Abstract B019: Characterization of the extracellular vesicle proteome in Li-Fraumeni Syndrome
Notice bibliographique
Résumé
Abstract Li-Fraumeni Syndrome (LFS) is a hereditary cancer predisposition syndrome associated with germline mutations in the TP53 tumor suppressor gene. People with LFS are burdened with an increased lifetime risk to develop a broad spectrum of malignancies, with a 21.2-fold higher relative risk for cancer development in children (0-19 years) versus non-LFS children. Mutations in TP53 (mutp53) abrogate normal tumor-suppressive functions, including DNA repair, cell cycle arrest, metabolism, and apoptosis. This causes cells to accumulate DNA damage, alters cellular behaviors inducing pro-proliferative effects, and alters the cellular secretome, including extracellular vesicles (EVs). In cancer, EVs are a key component of the tumor microenvironment and facilitate core cancer hallmark pathways to promote tumorigenesis and metastasis. LFS mutp53 carriers may be “primed” for cancer initiation, wherein pathogenic germline TP53 variants establish a pre-cancerous niche within the body. However, to our knowledge, no study has investigated the role of EVs in non-malignant mutp53 cells on the pre-cancerous state. We hypothesize that LFS cell-derived EVs contain unique cargo which play local and systemic roles to promote pre-cancer niche priming and tumorigenesis in LFS. EVs were isolated from cell culture conditioned media by differential ultracentrifugation from skin biopsy-derived dermal fibroblasts from LFS patients (R248Q, R273C, R273H mutations) and wildtype (WT) controls, each in triplicate. EVs were characterized using Western blotting, transmission electron microscopy, and nanoparticle tracking analysis. Liquid chromatography-tandem mass spectrometry identified and quantified EV protein cargo for differential expression analysis in R. Fibroblast-derived EV proteomes in both LFS and WT were distinguishable from their parent cell proteomes by principal component analysis. Within EV groups, we identified four significantly differentially expressed proteins (p<0.05; GAS6, P3H1, PSG4, VNN1), and key functions in LFS EVs compared to WT EVS. We further identified differences between EVs derived from specific LFS hotspot mutations, R248Q and R273C, including an additional four differentially expressed proteins (p<0.05; CDH2, KRT10, RPLP0, TPI1). Key functions and processes associated with inflammation, invasion, apoptosis, and immune cell interactions are being further explored through in vitro and in vivo methods. For the first time, we have demonstrated that basal differences exist in the EV protein cargo of LFS cells. Liquid biopsies provide a minimally invasive method to assess a patient’s cancer risk for a personalized medicine approach to LFS surveillance protocols. Further characterization of the LFS EV proteome may identify liquid biopsy biomarkers for early detection of cancer development and risk assessment for LFS individuals. These findings also suggest a novel approach to therapeutics in targeting LFS derived EVs. Investigating differentially expressed LFS EV proteins will identify potential targets unique to LFS individuals. Citation Format: Paula R. Quaglietta, Ashby Kissoondoyal, David Malkin. Characterization of the extracellular vesicle proteome in Li-Fraumeni Syndrome [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 B019.
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 | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».