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Record W1511682218 · doi:10.1158/1078-0432.ccr-09-1363

Preclinical Drug Development Must Consider the Impact on Metastasis

2009· article· en· W1511682218 on OpenAlexaff
Patricia S. Steeg, Robin L. Anderson, Menashe Bar‐Eli, Ann F. Chambers, Suzanne A. Eccles, Kent W. Hunter, Kazuyuki Itoh, Yibin Kang, Lynn M. Matrisian, Jonathan P. Sleeman, Dan Theodorescu, Erik W. Thompson, Danny R. Welch

Bibliographic record

VenueClinical Cancer Research · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsWestern University
FundersNational Institutes of Health
KeywordsMetastasisAngiogenesisMedicineDrug developmentDrugOncologyCancer researchInternal medicinePharmacologyCancer

Abstract

fetched live from OpenAlex

Recently, two landmark reports on antiangiogenic therapy were published: Paez-Ribes and colleagues (1) and Ebos and colleagues (2). The Board of the Metastasis Research Society (MRS) congratulates the authors for their informative articles (1, 2) that help to explain the puzzle of why antiangiogenic agents have had a relatively minor or no significant impact on patient survival. Using four model systems and several different strategies, these researchers showed that inhibition of angiogenesis reduced primary tumor growth and microvessel density in keeping with many earlier reports, but strikingly, accelerated invasion and metastasis.It is well known that the majority of cancer patients who succumb to their disease do so following development of incurable metastatic disease. However, the emphasis on preclinical testing of new compounds still rests on the responses of subcutaneous or orthotopic primary tumors from various mouse models over a relatively short time frame. The reports of both Ebos and colleagues (2) and Paez-Ribes and colleagues (1) elegantly reveal the limitations of this approach, at least with regard to targeting of angiogenesis.It is important to reflect on the fact that other drugs and preclinical compounds, when tested for both primary tumor size and metastasis, have exhibited discordant results. For example, cyclophosphamide inhibited primary lung adenocarcinoma but promoted metastasis to the lung and liver (3), and the Hsp90 inhibitor 17-AAG inhibited primary breast cancer but promoted metastasis to the bone (4). Vandetanib, a vascular endothelial growth factor receptor (VEGFR) inhibitor, reduced the growth of primary fibrosarcomas, but had no effect on their metastasis (5). Interestingly, a number of agents have been shown to exert no significant effects on primary tumor size, but still had the capacity to inhibit metastasis (6–13). Given the fact that primary tumors can often be controlled using conventional therapies, could agents that act specifically on the process of metastasis be more likely to increase long term patient survival?On the basis of these new reports and earlier data, we propose that preclinical drug development in general—and not only for antiangiogenic compounds—be required to show efficacy in at least one metastasis model, preferably incorporating metastasis from an orthotopic site. Robust models are available with relevant histology (i.e., similar to human) and imaging for quantification. The U.S. Food and Drug Administration (FDA), other regulatory agencies and their clients, and patients considering entrance into a clinical trial, currently have access to detailed information such as weight loss in mice exposed to a compound. In our opinion, it is just as important to reveal information on the capacity of a new compound to accelerate or inhibit invasion and tumor metastasis.No potential conflicts of interest were disclosed.

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)0.013
metaresearch head score (Gemma)0.012
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: Commentary · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0060.007
Open science0.0020.002
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0120.005

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 head0.288
GPT teacher head0.571
Teacher spread0.283 · 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
GenreCommentary

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

Citations1
Published2009
Admission routes1
Has abstractyes

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