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Enregistrement W2404961651 · doi:10.18632/oncoscience.134

BCC or not: Sufu keeps it in check

2015· article· en· W2404961651 sur OpenAlexaff
Wen-Chi Yin, Zhu Juan Li, Chi‐chung Hui

Notice bibliographique

RevueOncoscience · 2015
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueHedgehog Signaling Pathway Studies
Établissements canadiensHospital for Sick Children
Organismes subventionnairesnon disponible
Mots-clésHedgehogPTCH1Hedgehog signaling pathwayVismodegibBiologyCarcinogenesisCell biologyCancer researchTranscription factorSmoothenedGeneticsGeneSignal transduction

Résumé

récupéré en direct d'OpenAlex

Basal cell carcinoma (BCC), driven by aberrantly activated HEDGEHOG (HH) pathway, is the most common human malignancy. Current FDA-approved targeted therapy uses Vismodegib to inhibit SMO, a membrane component of the HH pathway. Despite initial impressive tumor regression, the positive clinical response is short-lived in some BCC patients as acquired SMO mutations confer secondary resistance[1]. Clearly, a deeper understanding of the molecular events underlying BCC tumorigenesis is required to devise effective treatments. The activity of SMO is repressed by the HH receptor PTCH1. Upon HH binding, SMO promotes dissociation of GLI transcription factors from the key negative intracellular regulator SUFU, thereby allowing expression of HH target genes[2]. Mutations in PTCH1, SMO, and SUFU, believed to unleash GLI activity, are frequently found in BCC. SUFU, like PTCH1, is a major negative regulator of the HH pathway. We have previously shown that loss of Sufu in mouse keratinocytes promotes Gli2 nuclear localization due to lack of cytoplasmic sequestration, and consequently leads to elevated target gene expression[3]. Surprisingly, unlike Ptch1, inactivation of Sufu alone in the mouse skin does not cause BCC. To identify the key oncogenic events in BCC formation, we performed microarray coupled with Gene Set Enrichment Analysis on Ptch1 and Sufu mutants[4]. The comparative analysis revealed that loss of Ptch1 in keratinocytes led to significant enrichment of gene sets involved in TGF-β signaling and extracellular matrix remodelling, consistent with the tumorigenic phenotype. In contrast, the majority of gene sets uniquely enriched in Sufu knockout keratinocytes are involved in cell cycle control, suggesting a novel role of Sufu in cell cycle regulation. Intriguingly, unlike Ptch1 knockout skin, which showed elevated number of mitotic cells, Sufu knockout skin exhibited normal mitotic count. Furthermore, while DNA damage was found in both mutants, Sufu knockout cells displayed DNA damage-induced G2/M checkpoint cell cycle arrest. These results indicate that Ptch1 knockout cells are able to override the checkpoint and continue proliferation with the unstable genome while Sufu knockouts halt, a key feature likely contributing to their differential cancer phenotypes. Arrest at G2 is typically coupled with accumulation of p53, which activates p21 and 14-3-3σ to sequester mitosis-promoting complex Cyclin-B1/CDK1. Strikingly, p53 protein and p21 transcripts remained low in Sufu mutants despite the arrest. These findings suggest that while both loss of Sufu and Ptch1 result in increased entry into cell cycle and impairment in p53 response to cell cycle-driven DNA damage, Sufu itself may be a positive regulator of cell cycle progression independent of the p53 checkpoint. Upregulation of the major HH pathway effector, Gli2, is a hallmark of BCC and is observed in Ptch1 mouse models. Consistent with our finding that loss of Ptch1 leads to genome instability and evasion of cell cycle checkpoints, Pantazi et al.[5] recently demonstrated that overexpression of GLI2 activator (GLI2sN) in human keratinocytes is sufficient to induce chromosomal aberrations. They also found that GLI2sN overexpression results in suppression of cell cycle regulators p21 and 14-3-3σ, and induction of anti-apoptotic mechanisms. These lines of evidence suggest that GLI2 is likely the major mediator of the malignant transformation induced by the loss of PTCH1 during BCC tumorigenesis. In vitro studies demonstrated that HH signaling can positively regulate cell cycle by promoting the expression of cell cycle regulators (D-type cyclins) and preventing the accumulation of p53. These are consistent with the active mitosis and evasion of cell cycle arrest observed in Ptch1 knockout cells. Our findings suggest that Sufu may also regulate cell cycle. However, it remains unclear why and how the loss of this negative HH pathway regulator causes cell cycle arrest. One possible mechanism is through DNA damage response, which involves the ATM/ATR, CHK1/CHK2, and CDC25C axis to inactivate the Cyclin-B1/CDK1 complex, leading to G2 arrest. Figure 1 Inactivation of Ptch1 and Sufu lead to distinct cellular events in keratinocytes Whether Sufu's cell cycle function is Gli-dependent is also unknown. Although ectopic HH target gene expression was found in both Sufu and Ptch1 mutants, Gli2 protein is significantly reduced in Sufu mutants compared to wildtype, with exclusive nuclear localization. It is possible that a certain threshold of Gli2 activity is required for evasion of cell cycle arrest and tumor surveillance, and that BCC tumorigenesis is stunted in Sufu mutants since the threshold is not achieved. Double knockout of Sufu and Ptch1 may help determine whether Sufu is required for the rapid cell cycle progression induced by loss of Ptch1. In addition, with the recent advances in BioID mass spectrometry[6], identification of Sufu's interactome in keratinocytes may give mechanistic insights into Sufu's involvement in cell cycle regulation. In conclusion, this comparative study of Ptch1 and Sufu mutant mice advanced our understanding of BCC tumorigenesis. Further investigations elucidating the role of Sufu in the cell cycle are warranted for the reason that if Sufu can also function as a positive regulator of the HH pathway, it may represent a potential target for therapeutic intervention of BCC.

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)0,001
score de la tête « metaresearch » (Gemma)0,001
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: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,404
Score d'incertitude au seuil0,322

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
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 Opus0,117
Tête enseignante GPT0,347
Écart entre enseignants0,229 · 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
GenreEmpirique

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

En bref

Citations4
Publié2015
Routes d'admission1
Résumé présentoui

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