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Record W3047389571 · doi:10.1038/s41392-020-0179-x

The AKT-independent MET–V-ATPase–MTOR axis suppresses liver cancer vaccination

2020· article· en· W3047389571 on OpenAlexfundno aff
Xing Huang, Xingyuan Xu, Xun Wang, Tianyu Tang, Enliang Li, Xiaozhen Zhang, Jian Xu, Hang Shen, Chengxiang Guo, Tao Xu, Jianhong Ren, Xueli Bai, Tingbo Liang

Bibliographic record

VenueSignal Transduction and Targeted Therapy · 2020
Typearticle
Languageen
FieldMedicine
TopicLiver physiology and pathology
Canadian institutionsnot available
FundersTsinghua-Berkeley Shenzhen instituteUniversity of TorontoNational Key Research and Development Program of ChinaZhejiang Provincial Program for the Cultivation of High-Level Innovative Health TalentsInstitut Gustave-RoussySoutheast UniversityZhejiang UniversitySichuan UniversityFrancis Crick InstituteChina Postdoctoral Science FoundationNational Natural Science Foundation of ChinaUniversity of Science and Technology of China
KeywordsPI3K/AKT/mTOR pathwayProtein kinase BCancerCancer researchMedicineLiver cancerSignal transductionBiologyInternal medicineCell biology

Abstract

fetched live from OpenAlex

Despite recent progress in hepatitis treatment, there have been no significant advances in the development of liver cancer vaccines in recent years. In this study, we investigated the regulatory effect and potential mechanism of hepatocyte growth factor receptor (MET, also known as HGFR) on tumor vaccinations for liver cancer in mice. Herein, we demonstrate that MET expression is significantly associated with the immunogenicity of liver cancer in mice and humans, and that MET depletion dramatically enhances the protective efficacy of chemotherapy-based anti-liver cancer vaccination. Mechanistically, MET repressed liver cancer immunogenicity independent of the traditional PI3K-AKT cascade, and MET interacted with vacuolar ATP synthase (V-ATPase) and mediated the activation of mammalian target of rapamycin (MTOR), thus suppressing liver cancer immunogenicity. The efficacy of chemotherapy-based liver cancer vaccination was markedly enhanced by targeting the MET-V-ATPase-MTOR axis, highlighting a translational strategy for identifying MET-associated drug candidates for cancer prevention.

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 categoriesInsufficient payload (model declined to judge)
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 score0.194
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

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 head0.034
GPT teacher head0.274
Teacher spread0.241 · 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 teacher head, not a consensus.

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

Citations15
Published2020
Admission routes1
Has abstractyes

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