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Abstract 3106: Targeting vitamin D signalling in metastatic neuroblastoma

2019· article· en· W4251150431 on OpenAlexaff
Yagnesh Ladumor, Bo Kyung A. Seong, Robin Hallett, Teresa Adderley, Yingying Wang, Lynn Kee, David L. Kaplan, Meredith S. Irwin

Bibliographic record

VenueClinical Research (Excluding Clinical Trials) · 2019
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsCalcipotriolCalcitriol receptorCancer researchMedicineCancerMetastasisInternal medicineIn vivoNeuroblastomaVitamin D and neurologyCell cultureOncologyEndocrinologyBiologyImmunologyGenetics

Abstract

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Background: Neuroblastoma (NB) is the most common extra-cranial solid tumor and the most frequent cause of cancer-related deaths in children. More than half of patients with NB have metastases and their survival is <50%, and only 5% after relapse. Currently, there are no therapies that specifically target metastatic NB and there is a lack of NB models that recapitulate the sites and burden of metastases observed in patients.Methods: To study metastatic NB, we have developed a mouse model using in vivo selection of SKNAS cells that metastasize following intra-cardiac injection. We isolated subpopulations from bone and brain with enhanced metastatic properties and compared their gene expression profiles to those of the parental SKNAS cells. Using Connectivity Map (CMap) analyses, we identified drugs that were predicted to change the gene expression in the metastatic subpopulations to a profile that is similar to that of parental cell lines.Results: Calcipotriol, a synthetic analogue of vitamin D, was identified from the CMap analysis to be a potentially selective agent for metastatic NB cell lines. In comparison to the parental cells, treatment of the metastatic subpopulations with calcipotriol resulted in reduced proliferation. Furthermore, calcipotriol sensitivity was reduced in metastatic cells with a knockout of vitamin D receptor (VDR) suggesting its effect is on-target. In contrast to the parental cells, following calcipotriol treatment metastatic subpopulations did not exhibit an increase in protein levels of CYP24A1, the enzyme that metabolizes vitamin D, suggesting a potential mechanism for the differential sensitivity of parental and metastatic cells. Calcipotriol treatment also reduced levels of hippo pathway effectors, YAP and TAZ, which we previously reported to play a role in mediating the metastatic phenotype of the isolated subpopulations. Additionally, metastatic cells that were pre-treated with calcipotriol showed reduced migration in a transwell assay whereas the migration potential of parental cells was not affected. Furthermore, RASSF2, an upstream regulator of the hippo pathway, was identified to be upregulated in a VDR-dependent manner after calcipotriol treatment in the metastatic subpopulations indicating a possible mechanistic link for the effects of calcipotriol on the hippo pathway in these metastatic cells.Conclusions: Calcipotriol was identified to be more effective against metastatic NB subpopulations in vitro and this may be in part due to defects in CYP24A1 induction in these metastatic cells. Our data also suggests a novel link between VDR, the hippo pathway and metastasis in NB. Further experiments are required to determine the role of VDR, mechanism of action of calcipotriol in selectively inhibiting growth of metastatic NB cells.Citation Format: Yagnesh Ladumor, Bo Kyung Alex Seong, Robin Hallett, Teresa Adderley, Yingying Wang, Lynn Kee, David Kaplan, Meredith Irwin. Targeting vitamin D signalling in metastatic neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3106.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.133
metaresearch head score (Gemma)0.282
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1330.282
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0020.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.653
GPT teacher head0.633
Teacher spread0.020 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2019
Admission routes1
Has abstractyes

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