Leval, Laurence de

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.

ABSTRACTNodal follicular helper T‐cell (T FH) lymphoma of the angioimmunoblastic (AITL) subtype has a dismal prognosis. Using whole‐exome sequencing (n = 124), transcriptomic (n = 78), and methylation (n = 40) analysis, we identified recurrent mutations in known epigenetic drivers (TET2, DNMT3A, IDH2 R172 ) and novel ones (TET3, KMT2D). TET2, IDH2 R172 , DNMT3A co‐mutated AITLs had poor prognosis (p < 0.0001). Genes regulating T‐cell receptor (TCR) signaling (CD28, PLCG1, VAV1, FYN) or activation (RHOA G17V ) or regulators of the PI3K‐pathway (PIK(3)C members, PTEN, PHLPP1, PHLPP2) were mutated. CD28 mutation/fusion was associated with poor prognosis (p = 0.02). WES of purified, neoplastic T‐cell (CD3+PD1+) demonstrated high concordance with whole tumor biopsies and validated the presence of TET2 and DNMT3A in tumor and non‐lymphoid cells, but other mutations (CD28, RHOA G17V , IDH2 R172 , PLCG1) in neoplastic cells. Integrated DNA‐methylation and mRNA expression analysis revealed epigenetic alterations in genes regulating TCR, cytokines, PI3K‐signaling, and apoptosis. RNA‐seq analysis identified fusion transcripts regulating TCR‐activation (8%), revealed a restricted TCR‐repertoire (α = 87%, β = 72%), and showed the presence of Epstein–Barr virus transcriptome (73%). GEP demonstrated the association of B‐cells or dendritic cells in the tumor milieu with prognosis (p < 0.01). RNA‐seq and WES analysis of 12 AITL‐patient‐derived‐xenografts (PDX) showed that bi‐allelic TET2 and DNMT3A mutations or sub‐clonal mutations (PLCG1, PHLPP2) propagated in sequential passages, and gene signatures related to T FH and T CM (central‐memory) were well‐maintained through passages. Gene expression signatures associated with late PDX passages (3rd–5th) were enriched with proliferation and metabolic reprogramming‐related genes and predicted prognosis in an independent AITL series. Low PHLPP2 mRNA expression predicted poor prognosis (p = 0.05) and engineered PHLPP2 or TET2 loss in CD4+ T‐cells showed enhanced PI(3)K activation, thus uncovering a therapeutic target for clinical trials.

Background: Anaplastic large cell lymphomas (ALCLs) represent a heterogeneous group of T-cell lymphomas that currently are classified by the presence or absence of ALK tyrosine kinase (TK) fusion genes (ALK+ or ALK−) and clinical presentation (systemic, cutaneous, or breast implant-associated). Two overarching molecular types of ALCL recently were discovered, defined by the presence (Type I) or absence (Type II) of a gene expression signature highly enriched for JAK-STAT3 activation. Fusions involving non-ALK TK genes occur in some ALK− cases, but the fusion landscape of ALCL remains incompletely characterized. Methods: Expert consensus pathology review was conducted in the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). RNAseq was performed and fusions were identified using FusionCatcher. Here, we focused on recurrent in-frame coding fusions. Previously unreported fusions were validated by RT-PCR. Type I/II was assigned using a previously validated gene expression-based model. Genes with adjusted (adj) P&lt;0.05 were considered differentially expressed. Overall survival (OS) was assessed for systemic ALCL, when available. Results: We evaluated 379 ALCLs (229M/150F; mean age, 56 y). Of 199 candidate fusions (excluding reciprocal events), 28 were recurrent and passed quality metrics. At least 1 of these 28 fusions was present in 150 cases (40%). ALK fusions were present in 106 ALK+ ALCLs (all Type I; P&lt;0.0001). Of these, NPM1::ALK was seen in 68/106 (64%). Alternate partners (X::ALK) included ATIC (N=24) and CTLC, COL1A2, MSN, MYH9, RNF213, SATB1, TFH, TPM3, and TRAF1 (1-3 cases each). X::ALK was associated with older age (mean, 52 y) than NPM1::ALK (32 y; P&lt;0.0001) and showed relative overexpression of 49 genes, including multiple activators of small GTPases such as CGNL1 (FC, 5.6; Padj=2.4×10-6), SRGAP1, ALS2, DOCK1, and NCKAP1. ALK expression was similar in cases with NPM1::ALK and X::ALK and there was no significant difference in OS. Non-ALK TK fusions were seen in 17/273 ALK− cases (6%), including TYK2 (N=9); JAK2 (N=6); and ROS1 (N=2). All were Type I ALCLs (P&lt;0.0001). ALK− cases with non-ALK TK fusions overexpressed 38 genes compared to ALK− cases without TK fusions, including cytokines involved in the IL17 signaling pathway such as CXCL6 (FC, 12.5; Padj=4.2×10-3), CXCL1, and CSF3. We then assessed the relationship between ALK− cases with non-ALK TK fusions and ALK+ cases by separately comparing each subset to ALK− cases without TK fusions. FC values for ALK− cases with non-ALK TK fusions were significantly correlated with FC values for ALK+ ALCLs over the set of expressed genes (R=0.54; P&lt;0.0001). At a median follow-up of 32 months, 0/4 systemic ALCL patients with non-ALK TK fusions had died, while 30% of those with ALK− ALCL without TK fusions had died, but this was not statistically significant (P=0.26). The other 13 ALK− cases with non-ALK TK fusions were either localized ALCLs or did not have outcome data available. Of 20 TP63 fusions, 17 (85%) were TBL1XR1::TP63 and 3 were X::TP63. As previously reported, TP63 fusions were associated with poor OS (median OS, 10 months; not reached for other ALK− ALCLs; P=0.007). Four ALCLs had a novel NCL::UBTF fusion involving genes encoding the nucleolar proteins nucleolin and nucleolar (upstream binding) transcription factor-1. Four cases each had PARG::BMS1 and TNK1::GPS2 (the latter seen only in Type I ALCLs). Conclusions: This large consortium-based analysis of coding fusions further elucidates the molecular distinction between Type I and Type II ALCLs. Both ALK and non-ALK TK fusions were seen exclusively in Type I ALCLs, which we have shown previously are enriched for JAK-STAT3 pathway genes and correlate strongly with pSTAT3Y705 positivity by immunohistochemistry. These fusions were not identified in Type II ALCLs, which previous data suggest are associated with epigenetic alterations. ALK+ ALCLs with NPM1::ALK and X::ALK showed differences in gene expression, suggesting biological differences. Furthermore, ALCLs with non-ALK TK fusions shared gene expression features with ALK+ ALCL. Clinical fusion detection could enhance molecular classification of Type I and Type II ALCLs and may guide precision therapy.

Background: Anaplastic large cell lymphomas (ALCLs) are CD30-positive T-cell lymphomas that share pathologic features but differ in clinical presentation, outcome, and molecular features. The World Health Organization (WHO) and International Consensus Classification (ICC) classify ALCLs by presence or absence of ALK rearrangements (R) and clinical presentation (systemic, cutaneous [c], or breast implant-associated [BIA]). ICC, but not WHO, recognizes DUSP22-R as defining a new genetic subtype of ALK- ALCL. The classifications otherwise do not reflect additional molecular heterogeneity in genetics (e.g., TP63-R) or therapeutic vulnerabilities (e.g., JAK-STAT3 pathway activation). Methods: ALCLs (N=689) underwent expert consensus review (WHO/ICC) through the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). All cases also underwent genetic subtyping (ALK, DUSP22, TP63, and triple-negative [TN]) using fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC), as well as IHC for phospho-STAT3 Tyr705 (pSTAT3). RNAseq was performed and evaluable in 393 cases; the remaining cases had insufficient tissue, tumor content, RNA yield or quality, and/or sequencing data quality. Sequenced and non-sequenced sub-cohorts had similar demographics and subtype distribution. Results: Unsupervised gene expression profiling (GEP) identified 2 main molecular types of ALCL. Type I ALCLs predominantly included ALK+ ALCLs, BIA-ALCLs, and a subset of TN ALCLs (designated TN-I), whereas Type II ALCLs predominantly included ALCLs with DUSP22-R, TP63-R, or both (double-hit; DH), and the remaining TN ALCLs (TN-II). Type I ALCLs were strongly associated with pSTAT3 expression (74.2±26.4% positive malignant cells vs 9.9±22.7% for Type II; P&lt;0.0001). An independently derived pSTAT3 staining threshold of 30% assigned Type I vs II with 91% accuracy. A third cluster of ALCLs, mostly cALCL, showed an epithelial GEP signature rather than a lymphoma signature; these cases were assigned to Types I or II based on pSTAT3 IHC. Distinct sub-signatures were identified for ALK+, DUSP22-R, TP63-R, and BIA ALCL (Fig. 1), but not ALK- ALCL or cALCL. Gene set enrichment analysis showed Type I ALCLs to be enriched for JAK-STAT3 signaling genes (normalized enrichment score [NES], 2.22; FDR&lt;0.0001) and related pathways, such as TNFα-NFκB signaling (NES, 2.21; FDR&lt;0.0001). In contrast, Type II ALCLs were enriched for cell cycle, DNA repair, epigenetic, and metabolic pathway genes, but not for major tyrosine kinase-mediated signaling pathway genes. Enriched epigenetic pathways included chromatin modifying enzymes (NES, -1.86; FDR=0.002) and histone methylation (NES, -1.71; FDR=0.002). EZH2 was the most overexpressed gene in Type II ALCLs (fold-change, 7.74; FDR=8.84×10 -306). At the protein level, EZH2 IHC H-scores were 275±45 in Type II and 168±70 in Type I ALCLs (P&lt;0.0001); H3K27me3 H-scores were 170±81 and 76±63, respectively (P&lt;0.001). The top metabolic gene set involved cholesterol biosynthesis (NES, -1.88; FDR=0.002). Overall survival (OS) data were available in 257 systemic ALCL patients (145 sequenced and 112 non-sequenced; cALCL and BIA-ALCL were excluded). Non-sequenced TN ALCLs were assigned to TN-I or TN-II using pSTAT3 IHC. The results supported earlier data indicating favorable prognosis of DUSP22-R ALCL (5 y OS, 95%) and ALK+ ALCL (87%), intermediate prognosis of TN ALCL (TN-I, 52% and TN-II, 38%; P=NS), and poor prognosis of TP63-R/DH ALCL (0%)(P&lt;0.0001; Fig. 2). Conclusions: Two overarching molecular types of ALCL exist, predominantly associated with the presence (Type I) or absence (Type II) of the JAK-STAT3 signaling program. Distinct GEP signatures exist for ALK+ ALCL and BIA-ALCL (predominantly Type I), and DUSP22-R ALCL and TP63-R ALCL (predominantly Type II). TN ALCLs lacking ALK-R, DUSP22-R, and TP63-R can be stratified into TN-I and TN-II subtypes. pSTAT3 IHC has &gt;90% accuracy as a surrogate for GEP-based subtyping. ALK- ALCL and cALCL cluster by molecular subtype rather than by defining GEP signatures. Type II ALCLs are enriched for targetable epigenetic and metabolic pathways, including EZH2/histone methylation and cholesterol biosynthesis. This molecular classification is diagnostically, prognostically, and potentially therapeutically relevant, and can be applied using FISH and IHC in routine practice and in the clinical trial setting.

Follicular helper T-cell lymphoma of the angioimmunoblastic type (AITL) is associated with dismal prognosis. We performed functional genomic approaches including whole-exome sequencing (WES; n=119), transcriptomic (n=78) and methylation (n=40) analysis. We identified recurrent mutations in known epigenetic drivers ( TET2, DNMT3A, IDH2 R172), and also identified novel ones (TET3, KMT2D). Somatic mutation of all three epigenetic drivers ( TET2, IDH2, and DNMT3A) was associated with poor prognosis (p&lt;.001). Mutations in genes regulating T-cell receptor (TCR) signaling ( CD28 VAV1, FYN, PLCG1) or activation ( RHOA G17V), and regulators of the PI3K pathway (PIK(3)C members, PTEN,PHLPP-1/-2) were also found. Genome-wide DNA-methylation analysis integrated with mRNA expression profiling also revealed epigenetic alterations in genes regulating TCR-RHOA/B/C or PI3K-signaling. TET2 loss was noted in 85% AITLs and was significantly associated with RHOA G17V, CD28 and IDH2 R172mutations. AITLs lacking RHOA G17V tended to have mutations regulating the JAK-STAT pathway ( JAK2, JAK3, STAT1, STAT3, SOCS1). RNA-seq analysis identified fusion transcripts in genes regulating TCR activation (8%), revealed a restricted TCR repertoire in the majority of cases (a=87%, b=72%), and showed the presence of Epstein-Barr virus transcriptome (73%). GEP demonstrated association of B-cells in the tumor-milieu with better prognosis (p=.006), while dendritic cells were associated with worse prognosis (p=.001), which was further validated by immunohistochemistry using CD20, CD68, and CD163 antibodies. RNA-seq and corresponding WES analysis of 12 AITL patient-derived-xenografts (PDX) showed that bi-allelic TET2 mutations, DNMT3A mutations or sub-clonal mutations ( PLCG1 PHLPP2) werepropagated in sequential passages. Gene signatures related to T FH (follicular helper) and T CM (central memory) were also well-maintained in secondary passages in PDX models. Gene signatures of late PDX passages (3 rd-5 th) were enriched with genes related to proliferation and metabolic reprogramming, and in an independent cohort of AITLs, high expression of T3/T5 related signatures was associated with worse outcome (p=0.02/p=0.009). Low mRNA expression of PHLPP2 predicted poor prognosis (p=.03) and engineered PHLPP2 loss showed enhanced PI(3)K activation and FOXO1 inactivation in CD4+ T-cells in-vitro. Thus, we defined the genomic landscape for AITL, which is largely characterized by epigenetic alterations, TCR signaling and PI3K/AKT dysregulation, which may be amenable for therapeutic targeting.

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 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 Primary mediastinal large B-cell lymphoma (MLBCL) is a clinically distinct entity that typically presents as localized, sclerotic disease in young, female patients. We previously characterized the transcriptional profiles of MLBCLs and identified important shared features with a clinically related disorder, classical Hodgkin lymphoma (cHL) (Blood 102:3871, 2003). Given the documented role of the NFkB survival pathway in Hodgkin Reed-Sternberg cells, we previously assessed NFkB activation in MLBCL by determining the subcellular location of the c-REL subunit of the NFkB heterodimer with a 2-color immunofluoresence assay. In a small pilot MLBCL series, c-REL was localized to the nucleus in the majority of examined cases, consistent with NFkB activation. In the current study, we evaluated c-REL subcellular localization in an additional series of MLBCLs and DLBCLs using a broadly applicable immunoperoxidase method. 100% of MLBCLs exhibited nuclear c-REL staining whereas DLBCL c-REL subcellular localization was more variable. Thereafter, we analyzed the transcription profiles of the 34 MLBCLs and 176 DLBCLs for coordinate expression of NFkB target genes, using literature-curated NFkB target gene lists from three independent sources and gene set enrichment analysis (GSEA). MLBCL signatures exhibited significant enrichment of 2 of the 3 NFkB target gene sets. In addition, 32 NFkB target genes from the combined set were significantly more abundant in MLBCLs than DLBCLs (&gt; 30% more abundant and &gt; 99th percentile in permutation analysis). Similar results were obtained in an independent series of MLBCLs and DLBCLs with available gene expression profiles (J. Exp. Med. 198:851, 2003). To assess the role of c-REL amplification in NFkB activation in our lymphoma series, we compared c-REL amplification, c-REL subcellular localization and coordinate expression of the identified NFkB target genes and classified the DLBCLs according to putative cell of origin. The majority of c-REL amplifications (67%) were found in DLBCLs of germinal center (GC) subtype, consistent with the observation that c-REL is part of the described GC signature. However, most (71%) of the examined GC DLBCLs had cytoplasmic c-REL expression and the GC DLBCLs did not have increased expression of NFkB target genes. Taken together with the MLBCL analyses, these studies indicate that: 1) NFkB is consistently activated in MLBCL; 2) c-REL amplification is not closely associated with NFkB activation in large cell lymphomas (LCLs); and 3) NFkB activation in LCL subtypes does not require amplification of the c-REL locus.

One-third of peripheral T-cell lymphomas are “not otherwise specified” (PTCL-NOS), but they have been subdivided into 2 subgroups based on gene expression profiling. Amador and colleagues generated an immunohistochemical algorithm that parallels the molecular separation of PTCL-NOS and provides useful prognostic information.