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Record W2078467208 · doi:10.1158/1538-7445.am2012-2477

Abstract 2477: Autophagy is correlated with chemoresistance in neuroblastoma

2012· article· en· W2078467208 on OpenAlexaff
Assila Belounis, Carine Nyalendo, Anissa Addioui, Sonia Cournoyer, Mohamed Mahma, Pierre Teira, Mona Beaunoyer, Élie Haddad, Christian Beauséjour, Hervé Sartelet

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
Fundersnot available
KeywordsAutophagyATG5VacuoleAutophagosomeProgrammed cell deathCancer researchNeuroblastomaBiologyCancer cellChemotherapyViability assayCellApoptosisCancerCell biologyCell cultureBiochemistry

Abstract

fetched live from OpenAlex

Abstract Neuroblastoma (NB) is a frequent pediatric tumor. After combined treatments of chemotherapy, bone marrow transplantation, surgery and/or radiotherapy, metastatic NBs still have a poor prognosis. Therefore, finding new therapeutic strategies to increase the survival rate of patients with NB is essential. Autophagy is a self-degradative process induced primarily by starvation and, with the intermediate of lysosomes, damaged macromolecules and cell organelles are degraded. This degradation insures cell survival by adapting to stress conditions. In addition, recent studies proposed that autophagy may contribute to cancer resistance to chemotherapy and radiotherapy. However, in some circumstances, autophagy can induce non-apoptotic programmed cell death. The aim of this study is to determine how autophagy is regulated and whether it is associated with chemoresistance in NB. Firstly, tissue Microarray blocks containing 184 patients NB were used for an immunohistochemistry study in order to identify the expression of LC3, a cytosolic protein required for autophagic vacuole (autophagosome) formation, and beclin 1, a positive regulator of autophagy. Secondly, in vitro and in vivo (NOD/SCID/IL2Rαc-null mice) studies were performed to determine the level of autophagy in NB cells following chemotherapy. Finally, autophagy was inhibited in NB cells with shRNA targeting Atg5 (an essential protein for autophagy) or with hydroxychloroquine (HCQ), a pharmacological inhibitor of autophagy. NB cells were further treated with conventional drugs used in NB treatments to evaluate if they retain their ability to resist to chemotherapy. Cell survival was measured using MTT cell proliferation assay. Autophagy was detected by labelling the autophagic vacuoles with monodansylcadaverine (MDC) and by Western blot analysis of LC3 cleavage and Atg5 expression. Our study demonstrated that autophagy is present at low levels in a majority of NB. LC3 expression was not correlated with any clinical pathological data. On the other hand, Beclin1 expression in NB was higher in children older than one year of age who have a poor prognosis. Also, it had a higher level in primitive tumors than in metastases. In our in vitro and in vivo studies, autophagy, which was detected by cleavage of LC3 and by MDC test, was correlated with increasing concentrations of therapeutic agents. Interestingly, inhibition of autophagy with either Atg5 shRNA or HCQ strongly increased the sensitivity of NB cells to chemotherapy.Overall, these results suggest that autophagy contributes to NB cells resistance to chemotherapy. Therefore, inhibition of autophagy in combination with current treatments may be of great interest in order to improve therapeutic strategies of NB. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2477. doi:1538-7445.AM2012-2477

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.062
GPT teacher head0.408
Teacher spread0.346 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2012
Admission routes1
Has abstractyes

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