Molecular clustering on ctdna improves the prognostic stratification of dlbcl patients compared to ctdna levels

Hematological Oncology(2023)

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摘要
Introduction: The quantification of circulating tumor DNA (ctDNA) on the liquid biopsy at the time of diagnosis allows to stratify the outcome of diffuse large B-cell lymphoma (DLBCL) patients but its integration with molecular clustering has not been evaluated so far. Methods: A multicenter cohort of newly diagnosed and homogeneously treated DLBCL provided with ctDNA and with genomic DNA from lymph node (LN) biopsy represented the training cohort. A validation cohort of newly diagnosed DLBCL patients provided with ctDNA was collected. The CAPP-Seq assay was used. Results: The training cohort included 77 newly diagnosed DLBCL patients treated with R-CHOP-based therapy. After a median follow-up of 33.9 months, the 40-month progression-free survival (PFS) and overall survival (OS) were 65.2% and 80.2%, respectively. Using the LymphGen tool on ctDNA, 9 patients were classified as MCD, 5 as ST2, 7 as EZB, 5 as BN2 and 1 as molecular composite (BN2/ST2). ST2 and BN2 patients in both ctDNA (p = 0.032) and in LN biopsy (p = 0.007) displayed an excellent PFS compared to other patients. By recursive partitioning, patients assigned to clusters ST2 or BN2 (N = 10) further split the outcome of patients with ctDNA levels ≥2.5Log10hGE (40-month PFS of 100% compared to 33.2% for patients classified as MCD or EZB or not classified, p = 0.009). Therefore, by combining ctDNA levels and molecular clusters identified on the liquid biopsy, patients with <2.5Log10hGE and/or assigned to cluster BN2 and ST2 presented a 40-month PFS and OS of 80.4% and 93.0%, compared to 33.2% and 54.8% for other patients, respectively (both p < 0.001) (Figure 1A). Interestingly, 80% of ST2/BN2 patients reached an early molecular response (EMR) and the 2 ST2/BN2 patients who did not achieve an EMR after 1 cycle of therapy are still in complete remission. To validate this finding, a validation cohort of 89 newly diagnosed DLBCL was collected. The PFS and OS of the training of the validation cohort were superimposable (p = 0.805 and p = 0.608, respectively). Also in the validation cohort, patients with <2.5Log10hGE and/or assigned to cluster BN2 and ST2 presented an excellent outcome with a 40-month PFS and OS of 73.2% and 79.7%, compared to 39.2% and 44.8% for other patients, respectively (both p = 0.001) (Figure 1B). By combining the training and the validation cohort, we performed a multivariate analysis on 166 patients. Both a ctDNA <2.5Log10hGE and the BN2/ST2 cluster maintained an independent association with an excellent outcome when adjusted for IPI and cell of origin (Figure 1C). Moreover, compared to ctDNA levels only, the addition of BN2/ST2 cluster improved the C statistics of the model (0.64 vs. 0.60 for PFS and 0.68 vs. 0.63 for OS, Figure 1D). Keywords: aggressive B-cell non-Hodgkin lymphoma, liquid biopsy The research was funded by: Molecular bases of disease dissemination in lymphoid malignancies to optimize curative therapeutic strategies, (5 x 1000 No. 21198), Associazione Italiana per la Ricerca sul Cancro Foundation Milan, Italy; Progetti di Rilevante Interesse Nazionale (PRIN; 2015ZMRFEA), Rome, Italy; the AGING Project—Department of Excellence—DIMET, Università del Piemonte Orientale, Novara, Italy; and Ricerca Finalizzata 2018 (project RF-2018-12365790), MoH, Rome, Italy; Swiss Cancer League, ID 3746, 4395 4660, and 4705, Bern, Switzerland; Research Advisory Board of the Ente Ospedaliero Cantonale, ABREOC 2019-22514, Bellinzona, Switzerland; European Research Council (ERC) Consolidator Grant CLLCLONE, ID: 772051; Swiss National Science Foundation, ID 320030_169670/1 and 310030_192439, Berne, Switzerland; Fondazione Fidinam, Lugano, Switzerland; Nelia & Amadeo Barletta Foundation, Lausanne, Switzerland; Fond’Action, Lausanne, Switzerland; The Leukemia & Lymphoma Society, Translational Research Program, ID 6594-20, New York. No conflicts of interests pertinent to the abstract.
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dlbcl patients,molecular clustering on ctdna,prognostic stratification
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