MétaCan
Menu
Back to cohort
Record W4384277000 · doi:10.1002/ptr.7942

Enterolactone and trabectedin suppress epithelial ovarian cancer synergistically via upregulating <scp>THBS1</scp>

2023· article· en· W4384277000 on OpenAlexaff
Zheng Zeng, Caiji Lin, Meng‐Chun Zhang, Pathum Kossinna, Pengfei Wang, Danli Cao, Jiaxing Wang, Mengzhi Xu, Xiaoyu Wang, Qing Li, Xiaohui Xu, Hao Yang, Songling Zhu, Gui‐Rong Liu, Kaihong Xie, Jiaming Yang, Yao Luo, Yao Wang, Xinghua Zhang, Jingwen Lin, Hang Chen, Shu‐Lin Liu, Huidi Liu

Bibliographic record

VenuePhytotherapy Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsUniversity of Calgary
FundersChina Scholarship CouncilChina Postdoctoral Science FoundationNational Natural Science Foundation of ChinaHarbin Medical University
KeywordsOvarian cancerCancer researchAngiogenesisPaclitaxelCancerMedicineBiologyPharmacologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Epithelial ovarian cancer (EOC) is the most common and fatal subtype of ovarian malignancies, with no effective therapeutics available. Our previous studies have demonstrated extraordinary suppressive efficacy of enterolactone (ENL) on EOC. A chemotherapeutic agent, trabectedin (Trabe), is shown to be effective on ovarian cancer, especially when combined with other therapeutics, such as pegylated liposomal doxorubicin or oxaliplatin. Thrombospondin 1 (THBS1), a kind of matrix glycoprotein, plays important roles against cancer development through inhibiting angiogenesis but whether it is involved in the suppression of EOC by ENL or Trabe remains unknown. To test combined suppressive effects of ENL and Trabe on EOC and possible involvement of THBS1 in the anticancer activities of ENL and Trabe. The EOC cell line ES-2 was transfected with overexpressed THBS1 by lentivirus vector. We employed tube formation assay to evaluate the anti-angiogenesis activity of ENL and of its combined use with Trabe after THBS1 overexpression and established drug intervention and xenograft nude mouse cancer models to assess the in vivo effects of the hypothesized synergistic suppression between the agents and the involvement of THBS1. Mouse fecal samples were collected for 16S rDNA sequencing and microbiota analysis. We detected strong inhibitory activities of ENL and Trabe against the proliferation and migration of cancer cells and observed synergistic effects between ENL and Trabe in suppressing EOC. ENL and Trabe, given either separately or in combination, could suppress the tube formation capability of human microvascular endothelial cells, and this inhibitory effect became even stronger with THBS1 overexpression. In the ENL plus Trabe combination group, the expression of tissue inhibitor of metalloproteinases 3 and cluster of differentiation 36 was both upregulated, whereas matrix metalloproteinase 9, vascular endothelial growth factor, and cluster of differentiation 47 were all decreased. With the overexpression of THBS1, the results became even more pronounced. In animal experiments, combined use of ENL and Trabe showed superior inhibitory effects to either single agent and significantly suppressed tumor growth, and the overexpression of THBS1 further enhanced the anti-cancer activities of the drug combination group. ENL and Trabe synergistically suppress EOC and THBS1 could remarkably facilitate the synergistic anticancer effects of ENL and Trabe.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.048
GPT teacher head0.367
Teacher spread0.319 · 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

Citations18
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuePhytotherapy ResearchSame topicAngiogenesis and VEGF in CancerFrench-language works237,207