Repurposing statins and phenothiazines to treat chemoresistant neuroblastoma
Ontology highlight
ABSTRACT: Relapse and treatment resistance are common in children with high-risk neuroblastoma, and novel therapies are needed. Conventional drug discovery is slow, expensive, often fails in practice, and consequently falls short in addressing pediatric and rare conditions. In such instances, drug repurposing is a promising strategy. Here, we used two independent in silico prediction tools including machine learning to identify approved drugs for repurposing against neuroblastoma. The combination of statins and phenothiazines showed strong synergistic effects in human neuroblastoma organoids, decreased tumor growth and prolonged survival in MYCN-amplified neuroblastoma patient-derived xenografts. The drug combination altered cholesterol metabolism through two different mechanisms and induced a phenotypic change towards an adrenergic state in vitro, which was associated with enhanced chemosensitivity. Integration of the drug combination into standard-of-care chemotherapy regressed tumors and prolonged survival in chemoresistant patient-derived xenografts. Thus, a combination of safe and approved medications added to standard-of-care chemotherapy outperforms chemotherapy alone in chemoresistant neuroblastoma.
INSTRUMENT(S): Liquid Chromatography MS - positive - reverse phase
PROVIDER: MTBLS13246 | MetaboLights | 2025-11-13
REPOSITORIES: MetaboLights
Dataset's files
Items per page: 5 1 - 4 of 4 |
Similar Datasets
Project description:Here we sought metabolic alterations specifically associated with amplified MYCN as nodes to indirectly target the MYCN oncogene. Liquid chromatography-mass spectrometry-based proteomics identified 7 proteins consistently correlated with MYCN in proteomes from 49 neuroblastoma biopsies and 13 cell lines. Among these were phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme in de novo serine synthesis. MYCN associated with two regions in the PHGDH promoter, supporting transcriptional PHGDH regulation by MYCN. Pulsed stable isotope-resolved metabolomics utilizing 13C-glucose labeling demonstrated higher de novo serine synthesis in MYCN-amplified cells compared to cells with diploid MYCN. An independence of MYCN-amplified cells from exogenous serine and glycine was demonstrated by serine and glycine starvation, which attenuated nucleotide pools and proliferation only in cells with diploid MYCN but did not diminish these endpoints in MYCN-amplified cells. Proliferation was attenuated in MYCN-amplified cells by CRISPR/Cas9-mediated PHGDH knockout or treatment with PHGDH small molecule inhibitors without affecting cell viability. PHGDH inhibitors administered as single-agent therapy to NMRI-Foxn1nu/nu mice harboring patient-derived MYCN-amplified neuroblastoma xenografts slowed tumor growth. However, combining a PHGDH inhibitor with the standard-of-care chemotherapy drug, cisplatin, revealed antagonism of chemotherapy efficacy in vivo. Emergence of chemotherapy resistance was confirmed in the genetic PHGDH knockout model in vitro. Altogether, PHDGH knockout and inhibition by small molecules consistently slows proliferation, but stops short of killing the cells, which then establish resistance to classical chemotherapy. Although PHGDH inhibition with small molecules has produced encouraging results in other preclinical cancer models, this approach must be considered with caution in patients with neuroblastoma.
2020-12-11 | PXD018300 | Pride
Project description:Inhibition of mechanistic target of rapamycin (mTOR) constitutes the standard of care of lymphangioleiomyomatosis (LAM). However, this treatment does not eradicate diseased cells and some patients show progressive decline of lung function. This study provides preclinical evidence for beneficial therapeutic approaches in combination with rapamycin. LAM tumorigenesis is reduced in vivo (ELT3-V3 tumor xenografts) using approved drugs for other human diseases and targeting monoamine oxidase A (MAO-A; clorgyline) or MAO-B (rasagiline).
2019-10-01 | GSE129399 | GEO
Project description:An estimated 284,000 Americans will be diagnosed with breast cancer in 2021. Of these individuals, 15-20% will be diagnosed with basal-like triple-negative breast cancer (TNBC), which is known to be highly metastatic. Chemotherapy is standard of care for TNBC patients, but acquired chemoresistance is a common clinical problem. There is currently a lack of alternative, targeted treatment strategies for TNBC; this study sought to identify novel therapeutic combinations to treat basal-like TNBCs. For these studies, a set of four human basal-like TNBC cell lines was utilized to determine the cytotoxicity profile of 1,363 unique clinically-used drugs. Ten promising therapeutic candidates were identified, and synergism studies were performed in vitro. Two drug combinations that included KPT-330, an XPO1 inhibitor, were synergistic in all four cell lines. In vivo testing of four basal-like patient-derived xenografts identified a combination, KPT-330 and GSK2126458 (a PI3K/mTOR inhibitor), that decreased tumor burden in mice significantly more than monotherapy with either single agent. Bulk and single-cell RNA-sequencing, immunohistochemical studies, and analysis of published genomic datasets found that XPO1 was abundantly expressed in human basal-like TNBC cell lines, patient-derived xenografts, and patient tumor samples; within basal-like patients, XPO1 overexpression was associated with greater rates of metastases. These studies identify a promising new combination therapy for patients with basal-like TNBC.
2021-10-20 | GSE174391 | GEO
Project description:Lacking effective targeted therapies, triple-negative breast cancer (TNBCs) is highly aggressive, metastatic, and clinically challenging breast cancer subtype with worst prognosis. Despite survival dependency on the proteasome pathway genes, the FDA-approved proteasome inhibitors induced minimal clinical response in TNBC patients due to weaker proteasome inhibition. Here, we show that a novel proteasome inhibitor Marizomib (Mzb), inhibited multiple proteasome catalytic activities and induced better anti-tumor response in TNBC cell line and patient-derived xenografts alone and in combination with a standard-of-care chemotherapy, doxorubicin. Mechanistically, Mzb inhibits oxidative phosphorylation (OXPHOS) via PGC-1α suppression in conjunction with proteasome inhibition in TNBC cells. Development of metastatic disease, especially brain metastasis, remains a reason for a greater mortality rate amongst TNBC patients. Mzb reduces lung and brain metastasis in vivo by reducing circulating tumor cells and the expression of multiple epithelial-to-mesenchymal genes. We also demonstrate that Mzb-induced OXPHOS inhibition upregulates glycolysis to fulfill the metabolic demand of TNBC cells and hence, combined inhibition of glycolysis with Mzb leads to a synergistic anti-cancer activity in vivo. Collectively, our data provide a strong rationale for the clinical evaluation of Mzb in primary and metastatic TNBC patients.
2020-05-27 | PXD015141 | Pride
Project description:Background Soft tissue sarcomas (STS) are a highly heterogeneous collection of tumors that arise from primitive mesenchymal cells. Survival outcomes for advanced STS patients remain poor, with effective agents limited primarily to cytotoxic chemotherapies, achieving responses below 15% as the standard of care. Although efforts to understand sarcomagenesis have identified potential biomarkers, the development of effective targeted therapies has been hindered by the diversity of STS subtypes and interpatient tumour heterogeneity. Given the uniquely individualized nature of STS, we hypothesized that the application of an ex vivo drug sensitivity platform, Quadratic Phenotypic Optimization Platform (QPOP), in primary STS patient samples can improve identification of effective drug regimens on a per-patient basis. In this study, we evaluated clinical concordance of QPOP to predict treatment outcomes in an STS cohort, and explored QPOP’s ranking function for drug combination discovery. Methods Freshly dissociated tumor samples were treated with a predesigned array of 155 test combinations to rank and compare all possible therapeutic combinations from a 12-drug set comprising STS standard of care, FDA approved drugs and promising investigational drugs. Concordance analysis was performed by comparing QPOP-defined outcomes with clinical outcomes from either QPOP-guided therapies or prior lines of treatment. Efficacy of the most frequently top-ranked drug combination was evaluated in both cell line and patient-derived models, and potential mechanisms were investigated using transcriptomic, ChIP-qPCR and in vivo studies. Results Across a total of 45 patient samples, QPOP demonstrated a total predictive value of 72.4% and an AUCROC of 74%, highlighting its discriminative ability in predicting treatment response in patients. We identified BETi and pazopanib as most frequently top-ranked in 67.8% of all patient samples, outperforming standard of care ifosfamide and doxorubicin. Validation in a panel of established patient lines and in vivo models supported its synergistic interaction, which shows repressed oncogenic MYC and related pathways. Conclusions Work here provides preliminary clinical evidence for QPOP to predict STS treatment outcomes and scientific rationale for an effective combinatorial therapeutic strategy validated in vivo that may offer new therapeutic options for sarcoma patients.
2025-03-06 | GSE282752 | GEO
Project description:Zhu2015 - Combined gemcitabine and birinapant
in pancreatic cancer cells - basic PD model
Mathematical model to illustrate the
effectiveness of combination chemotherapy involving gemcitabine and
birinapant against pancreatic cancer.
This model is described in the article:
Mechanism-based mathematical
modeling of combined gemcitabine and birinapant in pancreatic
cancer cells.
Zhu X, Straubinger RM, Jusko
WJ.
J Pharmacokinet Pharmacodyn 2015 Oct;
42(5): 477-496
Abstract:
Combination chemotherapy is standard treatment for
pancreatic cancer. However, current drugs lack efficacy for
most patients, and selection and evaluation of new combination
regimens is empirical and time-consuming. The efficacy of
gemcitabine, a standard-of-care agent, combined with
birinapant, a pro-apoptotic antagonist of Inhibitor of
Apoptosis Proteins (IAPs), was investigated in pancreatic
cancer cells. PANC-1 cells were treated with vehicle,
gemcitabine (6, 10, 20 nM), birinapant (50, 200, 500 nM), and
combinations of the two drugs. Temporal changes in cell
numbers, cell cycle distribution, and apoptosis were measured.
A basic pharmacodynamic (PD) model based on cell numbers, and a
mechanism-based PD model integrating all measurements, were
developed. The basic PD model indicated that synergistic
effects occurred in both cell proliferation and death
processes. The mechanism-based model captured key features of
drug action: temporary cell cycle arrest in S phase induced by
gemcitabine alone, apoptosis induced by birinapant alone, and
prolonged cell cycle arrest and enhanced apoptosis induced by
the combination. A drug interaction term Ψ was employed in
the models to signify interactions of the combination when data
were limited. When more experimental information was utilized,
Ψ values approaching 1 indicated that specific mechanisms
of interactions were captured better. PD modeling identified
the potential benefit of combining gemcitabine and birinapant,
and characterized the key interaction pathways. An optimal
treatment schedule of pretreatment with gemcitabine for 24-48 h
was suggested based on model predictions and was verified
experimentally. This approach provides a generalizable modeling
platform for exploring combinations of cytostatic and cytotoxic
agents in cancer cell culture studies.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000668.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000668 | BioModels
Project description:Zhu2015 - combined gemcitabine and birinapant
in pancreatic cancer cells - mechanistic PD model
Mechanistic mathematical model to
illustrate the effectiveness of combination chemotherapy involving
gemcitabine and birinapant against pancreatic cancer.
This model is described in the article:
Mechanism-based mathematical
modeling of combined gemcitabine and birinapant in pancreatic
cancer cells.
Zhu X, Straubinger RM, Jusko
WJ.
J Pharmacokinet Pharmacodyn 2015 Oct;
42(5): 477-496
Abstract:
Combination chemotherapy is standard treatment for
pancreatic cancer. However, current drugs lack efficacy for
most patients, and selection and evaluation of new combination
regimens is empirical and time-consuming. The efficacy of
gemcitabine, a standard-of-care agent, combined with
birinapant, a pro-apoptotic antagonist of Inhibitor of
Apoptosis Proteins (IAPs), was investigated in pancreatic
cancer cells. PANC-1 cells were treated with vehicle,
gemcitabine (6, 10, 20 nM), birinapant (50, 200, 500 nM), and
combinations of the two drugs. Temporal changes in cell
numbers, cell cycle distribution, and apoptosis were measured.
A basic pharmacodynamic (PD) model based on cell numbers, and a
mechanism-based PD model integrating all measurements, were
developed. The basic PD model indicated that synergistic
effects occurred in both cell proliferation and death
processes. The mechanism-based model captured key features of
drug action: temporary cell cycle arrest in S phase induced by
gemcitabine alone, apoptosis induced by birinapant alone, and
prolonged cell cycle arrest and enhanced apoptosis induced by
the combination. A drug interaction term Ψ was employed in
the models to signify interactions of the combination when data
were limited. When more experimental information was utilized,
Ψ values approaching 1 indicated that specific mechanisms
of interactions were captured better. PD modeling identified
the potential benefit of combining gemcitabine and birinapant,
and characterized the key interaction pathways. An optimal
treatment schedule of pretreatment with gemcitabine for 24-48 h
was suggested based on model predictions and was verified
experimentally. This approach provides a generalizable modeling
platform for exploring combinations of cytostatic and cytotoxic
agents in cancer cell culture studies.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000669.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000669 | BioModels
Project description:Mitochondria are gatekeepers of apoptotic processes and mediate drug resistance to several chemotherapy agents used to treat cancer. Neuroblastoma is a common solid cancer in young children with poor clinical outcomes following conventional chemotherapy. We sought druggable mitochondrial protein targets in neuroblastoma cells. Among mitochondria-associated gene targets, we found that high expression of the mitochondrial adenine nucleotide translocase 2 (SLC25A5/ANT2), was a strong predictor of poor neuroblastoma patient prognosis and contributed to a more malignant phenotype in pre-clinical models. Inhibiting this transporter with PENAO reduced cell viability in a panel of neuroblastoma cell lines in a TP53-status-dependent manner. We identified the histone deacetylase inhibitor, suberanilohydroxamic acid (SAHA), as the most effective drug in clinical use against mutant TP53 neuroblastoma cells. SAHA and PENAO synergistically reduced cell viability, and induced apoptosis, in neuroblastoma cells independent of TP53-status. The SAHA and PENAO drug combination significantly delayed tumour progression in pre-clinical neuroblastoma mouse models, suggesting that these clinically advanced inhibitors may be effective in treating the disease.
2022-02-05 | GSE196128 | GEO
Project description:MYCN amplification in neuroblastoma leads to aberrant expression of MYCN oncoprotein, which binds active genes promoting transcriptional amplification. Yet how MYCN coordinates transcription elongation to meet productive transcriptional amplification and which elongation machinery represents MYCN-driven vulnerability remain to be identified. We conducted a targeted screen of transcription elongation factors and identified the super elongation complex (SEC) as a unique vulnerability in MYCN-amplified neuroblastomas. MYCN directly binds EAF1 and recruits SEC to enhance processive transcription elongation. Depletion of EAF1 or AFF1/AFF4, another core subunit of SEC, leads to a global reduction in transcription elongation and elicits selective apoptosis of MYCN-amplified neuroblastoma cells. A combination screen reveals SEC inhibition synergistically potentiates the therapeutic efficacies of FDA-approved BCL2 antagonist ABT-199, in part due to suppression of MCL1 expression, both in MYCN-amplified neuroblastoma cells and in patient-derived xenografts. These findings identify disruption of the MYCN-SEC regulatory axis as a promising therapeutic strategy in neuroblastoma.
2023-05-10 | PXD039332 | Pride
Project description:Purpose: Colorectal cancer (CRC) patients with peritoneal metastases (CRPM) have limited treatment options and the lowest CRC survival rates. We aimed to determine whether organoid testing could help guide precision treatment for CRPM patients, as the clinical utility of prospective, functional drug screening including non-standard agents is unknown. Experimental Design: CRPM organoids (peritonoids) isolated from patients underwent parallel next-generation sequencing and medium-throughput drug panel testing ex vivo to identify specific drug sensitivities for each patient. We measured the utility of such a service including: success of peritonoid generation, time to cultivate peritonoids, reproducibility of the medium-throughput drug testing, and documented changes to clinical therapy as a result of the testing. Results: Peritonoids were successfully generated and validated from 68% (19/28) of patients undergoing standard care. Genomic and drug profiling was completed within 8 weeks and a formal report ranking drug sensitivities was provided to the medical oncology team upon failure of standard care treatment. This resulted in a treatment change for 2 patients, one of whom had a partial response despite previously progressing on multiple rounds of standard care chemotherapy. The barrier to implementing this technology in Australia is the need for drug access and funding for off-label indications. Conclusions: Our approach is feasible, reproducible and can guide novel therapeutic choices in this poor prognosis cohort, where new treatment options are urgently needed. This platform is relevant to many solid organ malignancies.
2020-05-31 | GSE147971 | GEO