Abstract A009 Single cell transcriptomic signature of Li-Fraumeni Syndrome soft tissue sarcomas
Notice bibliographique
Résumé
Abstract Li-Fraumeni Syndrome (LFS) is a genetic predisposition disorder associated with pathogenic germline Tp53 mutations. A subset of LFS-associated neoplasms occurs at an increased risk within the first 5 years of life, with the most common being soft tissue sarcomas (STS). Histological characterization of STS is one of the primary approaches to guiding treatment. However, the heterogeneity of STS has necessitated a further understanding of the molecular etiology of these tumors. Examining sarcomas using a single-cell transcriptomic approach has shown unique subsets of cells with dysregulations in cell fate and differentiation. Within LFS-associated tumors, including LFS-STS a major event in tumorigenesis is the copy-neutral loss of heterozygosity (LOH). LOH was determined to occur much earlier than cancer onset in LFS, suggesting a dormancy period from the LOH until tumorigenesis; cancer-defining events in LFS are likely occurring prenatally. During embryogenesis, Tp53 is involved in differentiation and pluripotency regulation, as well as cell cycle control and apoptosis. Here we hypothesize that the emergence of STS in LFS mice is associated with distinct disturbances in the cell fate and differentiation pathways. Specifically, there will be deficits in cell fate determination and the organization of cells across multiple cell types in LFS-Sarcomas. Single-cell RNAseq was performed on spontaneous tumors and healthy matched muscle tissue from male and female C57BL/6J Trp53R172H/WT mice. Cell types were determined based on differential gene expression between clusters defined by principal component analysis. Despite tumor heterogeneity between mice, there were consistent disruptions of developmental pathways among tumor cells. Moreover, when comparing matched cell types across tumor and healthy muscle tissue we observed dysregulation of pathways promoting tumorigenesis, and cell fate determination in cells originating from tumor tissue. For the first time to our knowledge, this study examines the single-cell transcriptome of LFS-STS. Current literature has speculated on the presence of an early precancer state of LFS-associated tumors. This study will provide evidence to determine whether this precancer state can be determined in tumor samples, and identify elements that constitute this state. Moreover, we will determine changes in supporting non-tumor cells and whether they also exhibit dysregulations in cell state and differentiation. Together these findings will hopefully contribute to improvements in molecular subtyping across STS, and particularly within LFS individuals. Citation Format: Ashby Kissoondoyal, David Malkin. Single cell transcriptomic signature of Li-Fraumeni Syndrome soft tissue sarcomas [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 A009.
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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 | 0,001 | 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) | 0,001 | 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 ».