Abstract 538: Cell-free whole genome sequencing for the detection of cancer in patients with germline <i>BRCA1/2</i> mutations
Notice bibliographique
Résumé
Abstract Background: Hereditary breast and ovarian cancer syndrome (HBOC) is caused by a germline likely/pathogenic variant in BRCA1 or BRCA2, leading to increased risk of developing breast, ovarian, prostate, and pancreatic cancers. While HBOC patients often undergo regular surveillance including breast imaging, other cancers have no effective screening or biomarkers. One emerging technology is the analysis of circulating tumor DNA (ctDNA), fragments of DNA that are shed from the tumor into the bloodstream. In sporadic cancer, several studies have demonstrated the advantages and sensitivity of cell-free whole genome sequencing (cfWGS) compared to targeted panel sequencing. However, the use of cfWGS for cancer detection in HBOC has not been explored. Methods: Matched tumor, germline, and plasma were collected from 5 HBOC patients (3 breast, 2 ovarian) as part of the Canada-wide CHARM consortium (https://charmconsortium.ca). Tumor (40x), germline (20x), and plasma (20x) underwent whole genome sequencing (WGS) and subsequent variant calling pipeline using an ensemble of 6 variant callers. Insertions, deletions, and structural variants were not included in downstream analyses. Plasma tumor fraction prediction and copy number alterations were performed using ichorCNA. Detection of tumor associated mutations in plasma was compared to MRDetect software. Results: Variant calling identified an average of 11,170 tumor (7,649-16,706) and 1,215 (544-3,205) plasma SNVs per patient. Somatic BRCA1/2 mutations were detected in 0/5; whereas deletion of the intact BRCA1/2 allele was identified in 5/5 patients. An average of 24.6% (8.3%-75.9%) of plasma mutations where shared with SNVs identified in matched tumor. Targeted panel deep-sequencing (20,000X) was only able to detect mutations in TP53 in 3/5 cases (0.8% - 8.6%). Plasma derived copy number alterations correlated well with tumor derived copy number alterations in 3/5 cases and ichorCNA predicted tumor fractions ranged from 0.038 to 0.196. Conclusions: Traditionally, targeted panel sequencing has been used to identify tumor associated mutations in plasma. While this technique is sensitive, major disadvantages include the narrow breadth of the captured regions and the inability to detect deletion events such as those that occur in BRCA1/2. Here we show that plasma WGS is effective for detecting tumor associated mutations in HBOC and is more sensitive than targeted panel sequencing. We are currently expanding our cohort to an additional 20 matched tumor pairs, including patients with pre-diagnosis plasma timepoints. Citation Format: Derek Wong, Adriana Aguilar-Mahecha, Josiane Lafleur, Clarissa Chan, Kirsten Farncombe, Maia Norman, Leslie Oldfield, Prabhjit Basra, Stephanie Pederson, Johanna Wellum, Stephenie Prokopec, Mark Basik, Raymond H. Kim, Trevor Pugh. Cell-free whole genome sequencing for the detection of cancer in patients with germline BRCA1/2 mutations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 538.
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 | 0,002 |
| 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 | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,002 |
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 ».