Abstract A039: Pediatric pan-cancer characterization of transposable elements and their modulation by germline <i>TP53</i> variants
Notice bibliographique
Résumé
Abstract Transposable elements (TEs) are dynamic repetitive regions constituting 50% of the genome. In adult cancers, TEs contribute to carcinogenesis through structural rearrangements that disrupt tumor suppressors and by onco-exaptation, which drives aberrant oncogene expression. TEs are characterized in adult malignancies, with epithelial cancers harbouring significantly more new insertions. However, the role of TEs in pediatric cancer is unknown. Many pediatric cancers arise from predisposition, such as Li-Fraumeni Syndrome, which is caused by germline TP53 (gTP53) variants. TP53 suppresses TEs by binding L1 elements to inhibit transcription and by inducing apoptosis in cells with high retrotransposition. Moreover, adult cancers with somatic TP53 variants harbour significantly more TEs than wildtype tumors. To investigate the pediatric context, we conducted a pan-cancer analysis of germline and tumor TE landscapes in pediatric patients with (n = 66 germline; n = 40 tumor) and without (n = 465 germline; n = 276 tumor) gTP53 variants. Germline TEs were identified using MELT, xTEA, and INSurVeyor, while tumor TEs were called with xTEA and TotalReCall. TEs were consolidated across individuals using JASMINE and annotated with AnnotSV. We excluded 21% of germline and 2% of tumor TEs classified as common, defined as present in over 3% of gnomAD or pediatric non-cancer controls (n=189). Overall, 11% of pediatric tumors harbored at least one L1 insertion, with a median of 0 insertions per tumor, substantially lower than the 21% reported in adult cancers using the same TE callers (Solovyov et al). Frequency in germline or tumor TEs did not vary significantly by tumor type, age of onset, sex, prior treatment, or disease state. Germline and tumor TEs were found in 35 and 147 cancer genes respectively. Tumor TEs significantly affected many cancer pathways, including those involved in mitosis. While no structural variants (SVs) involved TEs at both breakpoints, 171 SVs in six samples were associated with a TE at one breakpoint. Importantly, both germline and tumor TE burden did not differ between gTP53 carriers and wildtype individuals, nor did the number of evolutionarily young or full-length elements. Pathway enrichment analyses revealed no significant differences in TE-affected pathways between gTP53 and wildtype groups. However, a gradient-boosted tree model trained on TE distribution across genomic windows predicted gTP53 status with an AUPRC of 0.77, suggesting that gTP53 variants shape the germline TE landscape at a positional level rather than through global frequency changes. In summary, pediatric cancers exhibit a quiescent TE landscape, with low insertion rates across tumor types. gTP53 variants do not alter the germline or tumor TE frequency,but influence the location of germline insertions. TE analysis in pediatric cancer and gTP53 carriers will enhance our understanding of tumorigenesis, informing future treatment approaches. Citation Format: Brianne Laverty, Shilpa Yadahalli, Safa Majeed, Ashby Kissoondoyal, Alexander Solovyov, Scott Davidson, Yisu Li, Mehdi Layeghifard, Adam Shlien, Vallijah Subasri, David Malkin. Pediatric pan-cancer characterization of transposable elements and their modulation by germline TP53 variants [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Artificial Intelligence and Machine Learning; 2025 Jul 10-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(13_Suppl):Abstract nr A039.
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 | 0,001 |
| 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 | 0,000 |
| 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 ».