Biology subjects

Halasz, M.

Publications and source records attributed to Halasz, M..

4 recordsLinked to original sources

bioRxiv2024

Diphenyleneiodonium chloride inhibits MYCN-amplified neuroblastoma by targeting MYCN induced mitochondrial alterations

High-risk neuroblastoma is one of the most lethal childhood cancers. Half of these tumors are driven by MYCN gene amplification (MNA). Despite intensive chemo- and radiotherapy, only 40% of patients survive, and they often suffer from severe long-term side effects of these genotoxic treatments. Thus, new therapies are needed that are less toxic and more efficacious. Here, we identified diphenyleneiodonium (DPI) as a tool compound that preferentially targets MNA neuroblastoma. Using proteomic assays we investigated the DPI mode of action, finding that DPI induces the proteasomal degradation of MYCN and could reverse some alterations induced by high levels of MYCN. These include profound changes in the expression of proteins participating in the mitochondrial electron transport chain. Metabolic and biological assays suggested that alterations in mitochondrial function and the associated production of reactive oxygen species (ROS) are critical DPI targets in the context of MNA. DPI reduced the survival, and malignant transformation of neuroblastoma across a panel of cell lines at clinically achievable concentrations. DPI also shrank tumors and prevented metastatic spread in zebrafish models of MYCN-driven neuroblastoma. These findings suggest that processes impacted by complex I inhibitors could be valuable new targets for the development of non-genotoxic drugs against high-risk MNA neuroblastoma. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/619268v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@167e953org.highwire.dtl.DTLVardef@10749e4org.highwire.dtl.DTLVardef@1842598org.highwire.dtl.DTLVardef@c05d82_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

MYCN inhibits TrkC-mediated differentiation in neuroblastoma cells via disruption of the PKA signalling pathway

Neuroblastoma is a complex paediatric cancer with a spectrum of clinical outcomes ranging from spontaneous regression to aggressive metastatic disease. Low-risk patients achieve over 90% survival with no or minimal treatment, while high-risk patients face less than 50% survival despite intensive multimodal therapy. Half of the high-risk cases harbour amplification of the MYCN oncogene. In addition to MYCN status, Trk receptors have also been linked to prognosis. TrkA expression is seen with low-risk cases while TrkB expression often occurs in high-risk MYCN-amplified NB. While TrkA and TrkB are well studied in NB, the role of TrkC in neuroblastoma genesis is not clear. Therefore, this study investigates the interplay between MYCN status and NT-3/TrkC signalling in neuroblastoma. Using a panel of neuroblastoma cell lines with varying MYCN levels, we found that TrkC activation leads to neuronal differentiation of MYCN non-amplified cells, whereas it promotes proliferation of MYCN-amplified cells. Temporal phosphoproteomics revealed differential activation of the PKA pathway, which was crucial for TrkC-mediated differentiation. Manipulating the PKA pathway altered cell fate outcomes, underscoring its role. In MYCN-amplified cells, MYCN knockdown increased PKA and CREB activity, shifting the phenotype towards differentiation. Analysis of neuroblastoma patient data showed lower expression of PKA pathway genes in MYCN-amplified tumours. Additionally, miR-221, upregulated by MYCN, was identified as a suppressor of the PKA/CREB pathway. These findings highlight the context-dependent nature of NT-3/TrkC signalling influenced by MYCN; and suggest therapeutic potential in targeting the PKA pathway to induce differentiation of high-risk MYCN-amplified neuroblastoma.

cancer biology↗

bioRxiv2024

OXPHOS TARGETING OF MYCN-AMPLIFIED NEUROBLASTOMA

SummaryHigh risk - neuroblastoma (HR-NB) is a pediatric solid tumor with high lethality. Half of HR-NB are driven by MYCN gene amplification (MNA). These HR-NBs require high dosage chemotherapy and often relapse. Moreover, current therapies can cause severe long-term side effects and new therapies are urgently needed. This study investigates a novel therapeutic approach targeting the metabolic vulnerabilities of MNA NB cells. We discovered that Diphenyleneiodonium chloride (DPI), an inhibitor of flavoprotein enzymes and mitochondrial complex I, synergizes with mitoquinone mesylate (MitoQ), a mitochondria-targeted antioxidant in 2D and 3D in vitro models of NB. Similarly to DPI, MitoQ affects MNA cells in a MYCN-dependent fashion, being more toxic when MYCN levels are high. Furthermore, low nanomolar concentrations of MitoQ significantly decrease MYCN protein expression and induce differentiation of MNA cells. The DPI and MitoQ combination further synergizes with vincristine, a chemotherapeutic agent used in NB treatment. Phosphoproteomics and proteomics analysis suggests that the drug combination induces MNA NB cell death by arresting the cell cycle and inhibiting oxidative phosphorylation (OXPHOS) in the mitochondria. Thus, interference with mitochondrial metabolism may represent an effective strategy to enhance the activity of chemotherapeutic drugs in MNA-NB.

cancer biology↗

bioRxiv2020

Model-based identification of the crosstalks and feedbacks that determine the doxorubicin response dynamics of the JNK-p38-p53 network

Cellular responses to perturbations and drugs are determined by interconnected networks, rather than linear pathways. Individually, the JNK, p38 and p53 stress and DNA-damage response networks are well understood and regulate critical cell-fate decisions, such as apoptosis, in response to many chemotherapeutical agents, such as doxorubicin. To better understand how interactions between these pathways determine the dynamic behaviour of the entire network, we constructed a data-driven mathematical model. This model contains mechanistic details about the kinase cascades that activate JNK, p38, AKT and p53, and free parameters that describe possible interactions between these pathways. Fitting this model to experimental time-course perturbation data (five time-courses with six time-points under five different conditions), identified specific network interactions that can explain the observed network responses. JNK emerged as an important control node. JNK exhibited a positive feedback loop, was tightly controlled by negative feedback and crosstalk from p38 and AKT, respectively, and was the strongest activator of p53. Compared to static network reconstruction methods, such as modular response analysis, the model-based approach identifies biochemical mechanisms and explains the dynamic control of cell signalling.

systems biology↗