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Record W2358027606 · doi:10.18192/uojm.v6i1.1564

Gene Therapy and Modification as a Therapeutic Strategy for Cancer

2016· article· en· W2358027606 on OpenAlexaffvenue
Ahsen Chaudhry, Daud Akhtar

Bibliographic record

VenueUniversity of Ottawa Journal of Medicine · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGenetic enhancementCRISPROncolytic virusCancerGenome editingImmunotherapyVirotherapyCancer therapyGeneGene transferImmune systemCas9Gene deliveryCancer researchMedicineComputational biologyBiologyImmunologyGenetics

Abstract

fetched live from OpenAlex

Gene therapy is an exciting new field of personalized medicine, allowing for medical procedures that can target diseases such as cancer in novel ways. Technologies that involve gene transfer treatments allow for the insertion of foreign DNA into tumour cells, resulting in restored protein expression or altered function. Gene therapy can also be used as a form of immunotherapy, either by modifying cancer cells to make them better targeted by the immune system, or by modifying the body’s immune cells to make them more ag­gressive towards tumours. Additionally, oncolytic virotherapy uses classes of genetically modified viruses that can specifically target and interfere with tumour cells. The ongoing development of the CRISPR/Cas9 gene editing tool may also have promise in future therapeutic applications, with the tool being capable of removing cancer-causing, latent viral infections, such as HPV, from afflicted cells. Nonetheless, there are still many questions of safety, efficacy, and commercial viability which remain to be resolved with many gene therapy procedures. There is also emerging controversy over the ethical, legal, and moral implications that modifying the genetic content of human beings will have on society. These concerns must be confronted and addressed if the benefits promised by gene therapy are to be properly realized. La thérapie génétique est un nouveau domaine d’étude médicale personnalisée qui permet de cibler des maladies spécifiques comme le cancer de façon innovatrice. Cette thérapie utilise le transfert de gènes avec une insertion d’ADN étrangère dans les cellules can­céreuses dans le but de restaurer l’expression des protéines et de retrouver la fonction cellulaire. La thérapie génétique peut aussi être utilisée comme une forme d’immunothérapie, soit en modifiant les cellules cancéreuses pour qu’elles soient mieux ciblées par le système immunitaire ou en modifiant les cellules immunitaires du corps pour les rendre plus agressives envers les tumeurs. De plus, une virothérapie oncolytique utilise des virus génétiquement modifiés qui peuvent cibler spécifiquement et interférer avec des cellules cancéreuses. Le développement du système d’édition génétique CRISPR/Cas9 s’avère prometteur pour les applications thérapeutiques futures. Cet outil est capable d’enlever les infections virales latentes dans les cellules affectées qui peuvent causer le cancer, tel que l’HPV. Malgré ces découvertes, plusieurs questions importantes demeurent quant à la sécurité et à l’efficacité de leur application. Il s’agit d’un domaine controversé avec des implications éthiques, légales, et morales, car le tout implique une modification du contenu génétique humain. Ces inquiétudes doivent être adressées afin de pouvoir continuer à explorer les bienfaits de cette thérapie géné­tique. En poursuivant la recherche dans ce domaine, il serait possible de valider cette thérapie et optimiser ses bienfaits.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.025
GPT teacher head0.306
Teacher spread0.281 · 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

Citations1
Published2016
Admission routes2
Has abstractyes

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