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Henneman, A. A.

Publications and source records attributed to Henneman, A. A..

6 recordsLinked to original sources

EGFR upregulation drives signaling reactivation during EGFR inhibition in glioblastoma without broad kinome rewiring

BackgroundEpidermal growth factor receptor (EGFR) amplification occurs in [~]50% of IDH-wildtype glioblastoma (GBM) cases, frequently accompanied by expression of the oncogenic EGFRvIII variant. Although EGFR represents an attractive therapeutic target, EGFR-directed therapies have shown limited clinical efficacy in GBM. Resistance to kinase inhibitors is frequently attributed to activation of compensatory signaling pathways ("kinome rewiring"). We therefore investigated whether EGFR inhibition in GBM induces broad adaptive kinase responses that could be co-targeted to overcome resistance. MethodsWe molecularly profiled 29 patient-derived GBM cell lines for EGFR status and selected five representative models spanning EGFR amplification states for functional analyses. Cells were treated with EGFR inhibitors and responses were assessed using viability assays, time-resolved immunoblotting, and phosphoproteomics (LC-MS/MS) with kinase activity inference. ResultsEGFR inhibitors preferentially impaired viability in EGFR-driven models and transiently reduced EGFR phosphorylation during the initial response. However, partial restoration of EGFR phosphorylation and downstream signaling occurred after 24 hours of inhibitor exposure. Phosphoproteomics revealed no evidence of broad kinome rewiring within this timeframe but instead identified increased EGFR abundance, associated with partial restoration of EGFR pathway activity. The phosphorylated-to-total EGFR ratio remained stable, indicating that increased EGFR abundance may enable persistent residual kinase activity despite continued, but incomplete, target inhibition. ConclusionsEarly responses to EGFR inhibition in GBM were not characterized by broad kinome rewiring but by restoration of EGFR signaling associated with increased EGFR abundance. These findings suggest that adaptive signaling remains largely EGFR-dependent despite inhibitor exposure, identifying regulation of EGFR abundance as a potential contributor to therapeutic resistance. Key points- Early responses to EGFR inhibition occur without evidence of broad kinome rewiring. - EGFR signaling is restored during sustained inhibitor exposure. - Increased EGFR abundance is associated with restoration of pathway activity. Importance of the studyAdaptive resistance to EGFR-targeted therapies in GBM is commonly attributed to activation of alternative signaling pathways. Using patient-derived GBM models and phosphoproteomic profiling, we show that early adaptive responses to EGFR inhibition are not characterized by broad kinome signaling rewiring but instead remain centered on reactivation of EGFR signaling. Our findings suggest that increased EGFR abundance in response to inhibitor exposure may enhance residual EGFR signaling sufficiently to partially restore downstream pathway activity. These results indicate that early adaptive responses to EGFR inhibition may remain largely EGFR-dependent, potentially limiting the effectiveness of strategies primarily aimed at co-targeting alternative signaling pathways. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/744581v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@8d4ea3org.highwire.dtl.DTLVardef@125e3eeorg.highwire.dtl.DTLVardef@9742c0org.highwire.dtl.DTLVardef@9f4fa8_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Boosting the speed and accuracy of protein quantification algorithms in mass spectrometry-based proteomics

Current methods for protein level quantification in mass spectrometry-based proteomics do not scale with the increasing number of samples because of limited system memory and algorithmic complexities. Here we propose a new data structure that supports parsing of input as data stream, improve state of the art quantitation methods in performance by orders of magnitudes, and provide a generic method to boost the precision and accuracy by fragment weighting.

bioinformatics↗

NUAK1 regulates contraction in vascular smooth muscle cells derived from abdominal aortic aneurysm patients

AimAbdominal aortic aneurysms (AAA) are defined as a dilatation of the aortic wall. Impaired contractile ability of vascular smooth muscle cells (vSMC) is a hallmark of AAA. This study investigates the underlying mechanism of altered in vitro contractility of vSMC derived from AAA patients (AAA-SMC) compared to control vSMC (C-SMC). MethodsContractility of AAA-SMC (n=24) and C-SMC (n=8) was measured using Electric Cell- substrate Impedance Sensing. Large variability in AAA-SMC contraction was observed compared to C-SMC contraction, and AAA-SMC were therefore subdivided into low, intermediate (i.e. comparable to C-SMC contraction) and high contracting. To identify novel proteins involved in altered AAA-SMC contraction, a phosphoproteomic analysis was performed. ResultsThe proteomics data showed that Thrombospondin-1, PDZ and LIM domain protein 4 and ATPase plasma membrane Ca2+ transporting 1 expression correlated with vSMC contraction, but knockdown (KD) of these targets did not affect contraction. Next, the phosphoproteomics data identified NUAK family kinase 1 (NUAK1) as a potential regulator of contraction, since its kinase activity correlated with AAA-SMC contraction. NUAK1 regulates Myosin phosphatase targeting subunit 1 (MYPT1) activity by phosphorylation, as confirmed by the correlation between NUAK1 activity and phosphorylation levels of Ser445 and Ser910 on MYPT1. NUAK1 protein and RNA expression correlated with AAA-SMC contraction. Moreover, NUAK1 KD decreased contraction in AAA-SMC, combined with reduced phosphorylation levels of Myosin light chain (pMLC) and Vinculin gene expression, and increased F-actin cytoskeletal filament levels. ConclusionsNUAK1 regulates AAA-SMC contraction. Low NUAK1 expression decreased pMLC, potentially by higher MYPT1 activity, and subsequently reduced contraction. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/629332v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@41c0f0org.highwire.dtl.DTLVardef@e1dd1borg.highwire.dtl.DTLVardef@7b36d7org.highwire.dtl.DTLVardef@14d65b5_HPS_FORMAT_FIGEXP M_FIG C_FIG Elements were modified from Servier Medical Art, licensed under a Creative Common Attribution 3.0 Generic License. https://smart.servier.com/; https://creativecommons.org/licenses/by/3.0/ HighlightsO_LIQuantification of in vitro vascular smooth muscle cells (vSMC) contractile capacity revealed large variation in contraction of vSMC derived from human AAA tissue (AAA- SMC) compared to vSMC derived from healthy aortic biopsies (C-SMC). C_LIO_LIPhosphoproteomic analysis identified NUAK family kinase 1 (NUAK1) as a novel regulator of contraction in AAA-SMC, since its kinase activity and expression levels correlated with AAA-SMC contraction. C_LIO_LINUAK1 regulates contraction in AAA-SMC by regulating Myosin phosphatase targeting subunit 1 (MYPT1) activity through phosphorylation, which subsequently affects phosphorylation levels of Myosin light chain (pMLC), and by affecting Vinculin expression and F-actin cytoskeletal filament levels. C_LIO_LIGaining more insight into NUAK1 function and mechanisms leading to aortic wall weakening can ultimately contribute to better AAA disease prediction and treatment. C_LI

cell biology↗

CellEKT: A robust chemical proteomics workflow to profile cellular target engagement of kinase inhibitors

The human genome encodes 518 protein kinases that are pivotal for drug discovery in various therapeutic areas such as cancer and autoimmune disorders. The majority of kinase inhibitors target the conserved ATP-binding pocket, making it difficult to develop selective inhibitors. To characterize and prioritize kinase-inhibiting drug candidates, efficient methods are desired to determine target engagement across the cellular kinome. In this study, we present CellEKT (Cellular Endogenous Kinase Targeting), an optimized and robust chemical proteomics platform for investigating cellular target engagement of endogenously expressed kinases using the sulfonyl fluoride-based probe XO44 and two new probes ALX005 and ALX011. The optimized workflow enabled the determination of the kinome interaction landscape of covalent and non-covalent drugs across over 300 kinases, expressed as half maximum inhibitory concentration (IC50), which were validated using distinct platforms like phosphoproteomics and NanoBRET. With CellEKT, target engagement profiles were linked to their substrate space. CellEKT has the ability to decrypt drug actions and to guide the discovery and development of drugs. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=188 SRC="FIGDIR/small/616061v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@5dd891org.highwire.dtl.DTLVardef@1353379org.highwire.dtl.DTLVardef@1c67382org.highwire.dtl.DTLVardef@1c964eb_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

INKA, an integrative data analysis pipeline for phosphoproteomic inference of active phosphokinases

Identifying (hyper)active kinases in cancer patient tumors is crucial to enable individualized treatment with specific inhibitors. Conceptually, kinase activity can be gleaned from global protein phosphorylation profiles obtained with mass spectrometry-based phosphoproteomics. A major challenge is to relate such profiles to specific kinases to identify (hyper)active kinases that may fuel growth/progression of individual tumors. Approaches have hitherto focused on phosphorylation of either kinases or their substrates. Here, we combine kinase-centric and substrate-centric information in an Integrative Inferred Kinase Activity (INKA) analysis. INKA utilizes label-free quantification of phosphopeptides derived from kinases, kinase activation loops, kinase substrates deduced from prior experimental knowledge, and kinase substrates predicted from sequence motifs, yielding a single score. This multipronged, stringent analysis enables ranking of kinase activity and visualization of kinase-substrate relation networks in a biological sample. As a proof of concept, INKA scoring of phosphoproteomic data for different oncogene-driven cancer cell lines inferred top activity of implicated driver kinases, and relevant quantitative changes upon perturbation. These analyses show the ability of INKA scoring to identify (hyper)active kinases, with potential clinical significance.

systems biology↗

Proteomic identification of Axc, a novel beta-lactamase with carbapenemase activity in a meropenem-resistant clinical isolate of Achromobacterxylosoxidans

The development of antibiotic resistance during treatment is a threat to patients and their environment. Insight in the mechanisms of resistance development is important for appropriate therapy and infection control. Here, we describe how through the application of mass spectrometry-based proteomics, a novel beta-lactamase Axc was identified as an indicator of acquired carbapenem resistance in a clinical isolate of Achromobacter xylosoxidans.\n\nComparative proteomic analysis of consecutively collected susceptible and a resistant isolates from the same patient revealed that high Axc protein levels were only observed in the resistant isolate. Heterologous expression of Axc in Escherichia coli significantly increased the resistance towards carbapenems. Importantly, direct Axc mediated hydrolysis of imipenem was demonstrated using pH shift assays and 1H-NMR, confirming Axc as a legitimate carbapenemase. Whole genome sequencing revealed that the susceptible and resistant isolates were remarkably similar.\n\nTogether these findings provide a molecular context for the fast development of meropenem resistance in A. xylosoxidans during treatment and demonstrate the use of mass spectrometric techniques in identifying novel resistance determinants.

microbiology↗