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Record W2030908978 · doi:10.2174/187152011796011109

Therapeutic Potential of Targeting Glypican-3 in Hepatocellular Carcinoma

2011· review· en· W2030908978 on OpenAlexafffund
Mark Allegretta, Jorge Filmus

Bibliographic record

VenueAnti-Cancer Agents in Medicinal Chemistry · 2011
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsGlypican 3Hepatocellular carcinomaCancer researchMonoclonal antibodyImmunohistochemistryOncofetal antigenMedicinePathologyAntibodyBiologyImmunology

Abstract

fetched live from OpenAlex

Glypican-3 (GPC3) is a developmentally-regulated oncofetal protein that has been established as a clinically-relevant biomarker for early hepatocellular carcinoma (HCC). It is one of the first transcripts to appear during malignant hepatocyte transformation, and is expressed at the protein level in approximately half of high-grade dysplastic macronodules in cirrhotic liver. Several studies show it is expressed in most (75 to 100%) of HCCs confirmed by histopathology. The protein is anchored to the hepatocyte membrane by a glycosyl-phosphatidylinositol (GPI) anchor and shows consistent membrane immunostaining pattern, making it a viable target for immunotherapeutic approaches. Targeting GPC3 for therapeutic intervention is a promising approach for the clinical management of HCC and selected other tumors that express the marker. Keywords: Glypican-3, Hepatocellular Carcinoma, therapeutic antibody, peptide vaccine, immunohistochemistry, oncofetal protein, Wnt signaling, Carcinoma, monoclonal antibody (mAb), IMMUNOTHERAPEUTIC GPC3 VACCINE, ADCC, GC33, collagen and fibronectin, sGPC3

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.128
GPT teacher head0.338
Teacher spread0.209 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations27
Published2011
Admission routes2
Has abstractyes

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