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Record W4405640132 · doi:10.3390/curroncol31120594

Targeting TOP2A in Ovarian Cancer: Biological and Clinical Implications

2024· review· en· W4405640132 on OpenAlexvenueno aff
Fulvio Borella, Stefano Fucina, Ylenia Seminara, Domenico Ferraioli, Luca Bertero, Niccolò Gallio, Jessica Cusato, Giorgio Valabrega, Alberto Revelli, Luca Marozio, Stefano Cosma

Bibliographic record

VenueCurrent Oncology · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer therapeutics and mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsOvarian cancerMedicineCancer researchCancerTargeted therapyBioinformaticsBiologyInternal medicine

Abstract

fetched live from OpenAlex

The enzyme topoisomerase II alpha (TOP2A) plays a critical role in DNA replication and cell proliferation, making it a promising target for cancer therapy. In epithelial ovarian cancer (EOC), TOP2A overexpression is associated with poor prognosis and resistance to conventional treatments. This review explores the biological functions of TOP2A in EOC and discusses its potential as a therapeutic target. We highlight studies on the mechanisms through which TOP2A contributes to tumor progression and recurrence. Additionally, we evaluate the clinical implications of targeting TOP2A, including the use of TOP2A inhibitors and their combination with novel drugs. We provide a comprehensive overview of the current understanding and future directions for targeting TOP2A in the management of EOC.

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)0.000
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 score0.997
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.303
GPT teacher head0.541
Teacher spread0.239 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

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