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Record W1969512609 · doi:10.1158/0008-5472.can-04-4281

Identification of a Genetic Signature of Activated Signal Transducer and Activator of Transcription 3 in Human Tumors

2005· article· en· W1969512609 on OpenAlexaff
James V. Alvarez, Phillip G. Febbo, Sridhar Ramaswamy, Massimo Loda, Andrea L. Richardson, David A. Frank

Bibliographic record

VenueCancer Research · 2005
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsImmunovaccine (Canada)
FundersNational Institutes of HealthNational Cancer InstituteDana-Farber Cancer InstituteAlbert J. Ryan Foundation
KeywordsSTAT3STAT proteinCarcinogenesisBiologyCancer researchTranscription factorTissue microarrayTranscription (linguistics)ImmunohistochemistryGeneGeneticsImmunology

Abstract

fetched live from OpenAlex

Signal transducer and activator of transcription 3 (STAT3) is a transcription factor that is activated in diverse human tumors and may play a direct role in malignant transformation. However, the full complement of target genes that STAT3 regulates to promote oncogenesis is not known. We created a system to express a constitutively active form of STAT3, STAT3-C, in mouse fibroblasts and used it to identify STAT3 targets. We showed that a subset of these targets, which include transcription factors regulating cell growth, survival, and differentiation, are coexpressed in a range of human tumors. Using immunohistochemical staining of tissue microarrays, we showed that these targets are enriched in breast and prostate tumors harboring activated STAT3. Finally, we showed that STAT3 is required for the expression of these genes in a breast cancer cell line. Taken together, these results identify a cohort of STAT3 targets that may mediate its role in oncogenesis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.396
Teacher spread0.336 · 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 source (direct Gemma or distilled Codex), 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

Citations208
Published2005
Admission routes1
Has abstractyes

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