Abstract B024: Single cell transcriptomics and patient-derived tumoroids reveal that hepatobiliary lineage programs cooperate with Wnt pathway mutations to drive cell proliferation in hepatoblastoma
Notice bibliographique
Résumé
Abstract Cancers evolve not only through the acquisition and clonal transmission of somatic mutations but also by non-genetic mechanisms that modify cell phenotype. Such epigenetic causes of intra-tumoral heterogeneity may be particularly important in pediatric cancers with low rates of genomic mutations. Hepatoblastoma, the most common primary liver malignancy in children, has one of the lowest mutational burdens of all cancers, providing an ideal system to elucidate non-genetic mechanisms of intra-tumoral heterogeneity. Up to 80-90% of hepatoblastomas have activating mutations in CTNNB1 and the Wnt pathway. Yet, despite their simple genomics, these tumors exhibit significant histologic heterogeneity, including epithelial (embryonal and fetal histology) and mesenchymal components. Using transcriptomics and patient-derived tumoroids, we find that hepatobiliary lineage programs modulate the transcriptional outcome of mutated CTNNB1. A subset of cholangiocytic-like tumor cells express the growth factor FGF19, which promotes proliferation of neighboring cells in conjunction with activated Wnt signaling. To characterize the transcriptional profiles of the distinct histologic components of hepatoblastoma, we used laser capture microdissection to isolate tumor regions identified as embryonal, fetal, or mesenchymal histology, as well as adjacent normal liver. While all tumor regions showed increased expression of Wnt target genes as compared to normal liver, the embryonal components showed even higher expression of Wnt target genes as compared to the fetal components, as well as increased proliferation markers and higher expression of the embryonic biliary transcription factor SOX4. RNA in situ hybridization in primary hepatoblastomas revealed distinctive foci of embryonal hepatoblastoma cells that express the growth factor FGF19. These FGF19-expressing cells were surrounded by FGF19-negative cells that expressed KLB, the co-receptor for FGF19 signaling, and showed an increased proliferation. We therefore hypothesized that FGF19 acts in a paracrine fashion to drive cell cycle progression of hepatoblastoma cells in cooperation with constitutively active Wnt signaling. We further generated patient-derived tumoroids to systematically test the requirements for exogenous growth factors. We found that despite activated Wnt signaling, FGF19-negative tumor cells required additional exogenous growth factors to proliferate. In some tumoroids, subsets of cells expressed FGF19 endogenously, downstream of Wnt/beta-catenin and SOX4, acting as a paracrine signal. We conclude that the embryonic biliary transcription factor SOX4 cooperates with mutated beta-catenin, inducing FGF19 as a paracrine growth signal that can promote proliferation of FGF19-negative tumor cells. Thus, in this pediatric cancer presumed to originate from a multipotent hepatobiliary progenitor, lineage-driven heterogeneity results in a functional growth advantage, a non-genetic mechanism whereby developmental lineage programs influence tumor evolution, with implications for treatment. Citation Format: Peng V. Wu, Matt Fish, Florette K. Hazard, Chunfang Zhu, Sujay Vennam, Hannah Walton, Joanna Przybyl, Maurizio Morri, Norma Neff, Robert B. West, Roel Nusse. Single cell transcriptomics and patient-derived tumoroids reveal that hepatobiliary lineage programs cooperate with Wnt pathway mutations to drive cell proliferation in hepatoblastoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr B024.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| 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 ».