Gribben, John G.

The phase III AUGMENT trial (ClinicalTrials.gov identifier: NCT01938001 ) demonstrated improved efficacy for lenalidomide plus rituximab (R 2 ) versus rituximab with placebo (R-placebo) in patients with relapsed or refractory (R/R) indolent non-Hodgkin lymphoma (iNHL). Here, we present the long-term follow-up results and prespecified subgroup analyses of patients with follicular lymphoma (FL), including those 70 years and older. Patients with R/R grade 1 to 3a iNHL were randomly assigned 1:1 to receive R 2 or R-placebo. In this long-term follow-up report, progression-free survival (PFS) was assessed per the investigator. Secondary end points included overall survival (OS) and safety. Of the 358 randomly assigned patients (intent-to-treat [ITT] population), 295 had FL (≥70 years, n = 66). At long-term follow-up (median, 65.9 months), in the ITT iNHL population, PFS (hazard ratio [HR], 0.50 [95% CI, 0.38 to 0.66]) and OS (HR, 0.59 [95% CI, 0.37 to 0.95]) were improved with R 2 versus R-placebo. Safety findings were consistent with the primary analysis. Improved long-term efficacy with R 2 versus R-placebo and manageable safety with R 2 were observed in patients with FL, including those 70 years and older. With a follow-up of >5 years, data from the AUGMENT trial continue to support the use of R 2 as a standard of care for patients with R/R iNHL.

Abstract BACKGROUND Whilst the broad clonal architecture of naturally progressing chronic lymphocytic leukemia (CLL) has been described, a comprehensive picture of how chemotherapy and targeted agents reshape that landscape is lacking. Here we integrate clone-specific growth kinetics with mutational profiles, transcriptomic subtypes, and CpG-methylation-based epigenetic classes to capture the multidimensional evolutionary responses of CLL under native conditions and during treatment. METHODS We previously reported a systematic whole-exome sequencing (WES) analysis of 417 leukemia–germline pairs from 169 treatment-naïve patients ≥ 65 y (Karisani et al., Blood 2024). The treatment arm comprised 83 patients who received ibrutinib and 39 who received chlorambucil in the RESONATE-2 trial (NCT01722487). Forty-seven age-matched “watch-and-wait” patients from the CLL Research Consortium served as untreated controls. Peripheral-blood samples were collected at baseline and again ~300 d and ~600 d after therapy initiation (or diagnosis in the watch-and-wait cohort), enabling longitudinal clonal tracking. WES data were processed with PhylogicNDT to reconstruct clonal architectures, define phylogenies, and identify significant clonal shifts. MutSig tools identified mutations enriched in expanding or contracting clones. Pretreatment RNA-sequencing profiles were grouped into transcriptional subtypes by consensus clustering based on the Louvain algorithm. Differentially methylated regions plus epitypes were called from reduced representation bisulfite sequencing data. RESULTS Across the 169 patients with WES, we resolved 579 subclonal clusters. Significant clonal shifts (defined as a distribution shift of cancer cell fraction in a subclone of >95% between two timepoints) were uncommon during watch-and-wait (36%) but markedly higher after therapy — chlorambucil 67% (q = 0.01), and ibrutinib 77% (q < 10-4). In ibrutinib-treated CLL, regressing subclones were enriched for KRAS (q<10-3) and SF3B1 mutations (q<10-3), whereas expanding subclones preferentially harboured mutations in BIRC3 (q<10-4), NOTCH1 (q <10-3), TP53 (q=0.02), and POT1 (q=0.098). In chlorambucil-treated patients, no specific mutations were found to be enriched in expanding or regressing subclones. Using the recently defined CLL expression clusters (ECs) in patients treated with chemoimmunotherapy as defined by Knisbacher et al. (Nat Genet 2022), we were unable to identify any relationship between ECs and outcomes. We therefore sought to identify de novo ECs with prognostic relevance in the context of BTK-inhibition (BTKi-ECs). We identified a transcriptionally defined patient subgroup (C4, n=20) associated with inferior progression-free survival (median PFS = 63 months, log-rank q=0.05), independent of known prognostic clinical and molecular features, including epitypes, in multivariate analysis (Cox HR=3.7, 95% CI: 1.6-8.6, q=0.02). Gene-set enrichment in this cluster highlighted TNF-ɑ signalling via NF-κB (REL, TNFAIP3, NFKB2) and G2M checkpoint pathways (SMC4, EZH2). We also identified a distinct transcriptionally defined patient subgroup (C3, n=18) that was enriched for patients harboring at least one contracting subclone and no expanding subclones (q=0.005). This cluster showed a relative depletion of mutations within the chromatin modification pathway (6% vs 50%, q<0.01). Gene-set enrichment in this cluster highlighted a downregulation of genes in the TNF-ɑ signalling via NF-κB pathway (SOCS3, ICOSLG, NFKB2). CONCLUSION BTK inhibition and chemotherapy drive distinct evolutionary trajectories in CLL. Multi-omics profiling reveals mutation-defined subclones with divergent sensitivity to targeted therapy and delineates two informative expression states: a high-risk NF-κB/inflammatory cluster (C4; poor PFS) and a cluster enriched with contracting subclones with depleted TNF-ɑ signalling via NF-κB (C3). Integrating clonal growth kinetics with genomic, transcriptomic, and methylation data can potentially identify patients likely to progress on BTK inhibitors and identify actionable pathways for adaptive or combination therapy.

BACKGROUND Our knowledge of how the genomic landscape of chronic lymphocytic leukemia (CLL) is impacted by the selective pressure imposed by chemotherapy and targeted agents remains incomplete. We hypothesize that the extent of clonal evolution, baseline transcriptional state, and the overall and clone-specific growth kinetics of CLL will vary under native conditions or following exposure to chemotherapy and targeted therapy. METHODS We report the systematic genomic analysis of leukemia-normal whole-exome sequencing (WES) of 420 samples collected from 170 patients who were >65 years of age with treatment-naïve CLL. The treatment-cohort consisted of 83 patients who received ibrutinib (420mg daily) and 40 patients who received chlorambucil (0.5 mg/kg up to maximum 0.8 mg/kg, on days 1 and 15 of a 28-day cycle, up to 12 cycles) as part of the RESONATE-2 trial (NCT01722487). The ‘watch and wait’ (WW) cohort comprised 47 age-matched patients whose samples originated from the CLL Research Consortium and were untreated for their CLL during sampling. Sampling occurred at baseline and at day 300, and/or day 600, following initiation of therapy or following a diagnosis of CLL for those in the WW cohort. The WW cohort had more cases with a mutated IGHV (72% vs 40%), del17p (14% vs 0%), and del13q (72% vs 45%) when compared to the treatment cohort. Baseline CLL RNA-seq data were available for 150 patients. We used PhylogicNDT to reconstruct the clonal architecture from WES. By determining the fraction of cancer cells with each mutation (cancer cell fraction [CCF]) and their multiplicities (number of DNA molecules carrying a mutation per cancer cell), subclones were identified through clustering of CCFs of mutational events across samples from each patient. This allowed us to estimate the phylogenetic relationships and significant clonal shifts (defined as a distribution shift of CCF in a subclone of >95% between two timepoints, corresponding to a median ΔCCF of 18%) for each patient's CLL and to relate these shifts to somatic and clinical features. RESULTS In total, we identified 791 subclonal clusters across the three patient cohorts (ibrutinib = 406, chlorambucil = 189, WW = 196). We observed higher rates of significant clonal shifts between any two time points in patients exposed to chlorambucil (68%, q=0.008) and ibrutinib (77%, q<0.0001) when compared to patients on WW (36%). There was no significant difference in the number of patients exhibiting a clonal shift between those receiving ibrutinib and chlorambucil (q=0.3). More patients treated with ibrutinib (54%, q=0.0002) and chlorambucil (50%, q=0.004) harbored a clone that reduced in size than those on WW (17%). More patients treated with ibrutinib (71%, q<0.0002) and chlorambucil (55%, q=0.12) possessed at least one clone that increased in size during therapy than patients receiving WW (34%). In ibrutinib-treated patients, SF3B1 mutations (q=0.13, 14% vs 5%) and XPO1 mutations (q=0.13, 5% vs 0.3%) were enriched in subclones that significantly reduced over the complete time period. We also observed more BIRC3 mutations in subclones that had a significant shift in CCF when compared to subclones that remained stable over time (q=0.2, 5% vs 2%). Consistent with the overall study, with 8 years of follow-up in this patient subset, long-term progression-free survival (PFS) was significantly higher in the patients treated with ibrutinib when compared to chlorambucil (P<0.0001). This PFS benefit was also seen regardless of subclonal growth patterns. Using baseline RNA-seq data, we identified 7 of the 8 recently defined CLL expression clusters (EC), that were identified in the context of chemoimmunotherapy for CLL (Knisbacher et al. Nat Gen 2022), and could recapitulate the relationship to outcomes in individuals treated with chlorambucil. However, despite the larger cohort, no significant relationship between EC clusters and PFS were observed in ibrutinib-treated patients, suggesting that a distinct predictive baseline transcriptional signature may be present in ibrutinib-treated patients. CONCLUSION Our analyses highlight the need to interrogate the molecular features of CLL in relation to the impact of therapeutic selective pressure imposed by BTK inhibition, which appear distinct from exposure to chemotherapy. Ongoing analyses aim to identify relationships between patterns of growth and subclonal growth rates molecular and clinical features.

Background: Axicabtagene ciloleucel (axi-cel), an autologous chimeric antigen receptor (CAR) T-cell therapy, achieved an overall response rate (ORR) of 94% and a complete response (CR) rate of 79% in patients with relapsed or refractory (r/r) follicular lymphoma (FL) after two or more prior lines of therapy in the ZUMA-5 trial ( Jacobson et al. Lancet Oncol. 2022). Since its FDA approval in March 2021, there has been little evidence on comparative effectiveness (CE) studies of axi-cel vs standard-of-care (SoC), except ones using ZUMA-5 and historical SCHOLAR-5 data (eg, Ghione et al. Blood. 2022). This study was aimed to address this evidence gap in CE of axi-cel vs SoC used to treat r/r FL in real-world settings. Methods: The two data sources in this study were patients who received commercial axi-cel between March 2021 and May 2023 from the CIBMTR and patients who received historical SoC (eg, chemotherapy, anti-CD20 mAb + chemotherapy, immunomodulatory imide drugs) between July 2014 and December 2020 from SCHOLAR-5, which served as an external control of ZUMA-5 trial. The index date was defined as the initiation date of either the infusion for axi-cel patients or the last eligible systemic therapy for SoC patients. Patients were included if they were age ≥ 18, had documented r/r FL with histological grade 1, 2 or 3a, and received at least 2 prior lines of therapy at the index. Patients were excluded if they had transformed diffused large B-cell lymphoma, central nervous system involvement, prior receipt of CAR T or other non-CAR T cellular therapies or allogeneic stem cell transplant, or no post-index information on outcomes. Four effectiveness outcomes were ORR, CR rate, progression-free survival (PFS), and overall survival (OS). Imbalance in observed prognostic risk factors between the two was adjusted via a propensity score analysis using the standard mortality ratio weighting (SMRW). The primary analyses included weighted univariable analysis and multivariable logistic (ORR and CR rate) or Cox (PFS and OS) regressions that were adjusted for the covariates after the SMRW. A sub-analysis of patients age ≥ 65 was conducted using the same methods as the primary analyses. Results: The unweighted study cohort included 376 patients, in which 256 (68%) received axi-cel . Thepatients who received axi-cel were more likely to be younger (median age 61 for axi-cel vs 67 for SoC), have grade 3a FL (37% vs 12%), received 3 or more prior lines of therapy (83% vs 58%), or remained refractory to the last prior therapy (79% vs 73%) vs those who received SoC. The imbalance in the observed prognostic risk factors was mitigated via the SMRW. The weighted univariable analysis, in which the sample size by treatment reflected the SMRW, is shown in Table 1. In patients of all ages, ORR was 92% in axi-cel vs 67% in SoC, and CR rate was 84% vs 37%. Because of varying follow-up lengths by treatment (median 7 months for axi-cel and 37 months for SoC), survival outcomes were reported at month 6, at which time PFS rate was 88% in axi-cel vs 64% in SoC and OS rate was 97% vs 85%. The corresponding proportions for patients age ≥ 65 were similar to those reported for patients of all ages. In the weighted multivariable regressions, axi-cel was associated with statistically significantly better outcomes by all 4 effectiveness measures vs SoC (Table 1). Specifically, in patients of all ages, the odds ratios for axi-cel were 4.93 (95% CI, 2.35−10.34) for ORR and 16.72 (95% CI, 7.03−39.73) for CR rate, and the hazard ratios for axi-cel were 0.41 (95% CI, 0.22−0.77) for PFS and 0.15 (95% CI, 0.06−0.34) for OS. Similar to the patients of all ages in the primary analyses, patients age ≥ 65 in the sub-analysis also demonstrated improved outcomes associated with axi-cel (Figure 1). Conclusions: This study showed that patients with r/r FL after two or more prior lines of therapy treated with axi-cel experienced better outcomes compared with patients treated with SoC, and that older patients also benefited significantly from axi-cel. These findings suggest that axi-cel addresses an important unmet medical need in patients with r/r FL. Future research should include longer follow-up data on outcomes of axi-cel and CE of axi-cel vs other contemporary SoC therapies.

Abstract With the introduction of large-scale molecular profiling methods and high-throughput sequencing technologies, the genomic features of most lymphoid neoplasms have been characterized at an unprecedented scale. Although the principles for the classification and diagnosis of these disorders, founded on a multidimensional definition of disease entities, have been consolidated over the past 25 years, novel genomic data have markedly enhanced our understanding of lymphomagenesis and enriched the description of disease entities at the molecular level. Yet, the current diagnosis of lymphoid tumors is largely based on morphological assessment and immunophenotyping, with only few entities being defined by genomic criteria. This paper, which accompanies the International Consensus Classification of mature lymphoid neoplasms, will address how established assays and newly developed technologies for molecular testing already complement clinical diagnoses and provide a novel lens on disease classification. More specifically, their contributions to diagnosis refinement, risk stratification, and therapy prediction will be considered for the main categories of lymphoid neoplasms. The potential of whole-genome sequencing, circulating tumor DNA analyses, single-cell analyses, and epigenetic profiling will be discussed because these will likely become important future tools for implementing precision medicine approaches in clinical decision making for patients with lymphoid malignancies.

Abstract Despite the effectiveness of immuno-chemotherapy, 40% of patients with diffuse large B-cell lymphoma (DLBCL) experience relapse or refractory disease. Longitudinal studies have previously focused on the mutational landscape of relapse but fell short of providing a consistent relapse-specific genetic signature. In our study, we have focused attention on the changes in GEP accompanying DLBCL relapse using archival paired diagnostic/relapse specimens from 38 de novo patients with DLBCL. COO remained stable from diagnosis to relapse in 80% of patients, with only a single patient showing COO switching from activated B-cell–like (ABC) to germinal center B-cell–like (GCB). Analysis of the transcriptomic changes that occur following relapse suggest ABC and GCB relapses are mediated via different mechanisms. We developed a 30-gene discriminator for ABC–DLBCLs derived from relapse-associated genes that defined clinically distinct high- and low-risk subgroups in ABC–DLBCLs at diagnosis in datasets comprising both population-based and clinical trial cohorts. This signature also identified a population of <60-year–old patients with superior PFS and OS treated with ibrutinib–R-CHOP as part of the PHOENIX trial. Altogether this new signature adds to the existing toolkit of putative genetic predictors now available in DLBCL that can be readily assessed as part of prospective clinical trials.

Abstract Since the publication of the Revised European-American Classification of Lymphoid Neoplasms in 1994, subsequent updates of the classification of lymphoid neoplasms have been generated through iterative international efforts to achieve broad consensus among hematopathologists, geneticists, molecular scientists, and clinicians. Significant progress has recently been made in the characterization of malignancies of the immune system, with many new insights provided by genomic studies. They have led to this proposal. We have followed the same process that was successfully used for the third and fourth editions of the World Health Organization Classification of Hematologic Neoplasms. The definition, recommended studies, and criteria for the diagnosis of many entities have been extensively refined. Some categories considered provisional have now been upgraded to definite entities. Terminology for some diseases has been revised to adapt nomenclature to the current knowledge of their biology, but these modifications have been restricted to well-justified situations. Major findings from recent genomic studies have impacted the conceptual framework and diagnostic criteria for many disease entities. These changes will have an impact on optimal clinical management. The conclusions of this work are summarized in this report as the proposed International Consensus Classification of mature lymphoid, histiocytic, and dendritic cell tumors.

Abstract Approximately 10–15% of patients with CLL report a family history (FH) of CLL or a related lymphoproliferative disorder. Whether the biologic features of CLL that occurs within families differ from those that occur sporadically is unknown. A recent study addressing this question has reported that mutated IgVH is significantly more common among familial than sporadic CLL, 68% vs 47%, although the distribution of VH genes used was similar (Blood111:5691, 2008). Therefore we compared IgVH mutational status and gene usage, as well as other biologic features, between familial and sporadic CLL derived from patients enrolled on the CLL Research Consortium (CRC) Tissue Core. Of 4533 patients enrolled in the CRC database and tissue bank, 3328 had adequate family history information, and these were subdivided into 4 groups: FH of CLL (n=468), FH of other heme cancer but not CLL (n=421), FH of non-heme cancer (n=1444), and sporadic cases (no FH of any cancer) (n=995). Of those patients reporting a FH of CLL, 63% had at least one affected 1st degree relative, 20% at least one affected 2nd or greater degree relative, and 17% unknown. 68% of those reporting a FH of CLL also had other cancers in their family. Patients reporting a FH of CLL or non-CLL heme cancers were more frequently white (91%), compared to 87% of those with FH non-heme cancer and 84% of sporadic CLL patients (p=0.005). The proportion of CLL cases that were female was similar among groups, at 37.6% of patients with FH CLL, as compared to 32.5% of sporadic patients (p=0.12). The age at diagnosis of CLL also did not differ among the four groups, although a trend toward a difference was observed between the FH CLL patients, whose mean age at diagnosis was 54.9 (range 30, 93), and the sporadic patients, whose mean age at diagnosis was 56.1 (range 30, 84) (p=0.08). No significant difference was observed among groups in the frequency of IgVH mutation (defined as <98% homology to the most similar germline VH gene), which was present in 50.3% (95% CI 44.5–56.2) of patients with FH CLL, 56.3% (95% CI 49.7–62.7) of patients with FH other heme cancer, 51.9% (95% CI 48.5–55.3) of patients with FH non-heme cancer, and 51.3% (95% CI 47.0–55.5) of sporadic patients (p=0.53). The pattern of IgVH family gene usage also did not differ among the groups; the VH3 subgroup was most commonly used, at 45%, 52%, 46% and 47% of patients with FH CLL, FH other heme cancer, FH non-heme cancer and sporadic, respectively. The VH1 subgroup was next most common in all 4 groups, at 28%, 24%, 26% and 25%, respectively, followed by the VH4 subgroup, at 19%, 17%, 21% and 21%. In addition, no significant difference was observed in the distribution of ZAP-70 expression amongst the four family history subgroups (mean %ZAP-70 expression, 22.8% for FH CLL patients and 24.4% for sporadic patients, p=0.31), or in the fraction considered ZAP-70 positive (>20% expression), which was 40% for FH CLL patients and 45% for sporadic patients (p=0.16). The relative expression of CD23 and CD38 did not differ among groups, nor did levels of beta-2-microglobulin or IgG determined at time of CRC enrollment. Time from diagnosis to initial treatment for each of the subgroups is currently being analyzed. These data on patterns of biologic risk factors in this large group of familial CLLs compared to sporadic CLLs suggest that familial and sporadic CLL are biologically similar and therefore likely to have similar pathogenetic mechanisms, including perhaps an underlying genetic susceptibility.