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Record W2111772750 · doi:10.1517/14712598.7.9.1415

Myxoma virus and oncolytic virotherapy: a new biologic weapon in the war against cancer

2007· review· en· W2111772750 on OpenAlexaff
Marianne M. Stanford, Grant McFadden

Bibliographic record

VenueExpert Opinion on Biological Therapy · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsWestern University
Fundersnot available
KeywordsOncolytic virusMyxoma virusVirotherapyVacciniaTropismVirusVirologyTissue tropismCancerBiologyCancer researchImmunologyGene

Abstract

fetched live from OpenAlex

Oncolytic virotherapy is an innovative alternative to more conventional cancer therapies. The ability of some viruses to specifically target and kill malignant cancerous cells while leaving normal tissue unscathed has opened a large repertoire of new and selective cancer killing therapeutic candidates. Poxviruses, such as vaccinia virus, have a long history of use in humans as live vaccines and have more recently been studied as potential platforms for delivery of immunotherapeutics and attenuated variants of vaccinia have been explored as oncolytic candidates. In contrast, the poxvirus myxoma virus is a novel oncolytic candidate that has no history of use in humans directly, as it has a distinct and absolute host species tropism to lagomorphs (rabbits). Myxoma virus has been recently shown to be able to also selectively infect and kill human tumor cells, a unique tropism that is linked to dysregulated intracellular signalling pathways found in the majority of human cancers. This review outlines the existing knowledge on the tropism of myxoma virus for human cancer cells, as well as preclinical data exhibiting its ability to infect and clear tumors in animal models of cancer. This is an exciting new therapeutic option for treating cancer, and myxoma virus joins a growing group of oncolytic virus candidates that are being developed as a new class of cancer therapies in man.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.209
GPT teacher head0.461
Teacher spread0.252 · 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.

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

Citations80
Published2007
Admission routes1
Has abstractyes

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