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Record W2066697593 · doi:10.1158/0008-5472.can-07-0905

Antiangiogenic Strategies on Defense: On the Possibility of Blocking Rebounds by the Tumor Vasculature after Chemotherapy

2007· review· en· W2066697593 on OpenAlexaff
Yuval Shaked, Robert S. Kerbel

Bibliographic record

VenueCancer Research · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersNational Cancer InstituteNational Institutes of Health
KeywordsHoming (biology)Cytotoxic T cellBone marrowCancer researchChemotherapyMedicineAngiogenesisNeovascularizationImmunologyBiologyInternal medicineIn vitro

Abstract

fetched live from OpenAlex

Rapid or accelerated tumor cell repopulation after significant tumor cell killing induced by various cytotoxic agents often compromises the expected therapeutic benefit of such tumor responses. Here, we discuss the concept that tumor cell repopulation after certain cytotoxic therapies, using vascular disrupting agents as an example, may be aided by a reactive, systemic host response involving the mobilization of bone marrow-derived circulating cells, including endothelial progenitor cells, which subsequently home to the vasculature of treated tumors and promote tumor neovascularization. These vasculogenic "rebounds" can be blocked, at least in some cases, by treatment with an antiangiogenic drug. There is limited preliminary evidence that maximum tolerated dose chemotherapy causes a similar effect. This could constitute one way by which antiangiogenic therapy could increase the efficacy of conventional cytotoxic chemotherapy regimens; it also raises the specter of new molecular targets for systemic cancer therapies which are involved in therapy-induced bone marrow-derived cell mobilization, homing to tumors, and tumor retention.

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 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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.878
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.093
GPT teacher head0.438
Teacher spread0.344 · 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 teacher head, 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

Citations111
Published2007
Admission routes1
Has abstractyes

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