Inghirami, Giorgio

Abstract Few prospective benchmark studies exist to characterize the evolving contemporary real-world practice for peripheral T-cell lymphoma (PTCL). We report the patterns of first-line care and outcomes for 720 patients with systemic PTCL enrolled in 2 related prospective cohort studies, Lymphoma Epidemiology of Outcomes (LEO) from 2015 to 2020 and Molecular Epidemiology Resource (MER) from 2002 to 2015, both followed to 2024. The primary end points were event-free survival (EFS) and overall survival (OS) using Kaplan-Meier estimator and Cox regression model. Secondary end points included correlations of clinical and treatment factors with survival. The most common induction regimens were CHOP (cyclophosphamide, doxorubicin, vincristine, prednisone) based (70%), given as CHOP (36%), CHOP plus etoposide (23%), or CHOP-like plus novel agents (11.5%, including 5% BV-CHP [brentuximab plus cyclophosphamide, doxorubicin, and prednisone]). Consolidative autologous stem cell transplant was performed in 102 patients (14%). Within nodal PTCL, EFS and OS were adversely associated with International Prognostic Index 2 to 5, prognostic index for T-cell lymphoma score 1 to 4, and non–anaplastic large-cell lymphoma (ALCL) subtypes. Within LEO, which captured increasing first-line etoposide and brentuximab vedotin, adding etoposide to CHOP was associated with better OS in anaplastic lymphoma kinase-negative ALCL. BV-CHP showed a trend toward OS improvement in ALCL. Patients failing EFS6 and EFS24 had 5-year subsequent OS of 12% and 17%, respectively. The inferior outcomes in non-ALCL subtypes and patients failing EFS6 and EFS24 highlight unmet needs with CHOP-based induction, where clinical trials with targeted therapy should be prioritized. This trial was registered at www.clinicaltrials.gov as NCT02736357.

Abstract Anaplastic large cell lymphomas (ALCLs) are CD30+ T-cell lymphomas that share pathologic features but differ in presentation, outcome, and genetics. Current classification incorporates clinical presentation and anaplastic lymphoma kinase (ALK) status but inadequately addresses molecular heterogeneity and therapeutic vulnerabilities. We studied 689 patients with ALCL in the LLMPP (Lymphoma/Leukemia Molecular Profiling Project) and performed expert consensus review, genetic subtyping (ALK, DUSP22, TP63, and triple negative), and immunohistochemistry for phosphorylated STAT3Tyr705. RNA sequencing with unsupervised gene expression profiling in 393 patients identified 2 main molecular types of ALCL that could be predicted with 91% accuracy based on the presence (type I) or absence (type II) of phosphorylated STAT3Y705 expression. Type I ALCLs included ALK+ ALCL and a subset of triple-negative ALCLs (TN-I); type II ALCLs included tumors with DUSP22 and/or TP63 rearrangements and the remaining triple-negative ALCLs (TN-II). Type I ALCLs were enriched for JAK-STAT3, whereas type II ALCLs were enriched for non–tyrosine kinase pathways, particularly epigenetic regulators such as EZH2. Immunohistochemistry showed overexpression of EZH2 and its trimethylated substrate H3K27. Prognosis in systemic ALCL was favorable for DUSP22-rearranged ALCL (5-year overall survival, 95%) and ALK+ ALCL (88%), intermediate for triple-negative ALCL (TN-I, 52% and TN-II, 37%), and poor for TP63-rearranged ALCL (0%). We introduce an integrated molecular classification that preserves currently diagnosed ALCL entities but identifies 4 molecularly distinct ALK− ALCL subtypes (DUSP22-rearranged, TP63-rearranged, TN-I, and TN-II). This classification can be easily implemented on paraffin tissue in routine practice or clinical trials, and stratifies ALCL into diagnostically, prognostically, biologically, and potentially therapeutically relevant subtypes.

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.

Abstract Recent introduction of 2 different lymphoma classifications has raised concerns about consistency in diagnosis, management, and clinical trial enrollment. Data from a large cohort reflecting real-world clinical practice suggest that differences between the classifications will affect <1% of non-Hodgkin lymphomas.

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.

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.

PURPOSE Peripheral T-cell lymphoma (PTCL) includes heterogeneous clinicopathologic entities with numerous diagnostic and treatment challenges. We previously defined robust transcriptomic signatures that distinguish common PTCL entities and identified two novel biologic and prognostic PTCL-not otherwise specified subtypes (PTCL-TBX21 and PTCL-GATA3). We aimed to consolidate a gene expression–based subclassification using formalin-fixed, paraffin-embedded (FFPE) tissues to improve the accuracy and precision in PTCL diagnosis. MATERIALS AND METHODS We assembled a well-characterized PTCL training cohort (n = 105) with gene expression profiling data to derive a diagnostic signature using fresh-frozen tissue on the HG-U133plus2.0 platform (Affymetrix, Inc, Santa Clara, CA) subsequently validated using matched FFPE tissues in a digital gene expression profiling platform (nCounter, NanoString Technologies, Inc, Seattle, WA). Statistical filtering approaches were applied to refine the transcriptomic signatures and then validated in another PTCL cohort (n = 140) with rigorous pathology review and ancillary assays. RESULTS In the training cohort, the refined transcriptomic classifier in FFPE tissues showed high sensitivity (> 80%), specificity (> 95%), and accuracy (> 94%) for PTCL subclassification compared with the fresh-frozen–derived diagnostic model and showed high reproducibility between three independent laboratories. In the validation cohort, the transcriptional classifier matched the pathology diagnosis rendered by three expert hematopathologists in 85% (n = 119) of the cases, showed borderline association with the molecular signatures in 6% (n = 8), and disagreed in 8% (n = 11). The classifier improved the pathology diagnosis in two cases, validated by clinical findings. Of the 11 cases with disagreements, four had a molecular classification that may provide an improvement over pathology diagnosis on the basis of overall transcriptomic and morphological features. The molecular subclassification provided a comprehensive molecular characterization of PTCL subtypes, including viral etiologic factors and translocation partners. CONCLUSION We developed a novel transcriptomic approach for PTCL subclassification that facilitates translation into clinical practice with higher precision and uniformity than conventional pathology diagnosis.