Native top down proteomics reveals EGFR ER signaling crosstalk in breast cancer cells dissociates NUTF2 dimers to modulate ER signaling and cell growth
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ABSTRACT: Native top-down characterization of complexoforms in breast cancer cells
Project description:Oligomerization of proteins and their modified forms (proteoforms) produces functional protein complexes 1,2. Complexoforms are complexes that consist of the same set of proteins with different proteoforms 3. The ability to characterize these assemblies within cells is critical to understanding the molecular mechanisms involved in disease and to designing effective drugs. An outstanding biological question is how proteoforms drive function and oligomerization of complexoforms. However, tools to define endogenous proteoform-proteoform/ligand interactions are scarce 4. Here, we present a native top-down proteomics (nTDP) strategy that combines size-exclusion chromatography, nano liquid-chromatography in direct infusion mode, field asymmetric ion mobility spectrometry, and multistage mass spectrometry to identify protein assemblies (≤70 kDa) in breast cancer cells and in cells that overexpress EGFR, a resistance model of estrogen receptor-α (ER-α) targeted therapies. By identifying ~104 complexoforms from 17 protein complexes, our nTDP approach revealed several molecular features of the breast cancer proteome, including EGFR-induced dissociation of nuclear transport factor 2 (NUTF2) assemblies that modulate ER activity. Our findings show that the K4 and K55 posttranslational modification sites discovered with nTDP differentially impact the effects of NUTF2 on the inhibition of the ER signaling pathway. By characterizing endogenous proteoform-proteoform/ligand interactions, we reveal the molecular diversity of complexoforms, which allows us to propose a model for ER drug discovery in the context of designing effective inhibitors to selectively bind and disrupt the actions of targeted ER complexoforms.
Project description:A better understanding of the complex crosstalk among key receptors and signaling pathways involved in cancer progression is needed to improve current therapies. We have investigated in cell models representative of the major subtypes of breast cancer (BC) the interplay between the chemokine CXCL12/CXCR4/ACKR3 and EGF receptor (EGFR) family signaling cascades. These cell lines display a high heterogeneity in expression profiles of CXCR4/ACKR3 chemokine receptors, with a predominant intracellular localization and different proportions of cell surface CXCR4+, ACKR3+ or double-positive cell subpopulations, and display an overall modest activation of oncogenic pathways in response to exogenous CXCL12 alone. Interestingly, we find that in MDA-MB-361 (luminal B subtype, Her2-overexpressing), but not in MCF7 (luminal A) or MDA-MB-231 (triple negative) cells, CXCR4/ACKR3 and EGFR receptor families share signaling components and crosstalk mechanisms to concurrently promote ERK1/2 activation, with a key involvement of the G protein-coupled receptor kinase 2 (GRK2) signaling hub and the cytosolic tyrosine kinase Src. Our findings suggest that in certain BC subtypes, a relevant cooperation between CXCR4/ACKR3 and growth factor receptors takes place to integrate concurrent signals emanating from the tumor microenvironment and foster cancer progression.
Project description:There is a vital need for improved therapeutic strategies that are effective in both primary and metastatic triple-negative breast cancer (TNBC). Current treatment options for TNBC patients are restricted to chemotherapy; however tyrosine kinases are promising druggable targets due to their high expression in multiple TNBC subtypes. Since coexpression of receptor tyrosine kinases (RTKs) can promote signaling crosstalk and cell survival in the presence of kinase inhibitors, it is likely that multiple RTKs will need to be inhibited to enhance therapeutic benefit and prevent resistance. The MET and EGFR receptors are actionable targets due to their high expression in TNBC; however crosstalk between MET and EGFR has been implicated in therapeutic resistance to single agent use of MET or EGFR inhibitors in several cancer types. Therefore it is likely that dual inhibition of MET and EGFR is required to prevent crosstalk signaling and acquired resistance. In this study, we evaluated the heterogeneity of MET and EGFR expression and activation in primary and metastatic TNBC tumorgrafts and determined the efficacy of MET (MGCD265 or crizotinib) and/or EGFR (erlotinib) inhibition against TNBC progression. Here we demonstrate that combined MET and EGFR inhibition with either MGCD265 and erlotinib treatment or crizotinib and erlotinib treatment were highly effective at abrogating tumor growth and significantly decreased the variability in treatment response compared to monotherapy. These results advance our understanding of the RTK signaling architecture in TNBC and demonstrate that combined MET and EGFR inhibition may be a promising therapeutic strategy for TNBC patients.
Project description:MotivationNative top-down proteomics (nTDP) integrates native mass spectrometry (nMS) with top-down proteomics (TDP) to provide comprehensive analysis of protein complexes together with proteoform identification and characterization. Despite significant advances in nMS and TDP software developments, a unified and user-friendly software package for analysis of nTDP data remains lacking.ResultsWe have developed MASH Native to provide a unified solution for nTDP to process complex datasets with database searching capabilities in a user-friendly interface. MASH Native supports various data formats and incorporates multiple options for deconvolution, database searching, and spectral summing to provide a "one-stop shop" for characterizing both native protein complexes and proteoforms.Availability and implementationThe MASH Native app, video tutorials, written tutorials, and additional documentation are freely available for download at https://labs.wisc.edu/gelab/MASH_Explorer/MASHSoftware.php. All data files shown in user tutorials are included with the MASH Native software in the download .zip file.
Project description:Sensorimotor behaviors require processing of behaviorally relevant sensory cues and the ability to select appropriate responses from a vast behavioral repertoire. Modulation by the prefrontal cortex (PFC) is thought to be key for both processes, but the precise role of specific circuits remains unclear. We examined the sensorimotor function of anatomically distinct outputs from a subdivision of the mouse PFC, the anterior cingulate cortex (ACC). Using a visually guided two-choice behavioral paradigm with multiple cue-response mappings, we dissociated the sensory and motor response components of sensorimotor control. Projection-specific two-photon calcium imaging and optogenetic manipulations show that ACC outputs to the superior colliculus, a key midbrain structure for response selection, principally coordinate specific motor responses. Importantly, ACC outputs exert control by reducing the innate response bias of the superior colliculus. In contrast, ACC outputs to the visual cortex facilitate sensory processing of visual cues. Our results ascribe motor and sensory roles to ACC projections to the superior colliculus and the visual cortex and demonstrate for the first time a circuit motif for PFC function wherein anatomically non-overlapping output pathways coordinate complementary but distinct aspects of visual sensorimotor behavior.
Project description:Native mass spectrometry has recently moved alongside traditional structural biology techniques in its ability to provide clear insights into the composition of protein complexes. However, to date, limited software tools are available for the comprehensive analysis of native mass spectrometry data on protein complexes, particularly for experiments aimed at elucidating the composition of an intact protein complex. Here, we introduce ProSight Native as a start-to-finish informatics platform for analyzing native protein and protein complex data. Combining mass determination via spectral deconvolution with a top-down database search and stoichiometry calculations, ProSight Native can determine the complete composition of protein complexes. To demonstrate its features, we used ProSight Native to successfully determine the composition of the homotetrameric membrane complex Aquaporin Z. We also revisited previously published spectra and were able to decipher the composition of a heterodimer complex bound with two noncovalently associated ligands. In addition to determining complex composition, we developed new tools in the software for validating native mass spectrometry fragment ions and mapping top-down fragmentation data onto three-dimensional protein structures. Taken together, ProSight Native will reduce the informatics burden on the growing field of native mass spectrometry, enabling the technology to further its reach.
Project description:We examine how bottom-up (or stimulus-driven) and top-down (or goal-driven) processes govern the distribution of attention in risky choice. In three experiments, participants chose between a certain payoff and the chance of receiving a payoff drawn randomly from an array of eight numbers. We tested the hypothesis that initial attention is driven by perceptual properties of the stimulus (e.g., font size of the numbers), but subsequent choice is goal-driven (e.g., win the best outcome). Two experiments in which task framing (goal driven) and font size (stimulus driven) were manipulated demonstrated that payoffs with the highest values and the largest font sizes had the greatest impact on choice. The third experiment added a number in large font to the array, which could not be an outcome of the gamble (i.e., a distractor). Eye movement and choice data indicated that although the distractor attracted attention, it had no influence on option selection. Together with computational modeling analyses, the results suggest that perceptual salience can induce bottom-up effects of overt selection but that the perceived value of information is the crucial arbiter of intentional control over risky choice.
Project description:Native top-down proteomics allows for both proteoform identification and high-order structure characterization for cellular protein complexes. Unfortunately, tandem MS-based fragmentation efficiencies for such targets are low due to an increase in analyte ion mass and the low ion charge states that characterize native MS data. Multiple fragmentation methods can be integrated in order to increase protein complex sequence coverage, but this typically requires use of specialized hardware and software. Free-radical-initiated peptide sequencing (FRIPS) enables access to charge-remote and electron-based fragmentation channels within the context of conventional CID experiments. Here, we optimize FRIPS labeling for native top-down sequencing experiments. Our labeling approach is able to access intact complexes with TEMPO-based FRIPS reagents without significant protein denaturation or assembly disruption. By combining CID and FRIPS datasets, we observed sequence coverage improvements as large as 50% for protein complexes ranging from 36 to 106 kDa. Fragment ion production in these experiments was increased by as much as 102%. In general, our results indicate that TEMPO-based FRIPS reagents have the potential to dramatically increase sequence coverage obtained in native top-down experiments.
Project description:Native top-down mass spectrometry is a powerful approach for characterizing proteoforms and has recently been applied to provide similarly powerful insights into protein conformation. Current approaches, however, are limited such that structural insights can only be obtained for the entire conformational landscape in bulk or without any direct conformational measurement. We report a new ion-mobility-enabled method for performing native top-down MS in a conformation-specific manner. Our approach identified conformation-linked differences in backbone dissociation for the model protein calmodulin, which simultaneously informs upon proteoform variations and provides structural insights. We also illustrate that our method can be applied to protein-ligand complexes, either to identify components or to probe ligand-induced structural changes.
Project description:Protein complexes exhibit great diversity in protein membership, post-translational modifications and noncovalent cofactors, enabling them to function as the actuators of many important biological processes. The exposition of these molecular features using current methods lacks either throughput or molecular specificity, ultimately limiting the use of protein complexes as direct analytical targets in a wide range of applications. Here, we apply native proteomics, enabled by a multistage tandem MS approach, to characterize 125 intact endogenous complexes and 217 distinct proteoforms derived from mouse heart and human cancer cell lines in discovery mode. The native conditions preserved soluble protein-protein interactions, high-stoichiometry noncovalent cofactors, covalent modifications to cysteines, and, remarkably, superoxide ligands bound to the metal cofactor of superoxide dismutase 2. These data enable precise compositional analysis of protein complexes as they exist in the cell and demonstrate a new approach that uses MS as a bridge to structural biology.