Longitudinal Analysis of Circulating Tumor DNA (ctDNA) in Diffuse Large B-Cell Lymphoma (DLBCL) Using KAPA HyperCap Design Share Non-Hodgkin Lymphoma (KAPA HyperCap DS NHL) Next-Generation Sequencing (NGS) Panel
Notice bibliographique
Résumé
Introduction Studies have shown that dynamic changes in lymphoma ctDNA levels are associated with patient outcomes and that monitoring lymphoma ctDNA may help identify patients who are at risk of refractory disease or relapse. NGS panels can successfully identify patient-specific tumor reporter variants in plasma specimens using a tissue-naïve approach that avoids limitations of patient tissue availability. Recently, using the AVENIO Oncology Assay (AOA) NHL Test* validated by the Roche Molecular CAP/CLIA Laboratory, a pre-specified analysis plan using samples from ~800 DLBCL patients from the POLARIX study validated ctDNA as an early prognostic biomarker (Herrera et al., Blood 2022). To further support clinical research on early molecular response (EMR) to treatment and minimal residual disease (MRD) in NHL, we introduce a KAPA HyperCap DS NHL panel designed to cover 100% of the target regions in the AOA NHL Test used for the POLARIX study. We describe the NGS workflow and bioinformatics analysis suitable for identification and monitoring of ctDNA using a tissue-naïve approach. We further describe performance characterization studies and feasibility of ctDNA detection using plasma specimens from patients with DLBCL. Methods KAPA HyperCap DS NHL panel covers coding and/or untranslated regions of 383 genes, plus additional intergenic regions, for a total of 341 Kb. This panel is used in combination with KAPA HyperCap workflows and KAPA reagents on Illumina® platforms, to sequence plasma cfDNA and matched genomic (g)DNA to identify tumor-specific single-nucleotide variants (SNVs) and monitor the dynamics of ctDNA. ctDNA detection and monitoring are supported by open-source bioinformatics tools for a fully integrated MRD analysis solution. Contrived samples for workflow characterization were comprised of commercially available reference materials with known SNV allele frequencies (AF) mimicking cfDNA (SeraSeq® Complete Mutation Mix and Twist Pan-cancer Reference Standard), as well as pre-characterized healthy donor cfDNA. Clinically annotated DLBCL samples were characterized and serially diluted to demonstrate feasibility of longitudinal mutation analysis. Results Serially diluted cfDNA samples and high molecular weight gDNA samples were used to assess the performance of the plasma cfDNA and germline workflows. Library quality control metrics met the yield and size distribution criteria for sequencing. A median of 88 M raw reads were obtained across all libraries. De-duplication yielded a median coverage depth range from 5000-9100 across samples. Median on-target rate (% selected bases) was between 74% and 80%. Average error rate was between 0.00024 or 0.00031 mismatches/read depth. 9 and 3 variants were detected after germline and blocklist filtering in the two commercial reference samples. Variant calling sensitivity was 100% across replicates at 5, 1 and 0.5% AF. In the serial dilution analysis, ctDNA was detected in all replicates at 5, 0.1 and 0.05% mean AF. For samples at 0.01% mean AF, ctDNA detection sensitivity was 83%. Initial data demonstrate that 131 SNV reporters were detected at 23% mean AF in a plasma sample from a treatment-naïve DLBCL patient. 4 SNV reporters were detected at 1.9% mean AF in a plasma sample from an immunochemotherapy-treated DLBCL patient. After 10x and 500x dilution, ctDNA positivity was accurately called at 2.3% and 0.05% mean AF levels for the patient with 131 reporters, and at 0.19% mean AF level for the patient with 4 reporters (Monte Carlo p-value <0.0001). Conclusion The use of KAPA HyperCap DS NHL panel with KAPA HyperCap workflows and open-source bioinformatics tools enables the detection and monitoring of ctDNA for NHL research applications. In contrived samples, variants were detected with high reproducibility at AF as low as 0.05% and with good reproducibility at AF of 0.01%. For a DLBCL patient with 131 SNV reporters in plasma, ctDNA was detectable down to 0.05% mean AF levels, while for a DLBCL patient with 4 SNV reporters, ctDNA was detectable down to 0.19% mean AF levels, demonstrating that sensitivity of Monte Carlo-based ctDNA detection depends on the number of reporter variants. *AVENIO Oncology Assay (AOA) NHL Test and KAPA HyperCap Design Share panels are for Research Use Only, not for use in diagnostic procedures. AVENIO and KAPA are trademarks of Roche. All other product names and trademarks are the property of their respective owners.
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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 | 0,001 | 0,001 |
| 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 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».