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Record W4379984223 · doi:10.1158/1538-7445.am2023-1379

Abstract 1379: Studying the autophagic flux in response to hypoxia in BAP1-mutated pleural mesothelioma cells linked to asbestos exposure

2023· article· en· W4379984223 on OpenAlexaff
Chloe Michaud, Sandra Turcotte

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsMesotheliomaAutophagyCancer researchBAP1Tumor microenvironmentAsbestosCancer cellProgrammed cell deathHypoxia (environmental)CancerBiologyMedicineChemistryPathologyApoptosisInternal medicineTumor cellsMaterials science

Abstract

fetched live from OpenAlex

Abstract Introduction. Malignant mesothelioma is a rare cancer linked to asbestos exposure. It comes from the oncogenic transformation of mesothelioma cells, a protective membrane that covers several internal cavities including the pleura, peritoneum and pericardium. Malignant pleural mesothelioma (MPM) accounts for more than 90% of cases. The average survival of these patients is approximately 8 to 12 months, due to the resistance of tumors towards treatments. A well-known hallmark in cancer is tumor suppression gene inactivation. BAP1 is the most mutated gene in pleural mesothelioma (25-60%). BAP1 has a deubiquitinase activity involved in chromatin modifications, homologous recombination, DNA damage and programmed cell death. Moreover, hypoxia is an important microenvironment component within tumors, and it is demonstrated in patients with MPM. The bio-persistent localization of asbestos in mesothelioma cells has been shown to induce chronic inflammation that activates autophagic flux to survive. Autophagy is induced by several types of cellular stresses, including hypoxia. This suggests that MPM cells are dependent on autophagic flux when subjected to stress to ensure their continuity and proliferation. Hypothesis/Objectives. The hypothesis of this project is that MPM has vulnerabilities in the autophagy/lysosome process, which can thus be targeted by chemical inhibitors to improve treatment response and efficacy. The specific objectives are to i) examine autophagy flux in MPM cells with BAP1 mutations, ii) demonstrate autophagy modulation in MPM cells towards the hypoxic response, and iii) assess the potential for autophagy and lysosome inhibitors in MP cells with mutations on BAP1 or towards the hypoxic response. Methods/Results. To achieve this, molecular biology approaches are used to reintroduce (Gateway system), or repress (CRISRP/Cas9) the expression of BAP1 in Mero-25 and Mero-41 cells, respectively. Models were confirmed by western blot. The hypoxic chamber is used to manipulate cells in 1% O2, in which we confirmed the activation of autophagy in response to hypoxia in a kinetic timeframe of 24, 48 and 72hr. Subsequently, the autophagic flux was studied in presence of Bafilomycin A1 indicating an activation of this cellular process. The potential and cytotoxicity of autophagy or lysosome inhibitors will be evaluated by XTT and clonogenic assays. Conclusion. Malignant pleural mesothelioma has an unmet need in novel therapeutic strategies. Our studies could contribute to improve anticancer treatments using combinatory approaches that modulate autophagy. Citation Format: Chloe Michaud, Sandra Turcotte. Studying the autophagic flux in response to hypoxia in BAP1-mutated pleural mesothelioma cells linked to asbestos exposure [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1379.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.098
GPT teacher head0.411
Teacher spread0.313 · 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 designBench or experimental
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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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