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Record W4394328934 · doi:10.6084/m9.figshare.16912033

FAIM regulates autophagy through glutaminolysis in lung adenocarcinoma

2021· dataset· en· W4394328934 on OpenAlexaff
Tianyu Han, Pengcheng Wang, Yanan Wang, Wenze Xun, Jiapeng Lei, Tao Wang, Zhuo Lü, Mingxi Gan, Bentong Yu, Jianbin Wang

Bibliographic record

VenueFigshare · 2021
Typedataset
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsBruyèreQueen's University
Fundersnot available
KeywordsGlutaminolysisAutophagyExposomeCancer researchChemistryBiologyMedicineInternal medicinePathologyBiochemistryGlycolysisMetabolism

Abstract

fetched live from OpenAlex

Altered glutamine metabolism is an important aspect of cancer metabolic reprogramming. The GLS isoform GAC (glutaminase C), the rate-limiting enzyme in glutaminolysis, plays a vital role in cancer initiation and progression. Our previous studies demonstrated that phosphorylation of GAC was essential for its high enzymatic activity. However, the molecular mechanisms for GAC in maintaining its high enzymatic activity and protein stability still need to be further clarified. FAIM/FAIM1 (Fas apoptotic inhibitory molecule) is known as an important anti-apoptotic protein, but little is known about its function in tumorigenesis. Here, we found that knocking down FAIM induced macroautophagy/autophagy through suppressing the activation of the MTOR pathway in lung adenocarcinoma. Further studies demonstrated that FAIM could promote the tetramer formation of GAC through increasing PRKCE/PKCε-mediated phosphorylation. What’s more, FAIM also stabilized GAC through sequestering GAC from degradation by protease ClpXP. These effects increased the production of α-ketoglutarate, leading to the activation of MTOR. Besides, FAIM also promoted the association of ULK1 and MTOR and this further suppressed autophagy induction. These findings discovered new functions of FAIM and elucidated an important molecular mechanism for GAC in maintaining its high enzymatic activity and protein stability.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.439
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.4410.003

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 head0.031
GPT teacher head0.304
Teacher spread0.273 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations1
Published2021
Admission routes1
Has abstractyes

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