Abstract A037 Changes in T-cell repertoire during high-risk neuroblastoma therapy: A report from the Children’s Oncology Group
Notice bibliographique
Résumé
Abstract Introduction: High-risk neuroblastoma (HRNB) carries a poor prognosis, with a 5-year survival rate of ∼50% despite intensive treatment. The standard of care (SOC) for HRNB consists of induction chemotherapy, multimodal consolidation therapy, and post-consolidation immunotherapy. While previous research has linked infiltrating T-cells to better prognosis in some pediatric cancers, the importance of the peripheral T-cell repertoire and its T-cell receptors (TCRs) as immune biomarkers for HRNB remains unexplored. Here, we performed a preliminary immunogenomic analysis of a subset of blood samples from the Children’s Oncology Group phase 3 clinical trial NCT03126916, designed to evaluate the effects of adding targeted therapies (including 131I-MIBG) to the SOC on survival and response. Methods: To infer the nucleosome positioning of immune-related sites from coverage information, we generated blood cell-free whole genome sequencing (cfWGS) data for an initial group of 33 patients (N=35 samples). To track the T-cell repertoire, we sequenced TCRs for 12 of the 33 patients from cell-free DNA (cfDNA) (N=14 samples) and peripheral blood mononuclear cells (PBMCs) (N=26 samples) across diagnosis, mid-induction, and end of post-consolidation. Four patients have samples from all timepoints. We computed peripheral TCR diversity and measured TCR specificity using GLIPHII (Grouping Lymphocyte Interactions by Paratope Hotspots II), against a database of 3681 TCR sequences with empirically defined specificities. We included data from 99 children with non-HRNB cancers and 18 healthy adults as controls. Results: Our diversity analysis found a 4-fold decrease in PBMC TCR diversity from diagnosis (Shannon diversity, mean 619.81) to mid-induction (mean 154.55) and a subsequent increase from mid-induction to post-therapy (mean 557.94; Satterthwaite's mixed-effects model, p=0.003). Our specificity analysis detected 112 TCRs in PBMCs and cfDNA that overlap sequences found in ≥3 relapsed pediatric controls with non-HRNB cancers (per patient mean 3.1; range 0-14). This highlights the possibility to identify relapse-associated antigens for detection of early relapse. Our nucleosome positioning analysis indicated that lymphoid- and myeloid-related genes exhibit reduced accessibility in HRNB at diagnosis compared to healthy adult controls (Welch's t-test, central coverage: p<0.0001). By contrast, MYCN shows higher accessibility, consistent with high expression levels of this oncogene (p<0.0001). The differential accessibility at immune sites compared to oncogenic sites suggests potential mechanisms for immune response alterations. Conclusion: Our initial analysis revealed a mid-chemotherapy decrease in TCR diversity in PBMCs, followed by a partial post-therapy recovery. This shift in diversity was accompanied by the presence of relapse-linked TCRs in some patients but not others, highlighting their potential as emergent immune biomarkers. Additional samples are being analyzed for association with outcomes with standard of care with and without 131I-MIBG. Citation Format: Yiyue Jiang, Arash Nabbi, Arnavaz Danesh, Stephanie Pedersen, Jenna Eagles, Arlene Naranjo, Kai Tan, Natalie Collins, Steven G. DuBois, Rochelle Bagatell, Brian D. Crompton, Trevor J. Pugh. Changes in T-cell repertoire during high-risk neuroblastoma therapy: A report from the Children’s Oncology Group [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 A037.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».