Early Identification of Refractory/Relapsed Diffuse Large B Cell Lymphoma with Serial Ctdna Sampling
Notice bibliographique
Résumé
Background: Diffuse Large B Cell Lymphoma (DLBCL) is an aggressive lymphoma that is curable in 60% of patients with chemoimmunotherapy. Outcomes are poor for those experiencing relapsed or refractory disease (rrDLBCL), particularly for patients with primary refractory disease (REFR, < 9 months from diagnosis) and early relapse (ER, 9 months to 2 years from diagnosis). Some of these patients would be candidates for chimeric antigen receptor T cell therapy (CART) in second line, where outcomes are superior when the disease burden is low. Therefore, exploring strategies to identify these high-risk patients early is important. Plasma circulating tumor DNA has been shown to be prognostic in various DLBCL cohorts. Method: We developed a custom panel of 170 genes to identify early treatment failure in a cohort of 171 patients that had profiling performed on 323 plasma samples. Plasma samples were taken serially starting at diagnosis and as patients progressed through frontline treatment. All plasma samples underwent DNA extraction, library preparation and subsequent sequencing using a panel of DLBCL related genes at high read depth (~1000x). Single nucleotide variant (SNV) calling was carried out using a custom pipeline including paired normal DNA for improved somatic variant detection. ctDNA fraction was estimated based on the highest variant allele fraction detected, using a loss of heterozygosity somatic model. Our ctDNA analysis focused on samples at diagnosis, cycle 2 of therapy, and end of treatment in order to identify early determinants of refractory disease. Changes in ctDNA levels between time points were represented as log2 ratio of ctDNA fraction. Results: rrDLBCL cases were separated into 3 categories based on the time between diagnosis and progressive disease (PD): 47 REFR, 34 ER, and 31 late relapse (LR, >24 months). The remaining patients were disease free after frontline therapy for over 24 months (CR, n=59), resulting in a cohort enriched for rrDLBCL (65% of cases). The average international prognostic index (IPI) of each group at diagnosis was REFR=3.38, ER=2.87, LR=2.81, and CR=2.41. Cell of Origin, as determined by Hans algorithm, showed a higher number of non-GCB samples in ER and LR groups (53% and 60%, respectively) while REFR and CR displayed increased GCB cases (63% and 66%, respectively). The REFR patients were significantly more likely to be of a 4/5 IPI score at diagnosis than other groups (p=0.0203). Progression-free survival (PFS2) at relapse therapy for REFR (median=0.29 years) was shorter when compared to both ER (p=0.0104, median=0.44 years) and LR (p=0.0012, median=0.80 years). Using the diagnostic plasma sample, there was no significant difference in ctDNA fraction in any of the three groups. When the sample with the highest ctDNA fraction was compared between patients, REFR had significantly higher levels than LR and CR, consistent with a higher overall tumor burden (p=0.001 and 0.026, respectively). There was a trend towards higher ctDNA fraction at the end of treatment in both REFR and ER groups. As ctDNA dynamics are known to be informative of molecular response, we compared patients using the change in ctDNA fraction at cycle 2 of therapy (log2 ratio). This value was significantly different in REFR patients (p=0.0073 vs ER), consistent with a lower rate of molecular response to treatment. Conclusions: While refractory and later relapsed DLBCL have similar ctDNA features at diagnosis, we find they have distinct ctDNA dynamics during treatment. REFR had higher maximal ctDNA levels across time points and both REFR and ER patients exhibited higher levels of ctDNA at end of treatment. Moreover, patients with minimal change in ctDNA levels at cycle 2 of therapy are at a high risk of treatment failure and refractory disease. Further exploration of the specific mutational patterns is ongoing. These results could enable the earlier identification of rrDLBCL and facilitate the prioritization of approaches for therapeutic intervention in rrDLBCL.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| 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 | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».