Abstract B072: Cell alterations that drive vascular invasion and dissemination in pediatric liver cancer
Notice bibliographique
Résumé
Abstract Background: Hepatoblastoma (HB) and hepatocellular carcinoma (HCC) are the most common malignant hepatocellular tumors seen in children. Patients with vascular invasion and metastasis generally have poor outcomes. The aim of this study was to delineate the unique cellular changes that drive dissemination by performing comprehensive molecular and phenotypic profiling of samples representing disseminating cells, including primary circulating tumor cells (CTCs) from patients and orthotopic patient-derived xenograt (PDX) mouse models and cell lines grown in vitro in the presence of other cells that represent the tumor microenvironment (TME). Methods: With primary patient whole blood samples, we used a RosetteSep CD45 Depletion Cocktail (Stem Cell Technologies) to enrich CTCs. We validated that these cells were CTCs by staining for a panel of validated markers, including indocyanine green (ICG), Glypican-3 (GPC3), and DAPI. We then performed single cell RNA sequencing (scRNA-seq, 10x Genomics) to comprehensively analyze gene expression of these cells. To understand tumor dissemination mechanisms influenced by the TME, we grew HepT1 HB cells in the presence of supernatant from human umbilical vein endothelial cells (HUVECs). Specifically, HUVEC and HepT1 cells were cultured in separate plates in a combination of endothelial cell medium and minimal essential medium in a 1:1 ratio. The supernatant from each plate was then added to HepT1 cells, and we examined resulting transcriptomic changes with bulk RNA-seq and phenotypic alterations with proliferation (CCK8), scratch (Incucyte), and invasion (Boyden chamber) assays. We also worked to develop a pipeline to establish stable cell lines with primary patient- and murine-derived CTCs. Results: Using our ICG/GPC3/DAPI panel, we showed that the cells isolated from patient whole blood samples were CTCs. scRNA-seq analyses of these samples revealed that there was upregulation of key pathways in CTCs, including NRF2 activity, compared to low-risk primary HB tumors. Factors secreted by HUVECs influenced HepT1 cell phenotypes and gene expression. Specifically, we showed significantly higher migration and faster wound closure when HepT1 cells were grown in the presence of secreted factors from HUVECs, compared to control HepT1 cells. Conclusions: This study provides a comprehensive transcriptomic landscape of pediatric liver cancer CTCs. This work also underscores the importance of the interactions between endothelial cells and tumor cells in the initiation of metastasis. Taken together, this work builds a strong foundation for future studies elucidating the specific mechanisms of how pediatric liver tumor cells successfully disseminate with the overall goal of developing novel therapeutic regimens that target these mechanisms. Citation Format: Priyanka Rao, Andres Espinoza, Roma Patel, Mohammad J. Najaf Panah, Pavel Sumazin, Sanjeev A. Vasudevan, Sarah E. Woodfield. Cell alterations that drive vascular invasion and dissemination in pediatric liver cancer [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 B072.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,000 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».