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Investigating autophagy and glutamine metabolism as therapeutic targets for pancreatic cancer.

2015· article· en· W2589267164 on OpenAlexaff
Mario A. Jardon, Steve E. Kalloger, Christina Iggulden, Nancy E. Go, Paalini Sathiyaseelan, Donald T. Yapp, Daniel J. Renouf, David J. Schaeffer, Sharon M. Gorski

Bibliographic record

VenueJournal of Clinical Oncology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsVancouver General HospitalPancreas Centre (Canada)Simon Fraser UniversityBC Cancer Agency
Fundersnot available
KeywordsGlutamineAutophagyPancreatic cancerCancer researchGlutaminaseAsparagineCancer cellCancerMedicineDownregulation and upregulationChemistryEnzymeBiochemistryInternal medicineApoptosisAmino acidGene

Abstract

fetched live from OpenAlex

381 Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest types of cancer, for which new therapeutic approaches are urgently needed. We are developing novel combination therapy approaches based on the inhibition of glutamine metabolism and autophagy, to improve current treatments for PDAC. Since both processes are key mediators of multiple cancer hallmarks, and have inter-related but non-redundant roles, this combination may result in a more efficient disruption of cancer cell resistance to treatments. Methods: We interrogated the Pancreas Centre BC tissue micro-array, containing the epithelial component of 252 PDAC samples, for expression of three key glutamine-metabolizing proteins and two autophagy-related proteins: glutamine synthetase (GLUL), asparagine synthetase (ASNS), glutaminase C (GLS-GAC), microtubule-associated protein 1 light chain 3 beta (MAP1-LC3B or LC3B) and autophagy-related protein 4B (ATG4B). While previous efforts by other groups have focused on GLS-GAC, the role of GLUL in cancer has remained less well understood. We thus investigated the functional relevance of GLUL using a panel of PDAC cell lines. We are also investigating interactions between glutamine metabolism and autophagy, including the exploration of strategies to target GLUL and the evaluation of a new class of ATG4B inhibitors for the treatment of pancreatic cancers. Results: We found that GLUL, ASNS, GLS-GAC, LC3B and ATG4B were expressed in 31%, 58%, 99%, 51% and 73%, respectively, of PDAC samples. Furthermore, higher LC3B expression correlated with poor outcome. Our functional studies revealed that various PDAC cells express GLUL, which can be upregulated upon glutamine deprivation. In all cell lines tested, GLUL knockdown sensitized them to gemcitabine, as assessed by a long-term recovery assay. We also found that the candidate ATG4B inhibitors, shown to inhibit this target in cell-free assays, effectively inhibit PDAC cell proliferation at micromolar concentrations. Conclusions: Our study reveals that glutamine metabolism and autophagy are clinically relevant in PDAC and may have potential as therapeutic targets. Supported by Pancreas Centre BC, BC Cancer Foundation and VGH Foundation.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.109
GPT teacher head0.440
Teacher spread0.332 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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