Abstract A028: Growth factor signaling and kinase inhibitors regulate oncogenesis in desmoid fibromatosis by modulating activity of the beta-catenin transcription target ABL1
Notice bibliographique
Résumé
Abstract Introduction: While activation of beta-catenin is associated with desmoid fibromatosis (DF), mechanisms by which this oncogene initiates tumorigenesis are unclear as are factors underlying variable biologic behavior in the disease and vulnerability to targeted therapies. This study sought to define downstream pathways dysregulated by beta-catenin that may be modulated to potentially affect patient outcome. Methods: Multiple primary DF cell lines were developed from surgical specimens, validated by Sanger sequencing, and immortalized by ectopic expression of TERT. Gene expression was assessed in DF tumors (n=45) with U133A arrays and by RNA-seq in cells. Direct targets of beta-catenin were identified by CHIP-seq. Lentiviral systems were used to deliver shRNA (or scramble control) and overexpression constructs. Cell proliferation, protein levels/phosphorylation and gene expression were assessed by CyQuant DNA quantification, immunoblot, and RT-PCR, respectively. Endothelial cell (HUVEC) tube formation was quantitated using light microscopy. Results: Gene set enrichment analysis performed on RNA-seq data comparing DF cells treated with shRNA directed against CTNNB1 showed downregulation of hypoxia-regulated genes, and unsupervised analysis clustered 45 DF tumors separately from normal mesenchymal tissue based on the expression levels of these genes. CTNNB1 knockdown (KD) was associated with reduction in HIF1A and ability of DF cells to induced endothelial tube formation in HUVEC co-cultures (71%, p<0.001); ectopic expression of HIF1A in CTNNB1 KDs rescued this effect. HIF1A KD itself inhibited DF induction of HUVEC tube formation (49%, p<0.001), but did not affect DF cell proliferation. CHIP-seq nominated ABL1, a known regulator of HIF1 translation, as a direct target of beta-catenin. CTNNB1 KD caused 65% (p=0.01) decrease in ABL1 expression, and reduction in levels of c-ABL, its downstream target p-CRKL, and HIF1-alpha. Unlike HIF1A, ABL1 KD also reduced proliferation in multiple DF cell lines (up to 90%) as did direct inhibition of c-ABL with its inhibitor dasatinib (IC50 <50nM). Dasatinib and sorafenib, a PDGFR-beta inhibitor of clinical benefit in DF, both reduced cellular levels of p-ABL, p-CRKL and HIF1a expression in DF cells. Sorafenib also inhibited HUVEC tube-formation (59% at 1uM, p<0.05) induced by DF. Conversely, exogenous PDGF-BB stimulated DF proliferation (53% increase at 20ng/ml, p<0.05), increased p-ABL, p-CRKL and HIF1a in DF and promoted endothelial cell tube formation (2-fold, p<0.05) when added to DF and HUVEC co-cultures but not HUVEC cell cultures alone. Conclusion: ABL1 is a transcriptional target of beta-catenin in DF cells and is necessary for proliferation and maintenance of HIF1-alpha levels. Regulation of c-ABL activity by PDGFR-beta and targeted therapies modulates DF cell proliferation and paracrine signaling, suggesting a reason for variable biologic behavior between tumors and a mechanism for sorafenib activity in DF. This finding may point to markers predictive of outcome in patients. Citation Format: Jia Hu, Anthony Villano, Rachael O'Connor, Yuliy Rozenberg, Alankrta Venkatesh, Mrinal Gounder, Nicholas Socci, Samuel Singer, Meera Hameed, Aimee M. Crago. Growth factor signaling and kinase inhibitors regulate oncogenesis in desmoid fibromatosis by modulating activity of the beta-catenin transcription target ABL1 [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr A028.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».