Targeted Degradation of CDK9 Potently Disrupts the MYC Transcriptional Network.

Cyclin-dependent kinase 9 (CDK9) coordinates signaling events that regulate RNA polymerase II (Pol II) pause-release states. It is an important co-factor for transcription factors, such as MYC, that drive aberrant cell proliferation when their expression is deregulated. CDK9 modulation offers an approach for attenuating dysregulation in such transcriptional programs. As a result, numerous drug development campaigns to inhibit CDK9 kinase activity have been pursued. More recently, targeted degradation has emerged as an attractive approach. However, comprehensive evaluation of degradation versus inhibition is still critically needed to assess the biological contexts in which degradation might offer superior therapeutic benefits. We validated that CDK9 inhibition triggers a compensatory mechanism that dampens its effect on MYC expression and found that this feedback mechanism was absent when the kinase is degraded. Importantly, CDK9 degradation is more effective than its inhibition for disrupting MYC transcriptional regulatory circuitry likely through the abrogation of both enzymatic and scaffolding functions of CDK9. Highlights: - KI-CDK9d-32 is a highly potent and selective CDK9 degrader. - KI-CDK9d-32 leads to rapid downregulation of MYC protein and mRNA transcripts levels. - KI-CDK9d-32 represses canonical MYC pathways and leads to a destabilization of nucleolar homeostasis. - Multidrug resistance ABCB1 gene emerged as the strongest resistance marker for the CDK9 PROTAC degrader.

Benchmarking the Immersed Boundary Method for Viscoelastic Flows.

We present and analyze a series of benchmark tests regarding the application of the immersed boundary (IB) method to viscoelastic flows through and around non-trivial, stationary geometries. The IB method is widely used to simulate biological fluid dynamics and other modeling scenarios in which a structure is immersed in a fluid. Although the IB method has been most commonly used to model systems involving viscous incompressible fluids, it also can be applied to visoelastic fluids, and has enabled the study of a wide variety of dynamical problems including the settling of vesicles and the swimming of elastic filaments in fluids modeled by the Oldroyd-B constitutive equation. In the viscoelastic context, however, relatively little work has explored the accuracy or convergence properties of this numerical scheme. Herein, we present benchmarking results for an IB solver applied to viscoelastic flows in and around non-trivial geometries using either the idealized Oldroyd-B constitutive model or the more physcially realistic, polymer-entanglementbased Rolie-Poly constitutive equations. We use two-dimensional numerical test cases along with results from rheology experiments to benchmark the IB method and compare it to more complex finite element and finite volume viscoelastic flow solvers. Additionally, we analyze different choices of regularized delta function and relative Lagrangian grid spacings which allow us to identify and recommend the key choices of these numerical parameters depending on the present flow regime.

Transient crosslinking controls the condensate formation pathway within chromatin networks.

The network structure of densely packed chromatin within the nucleus of eukaryotic cells acts in concert with nonequilibrium processes. Using statistical physics simulations, we explore the control provided by transient crosslinking of the chromatin network by structural-maintenance-of-chromosome (SMC) proteins over (i) the physical properties of the chromatin network and (ii) condensate formation of embedded molecular species. We find that the density and lifetime of transient SMC crosslinks regulate structural relaxation modes and tune the sol-vs-gel state of the chromatin network, which imparts control over the kinetic pathway to condensate formation. Specifically, lower density, shorter-lived crosslinks induce sollike networks and a droplet-fusion pathway, whereas higher density, longer-lived crosslinks induce gellike networks and an Ostwald-ripening pathway.

Depletion Strategies for Crystallized Layers of Two-Dimensional Nanosheets to Enhance Lithium-Ion Conductivity in Polymer Nanocomposites.

The assembly of long-range aligned structures of two-dimensional nanosheets (2DNSs) in polymer nanocomposites (PNCs) is in urgent need for the design of nanoelectronics and lightweight energy-storage materials of high conductivity for electricity or heat. These 2DNS are thin and exhibit thermal fluctuations, leading to an intricate interplay with polymers in which entropic effects can be exploited to facilitate a range of different assemblies. In molecular dynamics simulations of experimentally studied 2DNSs, we show that the layer-forming crystallization of 2DNSs is programmable by regulating the strengths and ranges of polymer-induced entropic depletion attractions between pairs of 2DNSs, as well as between single 2DNSs and a substrate surface, by exclusively tuning the temperature and size of the 2DNS. Enhancing the temperature supports the 2DNS-substrate depletion rather than crystallization of 2DNSs in the bulk, leading to crystallized layers of 2DNSs on the substrate surfaces. On the other hand, the interaction range of the 2DNS-2DNS depletion attraction extends further than the 2DNS-substrate attraction whenever the 2DNS size is well above the correlation length of the polymers, which results in a nonmonotonic dependence of the crystallization layer on the 2DNS size. It is demonstrated that the depletion-tuned crystallization layers of 2DNSs contribute to a conductive channel in which individual lithium ions (Li ions) migrate efficiently through the PNCs. This work provides statistical and dynamical insights into the balance between the 2DNS-2DNS and 2DNS-substrate depletion interactions in polymer-2DNS composites and highlights the possibilities to exploit depletion strategies in order to engineer crystallization processes of 2DNSs and thus to control electrical conductivity.

Patient-specific signaling signatures predict optimal therapeutic combinations for triple negative breast cancer.

Triple negative breast cancer (TNBC) is a heterogeneous group of tumors which lack estrogen receptor, progesterone receptor, and HER2 expression. Targeted therapies have limited success in treating TNBC, thus a strategy enabling effective targeted combinations is an unmet need. To tackle these challenges and discover individualized targeted combination therapies for TNBC, we integrated phosphoproteomic analysis of altered signaling networks with patient-specific signaling signature (PaSSS) analysis using an information-theoretic, thermodynamic-based approach. Using this method on a large number of TNBC patient-derived tumors (PDX), we were able to thoroughly characterize each PDX by computing a patient-specific set of unbalanced signaling processes and assigning a personalized therapy based on them. We discovered that each tumor has an average of two separate processes, and that, consistent with prior research, EGFR is a major core target in at least one of them in half of the tumors analyzed. However, anti-EGFR monotherapies were predicted to be ineffective, thus we developed personalized combination treatments based on PaSSS. These were predicted to induce anti-EGFR responses or to be used to develop an alternative therapy if EGFR was not present.In-vivo experimental validation of the predicted therapy showed that PaSSS predictions were more accurate than other therapies. Thus, we suggest that a detailed identification of molecular imbalances is necessary to tailor therapy for each TNBC. In summary, we propose a new strategy to design personalized therapy for TNBC using pY proteomics and PaSSS analysis. This method can be applied to different cancer types to improve response to the biomarker-based treatment.

System-Level Analysis of the Effects of RPTPs on Cellular Signaling Networks.

Tyrosine phosphorylation regulates signaling network activity downstream of receptor tyrosine kinase (RTK) activation. Receptor protein tyrosine phosphatases (RPTPs) serve to dephosphorylate RTKs and their proximal adaptor proteins, thus serving to modulate RTK activity. While the general function of RPTPs is well understood, the direct and indirect substrates for each RPTP are poorly characterized. Here we describe a method, quantitative phosphotyrosine phosphoproteomics, that enables the identification of specific phosphorylation sites whose phosphorylation levels are altered by the expression and activity of a given RPTP. In a proof-of-concept application, we use this method to highlight several direct or indirect substrate phosphorylation sites for PTPRJ, also known as DEP1, and show their quantitative phosphorylation in the context of wild-type PTPRJ compared to a mutant form of PTPRJ with increased activity, in EGF-stimulated cells. This method is generally applicable to define the signaling network effects of each RPTP in cells or tissues under different physiological conditions.

Statistical Methods for Microrheology of Airway Mucus with Extreme Heterogeneity.

The mucus lining of the human airway epithelium contains two gel-forming mucins, MUC5B and MUC5AC. During progression of cystic fibrosis (CF), mucus hyper-concentrates as its mucin ratio changes, coinciding with formation of insoluble, dense mucus flakes. We explore rheological heterogeneity of this pathology with reconstituted mucus matching three stages of CF progression and particle-tracking of 200 nm and 1 micron diameter beads. We introduce statistical data analysis methods specific to low signal-to-noise data within flakes. Each bead time series is decomposed into: (i) a fractional Brownian motion (fBm) classifier of the pure time-series signal; (ii) high-frequency static and dynamic noise; and (iii) low-frequency deterministic drift. Subsequent analysis focuses on the denoised fBm classifier ensemble from each mucus sample and bead diameter. Every ensemble fails a homogeneity test, compelling clustering methods to assess levels of heterogeneity. The first binary level detects beads within vs. outside flakes. A second binary level detects within-flake bead signals that can vs. cannot be disentangled from the experimental noise floor. We show all denoised ensembles, within- and outside-flakes, fail a homogeneity test, compelling additional clustering; next, all clusters with sufficient data fail a homogeneity test. These levels of heterogeneity are consistent with outcomes from a stochastic phase-separation process, and dictate applying the generalized Stokes-Einstein relation to each bead per cluster per sample, then frequency-domain averaging to assess rheological heterogeneity. Flakes exhibit a spectrum of gel-like and sol-like domains, outside-flake solutions a spectrum of sol-like domains, painting a rheological signature of the phase-separation process underlying flake-burdened mucus.

Polymer Modeling Reveals Interplay between Physical Properties of Chromosomal DNA and the Size and Distribution of Condensin-Based Chromatin Loops.

Transient DNA loops occur throughout the genome due to thermal fluctuations of DNA and the function of SMC complex proteins such as condensin and cohesin. Transient crosslinking within and between chromosomes and loop extrusion by SMCs have profound effects on high-order chromatin organization and exhibit specificity in cell type, cell cycle stage, and cellular environment. SMC complexes anchor one end to DNA with the other extending some distance and retracting to form a loop. How cells regulate loop sizes and how loops distribute along chromatin are emerging questions. To understand loop size regulation, we employed bead-spring polymer chain models of chromatin and the activity of an SMC complex on chromatin. Our study shows that (1) the stiffness of the chromatin polymer chain, (2) the tensile stiffness of chromatin crosslinking complexes such as condensin, and (3) the strength of the internal or external tethering of chromatin chains cooperatively dictate the loop size distribution and compaction volume of induced chromatin domains. When strong DNA tethers are invoked, loop size distributions are tuned by condensin stiffness. When DNA tethers are released, loop size distributions are tuned by chromatin stiffness. In this three-way interaction, the presence and strength of tethering unexpectedly dictates chromatin conformation within a topological domain.

Dissecting signaling regulators driving AXL-mediated bypass resistance and associated phenotypes by phosphosite perturbations.

Receptor tyrosine kinase (RTK)-targeted therapies are often effective but invariably limited by drug resistance. A major mechanism of acquired resistance involves "bypass" switching to alternative pathways driven by non-targeted RTKs that restore proliferation. One such RTK is AXL whose overexpression, frequently observed in bypass resistant tumors, drives both cell survival and associated malignant phenotypes such as epithelial-to-mesenchymal (EMT) transition and migration. However, the signaling molecules and pathways eliciting these responses have remained elusive. To explore these coordinated effects, we generated a panel of mutant lung adenocarcinoma PC9 cell lines in which each AXL intracellular tyrosine residue was mutated to phenylalanine. By integrating measurements of phosphorylation signaling and other phenotypic changes associated with resistance through multivariate modeling, we mapped signaling perturbations to specific resistant phenotypes. Our results suggest that AXL signaling can be summarized into two clusters associated with progressive disease and poor clinical outcomes in lung cancer patients. These clusters displayed favorable Abl1 and SFK motifs and their phosphorylation was consistently decreased by dasatinib. High-throughput kinase specificity profiling showed that AXL likely activates the SFK cluster through FAK1 which is known to complex with Src. Moreover, the SFK cluster overlapped with a previously established focal adhesion kinase (FAK1) signature conferring EMT-mediated erlotinib resistance in lung cancer cells. Finally, we show that downstream of this kinase signaling, AXL and YAP form a positive feedback loop that sustains drug tolerant persister cells. Altogether, this work demonstrates an approach for dissecting signaling regulators by which AXL drives erlotinib resistance-associated phenotypic changes.

Phosphoproteomic Changes Induced by Cell-Derived Matrix and Their Effect on Tumor Cell Migration and Cytoskeleton Remodeling.

Increased fibrotic extracellular matrix (ECM) deposition promotes tumor invasion, which is the first step of the metastatic cascade. Yet, the underlying mechanisms are poorly understood as conventional studies of tumor cell migration are often performed in 2D cultures lacking the compositional and structural complexity of native ECM. Moreover, these studies frequently focus on select candidate pathways potentially overlooking other relevant changes in cell signaling. Here, we combine a cell-derived matrix (CDM) model with phosphotyrosine phosphoproteomic analysis to investigate tumor cell migration on fibrotic ECM relative to standard tissue culture plastic (TCP). Our results suggest that tumor cells cultured on CDMs migrate faster and in a more directional manner than their counterparts on TCP. These changes in migration correlate with decreased cell spreading and increased cell elongation. While the formation of phosphorylated focal adhesion kinase (pFAK)+ adhesion complexes did not vary between TCP and CDMs, time-dependent phosphoproteomic analysis identified that the SRC family kinase LYN may be differentially regulated. Pharmacological inhibition of LYN decreased tumor cell migration and cytoskeletal rearrangement on CDMs and also on TCP, suggesting that LYN regulates tumor cell migration on CDMs in combination with other mechanisms. These data highlight how the combination of physicochemically complex in vitro systems with phosphoproteomics can help identify signaling mechanisms by which the fibrotic ECM regulates tumor cell migration.

Overcoming lung cancer immunotherapy resistance by combining nontoxic variants of IL-12 and IL-2.

Engineered cytokine-based approaches for immunotherapy of cancer are poised to enter the clinic, with IL-12 being at the forefront. However, little is known about potential mechanisms of resistance to cytokine therapies. We found that orthotopic murine lung tumors were resistant to systemically delivered IL-12 fused to murine serum albumin (MSA, IL12-MSA) because of low IL-12 receptor (IL-12R) expression on tumor-reactive CD8+ T cells. IL2-MSA increased binding of IL12-MSA by tumor-reactive CD8+ T cells, and combined administration of IL12-MSA and IL2-MSA led to enhanced tumor-reactive CD8+ T cell effector differentiation, decreased numbers of tumor-infiltrating CD4+ regulatory T cells, and increased survival of lung tumor-bearing mice. Predictably, the combination of IL-2 and IL-12 at therapeutic doses led to significant dose-limiting toxicity. Administering IL-12 and IL-2 analogs with preferential binding to cells expressing Il12rb1 and CD25, respectively, led to a significant extension of survival in mice with lung tumors while abrogating dose-limiting toxicity. These findings suggest that IL-12 and IL-2 represent a rational approach to combination cytokine therapy whose dose-limiting toxicity can be overcome with engineered cytokine variants.

Actuated tissue engineered muscle grafts restore functional mobility after volumetric muscle loss.

Damage that affects large volumes of skeletal muscle tissue can severely impact health, mobility, and quality-of-life. Efforts to restore muscle function by implanting tissue engineered muscle grafts at the site of damage have demonstrated limited restoration of force production. Various forms of mechanical and biochemical stimulation have been shown to have a potentially beneficial impact on graft maturation, vascularization, and innervation. However, these approaches yield unpredictable and incomplete recovery of functional mobility. Here we show that targeted actuation of implanted grafts, via non-invasive transcutaneous light stimulation of optogenetic engineered muscle, restores motor function to levels similar to healthy mice 2 weeks post-injury. Furthermore, we conduct phosphoproteomic analysis of actuated engineered muscle in vivo and in vitro to show that repeated muscle contraction alters signaling pathways that play key roles in skeletal muscle contractility, adaptation to injury, neurite growth, neuromuscular synapse formation, angiogenesis, and cytoskeletal remodeling. Our study uncovers changes in phosphorylation of several proteins previously unreported in the context of muscle contraction, revealing promising mechanisms for leveraging actuated muscle grafts to restore mobility after volumetric muscle loss.

Decrypting the potency of anti-cancer therapeutics by using mass spectrometry to quantify post-translational modifications.

In a recent issue of Science, Zecha et al.1 present decryptM, an approach aimed at defining the mechanisms of action of anti-cancer therapeutics through systems-level analysis of protein post-translational modifications (PTMs). By using a broad range of concentrations, decryptM generates drug response curves for each detected PTM, enabling identification of drug effects at different therapeutic doses.

WSD-0922, a novel brain-penetrant inhibitor of epidermal growth factor receptor, promotes survival in glioblastoma mouse models.

Background: Although the epidermal growth factor receptor (EGFR) is a frequent oncogenic driver in glioblastoma (GBM), efforts to therapeutically target this protein have been largely unsuccessful. The present preclinical study evaluated the novel EGFR inhibitor WSD-0922. Methods: We employed flank and orthotopic patient-derived xenograft models to characterize WSD-0922 and compare its efficacy to erlotinib, a potent EGFR inhibitor that failed to provide benefit for GBM patients. We performed long-term survival studies and collected short-term tumor, plasma, and whole-brain samples from mice treated with each drug. We utilized mass spectrometry to measure drug concentrations and spatial distribution and to assess the impact of each drug on receptor activity and cellular signaling networks. Results: WSD-0922 inhibited EGFR signaling as effectively as erlotinib in in vitro and in vivo models. While WSD-0922 was more CNS penetrant than erlotinib in terms of total concentration, comparable concentrations of both drugs were measured at the tumor site in orthotopic models, and the concentration of free WSD-0922 in the brain was significantly less than the concentration of free erlotinib. WSD-0922 treatment provided a clear survival advantage compared to erlotinib in the GBM39 model, with marked suppression of tumor growth and most mice surviving until the end of the study. WSD-0922 treatment preferentially inhibited phosphorylation of several proteins, including those associated with EGFR inhibitor resistance and cell metabolism. Conclusions: WSD-0922 is a highly potent inhibitor of EGFR in GBM, and warrants further evaluation in clinical studies.

Predictive data-driven modeling of C-terminal tyrosine function in the EGFR signaling network.

The epidermal growth factor receptor (EGFR) has been studied extensively because of its critical role in cellular signaling and association with disease. Previous models have elucidated interactions between EGFR and downstream adaptor proteins or showed phenotypes affected by EGFR. However, the link between specific EGFR phosphorylation sites and phenotypic outcomes is still poorly understood. Here, we employed a suite of isogenic cell lines expressing site-specific mutations at each of the EGFR C-terminal phosphorylation sites to interrogate their role in the signaling network and cell biological response to stimulation. Our results demonstrate the resilience of the EGFR network, which was largely similar even in the context of multiple Y-to-F mutations in the EGFR C-terminal tail, while also revealing nodes in the network that have not previously been linked to EGFR signaling. Our data-driven model highlights the signaling network nodes associated with distinct EGF-driven cell responses, including migration, proliferation, and receptor trafficking. Application of this same approach to less-studied RTKs should provide a plethora of novel associations that should lead to an improved understanding of these signaling networks.

Immunopeptidomics reveals determinants of Mycobacterium tuberculosis antigen presentation on MHC class I.

CD8+ T cell recognition of Mycobacterium tuberculosis (Mtb)-specific peptides presented on major histocompatibility complex class I (MHC-I) contributes to immunity to tuberculosis (TB), but the principles that govern presentation of Mtb antigens on MHC-I are incompletely understood. In this study, mass spectrometry (MS) analysis of the MHC-I repertoire of Mtb-infected primary human macrophages reveals that substrates of Mtb's type VII secretion systems (T7SS) are overrepresented among Mtb-derived peptides presented on MHC-I. Quantitative, targeted MS shows that ESX-1 activity is required for presentation of Mtb peptides derived from both ESX-1 substrates and ESX-5 substrates on MHC-I, consistent with a model in which proteins secreted by multiple T7SSs access a cytosolic antigen processing pathway via ESX-1-mediated phagosome permeabilization. Chemical inhibition of proteasome activity, lysosomal acidification, or cysteine cathepsin activity did not block presentation of Mtb antigens on MHC-I, suggesting involvement of other proteolytic pathways or redundancy among multiple pathways. Our study identifies Mtb antigens presented on MHC-I that could serve as targets for TB vaccines, and reveals how the activity of multiple T7SSs interacts to contribute to presentation of Mtb antigens on MHC-I.

Modeling identifies variability in SARS-CoV-2 uptake and eclipse phase by infected cells as principal drivers of extreme variability in nasal viral load in the 48 h post infection.

The SARS-CoV-2 coronavirus continues to evolve with scores of mutations of the spike, membrane, envelope, and nucleocapsid structural proteins that impact pathogenesis. Infection data from nasal swabs, nasal PCR assays, upper respiratory samples, ex vivo cell cultures and nasal epithelial organoids reveal extreme variabilities in SARS-CoV-2 RNA titers within and between the variants. Some variabilities are naturally prone to clinical testing protocols and experimental controls. Here we focus on nasal viral load sensitivity arising from the timing of sample collection relative to onset of infection and from heterogeneity in the kinetics of cellular infection, uptake, replication, and shedding of viral RNA copies. The sources of between-variant variability are likely due to SARS-CoV-2 structural protein mutations, whereas within-variant population variability is likely due to heterogeneity in cellular response to that particular variant. With the physiologically faithful, agent-based mechanistic model of inhaled exposure and infection from (Chen et al., 2022), we perform statistical sensitivity analyses of the progression of nasal viral titers in the first 0-48 h post infection, focusing on three kinetic mechanisms. Model simulations reveal shorter latency times of infected cells (including cellular uptake, viral RNA replication, until the onset of viral RNA shedding) exponentially accelerate nasal viral load. Further, the rate of infectious RNA copies shed per day has a proportional influence on nasal viral load. Finally, there is a very weak, negative correlation of viral load with the probability of infection per virus-cell encounter, the model proxy for spike-receptor binding affinity.

Antigen discovery for the development of cancer immunotherapy.

Central to successful cancer immunotherapy is effective T cell antitumor immunity. Multiple targeted immunotherapies engineered to invigorate T cell-driven antitumor immunity rely on identifying the repertoire of T cell antigens expressed on the tumor cell surface. Mass spectrometry-based survey of such antigens ("immunopeptidomics") combined with other omics platforms and computational algorithms has been instrumental in identifying and quantifying tumor-derived T cell antigens. In this review, we discuss the types of tumor antigens that have emerged for targeted cancer immunotherapy and the immunopeptidomics methods that are central in MHC peptide identification and quantification. We provide an overview of the strength and limitations of mass spectrometry-driven approaches and how they have been integrated with other technologies to discover targetable T cell antigens for cancer immunotherapy. We highlight some of the emerging cancer immunotherapies that successfully capitalized on immunopeptidomics, their challenges, and mass spectrometry-based strategies that can support their development.

Antibody protection from SARS-CoV-2 respiratory tract exposure and infection.

The COVID-19 pandemic has underscored the need to understand the dynamics of SARS-CoV-2 respiratory infection and protection provided by the immune response. SARS-CoV-2 infections are characterized by a particularly high viral load, and further by the small number of inhaled virions sufficient to generate a high viral titer in the nasal passage a few days after exposure. SARS-CoV-2 specific antibodies (Ab), induced from vaccines, previous infection, or inhaled monoclonal Ab, have proven effective against SARS-CoV-2 infection. Our goal in this work is to model the protective mechanisms that Ab can provide and to assess the degree of protection from individual and combined mechanisms at different locations in the respiratory tract. Neutralization, in which Ab bind to virion spikes and inhibit them from binding to and infecting target cells, is one widely reported protective mechanism. A second mechanism of Ab protection is muco-trapping, in which Ab crosslink virions to domains on mucin polymers, effectively immobilizing them in the mucus layer. When muco-trapped, the continuous clearance of the mucus barrier by coordinated ciliary propulsion entrains the trapped viral load toward the esophagus to be swallowed. We model and simulate the protection provided by either and both mechanisms at different locations in the respiratory tract, parametrized by the Ab titer and binding-unbinding rates of Ab to viral spikes and mucin domains. Our results illustrate limits in the degree of protection by neutralizing Ab alone, the powerful protection afforded by muco-trapping Ab, and the potential for dual protection by muco-trapping and neutralizing Ab to arrest a SARS-CoV-2 infection. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Differential substrate specificity of ERK, JNK, and p38 MAP kinases toward Connexin 43.

Phosphorylation of connexin 43 (Cx43) is an important regulatory mechanism of gap junction (GJ) function. Cx43 is modified by several kinases on over 15 sites within its ∼140 amino acid-long C-terminus (CT). Phosphorylation of Cx43CT on S255, S262, S279, and S282 by ERK has been widely documented in several cell lines, by many investigators. Phosphorylation of these sites by JNK and p38, on the other hand, is not well-established. Indeed, ERK is a kinase activated by growth factors and is upregulated in diseases, such as cancer. JNK and p38, however, have a largely tumor-suppressive function due to their stress-activated and apoptotic role. We investigated substrate specificity of all three MAPKs toward Cx43CT, both in vitro and in two cell lines (MDCK - non-cancerous, epithelial cells and porcine PAECs - pulmonary artery endothelial cells). Cx43 phosphorylation was monitored through gel-shift assays on an SDS-PAGE, immunodetection with phospho-Cx43 antibodies, and LC-MS/MS phosphoproteomic analyses. Our results demonstrate that p38 and JNK specificity differ from each other and from ERK. JNK has a strong preference for S255 and S279, while p38 readily phosphorylates S279 and S282. In addition, while we confirmed that ERK can phosphorylate all four serines (255, 262, 279, and 282), we identified T290 as a novel ERK phosphorylation site. This work underscores the importance of delineating the effects of ERK, JNK, and p38 signaling pathways on Cx43 and GJ function.