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Record W4312224396 · doi:10.1186/s13046-022-02559-z

The traditional chinese medicine monomer Ailanthone improves the therapeutic efficacy of anti-PD-L1 in melanoma cells by targeting c-Jun

2022· article· en· W4312224396 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Experimental & Clinical Cancer Research · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsSKiN Health
FundersScience and Technology Innovative Research Team in Higher Educational Institutions of Hunan ProvinceProject 211Higher Education Discipline Innovation ProjectNational Natural Science Foundation of China
KeywordsMelanomaCancer researchFlow cytometryMedicineIn vitroApoptosisCombination therapyTumor microenvironmentPharmacologyImmunologyChemistryTumor cells

Abstract

fetched live from OpenAlex

BACKGROUND: C-Jun, a critical component of AP-1, exerts essential functions in various tumors, including melanoma, and is believed to be a druggable target for cancer therapy. Unfortunately, no effective c-Jun inhibitors are currently approved for clinical use. The advent of immune checkpoint inhibitor (ICI) has brought a paradigm shift in melanoma therapy, but more than half of patients fail to exhibit clinical responses. The exploration of new combination therapies has become the current pursuit of melanoma treatment strategy. This study aims to screen out Chinese herbal monomers that can target c-Jun, explore the combined effect of c-Jun inhibitor and ICI, and further clarify the related molecular mechanism. METHODS: We adopted a combinatorial screening strategy, including molecular docking, ligand-based online approaches and consensus quantitative structure-activity relationship (QSAR) model, to filter out c-Jun inhibitors from a traditional Chinese medicine (TCM) library. A mouse melanoma model was used to evaluate the therapeutic efficacy of monotherapy and combination therapy. Multicolor flow cytometry was employed to assess the tumor microenvironment (TME). Multiple in vitro assays were performed to verify down-streaming signaling pathway. CD4 + T-cell differentiation assay was applied to investigate Treg differentiation in vitro. RESULTS: Ailanthone (AIL) was screened out as a c-Jun inhibitor, and inhibited melanoma cell growth by directly targeting c-Jun and promoting its degradation. Surprisingly, AIL also facilitated the therapeutic efficacy of anti-programmed death ligand-1 (PD-L1) in melanoma cells by reducing the infiltration of Tregs in TME. Additionally, AIL treatment inhibited c-Jun-induced PD-L1 expression and secretion. As a consequence, Treg differentiation was attenuated after treatment with AIL through the c-Jun/PD-L1 axis. CONCLUSION: Our findings identified AIL as a novel c-Jun inhibitor, and revealed its previously unrecognized anti-melanoma effects and the vital role in regulating TME by Treg suppression, which provides a novel combination therapeutic strategy of c-Jun inhibition by AIL with ICI. AIL down-regulates c-Jun by reducing its stability, and inhibits the function of Tregs via AIL-c-Jun-PD-L1 pathway, ultimately suppressing melanoma progression and enhancing the efficacy of anti-PD-L1.

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.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.132
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.093
GPT teacher head0.441
Teacher spread0.348 · 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