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Record W1864382350 · doi:10.1158/1535-7163.641.3.5

Identification of human polo-like kinase 1 as a potential therapeutic target in pancreatic cancer

2004· article· en· W1864382350 on OpenAlexaff
Phillip J. Gray, David J. Bearss, Haiyong Han, Raymond B. Nagle, Ming‐Sound Tsao, Nicholas Dean, Daniel D. Von Hoff

Bibliographic record

VenueMolecular Cancer Therapeutics · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsPancreatic cancerIdentification (biology)CancerPolo-like kinaseKinaseBiologyCancer researchComputational biologyGeneticsCell cycle

Abstract

fetched live from OpenAlex

Pancreas cancer is the fourth leading cause of cancer-related death in adults in the United States. New molecular targets for diagnosis and therapy of this disease are desperately needed. In this study, we report on the mitotic serine-threonine kinase polo-like kinase 1 (Plk1) in pancreatic cancer. Plk1 mRNA was found to be overexpressed in 9 of 10 tested pancreatic cancer cell lines and in 4 of 4 tested human tumors. Immunohistochemical staining of a pancreatic tissue microarray showed that 26 of the 35 tumors taken directly from patients overexpressed Plk1. We also examined the effects of depleting Plk1 in pancreatic cancer cells by the use of antisense oligonucleotides. Antisense-treated pancreatic cancer cells showed cell cycle arrest in G(2)-M as well as a drastic reduction in proliferation rates. These data suggest that Plk1 is a potential therapeutic target in devising a treatment for patients with pancreatic cancer.

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 score0.003

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 integrity0.0000.000
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 head0.010
GPT teacher head0.282
Teacher spread0.272 · 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

Citations97
Published2004
Admission routes1
Has abstractyes

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