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Record W2004914870 · doi:10.1007/s12079-007-0008-9

Analysis of CCN2 promoter activity in PANC-1 cells: regulation by ras/MEK/ERK

2007· article· en· W2004914870 on OpenAlexafffund
Melissa Pickles, Andrew Leask

Bibliographic record

VenueJournal of Cell Communication and Signaling · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective Tissue Growth Factor Research
Canadian institutionsWestern University
FundersCanadian Institutes of Health ResearchArthritis Society
KeywordsCTGFMAPK/ERK pathwayMEK inhibitorPancreatic cancerCancer researchCell cultureCancer cellCancerPancreasGrowth factorBiologyChemistryMedicineKinaseCell biologyInternal medicineEndocrinologyReceptorGenetics

Abstract

fetched live from OpenAlex

Connective tissue growth factor (CTGF, CCN2) is overexpressed in pancreatic cancer. We mapped the minimal CCN2 promoter active in PANC-1 cells, a human pancreatic cancer cell line. Within this region, Sp1, BCE-1 and Ets elements were important for the activity of the CCN2 promoter. Constitutive hyperactivated ras is a hallmark of cancers, including that of the pancreas. Treatment of PANC-1 cells with the MEK inhibitor U0126 or the Sp1 inhibitor mithramycin reduced CCN2 mRNA and promoter activity. Mutation of the BCE-1, but not Sp1 or Ets, site abolished the responsiveness of the CCN2 promoter to U0126. Overexpressing constitutively active MEK1 or ras activated CCN2 promoter activity. Thus CCN2 is likely to act downstream of ras in PANC-1 cells. CCN2 is overexpressed in cancer cells. Activated ras/MEK/ERK is a hallmark of cancer, and we have shown that the elevated CCN2 expression in pancreatic cancer cells is dependent on this pathway.

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 score0.004

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.299
Teacher spread0.282 · 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

Citations30
Published2007
Admission routes2
Has abstractyes

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