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Record W2328418052 · doi:10.1158/1538-7445.am2013-4769

Abstract 4769: Growth hormone-releasing hormone (GHRH) antagonist attenuates cell motility of human endometrial cancer by down-regulating Twist and N-Cadherin expression.

2013· article· en· W2328418052 on OpenAlexaff
Hsien‐Ming Wu, Andrew V. Schally, Peter C. K. Leung

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMotilityGrowth hormone–releasing hormoneEndocrinologyInternal medicineAntagonistReceptorBiologyHormoneCancer researchMedicineCell biology

Abstract

fetched live from OpenAlex

Abstract Introduction : More than 25% of patients diagnosed with endometrial carcinoma have an invasive primary cancer accompanied by metastases. GHRH is secreted by the hypothalamus and stimulates the synthesis and secretion of GH from the pituitary. The expression of GHRH and its receptors has been demonstrated in peripheral tissues. In recent years, many antagonistic analogs of GHRH were developed. GHRH antagonists have effects on tumor cells, but the underlying molecular mechanism is not well known. Although Twist and N-Cadherin play important roles in cancer cell motility, it is not established whether Twist and N-Cadherin are required for GHRH antagonists-attenuated cell motility on endometrial cancer cells. In the present study, we examined the action of GHRH antagonist-attenuated cell motility and the mechanisms of the action in endometrial cancer. Methods and Materials : Endometrial cancer cell line Ishikawa and ECC-1 were derived from an endometrial adenocarcinoma. GHRH antagonist MIA-602 was synthesized by solid phase methods. Cell motility was estimated by invasion and migration assay. Immunoblot analysis and RT-PCR were performed to investigate the expression of GHRH receptor, GHRH, and the effects of GHRH antagonist in Twist and N-Cadherin. Human GHRH receptor siRNA was used to knock down the expression of GHRH receptor for elucidating the mechanisms of GHRH antagonist action. Results : The GHRH receptor was expressed in human endometrial cancer cells. The GHRH antagonist attenuated cell motility in a dose-dependent manner. GHRH antagonist-attenuated cell motility was restored in cells pretreated with GHRH receptor siRNA. GHRH antagonist suppressed Twist and N-Cadherin signaling. Knockdown of GHRH receptor with siRNA recovered the expression of Twist and N-Cadherin signaling. Conclusions These results demonstrate that the GHRH antagonist suppressed the cell motility of human endometrial cancer through the GHRH receptor and the down-regulation of Twist and N-Cadherin. Our findings represent a new concept regarding the mechanisms of GHRH antagonist-suppressed cell motility in human endometrial cancer, suggesting the possibility of GHRH antagonist as a potential therapeutic intervention for the treatment of human endometrial cancer. Citation Format: Hsien-Ming Wu, Andrew V. Schally, Peter C.K. Leung. Growth hormone-releasing hormone (GHRH) antagonist attenuates cell motility of human endometrial cancer by down-regulating Twist and N-Cadherin expression. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4769. doi:10.1158/1538-7445.AM2013-4769 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.050
GPT teacher head0.359
Teacher spread0.309 · 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 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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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