Abstract 2107: Insights into inherited genetic variations and genetic ancestry of patients with high-risk melanoma
Notice bibliographique
Résumé
Abstract Introduction. For melanoma patients (pts) with resectable regional or distant metastases, there is paucity of data related to inherited genetic variations and genetic ancestry in the North American patient population. Methods. We conducted genome-wide genotyping on samples from 744 consenting pts enrolled in E1609 adjuvant trial that tested ipilimumab vs interferon-α in high-risk melanoma including sites across the U. S. and Canada. We used Illumina Infinium Global Screening Array v.3.0. After imputation, pruning, and incorporating genotypes from 1KGP3 as reference, genetic ancestry was estimated using admixture v1.3.0 in the unsupervised mode. Population structure was visualized through a UMAP dimensionality reduction (R package umap_0.2.9.0). Genetic ancestry proportions were visualized using python package PONG v1.5. Results. In UMAP reduction, most (728) cases clustered with the 1KGP3 European (EUR) reference, with small subsets (12 and 14, respectively) clustering with the admixed American (AMR) and East Asian (EAS) references. Considering potential ancestral origins for the study pts, we assumed between 4 to 8 ancestral populations in order to capture a wider range of ancestral contributions. Unsupervised admixture inference on the combined genetic data from our cohort and the 1000 Genomes reference identified ancestral axes clearly along continental geographical lines. K=5 was deemed most optimal in broadly capturing the potential complexity of genetic contributions in U.S. context. The ancestry populations identified were Africa (AFR), AMR, EAS, EUR, South Asia (SAS). For most (734) samples, the estimated EUR proportion was >50%, while 4 had >50% EAS ancestry, 4 >50% AMR ancestry, and 2 >40% EUR and AMR ancestry. Most (725) participants self-reported their race as White, 4 as Asian, and 1 as multi-race; 14 missing information on race. For the 725 White participants, 13 identified as Hispanic and 24 missing information on ethnicity; and for these participants, there was a high degree of EUR ancestry (>95% in 22), with only 2 having between 4-6% combined AMR and AFR contributions. The 4 Asian participants had a high degree of EAS ancestry, and the multi-race participant had a high degree of EUR ancestry with minor degrees of AMR and EAS ancestry. Participants with missing information on self-reported race had either a high degree of EUR ancestry or various combinations of significant AMR, EUR, and AFR contributions. The 17 participants reporting Hispanic ethnicity had a significant AMR ancestral contribution. The vast majority of participants not reporting (699) or missing (28) information on Hispanic ethnicity did not have AMR ancestry. Conclusions. Our analysis in the context of a U.S. Intergroup phase 3 trial revealed important insights into genetic ancestry of patients with high-risk melanoma. Ongoing analyses are investigating associations with survival outcomes and the risk of irAEs. Citation Format: Ahmad A. Tarhini, Zhihua Chen, Sandra J. Lee, F. Stephen Hodi, Islam Eljilany, Tingyi Li, Howard Streicher, Vernon K. Sondak, Xuefeng Wang, Peter A. Kanetsky, John M. Kirkwood. Insights into inherited genetic variations and genetic ancestry of patients with high-risk melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2107.
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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 | 0,001 | 0,003 |
| 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 | 0,001 | 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) | 0,006 | 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 ».