Abstract 3141: Pro-Seq: A novel method to improve sequencing accuracy for liquid biopsy of ctDNA from healthy individuals and cancer patients
Notice bibliographique
Résumé
Abstract A significant barrier to widespread clinical deployment of sensitive circulating tumor DNA (ctDNA) assays (liquid biopsy) is the high assay cost compared to potential reimbursement. Assay cost is currently dominated by the large amount of DNA sequencing required to achieve coverage of a broad gene panel, and by the high read depth required for high clinical sensitivity. Attaching unique molecular barcodes to ctDNA fragments for the purpose of error reduction further increases sequencing requirements, making liquid biopsy commercialization in many clinical applications impractical. We present a novel library construction process for NGS sequencing that increases the accuracy of the combined library construction and sequencing process by an order of magnitude. Named Proximity-Sequencing (Pro-Seq), the method duplicates the sequence information in each original DNA strand prior to the bulk of library construction in such a way as to provide redundant, linked templates to the sequencer. The redundant templates remain linked through the library construction process, allowing detection of PCR errors as sequence disagreement between the two strands. The linked templates are amplified in a single sequencing reaction, such that base quality and incorporation information can be used to determine which bases of the sequence were corrupted during PCR amplification steps. Since both strands are amplified as part of the same sequencing read, sequencing accuracy is improved without requiring use of additional reads on the sequencer. A key element of this process is a novel linked-linear amplification in which DNA primers linked by a short molecule amplify a single strand in the same sense, ensuring twin copies in the same sense that remain physically linked. The method is entirely based on novel reagents and can be implemented without additional instrumentation beyond standard NGS equipment. The method is expected to have significant utility in any applications that require detection of rare sequence variants, including analysis of cell free DNA for liquid biopsy applications. We demonstrate the ability to achieve sequence accuracy similar to barcoded sequencing methods, without the additional sequencing burden required by such methods. We present the method using an Illumina platform, and present data from sequencing of bacterial and human cell free DNA that demonstrate error rates that are improved by an order of magnitude over the current state of the art NGS chemistries. The addition of Pro-Seq library construction to NGS assays enables lower cost, high sensitivity, and high specificity liquid biopsy tests to be developed, enabling commercialization in applications with limited reimbursement, potentially including early cancer detection. Citation Format: Andre Marziali. Pro-Seq: A novel method to improve sequencing accuracy for liquid biopsy of ctDNA from healthy individuals and cancer patients. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3141.
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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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».