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Enregistrement W7005929389

The role of the metastasis suppressor gene «KISS1» in uveal melanoma

2014· other· en· W7005929389 sur OpenAlexvenueno aff

Notice bibliographique

RevueLibrary and Archives Canada (Government of Canada) · 2014
Typeother
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueDevelopmental Biology and Gene Regulation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMetastasis Suppressor GeneMelanomaMetastasisMetastasis suppressorCancerDiseaseDownregulation and upregulationSuppressorTumor suppressor gene
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Uveal Melanoma (UM) is the most common intraocular tumor in adults. Liver metastasis is the leading cause of death in patients affected by this disease and in approximately 40% of the cases, metastasis occurs 10 years after initial diagnosis. Tumor dormancy has been considered as a leading theory for the delay of the manifestation of metastatic disease and it has been the subject of numerous studies, which includes investigating metastasis suppressor genes (MSG). Studies have shown that the MSG KISS1 plays a role in various human malignancies, including melanoma, and it seems to be involved in the dormancy phase of the metastatic cascade. Previous studies from our laboratory reported that loss of KISS1 expression is related to worse prognosis in UM. In this light, mechanisms that involve increase of KISS1 expression are of interest for UM researchers. Interestingly, pathways involved in UM progression include upregulation of c-KIT, a cell surface molecule normally found in melanoma cells. This process seems to occur at the same time that KISS1 is downregulated and overt metastasis become clinically detectable. Therefore, we verified if inhibition of c-KIT could be related to KISS1 expression in metastatic UM. In addition, considering that a newly identified class of small non coding RNAs (miRNAs) are master regulators of gene expression, we sought to investigate if miRNAs were involved in metastasis of UM. Therefore, the objective of this thesis was to identify mechanisms that increase the expression of KISS1 and to better understand UM metastasis. To address these questions, we used a c-KIT inhibitor, imatinib mesylate (IM), and miRNAs in this study. Human UM cell lines with different metastatic potential showed increased levels of KISS1, by real-time reverse transcriptase polymerase chain reaction (RT-PCR), after treatment with IM. Notably, an increase in KISS1 was observed at the protein level in a dose response manner when the most aggressive UM cell line (92.1) was treated with different concentrations of IM. Increased levels of KISS1 expression were confirmed in vivo using an experimental animal model (albino rabbits). Using a miRNA array, we were able to identify miRNAs with prometastatic and antimetastatic effects in different UM cell lines and under diverse conditions. The miRNAs 10a, 10b, 21, and let-7 were upregulated in a liver metastatic cell line compared to the primary UM cell line from the same patient. Additionally, the UM cell line with aggressive potential transfected with KISS1 showed decreased expression of the miR-221 and increased expression of miR-146 compared to the non-transfected control. Similar results were obtained when the same cell line was treated with IM. In order to translate these results to a clinical setting, in situ hybridization of miR-221 was performed in 15 human UM FFPE tissues; increased expression of miR-221 was positively correlated with metastasis in UM. In conclusion, KISS1 was upregulated following treatment with IM. In addition, down regulation of miR-221 was found in all miRNA arrays with increases in KISS1 and treatment with IM. To the best of our knowledge, this is the first study to show that treatment with a c-KIT inhibitor causes an upregulation of KISS1, and that miR-221 may promote metastasis in UM. Consequently, induction of KISS1 expression downregulates miR-221 and should be considered as potential targets for adjuvant therapy in UM metastasis.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,759
Score d'incertitude au seuil0,955

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,001
Tête enseignante GPT0,132
Écart entre enseignants0,131 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2014
Routes d'admission1
Résumé présentoui

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