21 research outputs found

    RANK signaling increases after anti-HER2 therapy contributing to the emergence of resistance in HER2-positive breast cancer

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    Background: Around 15-20% of primary breast cancers are characterized by HER2 protein overexpression and/or HER2 gene amplification. Despite the successful development of anti-HER2 drugs, intrinsic and acquired resistance represents a major hurdle. This study was performed to analyze the RANK pathway contribution in HER2-positive breast cancer and anti-HER2 therapy resistance. Methods: RANK and RANKL protein expression was assessed in samples from HER2-positive breast cancer patients resistant to anti-HER2 therapy and treatment-naive patients. RANK and RANKL gene expression was analyzed in paired samples from patients treated with neoadjuvant dual HER2-blockade (lapatinib and trastuzumab) from the SOLTI-1114 PAMELA trial. Additionally, HER2-positive breast cancer cell lines were used to modulate RANK expression and analyze in vitro the contribution of RANK signaling to anti-HER2 resistance and downstream signaling. Results: RANK and RANKL proteins are more frequently detected in HER2-positive tumors that have acquired resistance to anti-HER2 therapies than in treatment-naive ones. RANK (but not RANKL) gene expression increased after dual anti-HER2 neoadjuvant therapy in the cohort from the SOLTI-1114 PAMELA trial. Results in HER2-positive breast cancer cell lines recapitulate the clinical observations, with increased RANK expression observed after short-term treatment with the HER2 inhibitor lapatinib or dual anti-HER2 therapy and in lapatinib-resistant cells. After RANKL stimulation, lapatinib-resistant cells show increased NF-κB activation compared to their sensitive counterparts, confirming the enhanced functionality of the RANK pathway in anti-HER2-resistant breast cancer. Overactivation of the RANK signaling pathway enhances ERK and NF-κB signaling and increases lapatinib resistance in different HER2-positive breast cancer cell lines, whereas RANK loss sensitizes lapatinib-resistant cells to the drug. Our results indicate that ErbB signaling is required for RANK/RANKL-driven activation of ERK in several HER2-positive cell lines. In contrast, lapatinib is not able to counteract the NF-κB activation elicited after RANKL treatment in RANK-overexpressing cells. Finally, we show that RANK binds to HER2 in breast cancer cells and that enhanced RANK pathway activation alters HER2 phosphorylation status. Conclusions: Our data support a physical and functional link between RANK and HER2 signaling in breast cancer and demonstrate that increased RANK signaling may contribute to the development of lapatinib resistance through NF-κB activation. Whether HER2-positive breast cancer patients with tumoral RANK expression might benefit from dual HER2 and RANK inhibition therapy remains to be elucidated

    Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

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    IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

    Exploring Cellular Signalling : Perspectives on phosphoproteomic data use and interpretation in a model of drug resistance

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    Every single cell in our body is different from another, caused by their unique set of proteins they behold. This set, or the proteome, is highly dynamic and will change accordingly to the wishes of the cell. This dynamic character makes the study of proteins, or proteomics, an important source of information about our cells, in sickness and in health. But, at the same time it is the biggest hurdle in the field: due to its complexity it is a highly challenging task to study the proteome properly. The most important technique used in proteomics is mass spectrometry (MS). In this thesis I discussed several ways of studying the proteome with higher efficiency by using specific techniques and by re-using published data. Due to their importance in the cell, is it possible to use the study of proteins to study each existing disease. In this thesis I used MS to study drug resistance in cancer. Treatment of cancer cells with drugs will lead to change of shape, number and type of proteins within cells. This can lead to adaptation of cells to the drug, i.e. resistance, after which the tumour is able to re-grow. By comparing the proteome of cells with and without resistance, causes of resistance and weak points of cancer cells can be exposed. With the use of new knowledge of the behaviour of proteins in response to drug treatment and during development of resistance, it might be possible to prevent development of resistance, rather than cure it

    Proteomic tools to study drug function

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    With the ever growing repertoire of drugs being developed, new unbiased methods are urgently needed that allow fast screening of protein targets and off-targets. Ideally, these methods are capable of studying target engagement in a cellular context and provide a link between drug and cellular phenotype. Mass spectrometry based strategies provide an excellent way to study drug-target interactions as well as drug effects in a cellular context with excellent sensitivity and depth. In order to perform unbiased drug target screening several methods have been developed over the last years. In this review, we discuss affinity pull-down approaches to study direct drug-target interaction, methods which use alterations in protein stability as a measure for drug binding and the biological relevance of PTM enrichments to study the effect of inhibitors on cellular signalling

    Exploring Cellular Signalling: Perspectives on phosphoproteomic data use and interpretation in a model of drug resistance

    No full text
    Every single cell in our body is different from another, caused by their unique set of proteins they behold. This set, or the proteome, is highly dynamic and will change accordingly to the wishes of the cell. This dynamic character makes the study of proteins, or proteomics, an important source of information about our cells, in sickness and in health. But, at the same time it is the biggest hurdle in the field: due to its complexity it is a highly challenging task to study the proteome properly. The most important technique used in proteomics is mass spectrometry (MS). In this thesis I discussed several ways of studying the proteome with higher efficiency by using specific techniques and by re-using published data. Due to their importance in the cell, is it possible to use the study of proteins to study each existing disease. In this thesis I used MS to study drug resistance in cancer. Treatment of cancer cells with drugs will lead to change of shape, number and type of proteins within cells. This can lead to adaptation of cells to the drug, i.e. resistance, after which the tumour is able to re-grow. By comparing the proteome of cells with and without resistance, causes of resistance and weak points of cancer cells can be exposed. With the use of new knowledge of the behaviour of proteins in response to drug treatment and during development of resistance, it might be possible to prevent development of resistance, rather than cure it

    Adaptive resistance to EGFR-targeted therapy by calcium signaling in NSCLC cells

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    Targeted therapies against oncogenic receptor tyrosine kinases (RTK) show promising results in the clinic. Unfortunately, despite the initial positive response, most patients develop therapeutic resistance. Most research has focused on acquired resistance occurring after an extensive time of treatment; however, the question remains as to how cells can survive an initial treatment, as early resistance to apoptosis will enable cells to develop any growth-stimulating mechanism. Here, the non-small cell lung cancer (NSCLC) PC9 cell line was used to systematically profile, by mass spectrometry, changes in the proteome, kinome, and phosphoproteome during early treatment with the EGFR inhibitor afatinib. Regardless of the response, initial drug-sensitive cells rapidly adapt to targeted therapy, and within days, cells regained the capacity to proliferate, despite persisting target inhibition. These data reveal a rapid reactivation of mTOR and MAPK signaling pathways after initial inhibition and an increase in abundance and activity of cytoskeleton and calcium signaling- related proteins. Pharmacologic inhibition of reactivated pathways resulted in increased afatinib efficacy. However more strikingly, cells that were restricted from accessing extracellular calcium were extremely sensitive to afatinib treatment. These findings were validated using three additional inhibitors tested in four different NSCLC cell lines, and the data clearly indicated a role for Ca2+ signaling during the development of adaptive resistance. From a therapeutic point of view, the increased inhibitor efficacy could limit or even prevent further resistance development. Implications: Combined targeting of calcium signaling and RTKs may limit drug resistance and improve treatment efficacy

    Metabolomic and proteomic analysis of a clonal insulin-producing beta-cell line (INS-1 832/13).

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    Metabolites generated from fuel metabolism in pancreatic beta-cells control exocytosis of insulin, a process which fails in type 2 diabetes. To identify and quantify these metabolites, global and unbiased analysis of cellular metabolism is required. To this end, polar metabolites, extracted from the clonal 832/13 beta-cell line cultured at 2.8 and 16.7 mM glucose for 48 h, were derivatized followed by identification and quantification, using gas chromatography (GC) and mass spectrometry (MS). After culture at 16.7 mM glucose for 48 h, 832/13 beta-cells exhibited a phenotype reminiscent of glucotoxicity with decreased content and secretion of insulin. The metabolomic analysis revealed alterations in the levels of 7 metabolites derived from glycolysis, the TCA cycle and pentose phosphate shunt, and 4 amino acids. Principal component analysis of the metabolite data showed two clusters, corresponding to the cells cultured at 2.8 and 16.7 mM glucose, respectively. Concurrent changes in protein expression were analyzed by 2-D gel electrophoresis followed by LC-MS/MS. The identities of 86 spots corresponding to 75 unique proteins that were significantly different in 832/13 beta-cells cultured at 16.7 mM glucose were established. Only 5 of these were found to be metabolic enzymes that could be involved in the metabolomic alterations observed. Anticipated changes in metabolite levels in cells exposed to increased glucose were observed, while changes in enzyme levels were much less profound. This suggests that substrate availability, allosteric regulation, and/or post-translational modifications are more important determinants of metabolite levels than enzyme expression at the protein level

    Proteome alterations associated with transformation of multiple myeloma to secondary plasma cell leukemia

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    Plasma cell leukemia is a rare and aggressive plasma cell neoplasm that may either originate de novo (primary PCL) or by leukemic transformation of multiple myeloma (MM) to secondary PCL (sPCL). The prognosis of sPCL is very poor, and currently no standard treatment is available due to lack of prospective clinical studies. In an attempt to elucidate factors contributing to transformation, we have performed super-SILAC quantitative proteome profiling of malignant plasma cells collected from the same patient at both the MM and sPCL stages of the disease. 795 proteins were found to be differentially expressed in the MM and sPCL samples. Gene ontology analysis indicated a metabolic shift towards aerobic glycolysis in sPCL as well as marked down-regulation of enzymes involved in glycan synthesis, potentially mediating altered glycosylation of surface receptors. There was no significant change in overall genomic 5-methylcytosine or 5-hydroxymethylcytosine at the two stages, indicating that epigenetic dysregulation was not a major driver of transformation to sPCL. The present study constitutes the first attempt to provide a comprehensive map of the altered protein expression profile accompanying transformation of MM to sPCL in a single patient, identifying several candidate proteins that can be targeted by currently available small molecule drugs. Our dataset furthermore constitutes a reference dataset for further proteomic analysis of sPCL transformation

    ATG16L1 and IL23R Are Associated With Inflammatory Bowel Diseases but Not With Celiac Disease in The Netherlands

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    BACKGROUND: Inflammatory bowel disease (IBD)-Crohn's disease (CD) and ulcerative colitis (UC)-and celiac disease are intestinal inflammatory disorders with a complex genetic background. Recently, two novel genes were found to be associated with IBD susceptibility. One, an uncommon coding variant (rs11209026) in the gene encoding for the interleukin-23 receptor (IL23R), conferred strong protection against CD. The other, rs2241880 in the autophagy-related 16-like 1 gene (ATG16L1), was associated with CD. We performed a case-control study for the association of IBD with IL23R and ATG16L1 in a Dutch cohort. We also looked at the association of IL23R and ATG16L1 with celiac disease. METHODS: Five hundred eighteen Dutch white IBD patients (311 CD and 207 UC, including 176 trios of patients with both parents), 508 celiac disease patients, and 893 healthy controls were studied for association with the rs11209026 (IL23R) and rs2241880 (ATG16L1) single nucleotide polymorphisms (SNP). RESULTS: The rs11209026 SNP in IL23R had a protective effect for IBD in the case-control analysis (odds ratio [OR] 0.19, 95% confidence interval [CI] 0.10-0.37, P = 6.6E-09). Both CD (OR 0.14, CI 0.06-0.37, P = 3.9E-07) and UC (OR 0.33, CI 0.15-0.73, P = 1.4E-03) were associated with IL23R. For ATG16L1, the rs2241880 SNP was associated with CD susceptibility (OR 1.36, CI 1.12-1.66, P = 0.0017). The population-attributable risk of carrying allele G is 0.24 and is 0.19 for homozygosity for allele G in CD. No association was found between IL23R or ATG16L1 and celiac disease. CONCLUSIONS: We confirmed the association of IL23R and ATG16L1 with CD susceptibility and also the association of IL23R with UC. We found IL23R and ATG16L1 were not associated with celiac disease susceptibility. (Am J Gastroenterol 2008;103:621-627)
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