MétaCan
Menu
Back to cohort
Record W4377047016 · doi:10.1038/s42003-023-04828-9

Identification of acquired Notch3 dependency in metastatic Head and Neck Cancer

2023· article· en· W4377047016 on OpenAlexafffund
Maria Kondratyev, Aleksandra Pesic, Troy Ketela, Natalie Stickle, Christine Beswick, Zvi Shalev, Stefano Marastoni, Soroush Samadian, Anna Dvorkin‐Gheva, Azin Sayad, Mikhail Bashkurov, Pedro Boasquevisque, Alessandro Datti, Trevor J. Pugh, Carl Virtanen, Jason Moffat, Reidar Grénman, Marianne Koritzinsky, Bradly G. Wouters

Bibliographic record

VenueCommunications Biology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
FundersTerry Fox Foundation
KeywordsMetastasisHead and neck cancerCancer researchCancerMedicineOncologyBiologyInternal medicine

Abstract

fetched live from OpenAlex

During cancer development, tumor cells acquire changes that enable them to invade surrounding tissues and seed metastasis at distant sites. These changes contribute to the aggressiveness of metastatic cancer and interfere with success of therapy. Our comprehensive analysis of "matched" pairs of HNSCC lines derived from primary tumors and corresponding metastatic sites identified several components of Notch3 signaling that are differentially expressed and/or altered in metastatic lines and confer a dependency on this pathway. These components were also shown to be differentially expressed between early and late stages of tumors in a TMA constructed from over 200 HNSCC patients. Finally, we show that suppression of Notch3 improves survival in mice in both subcutaneous and orthotopic models of metastatic HNSCC. Novel treatments targeting components of this pathway may prove effective in targeting metastatic HNSCC cells alone or in combination with conventional therapies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
Threshold uncertainty score0.274

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)0.0000.000

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 head0.037
GPT teacher head0.353
Teacher spread0.316 · 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 designObservational
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

Citations9
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueCommunications BiologySame topicDevelopmental Biology and Gene RegulationFrench-language works237,207