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Record W2118104227

miR-221 Is down-regulated in TMPRSS2:ERG fusion-positive prostate cancer.

2011· article· en· W2118104227 on OpenAlexaff
Aida Gordanpour, Aleksandra Stanimirovic, Robert K. Nam, Carlos S. Moreno, Christopher Sherman, Linda Sugar, Arun Seth

Bibliographic record

VenuePubMed · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsSunnybrook HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsTMPRSS2Prostate cancerProstateFusion geneCancer researchmicroRNAOncogenePCA3ErgBiologyCancerMedicineOncologyInternal medicineGeneCell cycleDiseaseGenetics
DOInot available

Abstract

fetched live from OpenAlex

Expression profiling studies using microarrays and other methods have shown that microRNAs (miRNAs) are dysregulated in a wide variety of human cancers. The up-regulation of miR-221 has been reported in carcinomas of the pancreas, breast, and papillary thyroid, as well as in glioblastoma and chronic lymphocytic leukaemia. In prostate cancer, however, down-regulation of miR-221 has been repeatedly confirmed in miRNA expression studies. Also unique to prostate cancer, and found in more than 50% of patients, is the aberrant expression of a known oncogene, the TMPRSS2:ERG fusion. To date, there has been no published study describing miRNA associations in prostate tumours that overexpress the ERG oncogene from the TMPRSS2:ERG fusion transcript. Herein we report that in a large and diverse cohort of prostate carcinoma samples, miR-221 is down-regulated in patients with tumours bearing TMPRSS2:ERG fusion transcripts, thus providing a link between miRNA and gene fusion expression.

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 score0.001
Threshold uncertainty score0.005

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.219
Teacher spread0.206 · 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

Citations52
Published2011
Admission routes1
Has abstractyes

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