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Record W3013487151 · doi:10.1080/15384101.2020.1743902

The ectopic expression of meiCT genes promotes meiomitosis and may facilitate carcinogenesis

2020· review· en· W3013487151 on OpenAlexafffund
Jennifer Gantchev, Amelia Martínez Villarreal, Scott R. Gunn, Monique Zetka, N Odum, Ivan V. Litvinov

Bibliographic record

VenueCell Cycle · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersFonds de Recherche du Québec - SantéNovo Nordisk FondenCanadian Dermatology Foundation
KeywordsBiologyEctopic expressionCarcinogenesisGeneAneuploidySomatic cellGenome instabilityGeneticsContext (archaeology)MitosisMeiosisGermlineCancer researchCell biologyDNA damageChromosomeDNA

Abstract

fetched live from OpenAlex

Cancer meiomitosis is defined as the concurrent activation of both mitotic and meiotic machineries in neoplastic cells that confer a selective advantage together with increased genomic instability. MeiCT (meiosis-specific cancer/testis) genes that perform specialized functions in the germline events required for the first meiotic division are ectopically expressed in several cancers. Here we describe the expression profiles of meiCT genes and proteins across a number of cancers and review the proposed mechanisms that increase aneuploidy and elicit reduction division in polyploid cells. These mechanisms are centered on the overexpression and function of meiCT proteins in cancers under various conditions that includes a response to genotoxic stress. Since meiCT genes are transcriptionally repressed in somatic cells, their target offers a promising therapeutic approach with limited toxicity to healthy tissues. Throughout the review, we provide a detailed description of the roles for each gene in the context of meiosis and we discuss proposed functions and outcomes resulting from their ectopic reactivation in cancer.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.709
Threshold uncertainty score0.745

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 integrity0.0000.000
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 head0.024
GPT teacher head0.261
Teacher spread0.237 · 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 designOther design
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

Citations24
Published2020
Admission routes2
Has abstractyes

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