subtypes and thus to the development of islet-like structures. Using this cutting-edge cell model, the aim of the study was to decipher the signaling signature that underlines β-cell subtypes, with a focus on the search for the activity of motifs of important transcription regulators (TRs). The investigation was performed using data from previous single-cell sequencing analysis introduced into the integrated system for motif activity response analysis (ISMARA) of transcription regulators. We extracted the matrix of important TRs activated in the β-cell subpopulation and bi-hormonal-like β-cells. Based on these TRs and their targets, we built specific regulatory networks for main cell subpopulations. Our data confirmed the transcriptomic heterogeneity of the β-cell subtype lineage and suggested a mechanism that could account for the differentiation of β-cell subtypes during pancreas development. We do believe that our findings could be instrumental for understanding the mechanisms that affect the balance of β-cell subtypes, leading to impaired insulin secretion in type 2 diabetes.

Detection of medically relevant volatile organic compounds with graphene field-effect transistors and separated by low-frequency spectral and time signatures.

Exhaled human breath contains a mixture of gases including nitrogen, oxygen, carbon dioxide, water vapour and low molecular weight volatile organic compounds (VOCs). Different VOCs detected in human breath condensate have been recently related to several metabolic processes occurring inside body tissues in the pathological state, as candidate biomarkers for monitoring conditions such as lung injury, airway inflammation, immunity dysfunction, infection, and cancer. Current techniques for detecting these compounds include several types of mass spectroscopy, which are highly costly, time-consuming and dependent on trained personnel for sample analysis. The need for fast and label-free biosensors is paving the way towards the design of novel and portable electronic devices for point-of-care diagnosis with VOCs such as E-noses, and based on the measurement of signal signatures derived from their chemical composition. In this paper, we propose a device for VOC detection that was tested inside a controlled gas flow setup, resorting to graphene field-effect transistors (GFETs). Electrical measurements from graphene directly exposed to nitrogen plus VOC vapours involved cyclic measurements for the variation of graphene's resistance and low-frequency spectral noise in order to obtain distinctive signatures of the tested compounds in the time and frequency domains related, respectively, to Gutmann's theory for donor-acceptor chemical species and spectral sub-band analysis.

Cancer predisposition signaling in Beckwith-Wiedemann Syndrome drives Wilms tumor development.

Wilms tumor (WT) exhibits structural and epigenetic changes at chromosome 11p15, which also cause Beckwith-Wiedemann Syndrome (BWS). Children diagnosed with BWS have increased risk for WT. The aim of this study is to identify the molecular signaling signatures in BWS driving these tumors. We performed whole exome sequencing, methylation array analysis, and gene expression analysis on BWS-WT samples. Our data were compared to publicly available nonBWS data. We categorized WT from BWS and nonBWS patients by assessment of 11p15 methylation status and defined 5 groups- control kidney, BWS-nontumor kidney, BWS-WT, normal-11p15 nonBWS-WT, altered-11p15 nonBWS-WT. BWS-WT samples showed single nucleotide variants in BCORL1, ASXL1, ATM and AXL but absence of recurrent gene mutations associated with sporadic WT. We defined a narrow methylation range stratifying nonBWS-WT samples. BWS-WT and altered-11p15 nonBWS-WT showed enrichment of common and unique molecular signatures based on global differential methylation and gene expression analysis. CTNNB1 overexpression and broad range of interactions were seen in the BWS-WT interactome study. While WT predisposition in BWS is well-established, as are 11p15 alterations in nonBWS-WT, this study focused on stratifying tumor genomics by 11p15 status. Further investigation of our findings may identify novel therapeutic targets in WT oncogenesis.

In-situ versus accreted Milky Way globular clusters: a new classification method and implications for cluster formation

ABSTRACT We present a new scheme for the classification of the in-situ and accreted globular clusters (GCs). The scheme uses total energy E and z-component of the orbital angular momentum and is calibrated using the [Al/Fe] abundance ratio. We demonstrate that this classification results in two GC populations with distinct spatial, kinematic, and chemical abundance distributions. The in-situ GCs are distributed within the central 10 kpc of the Galaxy in a flattened configuration aligned with the Milky Way (MW) disc, while the accreted GCs have a wide distribution of distances and a spatial distribution close to spherical. In-situ and accreted GCs have different $\rm [Fe/H]$ distributions with the well-known bimodality present only in the metallicity distribution of the in-situ GCs. Furthermore, the accreted and in-situ GCs are well separated in the plane of $\rm [Al/Fe]-[Mg/Fe]$ abundance ratios and follow distinct sequences in the age–$\rm [Fe/H]$ plane. The in-situ GCs in our classification show a clear disc spin-up signature – the increase of median Vϕ at metallicities −1.3 < [Fe/H] < −1 similar to the spin-up in the in-situ field stars. This signature signals the MW’s disc formation, which occurred ≈11.7−12.7 Gyr ago (or at z ≈ 3.1−5.3) according to in-situ GC ages. In-situ GCs with metallicities of $\rm [Fe/H]\gtrsim -1.3$ were thus born in the MW disc, while lower metallicity in-situ GCs were born during early, turbulent, pre-disc stages of the evolution of the Galaxy and are part of its Aurora stellar component.

Identification, functional characterization and expression pattern of interferon-gamma (IFN-γ) and interferon-gamma receptor 1 (IFNGR1) in Nibea albiflora

Interferon-gamma (IFN-γ) is an inflammatory cytokine that plays a crucial role in regulating both innate and cell-mediated immune responses by binding to a receptor complex made up of IFNGR1 and IFNGR2. In this study, the complete cDNA of IFN-γ and IFNGR1 from Nibea albiflora were cloned and functionally characterized (named NaIFN-γ and NaIFNGR1), whose complete cDNA sequences were 1593 bp and 2792 bp, encoding 201 and 399 amino acids, respectively. Multiple sequence alignment and phylogenetic analysis showed that the concluded amino acids sequences of NaIFN-γ and NaIFNGR1 shared high identity with their teleost orthologues including the IFN-γ signature and nuclear localization signal (NLS) motif in NaIFN-γ and FN Ⅲ domain in NaIFNGR1. Real-time PCR showed that NaIFN-γ and NaIFNGR1 constitutively expressed in all tested tissues, such as the head-kidney, spleen, liver, kidney, gill, muscle, blood, and intestine with the highest expression of NaIFN-γ and NaIFNGR1 appearing in the liver and gill, respectively. After experiencing stimulation with Polyinosinic-polycytidylic acid (Poly (I:C)), Vibrio alginolyticus (V. alginolyticus) or Vibrio parahaemolyticus (V. parahaemolyticus), NaIFN-γ and NaIFNGR1 mRNA were up-regulated with the time-dependent model. Due to the presence of a nuclear localization signal (NLS), the subcellular localization revealed that NaIFN-γ dispersed throughout the cytoplasm and nucleus. NaIFNGR1, as a member of Cytokine receptor family B, was primarily expressed on the cell membrane. When NaIFN-γ and NaIFNGR1 were co-transfected, their fluorescence signals overlapped on the membrane of HEK 293T cells indicating the potential interaction between IFN-γ and IFNGR1. The GST-pull-down results further showed that NaIFN-γ could directly interact with the extracellular region of NaIFNGR1, further confirming the affinity between IFN-γ and IFNGR1. Taken together, the results firstly demonstrated that the NaIFN-γ ligand-receptor system existed in N.albiflora and played a pivotal part in N.albiflora's immune response against pathogenic bacterial infections, which contributed to the better understanding of the role of IFN-γ in the immunomodulatory mechanisms of teleost.

Polarization Criterion in Targeted SETI Observation

In this paper, we propose a novel method for distinguishing extraterrestrial intelligence (ETI) signals from radio frequency interference (RFI) by leveraging polarization features. We exploit the sinusoidal variation of the linearly polarized components of Stokes parameters with the parallactic angle as a characteristic signature of ETI signals, while such linearly polarized components remain relatively stable for terrestrial RFI. Typically, a minimum of 4–8 hr of observation time is required to detect these sinusoidal variations. The polarization approach in the search for extraterrestrial intelligence also enables us to study the radio stellar bursts emitted by M-type stars as ancillary science, which is relevant to assessing the habitability of exoplanets. Compared to the frequency drift method, the polarization method effectively reduces the required observation time for signal identification while improving the signal identification process.

Superior compressive and tensile bi-directional strain sensing capabilities achieved using liquid metal Hybrid-Hydrogels empowered by Machine learning algorithms

Hydrogel-based flexible strain sensors have great potentials for applications in wearable electronics, human–machine interfaces, and soft robotics. Although great efforts have been made on enhancing tensile strain sensing capability of hydrogels, their sensing capabilities under compressive deformation have seldom been explored. Herein, we report a liquid metal-based hybrid hydrogel which achieves high stretchability (2300 %), superior bi-directional responses to both compressive strains (with a gauge factor of 33.43) and tensile strains (with a gauge factor of 9.59), fast response time (190 ms), and excellent durability (>1500 cycles). This conductive hybrid hydrogel with multi-interpenetrating networks is constructed by incorporating liquid metal, graphene oxide, poly-dopamine, and potassium chloride into a polymer double-network of polyacrylamide and poly(3,4-ethylenedioxythiophene): poly (styrene sulfonate). By integrating machine-learning algorithm with the hybrid hydrogel sensors, an intelligent dual-mode handwriting recognition system is developed for perceiving finger touch signals (in compressive-strain mode) and finger bending signals (in tensile-strain mode), with high accuracy (>93 %) and fast recognition time (<1s) when recognizing numbers, letters, and signature signals. Furthermore, this handwriting recognition system demonstrates advanced performance for human–machine interactions (e.g., playing music) and virtual reality interactions. This study offers a promising strategy to develop hydrogel electronics with bidirectional sensing capabilities for diversified practical applications.

Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Trial

Molecular subtyping of breast cancer is based mostly on HR/HER2 and gene expression-based immune, DNA repair deficiency, and luminal signatures. We extend this description via functional protein pathway activation mapping using pre-treatment, quantitative expression data from 139 proteins/phosphoproteins from 736 patients across 8 treatment arms of the I-SPY 2 Trial (ClinicalTrials.gov: NCT01042379). We identify predictive fit-for-purpose, mechanism-of-action-based signatures and individual predictive protein biomarker candidates by evaluating associations with pathologic complete response. Elevated levels of cyclin D1, estrogen receptor alpha, and androgen receptor S650 associate with non-response and are biomarkers for global resistance. We uncover protein/phosphoprotein-based signatures that can be utilized both for molecularly rationalized therapeutic selection and for response prediction. We introduce a dichotomous HER2 activation response predictive signature for stratifying triple-negative breast cancer patients to either HER2 or immune checkpoint therapy response as a model for how protein activation signatures provide a different lens to view the molecular landscape of breast cancer and synergize with transcriptomic-defined signatures.

High‐frequency wide‐angle reflection and refraction method for structural engineering ground‐penetrating radar surveys

AbstractElectromagnetic wave velocity in ground‐penetrating radar (GPR) constant offset data can be estimated via the diffraction hyperbola fitting method. This method is applicable when radargrams contain diffraction events (hyperbolic patterns) caused by scatters in the host smaller or equal to the dominant wavelength. An alternative method for velocity estimation, if no intrusive information is available for a direct correlation, requires the collection of multi‐offset data. The method is quite common for broad geophysical applications; however, it seems not to be fully utilized for engineering applications, such as slabs/walls where thickness estimation and depth of the embedded features are critical requirements for structural assessments. This method would also overcome the limitations in velocity calibration in environments with no hyperbolic signal signatures. The aim of this study is to explore multi‐offset high‐frequency GPR applications, specifically the wide‐angle reflection and refraction method, for structural engineering, to understand whether it is feasible, possible limitations, and advantages. Numerical models reproducing reinforced concrete elements and a cavity wall were analysed to understand the wave behaviour and predict the response prior to testing on real cases. The main purpose is to explore how reinforcing bars can affect the velocity spectra derived from semblance analysis and what the response would be in a case of multi‐layered structure with increasing velocity with depth (cavity wall). The comparison with real cases showed that, despite some intrinsic limitations, high‐frequency multi‐offset approach could be part of standard workflow for all those surveys where no other velocity estimation method is feasible.

Circulating Proteins as Diagnostic Markers in Gastric Cancer

Gastric cancer (GC) is a highly malignant disease affecting humans worldwide and has a poor prognosis. Most GC cases are detected at advanced stages due to the cancer lacking early detectable symptoms. Therefore, there is great interest in improving early diagnosis by implementing targeted prevention strategies. Markers are necessary for early detection and to guide clinicians to the best personalized treatment. The current semi-invasive endoscopic methods to detect GC are invasive, costly, and time-consuming. Recent advances in proteomics technologies have enabled the screening of many samples and the detection of novel biomarkers and disease-related signature signaling networks. These biomarkers include circulating proteins from different fluids (e.g., plasma, serum, urine, and saliva) and extracellular vesicles. We review relevant published studies on circulating protein biomarkers in GC and detail their application as potential biomarkers for GC diagnosis. Identifying highly sensitive and highly specific diagnostic markers for GC may improve patient survival rates and contribute to advancing precision/personalized medicine.

Secure message recovery in presence of the cyber-attack using discrete-time chaotic modulation approach

The secure message recovery problem in presence of cyber-attack is considered in this paper. The message is modulated by a master chaotic system which may be vulnerable to a cyber-attack and then transmitted to a receiver. By designing a novel observer at the receiver side, the message is recovered correctly. All the design process is performed in discrete-time domain which is suitable for digital communications. Besides, there are no restrictions on the message signal and nonlinear term signature matrix which makes the proposed approach more suitable in the real applications. Numerical simulations are introduced to show the feasibility and the superior performance of the proposed scheme in comparison with the conventional methods.

3-D culture of human lung fibroblasts decreases proliferative and increases extracellular matrix remodeling genes.

Fibroblasts are the main producers of extracellular matrix (ECM) responsible for ECM maintenance and repair, a process often disrupted in chronic lung diseases. The accompanying mechanical changes adversely affect resident cells and overall lung function. Numerous models have been used to elucidate fibroblast behavior that are now evolving toward complex three-dimensional (3-D) models incorporating ECM, aiming to replicate the cells' native environment. Little is known about the cellular changes that occur when moving from two-dimensional (2-D) to 3-D cell culture. This study compared the gene expression profiles of primary human lung fibroblasts from seven subjects with normal lung function, that were cultured for 24 h on 2-D collagen I-coated tissue culture plastic and in 3-D collagen I hydrogels, which are commonly used to mimic ECM in various models, from contraction assays to intricate organ-on-a-chip models. Comparing 3-D with 2-D cell culture, 6,771 differentially expressed genes (2,896 up, 3,875 down) were found; enriched gene sets within the downregulated genes, identified through Gene Set Enrichment Analysis and Ingenuity Pathway Analysis, were involved in the initiation of DNA replication which implied downregulation of fibroblast proliferation in 3-D. Observation of cells for 72 h in 2-D and 3-D environments confirmed the reduced progression through the cell cycle in 3-D. A focused analysis, examining the Hippo pathway and ECM-associated genes, showed differential patterns of gene expression in the 3-D versus 2-D culture. Altogether, the transcriptional response of fibroblasts cultured in 3-D indicated inhibition of proliferation, and alterations in Hippo and ECM pathways indicating a complete switch from proliferation to ECM remodeling.NEW & NOTEWORTHY With the introduction of complex three-dimensional (3-D) lung models, comes a need for understanding cellular behavior in these models. We compared gene expression profiles of human lung fibroblasts grown on two-dimensional (2-D) collagen I-coated surfaces with those in 3-D collagen I hydrogels. RNA sequencing and subsequent pathway analyses showed decreased proliferation, increased extracellular matrix (ECM) remodeling, and altered Hippo signaling and ECM deposition-related gene signatures. These findings highlight unique responses of fibroblasts in 3-D models.

AI-enabled crack-length estimation from acoustic emission signal signatures

Abstract This article addresses the classification of fatigue crack length using artificial intelligence (AI) applied to acoustic emission (AE) signals. The AE signals were collected during fatigue of two specimen types. One specimen type had a 1-mm hole for crack initiation. The other specimen type had a 150-micron wide slit of various lengths. Fatigue testing was performed under stress-intensity-factor control to moderate crack advancement. The slit specimen produced AE signals only from crack advancement at the slit tips whereas the 1-mm hole specimens produced AE signals both from crack tip advancement and crack rubbing or clapping. The AE signals were captured with a piezoelectric wafer active sensor (PWAS) array connected to MISTRAS instrumentation and AEwin software. The collected AE signals were preprocessed using time-of-flight filtering and denoising. Choi Williams transform converted time-domain AE-signals into spectrograms. To apply machine learning, the spectrogram images were used as input data for the training, validation, and testing of a GoogLeNet convolutional neural network (CNN). The CNN was trained to sort the AE signals into crack-length classes. CNN performance enhancements, including synthetic data generation and class balancing were developed. A three-class example with crack lengths of (i) 10-12 mm; (ii) 12-14 mm; and (iii) 14-16 mm is provided. Our AI approach was able to classify the AE signals into these three classes with 91% accuracy thus proving that the AE signals contain sufficient information for crack estimation using an AI-enabled approach.

Sting Activation Improves T-Cell Engaging Immunotherapy of Acute Myeloid Leukemia

Background: Despite emerging therapeutic options for Acute myeloid leukemia (AML) patients, for the majority of relapsed/refractory patients the outcome remains poor. Allogeneic stem cell transplantation has proven the power of T cells in eradicating residual leukemic cells, but alternative strategies based on T-cell recruiting bispecifics have so far failed to induce sustained responses. Resistance is mediated by the immunosuppressive tumor-microenvironment and secretion of immune dampening metabolites by AML cells. We hypothesized that combining a CD33-directed T cell engager (CD33 BiTE ® molecule or AMG 330) with a cGAS-STING agonist has the potential to augment anti-leukemic activity. Methods: In vitro co-culture assays of human T cells and AML cell lines for up to 72 h were performed to study the effect of AMG 330 in combination with the physiological STING-agonist 2‘-3‘ cGAMP (cGAMP). The cytotoxicity against the AML cell lines HL-60, MOLM-13 and OCI-AML-3 was assessed by flow cytometry. T-cell proliferation, T-cell degranulation (CD107a), as well as Granzyme B and TRAIL expression were characterized by flow cytometry. The secretion of effector cytokines (IFNy, TNF, IL-2, IFNa2a, CXCL10) was analyzed via CBA and ELISA assays. To better understand how AMG 330 and cGAMP work together, immunoblotting, transcriptomic analysis (bulk RNA-sequencing) and comprehensive CRISPRCas9 knockout-studies were carried out. Results: We observed a significant increase in AMG 330-mediated cytotoxicity of AML target cells upon co-application of cGAMP (Fig1A). The latter observation was enhanced upon prolongation of the culture and was also notable at low effector-to-target ratios. Monotherapy or addition of cGAMP by itself exerted only minor cytotoxicity against AML cells. The increase in AMG 330 mediated cytotoxicity through cGAMP was accompanied by an increase in T-cell proliferation, degranulation, Granzyme B secretion and TRAIL expression. Moreover, we observed a strong increase in secretion of proinflammatory cytokines (IFNy, IL-2 and IFNa2a). Bulk RNA-sequencing of AMG 330 and cGAMP stimulated co-cultures revealed type-I-IFN signature in the target (HL-60) and the effector cell (T cells) cell population. In addition, distinct phenotypes were found in each cell population: T cells demonstrated a marked increase in TNFa, IFNy and GZMB expression through the co-treatment, whereas HL-60 cells displayed an IFNy signaling signature (Fig1B). Importantly, the responsiveness of AML target cells to STING activation in terms of interferon stimulated gene (ISG)-induction was increased by the co-treatment, evidenced by further upregulation of STAT1, IRF7, WARS, CXCL11, IFI16, RSAD2 and CXCL10. An increase in type-I-IFN production and subsequent ISG-induction could also be confirmed on the protein level by measuring IFNα2a and CXCL-10. Knockout-studies revealed that the cGAMP enhanced AMG 330-mediated cytotoxicity was fully dependent on target cell intrinsic STING and IRF3 signaling, but also dependent on functional IFNy and TNFa signaling. Notably, the increased IFNy production by T cells upon cGAMP addition was dependent on functional target cell STING and IFNy signaling. These observations imply a crosstalk between effector and target cells and an intricate interdependence between target cell intrinsic IFNγ- and STING-signaling. Of note, the deletion of the IFNy-receptor in AML target cells also reduced AMG 330-dependent cytotoxicity under steady state conditions. Finally, we demonstrated that the combination of IFNy, TNFa and cGAMP sufficed to induce an apoptotic cell death of AML cells, similar to the cGAMP containing T-cell-HL-60 cocultures. Conclusion: We propose a novel mechanism by which AMG 330-activated T cells prime and sensitize AML target cells in a forward feedback loop towards STING activation, leading to increased type-I-IFN production and induction of ISGs. The beneficial effect of physiological cGAMP in enhancing AMG 330-mediated cytotoxicity was accompanied by the pronounced expression of effector cytokines and an overall cytotoxic T-cell phenotype. We established a key role for interferon gamma in AMG 330-mediated cytotoxicity of AML cells and in rendering AML cells responsive to STING agonism. We are currently conducting in vivoexperiments to further validate our findings.

A CNN-SVM Study Based on the Fusion of Spectrogram and Thermal Imaging Heterogeneous Features for Pig Cough Recognition in Field Situation

Accurate identification of pig cough is essential for comprehensive monitoring and diagnosis of the respiratory health status of pigs. It contributes to stress-free animal health management, reduces pig mortality and improves the economics of farming. Creating a representative multisource signal signature of pig cough is a critical step in achieving automatic recognition of pig cough. For this reason, in this paper, we propose a feature fusion classification method that combines the spectrogram deep features and thermal image deep features to be fed into a support vector machine (SVM) classifier to accomplish cough classification. First, we use a time–frequency transformation algorithm to convert a one-dimensional cough sound signal into a two-dimensional acoustic spectrogram. Then, the corresponding heterogeneous deep features are extracted from the cough spectrogram and thermal image by fine-tuning Lenet-5 and a customized CoughRNet shallow convolutional neural network. Finally, we employ an early fusion technique to align and splice the extracted heterogeneous deep features and feed them into an SVM for the automatic classification task of pig cough. Our study evaluates the classification performance, recognition speed and model size of the proposed deep feature fusion classification network with satisfactory results. Experimental results show that the method achieves 99.77% accuracy in pig cough recognition. This further demonstrates the effectiveness of combining abstract heterogeneous sound and thermal image deep features as a method for automated detection of pig respiratory health.

Identification of tumor-agnostic biomarkers for predicting prostate cancer progression and biochemical recurrence.

The diverse clinical outcomes of prostate cancer have led to the development of gene signature assays predicting disease progression. Improved prostate cancer progression biomarkers are needed as current RNA biomarker tests have varying success for intermediate prostate cancer. Interest grows in universal gene signatures for invasive carcinoma progression. Early breast and prostate cancers share characteristics, including hormone dependence and BRCA1/2 mutations. Given the similarities in the pathobiology of breast and prostate cancer, we utilized the NanoString BC360 panel, comprising the validated PAM50 classifier and pathway-specific signatures associated with general tumor progression as well as breast cancer-specific classifiers. This retrospective cohort of primary prostate cancers (n=53) was stratified according to biochemical recurrence (BCR) status and the CAPRA-S to identify genes related to high-risk disease. Two public cohort (TCGA-PRAD and GSE54460) were used to validate the results. Expression profiling of our cohort uncovered associations between PIP and INHBA with BCR and high CAPRA-S score, as well as associations between VCAN, SFRP2, and THBS4 and BCR. Despite low levels of the ESR1 gene compared to AR, we found strong expression of the ER signaling signature, suggesting that BCR may be driven by ER-mediated pathways. Kaplan-Meier and univariate Cox proportional hazards regression analysis indicated the expression of ESR1, PGR, VCAN, and SFRP2 could predict the occurrence of relapse events. This is in keeping with the pathways represented by these genes which contribute to angiogenesis and the epithelial-mesenchymal transition. It is likely that VCAN works by activating the stroma and remodeling the tumor microenvironment. Additionally, SFRP2 overexpression has been associated with increased tumor size and reduced survival rates in breast cancer and among prostate cancer patients who experienced BCR. ESR1 influences disease progression by activating stroma, stimulating stem/progenitor prostate cancer, and inducing TGF-β. Estrogen signaling may therefore serve as a surrogate to AR signaling during progression and in hormone-refractory disease, particularly in prostate cancer patients with stromal-rich tumors. Collectively, the use of agnostic biomarkers developed for breast cancer stratification has facilitated a precise clinical classification of patients undergoing radical prostatectomy and highlighted the therapeutic potential of targeting estrogen signaling in prostate cancer.

GLP-1R signaling neighborhoods associate with the susceptibility to adverse drug reactions of incretin mimetics

G protein-coupled receptors are important drug targets that engage and activate signaling transducers in multiple cellular compartments. Delineating therapeutic signaling from signaling associated with adverse events is an important step towards rational drug design. The glucagon-like peptide-1 receptor (GLP-1R) is a validated target for the treatment of diabetes and obesity, but drugs that target this receptor are a frequent cause of adverse events. Using recently developed biosensors, we explored the ability of GLP-1R to activate 15 pathways in 4 cellular compartments and demonstrate that modifications aimed at improving the therapeutic potential of GLP-1R agonists greatly influence compound efficacy, potency, and safety in a pathway- and compartment-selective manner. These findings, together with comparative structure analysis, time-lapse microscopy, and phosphoproteomics, reveal unique signaling signatures for GLP-1R agonists at the level of receptor conformation, functional selectivity, and location bias, thus associating signaling neighborhoods with functionally distinct cellular outcomes and clinical consequences.

Integrin signaling is critical for myeloid-mediated support of T-cell acute lymphoblastic leukemia

We previously found that T-cell acute lymphoblastic leukemia (T-ALL) requires support from tumor-associated myeloid cells, which activate Insulin Like Growth Factor 1 Receptor (IGF1R) signaling in leukemic blasts. However, IGF1 is not sufficient to sustain T-ALL in vitro, implicating additional myeloid-mediated signals in leukemia progression. Here, we find that T-ALL cells require close contact with myeloid cells to survive. Transcriptional profiling and in vitro assays demonstrate that integrin-mediated cell adhesion activates downstream focal adhesion kinase (FAK)/ proline-rich tyrosine kinase 2 (PYK2), which are required for myeloid-mediated T-ALL support, partly through activation of IGF1R. Blocking integrin ligands or inhibiting FAK/PYK2 signaling diminishes leukemia burden in multiple organs and confers a survival advantage in a mouse model of T-ALL. Inhibiting integrin-mediated adhesion or FAK/PYK2 also reduces survival of primary patient T-ALL cells co-cultured with myeloid cells. Furthermore, elevated integrin pathway gene signatures correlate with higher FAK signaling and myeloid gene signatures and are associated with an inferior prognosis in pediatric T-ALL patients. Together, these findings demonstrate that integrin activation and downstream FAK/PYK2 signaling are important mechanisms underlying myeloid-mediated support of T-ALL progression.

Malignant Peripheral Nerve Sheath Tumors Activate Distinct Immunosuppressive Pathways Following Radiotherapy and are Associated with Immune Depletion In Vivo

Patients with neurofibromatosis type I, caused by NF1 loss, develop benign plexiform neurofibromas (pNF) in their peripheral nervous system (PNS). Malignant transformation of pNFs into malignant peripheral nerve sheath tumors (MPNSTs) occurs following CDKN2A/B and SUZ12 loss, a process associated with radiotherapy (RT). However, the molecular mechanisms underlying RT responses by different PNS cell types remain unclear. We hypothesized normal peripheral nerve cells, pNFs, and MPNSTs harbor distinct RT responses. Patient derived NF1 WT immortalized peripheral nerve cells (iPNs), NF1 mutant pNF cells, and NF1/CDKN2AB/SUZ12 mutant MPNST cells were used to study RT responses in vitro. CRISPRi was used to assess the functional effects of candidate gene repression. In vitro viability was measured by cell counts. Transcriptomic signatures were measured by bulk RNA-sequencing and integrated with single-cell RNA sequencing (scRNA-seq) data from patient-derived pNF and MPNST resection specimens. Radiation dose response curves revealed pNF cells (IC50 0.61 Gy) were more radiosensitive than MPNST cells (4.15 Gy). WT iPNs, NF1 deficient iPNs, and pNFs cells displayed no difference in cell viability (p = 0.67; t-test) following initiation of 2 Gy x 5 fractions, while MPNST cells were significantly more viable (p = 0.02; t-test). Principal component analysis of bulk RNA-sequencing data at 5 or 14 days following 2 Gy x 5 fractions revealed cell line of origin accounted for the greatest inter-sample variation (64.9% variance), with additional components separating samples based on radiation presence and timing. Using the most variable genes in PCA space to identify markers of RT response, iPNs and pNFs upregulated pro-apoptotic pathways (BAD, DAPK3) at 5 days post-radiation while MPNST cells alone upregulated pro-survival growth factor signaling). At 14 days post radiation, MPNST cells uniquely upregulated TGFβ signaling and interferon response circuits. Incorporation of scRNA-seq data revealed enrichment of growth factor signaling and TGFβ signatures in MPNSTs compared to pNF. Moreover, MPNST harbored significantly fewer immune cells than pNFs (p = 0.008, t-test), suggesting cell-autonomous signaling and crosstalk with the microenvironment are both critical to MPNST radioresistance. Our data indicate additional genetic hits beyond NF1 loss may be required for RT-associated malignant transformation of pNFs and radioresistance in MPNSTs. Analysis of transcriptomic responses to RT suggests that upregulated growth factor signaling and TGFβ-associated immunosuppression are distinct features of MPNST. Future work will focus on CRISPRi screens to unbiasedly nominate functional modifiers of RT response in NF1/CDKN2AB deficient tumors, which may be broadly useful in cancer.

The Genomic Signatures of Linitis Plastica Signal the Entrance into a New Era: Novel Approaches for Diagnosis and Treatment.

Linitis Plastica (LP) is a rare and aggressive tumor with a distinctive development pattern, leading to the infiltration of the gastric wall, the thickening of the gastric folds and a "leather bottle appearance". LP is an extremely heterogeneous tumor caused by mutations in oncogenic and tumor suppressive genes, as well as molecular pathways, along with mutations in stromal cells and proteins related to tight junctions. Elucidating the molecular background of tumorigenesis and clarifying the correlation between cancerous cells and stromal cells are crucial steps toward discovering novel diagnostic methods, biomarkers and therapeutic targets/agents. Surgery plays a pivotal role in LP management, serving both as a palliative and curative procedure. In this comprehensive review, we aim to present all recent data on the molecular background of LP and the novel approaches to its management.