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Record W2166242782 · doi:10.1261/rna.042168.113

Tumor microenvironment–associated modifications of alternative splicing

2013· article· en· W2166242782 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRNA · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health ResearchUniversité de Sherbrooke
KeywordsRNA splicingBiologyAlternative splicingTumor microenvironmentSplicing factorMinigeneOvarian cancerCancer researchMessenger RNACell biologyCancerGeneGeneticsRNA

Abstract

fetched live from OpenAlex

Pre-mRNA alternative splicing is modified in cancer, but the origin and specificity of these changes remain unclear. Here, we probed ovarian tumors to identify cancer-associated splicing isoforms and define the mechanism by which splicing is modified in cancer cells. Using high-throughput quantitative PCR, we monitored the expression of splice variants in laser-dissected tissues from ovarian tumors. Surprisingly, changes in alternative splicing were not limited to the tumor tissues but were also found in the tumor microenvironment. Changes in the tumor-associated splicing events were found to be regulated by splicing factors that are differentially expressed in cancer tissues. Overall, ∼20% of the alternative splicing events affected by the down-regulation of the splicing factors QKI and RBFOX2 were altered in the microenvironment of ovarian tumors. Together, our results indicate that the tumor microenvironment undergoes specific changes in alternative splicing orchestrated by a limited number of splicing factors.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.218

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 head0.013
GPT teacher head0.253
Teacher spread0.241 · 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

Quick stats

Citations69
Published2013
Admission routes2
Has abstractyes

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