Abstract 2689: Investigating the molecular mechanisms linking disrupted growth homeostasis to tumourigenesis in Li-Fraumeni Syndrome
Notice bibliographique
Résumé
Abstract Li-Fraumeni Syndrome (LFS) is a highly penetrant cancer predisposition syndrome caused by germline TP53 mutations. Patients face an increased lifetime risk to develop a broad spectrum of cancers. Implementation of comprehensive cancer screening protocols has led to improvements in survival for LFS patients. However, these interventions pose a significant burden to both patient quality of life and health resource utilization. While these interventions will always be important, recent evidence has suggested an additional approach which may improve patient outcomes: pharmacological prevention of cancer onset. mTORC1 inhibition selectively targets tumor initiation. While rapamycin, an mTORC1 inhibitor, has not shown efficacy in treatment of established cancers, it is reported to prevent tumor onset in mice that are genetically predisposed to cancer, including mouse models of LFS. mTORC1 is associated with protein synthesis and cellular growth. Hyperactivated cellular growth is associated with gain-of-function (GOF) TP53 mutations that underlie many cases of LFS. Wild-type p53 (wtp53) inhibits mTORC1 and, as a consequence, biosynthesis. We have shown that mutant p53 with oncogenic GOF (mutp53) may promote the opposite effect. Under conditions of inappropriately elevated protein synthesis, as is seen in cancer, stress responses, such as the unfolded protein response (UPR), are activated. UPR activation contributes to the secretion of pro-tumorigenic cytokines. We hypothesized that under conditions of elevated protein synthesis, mutp53 engages in a feedforward activation of biosynthesis which hyperactivates UPR-mediated secretion of pro-tumorigenic cytokines. In order to harness the cancer risk reduction potential of mTORC1 inhibition, we undertook investigation of the stress responses which may underlie tumorigenesis in LFS. We sought to establish whether mTORC1 ablation in the tumor microenvironment could influence growth of tumor xenografts formed from the co-injection of LFS patient-derived mutp53 fibroblasts and RH4 rhabdomyosarcoma cells, a representative LFS spectrum cancer cell line. While both wtp53 fibroblasts and mutp53 fibroblasts supported tumor growth, only the tumor growth reinforced by mutp53 fibroblasts was suppressed by rapamycin. Additionally, we utilized protein arrays to profile conditioned media collected from mutp53 and wtp53 fibroblast cultures. Mutp53 fibroblasts secreted higher levels of various pro-tumorigenic cytokines compared to wtp53 fibroblasts, which was partially negated by rapamycin. UPR target gene expression is elevated in fibroblasts expressing mutp53, and this effect is negated by rapamycin. Altogether, our work supports a role for mutp53-driven, mTORC1-mediated hyperactivated protein biosynthesis and subsequent engagement of the UPR, resulting in production of a pro-tumorigenic secretory milieu. Citation Format: Camilla Giovino, Frank Telfer, Nish Patel, Sangeetha Paramathas, Ran Kafri, David Malkin. Investigating the molecular mechanisms linking disrupted growth homeostasis to tumourigenesis in Li-Fraumeni Syndrome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2689.
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 | 0,001 | 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 | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».