Abstract 223: Identifying gene amplifications in p53 abnormal endometrial carcinomas by shallow whole genome sequencing
Notice bibliographique
Résumé
Abstract Endometrial carcinoma (EC) is the most common gynecologic cancer in North America. A clinically molecular classifier called ProMisE (Proactive Molecular Risk Classifier for Endometrial Cancer) was developed based on the TCGA classification. p53abn EC is the most aggressive of the four ProMisE prognostic molecular subtypes, responsible for 50-70% of EC mortality. Therapeutic advances are urgently needed to improve outcomes for these patients. This research focuses on determining the significance of HER2 and CCNE1 amplifications in p53abn EC to identify therapeutic opportunities for this aggressive cancer. Tumor DNA extracted from cores of 203 formalin-fixed paraffin-embedded (FFPE) p53abn EC were Shallow Whole Genome (sWGS) sequenced. sWGS is a high-throughput technology designed to achieve genome-wide genetic variation accurately and cost-effectively. Raw data were aligned and treated to correct CG content and discard low-quality reads. Copy number alterations were called considering 5 to 9 copies as amplification and more than 9 as high-level amplification. Amplification data was later compared to HER2 and CCNE1 whole-section immunohistochemistry (IHC). Gene amplification is one of the major molecular pathways that can drive tumorigenesis, and many amplified genes have emerged as biological markers and therapeutic targets. HER2 amplification has an important prognostic and therapeutic implications in breast and gastric cancer. It is also seen in EC, arising as a possible targeted treatment opportunity for p53abn EC using anti-HER2 drugs. CCNE1 amplifications have been reported in platinum resistance aggressive ovarian and endometrial cancers and is known to be a biomarker to predict responsive to low-dose WEE1i-ATRi. Amplifications in CCNE1 were identified in 13% (26/203) of the cohort while the IHC overexpression (2/3+) was recorded in 64% of cases. HER2 amplifications were observed in 11% (22/203) of p53abn ECs compared to the IHC overexpression (2/3+) detected in 21%. Significant intratumor heterogeneity was identified. We found discrepancy between the techniques, with IHC detecting a significantly greater proportion of p53abn ECs overexpressing HER2 and CCNE1 than amplification found on sWGS. This phenomenon may be explained by the intratumor heterogeneity that was identified during the IHC scoring. The IHC was performed in whole sections while cores were used to extract DNA for the sWGS, which may have missed the gene amplification areas. Although there are some limitations, sWGS is a relatively inexpensive assay that can be performed on FFPE, and it is able to obtain whole genome sequence at a very low coverage (between 0.4x and 1x) with over 99% accuracy for copy number calls. In recent years sWGS have been used efficiently for copy number profiling tumors and for amplification detection thus having the potential to be implemented in clinical practice to guide targeted therapy. Citation Format: Juliana Sobral de Barros, Amy Jamieson, Dawn Cochrane, Maxwell Douglas, Janine Senz, Blake Gilks, Christine Chow, Shelby Thornton, Jessica N. McAlpine, David G. Huntsman. Identifying gene amplifications in p53 abnormal endometrial carcinomas by shallow whole genome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 223.
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 | 0,001 |
| 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) | 0,001 | 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 ».