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Record W2011966810 · doi:10.2217/14796694.3.5.539

Targeting the Rna-Binding Protein Sam68 As A Treatment For Cancer?

2007· review· en· W2011966810 on OpenAlex
Kiven Erique Lukong, Stéphane Richard

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 · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsSuppressorRNA-binding proteinOncogeneRNABiologyCarcinogenesisCancer researchCancerBreast cancerMammary tumorHaploinsufficiencyCell biologyGeneticsGenePhenotype

Abstract

fetched live from OpenAlex

The contradictory properties of RNA-binding proteins (RBPs) have mystified their roles in human diseases including cancer. Are certain RBPs oncogenes or tumor suppressors? In the case of the signal transduction activator of RNA metabolism (STAR) family of hnRNP K homology (KH)-domain-containing RBPs, the dominant view with loose experimental evidence is that these proteins are tumor suppressors. However, recent developments support a pro-oncogenic role for archetypical STAR protein Sam68. Sam68-null mice are not prone to cancer, but instead display pronounced defects in mammary gland ductal development, and haploinsufficiency of Sam68 impedes mammary tumor onset and tumor multiplicity in mouse models expressing the mammary-targeted polyoma middle T antigen oncogene. These advances have increased the interest in the role of Sam68 as a positive regulator of cancer progression and position Sam68 as a viable therapeutic target. Retrospective and perspective implications of Sam68 in cancer are discussed.

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 score0.992
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.053
GPT teacher head0.420
Teacher spread0.367 · 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