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Record W4390789116 · doi:10.1186/s13048-023-01332-w

The regulation of plasma gelsolin by DNA methylation in ovarian cancer chemo-resistance

2024· article· en· W4390789116 on OpenAlexafffund
Hafiza Bushra Manzoor, Meshach Asare-Werehene, Satyajit Dey Pereira, Kapaettu Satyamoorthy, Benjamin K. Tsang

Bibliographic record

VenueJournal of Ovarian Research · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of TorontoOttawa HospitalInstitute of Infection and ImmunityUniversity of Ottawa
FundersGénome QuébecMcGill UniversityCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsGelsolinOvarian cancerCancer researchDNA methylationCisplatinMethylationCancerBiologyMolecular biologyMedicineGene expressionGeneInternal medicineCell biologyChemotherapyGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: Ovarian cancer (OVCA) is the most lethal gynecologic cancer and chemoresistance remains a major hurdle to successful therapy and survival of OVCA patients. Plasma gelsolin (pGSN) is highly expressed in chemoresistant OVCA compared with their chemosensitive counterparts, although the mechanism underlying the differential expression is not known. Also, its overexpression significantly correlates with shortened survival of OVCA patients. In this study, we investigated the methylation role of Ten eleven translocation isoform-1 (TET1) in the regulation of differential pGSN expression and chemosensitivity in OVCA cells. METHODS: Chemosensitive and resistant OVCA cell lines of different histological subtypes were used in this study to measure pGSN and TET1 mRNA abundance (qPCR) as well as protein contents (Western blotting). To investigate the role of DNA methylation specifically in pGSN regulation and pGSN-induced chemoresistance, DNMTs and TETs were pharmacologically inhibited in sensitive and resistant OVCA cells using specific inhibitors. DNA methylation was quantified using EpiTYPER MassARRAY system. Gain-and-loss-of-function assays were used to investigate the relationship between TET1 and pGSN in OVCA chemoresponsiveness. RESULTS: We observed differential protein and mRNA expressions of pGSN and TET1 between sensitive and resistant OVCA cells and cisplatin reduced their expression in sensitive but not in resistant cells. We observed hypomethylation at pGSN promoter upstream region in resistant cells compared to sensitive cells. Pharmacological inhibition of DNMTs increased pGSN protein levels in sensitive OVCA cells and decreased their responsiveness to cisplatin, however we did not observe any difference in methylation level at pGSN promoter region. TETs inhibition resulted in hypermethylation at multiple CpG sites and decreased pGSN protein level in resistant OVCA cells which was also associated with enhanced response to cisplatin, findings that suggested the methylation role of TETs in the regulation of pGSN expression in OVCA cells. Further, we found that TET1 is inversely related to pGSN but positively related to chemoresponsiveness of OVCA cells. CONCLUSION: Our findings broaden our knowledge about the epigenetic regulation of pGSN in OVCA chemoresistance and reveal a novel potential target to re-sensitize resistant OVCA cells. This may provide a future therapeutic strategy to improve the overall OVCA patient survival.

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)0.004
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.060
GPT teacher head0.401
Teacher spread0.342 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations7
Published2024
Admission routes2
Has abstractyes

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