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Record W4403917842 · doi:10.1126/sciadv.ado8275

Inhibition of Notch enhances efficacy of immune checkpoint blockade in triple-negative breast cancer

2024· article· en· W4403917842 on OpenAlexafffund
Qiang Shen, Kiichi Murakami, Valentin Sotov, Marcus O. Butler, Pamela S. Ohashi, Michael Reedijk

Bibliographic record

VenueScience Advances · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsCanada Research ChairsPrincess Margaret Cancer CentreOntario Institute for Cancer ResearchDiscovery CentreUniversity Health NetworkUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsTriple-negative breast cancerCancer researchBlockadeImmune checkpointTumor microenvironmentImmune systemCytotoxic T cellCytokineNotch signaling pathwayBreast cancerImmunotherapyMedicineCancerImmunologyBiologyInternal medicineReceptor

Abstract

fetched live from OpenAlex

Aberrant Notch, which is a defining feature of triple-negative breast cancer (TNBC) cells, regulates intercellular communication in the tumor immune microenvironment (TIME). This includes tumor-associated macrophage (TAM) recruitment through Notch-dependent cytokine secretion, contributing to an immunosuppressive TIME. Despite the low response rate of TNBC to immune checkpoint blockade (ICB), here, we report that inhibition of Notch-driven cytokine-mediated programs reduces TAMs and induces responsiveness to sequentially delivered ICB. This is characterized by the emergence of GrB + cytotoxic T lymphocytes (CTLs) in the primary tumor. A more impressive effect of sequential treatment is observed in the lung where TAM depletion and increased CTLs are accompanied by near-complete abolition of metastases. This is due to (i) therapeutic reduction in Notch-dependent, prometastatic circulating factors released by the primary tumor, and (ii) elevated PD ligand 1 (PD-L1) in lung metastases, rendering them profoundly sensitive to ICB. These findings highlight the potential of combination cytokine inhibition and ICB as an immunotherapeutic strategy in TNBC.

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)0.001
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 score0.047
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.291
Teacher spread0.282 · 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.

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

Citations13
Published2024
Admission routes2
Has abstractyes

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