In the present study, we screened 84 Follicular Lymphoma patients for somatic mutations suitable as liquid biopsy MRD biomarkers using a targeted next-generation sequencing (NGS) panel. We found trackable mutations in 95% of the lymph node samples and 80% of the liquid biopsy baseline samples.Then, we use an ultra-deep sequencing approach with 2 • 10 − 4 sensitivity (LiqBio-MRD) to track those mutations on 156 follow-up liquid biopsy samples from 55 treated patients. Positive LiqBio-MRD correlated with a higher risk of progression both at the interim evaluation (HR 13.0, 95% CI 2.70-63.4, p < 0.001) and at the end of treatment (EOT, HR 14.3, 95% CI 4.4-46.4, p < 0.001). Similar results were observed by PET/CT Deauville score, with a median PFS of 19 months vs. NR (p < 0.001) at the interim and 13 months vs. NR (p < 0.001) at EOT. LiqBio-MRD and PET/CT combined identi ed the patients that progressed in less than two years with 89% sensitivity and 100% speci city. Our results demonstrate that LiqBio-MRD is a robust and non-invasive approach, complementary to metabolic imaging, for identifying FL patients at high risk of failure during the treatment and should be considered in future responseadapted clinical trials.
The screening of the BCR::ABL1 kinase domain (KD) mutation has become a routine analysis in case of warning/failure for chronic myeloid leukemia (CML) and B-cell precursor acute lymphoblastic leukemia (ALL) Philadelphia (Ph)-positive patients. In this study, we present a novel DNA-based next-generation sequencing (NGS) methodology for KD ABL1 mutation detection and monitoring with a 1.0E−4 sensitivity. This approach was validated with a well-stablished RNA-based nested NGS method. The correlation of both techniques for the quantification of ABL1 mutations was high (Pearson r = 0.858, p < 0.001), offering DNA-DeepNGS a sensitivity of 92% and specificity of 82%. The clinical impact was studied in a cohort of 129 patients (n = 67 for CML and n = 62 for B-ALL patients). A total of 162 samples (n = 86 CML and n = 76 B-ALL) were studied. Of them, 27 out of 86 harbored mutations (6 in warning and 21 in failure) for CML, and 13 out of 76 (2 diagnostic and 11 relapse samples) did in B-ALL patients. In addition, in four cases were detected mutation despite BCR::ABL1 < 1%. In conclusion, we were able to detect KD ABL1 mutations with a 1.0E−4 sensitivity by NGS using DNA as starting material even in patients with low levels of disease.
Purpose: To assess the potential value of LiqBio as a complementary tool for diagnosis and surveillance of BCL. Methods: This prospective multi-center study included 78 patients (25 follicular lymphomas (FL) and 53 large B-cell lymphomas (LBCL)). We performed next-generation sequencing (NGS) of cfDNA LiqBio and paired gDNA tissue biopsies at diagnosis and compared the mutational statuses. Also, through NGS of LiqBio, we identified MRD biomarkers and compared this novel LiqBio–MRD method with PET/CT in detecting MRD at follow-up. Results: We identified mutations in 71% of LiqBio and 95% of tissue biopsies, and found a correlation between variant allele frequency of somatic mutations. Additionally, we identified mutations in 73% of LiqBio from patients with no available tissue samples or no mutations in them. Regarding the utility of LiqBio–MRD as a dynamic monitoring tool, when compared with the PET/CT method, a lower sensitivity was observed for LiqBio–MRD at 92.3% (vs. 100% for PET/CT), but a higher specificity of 91.3% (vs. 86.9% for PET/CT). Conclusion: Genetic profiling of tumor cfDNA in plasma LiqBio is a complementary tool for BCL diagnosis and MRD surveillance.
by PET/CT (2 yr PFS of 84% vs. 34%; p < 0.001 Figure 1B) identified two subgroups with different prognosis. Combining both approaches MMR and ΔSUVmax reduction, a better stratification was observed (2 yr PFS of 87% vs. 20% vs. 0%, p < 0.001; Figure 1C).
Conclusions:The Euroclonality-NDC panel allows the detection of a molecular marker in the ctDNA in >90% of DLBCL. ctDNA reduction at 2 cycles and its combination with PET interim allows the identification of patients with significantly different PFS. These results should be validated in larger series.
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