Abstract 5058: Genomic alterations predictive of outcome in early staged cervical cancer: <i>A translational investigation from the SENTICOL III trial</i>
Notice bibliographique
Résumé
Abstract Background: The risk of relapse in patients with early-stage cervical cancer (ESCC) ranges from 4-14% (LACC study). Risk-factors for recurrence are mainly derived from histopathological factors. Senticol III is a large multicenter international randomized prospective study aims to validate sentinel lymph node biopsy in the surgical management of ESCC. Our objective is to characterize prognostic and actionable biomarkers in ESCC. Methods: FFPE-fixed tumoral slides of the first 150 randomized patients were analyzed based on SEDLIS criteria. We characterized TIL’s infiltration, PD-L1 expression and HPV status. Sequencing of tumor DNA was carried out using an in-house targeted next-generation sequencing panel (571 genes). Relapse-free survival (RFS) was defined as the time between randomization and relapse of any type. We performed Fisher’s exact test and Student’s t-test to compare distributions of categorical variables and Log Rank test. Results: The sequencing quality control criteria were met for 135 samples. PIK3CA was the most commonly altered gene (17%). Loss-of-function variants in KMT2-family genes (KTM2C 9%, KMT2D 6%, KMT2A 1%) were found in 16% of samples. The loss-of-function variant of ARID1A was mostly non-sense mutation (6%). Activations of ERBB2 (5%) were 3 focal amplifications and 4 hotspot missense mutations. Two samples were found to have microsatellite instability due to an alteration of MLH1. The Pik3/AKT/mTOR (26%) and the chromatin remodeling (23%) pathways were the most altered pathways. The median follow-up period was 20 months. There were 6 relapses, of which 80% were considered as low risk based on SEDLIS criteria. Recurrences were local and occurred 9-23 months following surgery. Multiparity was the only clinical feature associated with RFS (p < 0,001). Tumor size, histological subtypes, PD-L1 status, number of TIL’s, presence or absence of lymphovascular emboli and deep stromal invasion were not associated with RFS in our cohort.KMT2C (p=0,018) and ARID1A (p < 0,001) pathogen variants were significantly associated with RFS. The pathway chromatin remodeling (p=0,063) showed a trend toward association with RFS. We found 32% of genomic alterations actionable for a target therapy including mutations of PIK3CA, ERBB2, ARID1A, PTEN, BRCA2, KRAS, BRAF, CDK12, FGFR2, NF1, AKT1, BRCA1, TP53 and MSI-high. Conclusion: Our prospective, randomized and multicentric study suggests a genomic profile from a homogeneous cohort of 150 patients. We identified genes involved in chromatin remodeling (ARID1A and KMT2C) as prognostic biomarkers of clinical interest and suggesting the relevance of epidrugs in ESCC. Theranostic annotations of variants identify a matched to target therapy for 32% of alterations. Those targets represent multiple tracks for personalized therapy in ESCC. Citation Format: Maryame El Gani, Sabrina Ibadioune, Zakhia El Beaino, Abderraouf Hamza, Sophie Vacher, Emmanuelle Jeannot, Julien Masliah-Planchon, Anne Salomon, Alexandre Degnieau, Anne-Sophie Bats, Martin Koskas, Virginie Fourchotte, Estelle Wafo, Nicolas Bourdel, Raffaele Fauvet, Marie Plante, Patrice Mathevet, Maud Kamal, Fabrice Lecuru, Ivan Bièche. Genomic alterations predictive of outcome in early staged cervical cancer: A translational investigation from the SENTICOL III trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5058.
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 | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».