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Piersma, S. R.

Publications and source records attributed to Piersma, S. R..

13 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↗

HOOK2 downregulation compromises the tumorigenic and stemness properties of ovarian cancer cells by increasing endoplasmic reticulum stress

Ovarian cancer stands out as one of the tumors with a high mortality rate in women. Therefore, the search for new therapeutic targets is essential to enhance patient prognosis. There is evidence suggesting that Hook2, an adaptor protein involved in microtubule transport, may play a role in cancer, particularly ovarian cancer. This study examines the role of HOOK2 in the progression of ovarian tumors. The findings reveal that a decrease in HOOK2 levels leads to diminished growth and cellular migration in ovarian cancer cells, impeding the in vivo formation of tumors. The reduction of HOOK2 is associated with both an increase in endoplasmic reticulum stress and an elevation in cell death, the latter likely caused by the activation of the unfolded protein response. Moreover, the study observes that the decrease in HOOK2 diminishes the properties of cancer stem cells in ovarian cancer, possibly due to the increase in cell death specifically found within these stem cells. Given the profound impact of reduced HOOK2 levels on ovarian cancer cells, this gene emerges as a promising therapeutic strategy for treating ovarian cancer patients.

cancer biology↗

Integrated Multi-Omics Mapping of Mitochondrial Dysfunction and Substrate Preference in Barth Syndrome Cardiac Tissue

Barth syndrome (BTHS) is a rare X-linked recessively inherited disorder caused by variants in the TAFAZZIN gene, leading to impaired conversion of monolysocardiolipin (MLCL) into mature cardiolipin (CL). Accumulation of MLCL and CL deficiency are diagnostic markers for BTHS. Clinically, BTHS includes cardiomyopathy, skeletal myopathy, neutropenia, and growth delays. Severely affected patients may require early cardiac transplants due to unpredictable cardiac phenotypes. The pathophysiological mechanisms of BTHS are poorly understood, and treatments remain symptomatic. This study analyzed heart samples from five pediatric male BTHS patients (5 months-15 years) and compared them to tissues from 24 non-failing donors (19-71 years) using an integrated omics method combining metabolomics, lipidomics, and proteomics. The analysis confirmed changes in diagnostic markers (CL and MLCL), severe mitochondrial alterations, metabolic shifts, and elevated heart-failure markers. It also revealed significant interindividual differences among BTHS patients. With this study describe a powerful analytical tool for the in-depth analysis of metabolic disorders and a solid foundation for the understanding of BTHS disease phenotypes in cardiac tissues.

molecular biology↗

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↗

Large pan-cancer cell screen coupled to (phospho-) proteomics underscores high-dose vitamin C as a potent anti-cancer agent

Increasing preclinical and clinical evidence has positioned high-dose vitamin C as a promising anti-cancer treatment that merits more clinical attention. Multiple cytotoxicity mechanisms have been described, including pro-oxidant effects. To contribute to the preclinical understanding of the broad pan-cancer effects of high-dose vitamin C in a global manner, we determined the IC50 of a large panel of cancer cell lines (n=51) representing 7 solid tumour types and generated proteome data. The majority of cell lines were highly sensitive (IC50 range 0.036-10mM, mean 1.7 {+/-} 0.4 mM), well below a clinically achievable dose. The proteome data (>5000 proteins per sample), showed that high sensitivity is associated with proliferation, as indicated by functional enrichment of cell cycle, RNA splicing and chromatin organization, while lower sensitivity is linked to extracellular vesicles, glycolysis, fatty acid metabolism and mitochondria. Moreover, (phospho-)proteome analysis of on-treatment vitamin C effects on four pancreatic ductal adenocarcinoma (PDAC) cells dosed at a range of IC50 values (Hs766 T, 2 mM; Capan-2, 0.6 mM; PANC-1, 0.14 mM and Suit-2, 0.1 mM) revealed, next to cell line specific effects, down-modulation of AKT-MTOR signalling and immune suppressive signalling, while IFN- response was enhanced upon vitamin C. Altogether, our comprehensive pharmacological and (phospho-)proteome analysis is the first to assess cancer vulnerabilities and effects of vitamin C on a large cancer cell line panel and underscores the potential of high-dose vitamin C as an anti-cancer agent.

cancer biology↗

DPHL v2: An updated and comprehensive DIA pan-human assay library for quantifying more than 14,000 proteins.

A comprehensive pan-human spectral library is critical for biomarker discovery using mass spectrometry (MS)-based proteomics. DPHL v1, a previous pan-human library built from 1096 data-dependent acquisition (DDA) MS data of 16 human tissue types, allows quantifying 10,943 proteins. However, a major limitation of DPHL v1 is the lack of semi-tryptic peptides and protein isoforms, which are abundant in clinical specimens. Here, we generated DPHL v2 from 1608 DDA-MS data acquired using Orbitrap mass spectrometers. The data included 586 DDA-MS newly acquired from 17 tissue types, while 1022 files were derived from DPHL v1. DPHL v2 thus comprises data from 24 sample types, including several cancer types (lung, breast, kidney, and prostate cancer, among others). We generated four variants of DPHL v2 to include semi-tryptic peptides and protein isoforms. DPHL v2 was then applied to a publicly available colorectal cancer dataset with 286 DIA-MS files. The numbers of identified and significantly dysregulated proteins increased by at least 21.7% and 14.2%, respectively, compared with DPHL v1. Our findings show that the increased human proteome coverage of DPHL v2 provides larger pools of potential protein biomarkers.

bioinformatics↗

Multi-omics analysis reveals distinct non-reversion mechanisms of PARPi resistance in BRCA1- versus BRCA2-deficient mammary tumors

BRCA1 and BRCA2 both function in DNA double-strand break repair by homologous recombination (HR). Due to their HR-defect, BRCA1/2-deficient cancers are sensitive to poly(ADP-ribose) polymerase inhibitors (PARPi) but they eventually acquire resistance. Preclinical studies yielded several PARPi resistance mechanisms that do not involve BRCA1/2 reactivation, but their relevance in the clinic remains elusive. To investigate which BRCA1/2-independent mechanisms drive spontaneous resistance in vivo, we combined molecular profiling with functional analysis of the HR status of matched PARPi-naive and PARPi-resistant mouse mammary tumors harboring large intragenic deletions that prevent functional restoration of BRCA1/2. We observed restoration of HR in 64% of PARPi-resistant BRCA1-deficient tumors but none in the PARPi-resistant BRCA2-deficient tumors. Moreover, we found that 53BP1 loss is the prevalent resistance mechanism in HR-proficient BRCA1-deficient tumors, whereas resistance in BRCA2-deficient tumors is mainly induced by the loss of PARG. Our combined multi-omics analysis catalogued additional genes and pathways potentially involved in modulating PARPi response.

cancer biology↗

The ESX-1 substrate PPE68 has a key function in the ESX-1 mediated secretion in Mycobacterium marinum

Mycobacteria use specialized type VII secretion systems (T7SSs) to secrete proteins across their diderm cell envelope. One of the T7SS subtypes, named ESX-1, is a major virulence determinant in pathogenic species such as Mycobacterium tuberculosis and the fish pathogen Mycobacterium marinum. ESX-1 secretes a variety of substrates, called Esx, PE, PPE and Esp proteins, at least some of which as folded heterodimers. Investigations into the functions of these substrates is problematic, because of the intricate network of co-dependent secretion between several ESX-1 substrates. Here, we describe that the ESX-1 substrate PPE68 is essential for secretion of the highly immunogenic substrate EsxA and EspE via the ESX-1 system in M. marinum. While secreted PPE68 is processed on the cell surface, the majority of cell-associated PPE68 of M. marinum and M. tuberculosis is present in a cytosolic complex with its PE partner and the EspG1 chaperone. Interfering with the binding of EspG1 to PPE68 blocked its export and the secretion of EsxA and EspE. In contrast, esxA is not required for the secretion of PPE68, revealing hierarchy in co-dependent secretion. Remarkably, the final ten residues of PPE68, a negatively charged domain, seem essential for EspE secretion, but not for the secretion of EsxA and PPE68 itself. This indicates that distinctive domains of PPE68 are involved in secretion of the different ESX-1 substrates. Based on these findings, we propose a mechanistic model for the central role of PPE68 in ESX-1 mediated secretion and substrate co-dependence. ImportanceMycobacterium tuberculosis use type VII secretion systems (T7SSs) to secrete proteins across its uniquely hydrophobic diderm cell envelope. A T7SS subtype, called ESX-1, is one of its most important virulence determinants by mediating intracellular survival through phagosomal rupture and subsequent translocation of the mycobacterium to the host cytosol. Identifying the ESX-1 substrate that is responsible for this process is problematic because of the intricate network of co-dependent secretion between ESX-1 substrates. Here, we provide mechanistic insight into the central role of the ESX-1 substrate PPE68 for the secretion of ESX-1 substrates, using the model organism Mycobacterium marinum. Unravelling the mechanism of co-dependent secretion will aid the functional understanding of T7SSs and will allow the analysis of the individual roles of ESX-1 substrates in the virulence caused by this significant human pathogen.

microbiology↗

Feasibility of phosphoproteomics on leftover samples after RNA extraction with guanidinium thiocyanate

In daily practice, different types of biomolecules are usually extracted for large-scale omics analysis with tailored protocols. However, when sample material is limited, an all-in-one strategy is preferable. While lysis of cells and tissues with urea is the accepted standard for phosphoproteomic applications, DNA, RNA and proteins can be simultaneously extracted from small samples using acid guanidinium thiocyanate-phenol-chloroform (AGPC). Use of AGPC for mass spectrometry (MS)-based phosphoproteomics has been reported, but not benchmarked. Here we compared urea-with AGPC-based protein extraction, profiling phosphorylations in the DNA damage response pathway after ionizing irradiation of U2OS cells as proof of principle. On average we identified circa 9000 phosphosites per sample with both extraction methods. Moreover, we observed high similarity of phosphosite characteristics (e.g. 94% shared class 1 identifications) and deduced kinase activities (e.g. ATM, ATR, CHEK1/2, PRKDC). AGPC-based sample extraction can thus replace standard cell lysates for phosphoproteomic workflows and may thus be an attractive way to obtain input material for multiple omics workflows, yielding several data types from a single sample.

molecular biology↗

Standardization and Harmonization of Distributed Multi-National Proteotype Analysis supporting Precision Medicine Studies

Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrated robust, sensitive, and reproducible data generation across eleven sites in nine countries on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality.

molecular biology↗

DPHL: A pan-human protein mass spectrometry library for robust biomarker discovery using Data-Independent Acquisition and Parallel Reaction Monitoring

To answer the increasing need for detecting and validating protein biomarkers in clinical specimens, proteomic techniques are required that support the fast, reproducible and quantitative analysis of large clinical sample cohorts. Targeted mass spectrometry techniques, specifically SRM, PRM and the massively parallel SWATH/DIA technique have emerged as a powerful method for biomarker research. For optimal performance, they require prior knowledge about the fragment ion spectra of targeted peptides. In this report, we describe a mass spectrometric (MS) pipeline and spectral resource to support data-independent acquisition (DIA) and parallel reaction monitoring (PRM) based biomarker studies. To build the spectral resource we integrated common open-source MS computational tools to assemble an open source computational workflow based on Docker. It was then applied to generate a comprehensive DIA pan-human library (DPHL) from 1,096 data dependent acquisition (DDA) MS raw files, and it comprises 242,476 unique peptide sequences from 14,782 protein groups and 10,943 SwissProt-annotated proteins expressed in 16 types of cancer samples. In particular, tissue specimens from patients with prostate cancer, cervical cancer, colorectal cancer, hepatocellular carcinoma, gastric cancer, lung adenocarcinoma, squamous cell lung carcinoma, diseased thyroid, glioblastoma multiforme, sarcoma and diffuse large B-cell lymphoma (DLBCL), as well as plasma samples from a range of hematologic malignancies were collected from multiple clinics in China, the Netherlands and Singapore and included in the resource. This extensive spectral resource was then applied to a prostate cancer cohort of 17 patients, consisting of 8 patients with prostate cancer (PCa) and 9 with benign prostate hyperplasia (BPH), respectively. Data analysis of DIA data from these samples identified differential expressions of FASN, TPP1 and SPON2 in prostate tumors. Thereafter, PRM validation was applied to a larger PCa cohort of 57 patients and the differential expressions of FASN, TPP1 and SPON2 in prostate tumors were validated. As a second application, the DPHL spectral resource was applied to a patient cohort consisting of samples from 19 DLBCL patients and 18 healthy individuals. Differential expressions of CRP, CD44 and SAA1 between DLBCL cases and healthy controls were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supported that DIA-PRM MS pipeline enables robust protein biomarker discoveries.

bioinformatics↗

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↗