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Record W4398154122 · doi:10.1101/2022.12.28.522091

Adaptation of redox metabolism in drug-tolerant persister cells is a vulnerability to prevent relapse in pancreatic cancer

2022· preprint· en· W4398154122 on OpenAlexaff
Nadine Abdel Hadi, Gabriela Reyes‐Castellanos, Tristan Gicquel, Scarlett Gallardo-Arriaga, Emeline Boët, Jean‐Emmanuel Sarry, Rawand Masoud, Juan Iovanna, Alice Carrier

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsCrandall University
Fundersnot available
KeywordsAdaptation (eye)Vulnerability (computing)Pancreatic cancerDrug metabolismDrugCancerBiologyPharmacologyMedicineInternal medicineNeuroscienceComputer scienceComputer security

Abstract

fetched live from OpenAlex

ABSTRACT Pancreatic Ductal Adenocarcinoma (PDAC) remains a major unresolved disease because of its remarkable therapeutic resistance. Even patients who respond to initial therapy experience relapse in most cases. The mechanisms underlying therapy-acquired resistance supporting relapse are poorly understood. In this study, we aimed to determine the metabolic features of PDAC during relapse, specifically adaptations of mitochondrial and redox metabolism. We used preclinical PDAC mouse models (patient-derived xenografts and murine syngeneic allografts) that present complete regression under initial chemotherapeutic treatment but relapse after a certain time. Relapsed tumors were analyzed ex vivo by flow cytometry to measure mitochondrial and redox characteristics. Molecular mechanisms were investigated by quantification of ATP and antioxidants levels, RT-qPCR and bulk RNA-sequencing. Our findings show that mitochondrial metabolism is reprogrammed during relapse, with increased mitochondrial mass, ATP levels, mitochondrial superoxide anions, and total ROS levels, in relapsed compared to control tumors in both models; mitochondrial membrane potential is increased in the xenografts model only. This mitochondrial metabolic reprogramming occurs during treatment-induced regression and at relapse onset. At the molecular level, antioxidant defenses are increased in relapsed tumors and during treatment. These data suggest that treatment-induced oxidative stress may cause the appearance of treatment-adapted cells, known as drug-tolerant persister (DTP) cells. Finally, the combined treatment of arsenic trioxide (ROS inducer) and buthionine sulfoximine (glutathione synthesis inhibitor) is able to completely prevent relapse in PDAC xenografts. In conclusion, targeting redox metabolism via ROS production and antioxidant inhibition is a very promising approach to prevent relapse in PDAC patients. Significance Mitochondrial and redox metabolisms are reprogrammed during treatment-acquired resistance in pancreatic cancer promoting the survival of drug-tolerant persister cancer cells, opening up new avenues for better therapeutic management of patients.

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 score0.001
Threshold uncertainty score0.003

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

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