Tumor-agnostic genomic and clinical analysis of solid tumors with <i>BRAF </i>fusions.
Notice bibliographique
Résumé
3146 Background: Approximately 15% of cancers harbor BRAF alterations, of which ~5% are BRAF fusions. BRAF fusions are class II alterations that have worse outcomes than class I V600E alterations. While prior investigational therapies for BRAF fusions had disappointing outcomes, novel therapies are in clinical trials, underscoring the need to better characterize these tumors. Methods: Data from adult and pediatric patients with BRAF fusion+ cancers identified between January 2014 and November 2022 utilizing a center-wide next generation sequencing (NGS) program of >99,000 sequenced samples were analyzed. DNA-based hybrid capture tumor NGS (MSK-IMPACT), ctDNA targeted NGS (MSK-ACCESS), and/or RNA anchored multiplex PCR tumor NGS (MSK-Fusion) were used. Fusions were manually reviewed and considered to have oncogenic potential if they had an in-frame protein fusion involving a non-BRAF partner gene and an intact BRAF kinase domain (exons 11-18). Fusions not previously reported in OncoKB, COSMIC, TCGA, NIH gene, Fusion GDB2, and PubMED were classified as novel. All cases underwent clinical data curation including baseline demographic, tumor characteristics, and treatment histories. Results: 212 patients (0.2%) with BRAF-fusion positive solid tumors were identified. 194 were identified by DNA-based tumor NGS (96 had sufficient tissue for confirmatory RNA-based NGS, all of which were positive). Six were identified by ctDNA NGS and 12 by RNA-based tumor NGS only (5 had insufficient tissue for DNA-based tumor NGS). 83 unique 5’ fusion partners were found, of which 42 were novel. The most frequent tumor types were pilocytic astrocytoma (n=30, 14%), prostate CA (n=28, 13%), melanoma (n=24, 11%), lung CA (n=21, 10%), and colon CA (n=15, 7%). 44% of patients with pilocytic astrocytoma had BRAF fusions, of which 90% were BRAF-KIAA1549. Concomitant alterations (≥10% frequency) included TP53 (24%), TERT (18%), CDKN2A deletions (13%), and CDKN2B deletions (12%). 20% (n=43) were treated with MAPK-pathway directed therapies spanning multiple histologies and lines of therapies. Of the 212 patients, 17 had acquired BRAF fusions after targeted therapy for another oncogene ( EGFR mutation (n=11), BRAF V600E (n=4), FGFR fusion (n=1), NTRK fusion (n=1)). The majority of patients with acquired BRAF fusions had EGFR-mutant lung adenocarcinoma (n=11, 76%); the median time from EGFR targeted therapy initiation to BRAF fusion detection was 25 months (range 16-38 months). Conclusions: A wide variety of adult and pediatric solid tumors harbored de novo BRAF fusions. Complementary RNA sequencing optimized fusion identification in many cases. Multiple novel fusion partners were found. Acquired BRAF fusions were identified after targeted therapy for a variety of distinct oncogenes, the majority of which were EGFR mutations.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 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 | 0,001 |
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 ».