Abstract Molecular characterization of high-grade B-cell lymphoma, not otherwise specified (HGBCL-NOS), is hindered by its rarity, evolving definition, and poor diagnostic reproducibility. To address this challenge, we analyzed 92 HGBCL-NOS tumors collected across Lymphoma/Leukemia Molecular Profiling Project sites. Leveraging comparison cohorts of diffuse large B-cell lymphoma, NOS (DLBCL-NOS) and Burkitt lymphoma (BL), and molecular frameworks described in these entities, our analysis revealed a heterogenous molecular landscape, reminiscent of DLBCL-NOS but with an enrichment of BL features. By cell-of-origin classification, 59% were germinal center B-cell–like (GCB), and 25% were activated B-cell–like (ABC). LymphGen, a genetic classifier for DLBCL-NOS, assigned a genetic subtype to 34% of HGBCL-NOS. Although classification rate was lower than in DLBCL-NOS (66%), assigned subtypes spanned the spectrum of LymphGen classes, including 31% of ABCs classified as MCD. Features differentiating HGBCL-NOS from DLBCL-NOS included MYC rearrangement (47% vs 6%); dark zone signature (DZsig) expression (45% vs 7%); and more frequent mutation of ID3, MYC, CCND3, and TP53, all common to BL. A genetic classifier that differentiates DLBCL-NOS from BL classified 53% of DZsig+ tumors as BL-like, and those classified as DLBCL-like were frequently BCL2-rearranged. Among DZsig− GCB tumors, 95% were DLBCL-like. Centralized pathology review reclassified almost half of tumors as DLBCL-NOS but did not identify a more homogenous HGBCL-NOS population, with no difference in features between confirmed and reclassified tumors. In conclusion, molecular testing enables a subset of HGBCL-NOS to be assigned to established categories. Based on rarity and diagnostic challenges, broader inclusion of HGBCL-NOS should be considered in biomarker-driven DLBCL trials.
Motive and opportunity: MYC rearrangements in high-grade B-cell lymphoma with MYC and BCL2 rearrangements (an LLMPP study)
Abstract Rearrangements that place the oncogenes MYC, BCL2, or BCL6 adjacent to superenhancers are common in mature B-cell lymphomas. Lymphomas with diffuse large B-cell lymphoma (DLBCL) or high-grade morphology with both MYC and BCL2 rearrangements are classified as high-grade B-cell lymphoma with MYC and BCL2 rearrangements (“double hit”; HGBCL-DH-BCL2) and are associated with aggressive disease and poor outcomes. Although it is established that MYC rearrangements involving immunoglobulin (IG) loci are associated with inferior outcomes relative to those involving other non-IG superenhancers, the frequency of and mechanisms driving IG vs non-IG MYC rearrangements have not been elucidated. Here, we used custom targeted capture and/or whole-genome sequencing to characterize oncogene rearrangements across 883 mature B-cell lymphomas including Burkitt lymphoma, follicular lymphoma, DLBCL, and HGBCL-DH-BCL2 tumors. We demonstrate that, although BCL2 rearrangement topology is consistent across entities, HGBCL-DH-BCL2 have distinct MYC rearrangement architecture relative to tumors with single MYC rearrangements or with both MYC and BCL6 rearrangements (HGBCL-DH-BCL6), including both a higher frequency of non-IG rearrangements and different architecture of MYC::IGH rearrangements. The distinct MYC rearrangement patterns in HGBCL-DH-BCL2 occur on the background of high levels of somatic hypermutation across MYC partner loci in HGBCL-DH-BCL2, creating more opportunity to form these rearrangements. Furthermore, because 1 IGH allele is already disrupted by the existing BCL2 rearrangement, the MYC rearrangement architecture in HGBCL-DH-BCL2 likely reflects selective pressure to preserve both BCL2 and B-cell receptor expression. These data provide new mechanistic explanations for the distinct patterns of MYC rearrangements observed across different lymphoma entities.
Genetic Determinants of Isolated and Systemic Testicular Diffuse Large B-Cell Lymphoma Highlight a Disease Spectrum
Abstract Introduction : Follicular lymphoma (FL) remains an incurable malignancy as patients eventually experience progressive disease. A subset of patients is at risk of early lymphoma-related mortality due to histological transformation (TFL) to aggressive lymphoma (2-3% of patients per year) or early progression after immuno-chemotherapy, each of which leads to shortened survival. Mutations associated with transformation and/or early progression have been reported in the literature (e.g. CDKN2A, TP53, B2M) and the m7-FLIPI clinico-genetic risk model defines a high-risk patient group with poor failure-free survival after first-line treatment. However, the current knowledge of genetic alterations underlying transformation and/or early progression is inadequate to explain the majority of transformed cases and accurately predict early progressive disease. Materials and Methods: We performed targeted capture-based sequencing of 94 genes in a large cohort of fresh-frozen and formalin-fixed and paraffin-embedded patient specimens (402 samples in total). This cohort comprised 277 samples from 159 patients that experienced transformation (including 128 samples at T1 (the time of FL) and 149 samples at T2 (the time of transformation) with 118 paired biopsies) and 125 samples from 125 patients (pre-treatment samples only) presenting with either early progression within 2.5 years after starting immunochemotherapy (n=41) or late or never progression for at least 5 years after starting immunochemotherapy or observation (n=84). Mutations were called using MutationSeq and putative single nucleotide polymorphisms were filtered out using either matching germline samples (n=84) or dbSNP (v147). Bayesian proportion tests were used to compare the prevalence of gene mutations between groups. Results : We first compared T1 (n=128) and T2 (n=149) samples from 159 patients experiencing transformation. Eleven genes were more commonly altered in transformed lymphoma. These included genes that had previously been associated with transformation, such as TP53, B2M, MYC and EBF1, as well as genes that have not yet been implicated as contributing to this process, for example EZH2, CCND3, PIM1 and ITPKB. Moreover, mutations in GNA13, S1PR2 and P2RY8, that have been implicated in dissemination of germinal centre B cells, were enriched in T2 samples. In addition, cell-of-origin classification was available for 108 of the TFL cases with DLBCL histology, 18 and 90 of which were of the ABC and GCB subtype, respectively. Although the number of ABC-TFL cases was small, we observed higher percentages of BCL10 (16% versus 1%, Fisher P=0.004), CD79B (22% versus 4%, Fisher P=0.005) and MYD88 mutations (28% versus 9%, P=0.006) in ABC-TFL than in GCB-TFL, suggesting that B-cell receptor signaling and NF-κB signaling are important contributors to the ABC phenotype in TFL. Next, we assessed the association of gene mutations with patient outcomes contrasting early progressers (n=41) and late or non-progressers (n=84). Eleven genes were mutated more commonly in early progressers than in late progressers, including KMT2C, TP53, BTG1, MKI67, XBP1 and SOCS1. Overall, 32 out of 41 early progressers (78%) had mutations in at least one of the 11 early progression-associated genes, but none of the individual early progression-associated genes were mutated at a frequency > 22%. Thus, early progression appears to be related to relatively infrequent genetic alterations. None of the early progression-associated gene mutations form part of the m7-FLIPI outcome predictor. Furthermore, in our cohort that was enriched for clinical extremes, the m7-FLIPI was similarly associated with early progression when compared to the FLIPI but it was not superior, having higher specificity (89% versus 76%), but lower sensitivity (36% versus 63%). Conclusions: We found novel associations of gene mutations with transformation and showed that TFL is molecularly heterogeneous, with the ABC subtype being characterized by differential gene mutation when compared to the GCB subtype. With regards to progressive disease after immuno-chemotherapy, our approach identified early progression as a distinct clinico-genetic disease category that is imperfectly captured by traditional prognostic tools. Disclosures Connors: Seattle Genetics: Research Funding; Bristol Myers Squib: Research Funding; F Hoffmann-La Roche: Research Funding; NanoString Technologies: Research Funding; Millennium Takeda: Research Funding. Scott:NanoString Technologies: Patents & Royalties: named inventor on a patent for molecular subtyping of DLBCL that has been licensed to NanoString Technologies.
Prognostic significance of the proliferation signature in mantle cell lymphoma measured using digital gene expression in formalin-fixed paraffin-embedded tissue biopsies.
The MCL35 gene expression proliferation assay predicts high‐risk MCL patients in a Norwegian cohort of younger patients given intensive first line therapy
SummaryPatients with mantle cell lymphoma (MCL) generally have a dismal prognosis. Intensified induction treatment with rituximab and high dose cytarabine (R_HDAC), and consolidation with high‐dose therapy with autologous stem cell support has resulted in 10‐year overall survival (OS) higher than 60%. However, the clinical course varies. Diagnostic tools capable of stratifying patients include the MCL International Prognostic Index (MIPI), gene expression‐based proliferation signature, Ki‐67 proliferation index or tumour cell morphology. Here, we tested the performance of a newly developed Nanostring‐based RNA expression‐based proliferation assay (MCL35) on formalin‐fixed paraffin‐embedded tumour tissue from younger patients recruited in or treated according to Nordic MCL protocols compared to the prognosticators listed above. Seventy‐four patients were included and the assay performed well in all cases except four, which had inadequate RNA quality. The patients were evenly distributed in the MCL35 low‐, intermediate‐ and high‐risk categories. MCL35 low‐ and intermediate‐ risk groups had overlapping progression‐free survival (PFS), while patients in the high‐risk category had significantly inferior PFS. Combining MCL35 with MIPI or the MIPI‐C (MIPI with the addition of binary Ki67 score +/−30%) showed a better discrimination than either assessment alone. In conclusion, the MCL35 assay alone or combined with MIPI or MIPI‐C scores can identify patients who still have a dismal outcome despite intensified treatment.