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Purpose: Follicular lymphoma (FL) is the most frequent indolent non-Hodgkin lymphoma. Around 20% of patients suffer early disease progression within 24 months (POD24) of diagnosis. This study examined the significance of circulating tumor DNA (ctDNA) in predicting response to therapy and POD24 in patients with FL. Experimental Design: We collected 100 plasma samples, before and during the treatment, from 36 patients with FL prospectively enrolled in 8 Spanish hospitals. They were treated with a chemotherapy-rituximab regimen and followed up for a median of 3.43 years. We performed targeted deep sequencing in cell-free DNA (cfDNA) and tumor genomic DNA from 31 diagnostic biopsy samples. Results: Of the alterations detected in the diagnostic tissue samples, 73% (300/411) were also identified in basal cfDNA. The mean numbers of alterations per basal cfDNA sample in patients who suffered progression of disease within 24 months (POD24-pos) or did not achieve complete response (non-CR) were significantly higher than in POD24-neg or CR patients (unpaired samples t test, P = 0.0001 and 0.001, respectively). Pretreatment ctDNA levels, as haploid genome equivalents per milliliter of plasma, were higher in patients without CR (P = 0.02) and in POD24-pos patients compared with POD24-neg patients (P < 0.001). Dynamic analysis showed that ctDNA levels decreased dramatically after treatment, although the reduction was more significant in patients with CR and POD24-neg patients. Conclusions: Basal ctDNA levels are associated with the risk of early progression and response to treatment in FL. cfDNA monitoring and genotyping during treatment and follow-up predict response to treatment and early progression.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease whose prognosis is associated with clinical features, cell-of-origin and genetic aberrations. Recent integrative, multi-omic analyses had led to identifying overlapping genetic DLBCL subtypes. We used targeted massive sequencing to analyze 84 diagnostic samples from a multicenter cohort of patients with DLBCL treated with rituximab-containing therapies and a median follow-up of 6 years. The most frequently mutated genes were IGLL5 (43%), KMT2D (33.3%), CREBBP (28.6%), PIM1 (26.2%), and CARD11 (22.6%). Mutations in CD79B were associated with a higher risk of relapse after treatment, whereas patients with mutations in CD79B, ETS1, and CD58 had a significantly shorter survival. Based on the new genetic DLBCL classifications, we tested and validated a simplified method to classify samples in five genetic subtypes analyzing the mutational status of 26 genes and BCL2 and BCL6 translocations. We propose a two-step genetic DLBCL classifier (2-S), integrating the most significant features from previous algorithms, to classify the samples as N12-S, EZB2-S, MCD2-S, BN22-S, and ST22-S groups. We determined its sensitivity and specificity, compared with the other established algorithms, and evaluated its clinical impact. The results showed that ST22-S is the group with the best clinical outcome and N12-S, the more aggressive one. EZB2-S identified a subgroup with a worse prognosis among GCB-DLBLC cases.

Introduction: Nodal peripheral T-cell lymphoma (PTCL) subclassification (Angioimmunoblastic TCL, PTCL-with T Follicular Helper phenotype and PTCL-NOS) and therapeutic targeting is still controversial. Overall survival (OS) is only around 30% after 5 years. Methods: We performed targeted next-generation sequencing of 61 selected genes in 76 PTCL patients. Among the 76cases, 44 were classified as AITL, 18 as PTCL-TFH and 14 as PTCL-NOS. Results: Our analysis revealed a wide variety of genetic variants that possibly drive the development of AITL, PTCL-TFH and/or PTCL-NOS. We identified an average of 4 variants per patient, mainly clustered in genes regulating chromatin conformation (TET2, DNMT3A) and T-cell differentiation (RHOA, MTOR, IDH2, VAV1 and NOTCH1). More frequently mutated genes were TET2 (76,31%) and DNMT3A (27,63%). Multiple mutations were found in TET2, VAV1, RHOA, NOTCH1, MTOR, JAK1, ZEB1, ATM, DNMT3A and ARID1B. Main difference among the three Nodal PTCL classes was the higher frequency of RHOAG17V mutations (p Conclusions: There is a common molecular basis for the three Nodal PTCL with very frequent mutations in genes regulating chromatin conformation associated with mutations in genes governing T-cell differentiation. RHOA G17V mutations were highly significant enriched in AITL. Findings suggesting Clonal Hematopoiesis were found in the three types of nodal PTCL.

Diffuse large B-cell lymphoma (DLBCL) is an aggressive and heterogeneous disease with variable prognosis associated with clinical features, cell-of-origin and genetic aberrations. The main problems for DLBCL patients are that a substantial percentage of them (30-40%) are refractory to treatment or relapse and the lack of accurate predictive markers that adequately determine which patients will benefit from immunochemotherapy. Several recent deep-sequencing studies have proposed new genetic subtypes based on the DLBCL genomic profile (Wright et al., 2020; Lacy et al. 2020) and associated with clinical outcome. However, a consensus and validated classification is still needed. The aim was to determine whether genetic alterations of individual genes or genes clustered in pathways are associated with clinical outcome in immunochemotherapy-treated patients. We used targeted massive sequencing to analyze 84 diagnostic samples from a multicentric cohort of patients with DLBCL treated with rituximab-containing therapies with a median follow up of 6 years. A two-step genetic classifier was built with mutation information from 27 genes and BCL2/BCL6 translocations, based on recently proposed genetic subtypes (Wright et al., 2020; Lacy et al. 2020). Logistic regression and Kaplan-Meier analyses for survival and risk of relapse were performed to assess the potential clinical value of the classifier. Moreover, this two-step classifier was validated in an external cohort and its specificity and sensitivity were tested to determine its accuracy in classifying patients compared to the previous approaches. We found that the most frequently mutated genes were IGLL5 (43%), KMT2D (33.3%), CREBBP (28.6%), PIM1 (26.2%), and CARD11 (22.6%). Mutations in CD79B, PRDM1, and NOTCH2 were associated with a higher risk of relapse after treatment, whereas patients with mutations in CD79B, ETS1, PRDM1, and TNFAIP3 had significantly shorter survival. Analyzing the impact of gene mutations on predefined gene sets related to lymphomagenesis revealed that mutations in genes involved in B-cell development, and BCR-PI3K and MAPK-ERK pathways were significantly associated with a higher risk of relapse and/or shorter overall survival. These results confirmed the current landscape of genetic alterations in DLBCL. According to the two-step classifier, we categorized the samples into MCD, BN2, EZB, ST2, and N1 genetic subgroups (Figure). We tested the accuracy of our classification in an external series (UK population-based Haematological Malignancy Research Network cohort [HMRN]) to determine its specificity and sensitivity compared with their own classification (Lacy et al. 2020) and the LymphGen algorithm (Wright et al., 2020). The comparison demonstrated (Wright et al., 2020; Lacy et al. 2020), a specificity and sensitivity higher than 85% for each subtype, except for BN2. This controversy may be explained by the fact that BN2 is less strongly defined than the other subtypes. We then tested their clinical impact and found the EZB and ST2 subtypes to have a better clinical course and a lower risk of relapse. The BN2 group had the worst clinical outcome of our series, unlike other published studies (Figure). These results were validated in the HMRN cohort, in which N1 showed a higher risk of relapse and shorter overall survival, whereas ST2 is the group with the most favorable outcome. Although N1 was not included for clinical outcome analysis in our cohort due to the small number of cases, the validation of our classifier defined N1 as the most aggressive subtype. In summary, we propose and validate a feasible genetic DLBCL classifier based on an optimized panel of genes that unifies previous genetic classification algorithms in such a way as to facilitate its implementation as part of pathology laboratories for routine patient management. This genetic classifier, combined with clinical data and other molecular characteristics, should eventually help develop improved risk models for DLBCL patients, and guide precision therapy. Figure Disclosures Perez Callejo: F. Hoffmann-La Roche: Current Employment, Current equity holder in publicly-traded company.