MétaCan
Menu
Back to cohort
Record W2013307793 · doi:10.2217/14796694.2.5.627

Tumor Dormancy and the Role of Metastasis Suppressor Genes In Regulating Ectopic Growth

2006· review· en· W2013307793 on OpenAlex
Benjamin D. Hedley, Alison L. Allan, Ann F. Chambers

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

VenueFuture Oncology · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMechanisms of cancer metastasis
Canadian institutionsWestern University
Fundersnot available
KeywordsMetastasisEctopic expressionMetastasis suppressorSuppressorDormancyMetastasis Suppressor GeneCancer researchMedicineMalignancyGenePrimary tumorCancerBiologyOncologyInternal medicineGeneticsBotany

Abstract

fetched live from OpenAlex

Metastasis, or tumor growth in an ectopic site, may occur several years after apparently successful treatment of the primary malignancy. Clinical dormancy is seen in a large number of cancer patients, but once growth in an ectopic site initiates, current adjuvant therapies are inadequate and the majority of patients with metastatic disease will die. Many genes may regulate ectopic growth in a secondary site, including a small subset, termed the metastasis suppressor genes. Investigation into this class of genes holds promise in terms of gaining a greater understanding of tumor dormancy and how the process of metastasis may be naturally inhibited. This review will focus on the role of metastasis suppressor genes in tumor dormancy. Insights into the metastatic process from studies of metastasis suppressor genes may lead to novel targets for antimetastatic therapy through drug-induced reactivation of one or more of these genes and/or their respective signaling pathways.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.012
GPT teacher head0.293
Teacher spread0.281 · 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