ALBERT

Description: Non-Hodgkin lymphomas (NHL) are a diverse group of blood cancers on the rising trend both worldwide and in Singapore. Better understanding of the pathogenesis and biology of these tumors is urgently required to improve the diagnosis and prognostication. Moreover, the outcome using currently available therapies is poor and there is an immediate need for better treatment options. With an increasing number of genomic studies published, there is a growing demand to bring these discoveries into in vitro and in vivo models. However, the lack of publicly available cell lines and/or animal models for the majority of the NHL subtypes makes these studies difficult to proceed. With that objective, we have started collecting fresh NHL tumor samples and implanting them into NOD scid gamma (NSG) mice to generate patient-derived xenograft (PDX) models. After tumor dissemination, the cells are injected either subcutaneously or intraperitoneally into 6-10 week old mice. Each passage is thoroughly immunohistochemically characterized by a senior hematopathologist and contrasted to the primary patient specimen. Whole exome sequencing (WES) is performed and compared to the primary patient data where possible. A model is considered stable if it has not changed its phenotype for at least 3 passages. A full list of currently available stable models is listed in Table 1. Efforts are also under way to generate stable cell lines based on these models. Strategies tested are spontaneous immortalization, human telomerase reverse transcriptase (TERT), Herpesvirus saimiri (HVS) or Epstein-Barr virus (EBV) transduction and feeder culture. We have recently reported a comprehensive molecular profiling of monomorphic epitheliotropic intestinal T-cell lymphoma (MEITL; previously also known as type II enteropathy-associated T-cell lymphoma; Nairismagi et al., Leukemia, 2016). MEITL, a newly recognized WHO entity, is a rare aggressive primary intestinal disease with poor prognosis and a median overall survival of only 7 months. Frequent alterations were identified in the JAK-STAT and G-protein-coupled receptor signaling pathways and a number of epigenetic regulators. Specifically, 60-30% mutation frequencies were found in the STAT5B, JAK3, SETD2, GNAI2 and CREBBP genes. Tumor tissue was collected from a 55 year old Chinese male with relapsed MEITL. The cells have been propagated in the NSG mouse by subcutaneous or intraperitoneal injection up to 6 and 3 passages, respectively. All passages have been histologically characterized and maintained their CD3+ CD8alpha-alpha+ cytotoxic granules+ MATK+ and EBER- phenotype with aberrant expression of both TCR beta and gamma. WES was performed both in the patient primary sample and in passage 1 (P1) PDX sample. There were 83 somatic mutations present in the primary sample, all of which were also identified in the P1 PDX sample. Furthermore, Sanger sequencing was used to validate the presence of all 83 mutations in the remaining passages. There was only 1 mutation lost in the P6 subcutaneous PDX model compared to the primary patient specimen demonstrating the outstanding stability of this model. Using peritoneal fluid cells from P2 we have previously performed ex vivo studies and identified novel treatment modalities for this deadly disease (Nairismagi et al., Leukemia, 2016). Efforts are currently under way to test these regimens also in in vivo setting. In summary, we have generated a number of NHL PDX models with the objective to enhance drug testing. MEITL presents a real life situation where clinical trials are not possible due to the rarity of the disease; however, the availability of PDX models allows for efficient testing of novel therapies and can lead to improved patient outcome. Efforts are under way to further characterize the existing models and tissue collection is ongoing to establish more models. Table 1 List of available stable non-Hodgkin lymphoma models. AITL, angioimmunoblastic T-cell lymphoma; DLBCL, diffuse large B-cell lymphoma; EBV, Epstein-Barr virus; GC, germinal center; MCL, mantle cell lymphoma; MEITL, monomorphic epitheliotropic intestinal T-cell lymphoma; NK/TCL, natural killer/T-cell lymphoma and PTCL NOS, peripheral T-cell lymphoma not otherwise specified. Table 1. List of available stable non-Hodgkin lymphoma models. AITL, angioimmunoblastic T-cell lymphoma; DLBCL, diffuse large B-cell lymphoma; EBV, Epstein-Barr virus; GC, germinal center; MCL, mantle cell lymphoma; MEITL, monomorphic epitheliotropic intestinal T-cell lymphoma; NK/TCL, natural killer/T-cell lymphoma and PTCL NOS, peripheral T-cell lymphoma not otherwise specified. Disclosures No relevant conflicts of interest to declare.

Description: Key Points Mutations in a VHL cryptic exon may be found in patients with familial erythrocytosis or VHL disease. Synonymous mutations in VHL exon 2 may induce exon skipping and cause familial erythrocytosis or VHL disease.

Description: Peripheral T-cell lymphoma (PTCL) is a group of complex clinicopathological entities, often associated with an aggressive clinical course. Angioimmunoblastic T-cell lymphoma (AITL) and PTCL-not otherwise specified (PTCL-NOS) are the 2 most frequent categories, accounting for 〉50% of PTCLs. Gene expression profiling (GEP) defined molecular signatures for AITL and delineated biological and prognostic subgroups within PTCL-NOS (PTCL-GATA3 and PTCL-TBX21). Genomic copy number (CN) analysis and targeted sequencing of these molecular subgroups revealed unique CN abnormalities (CNAs) and oncogenic pathways, indicating distinct oncogenic evolution. PTCL-GATA3 exhibited greater genomic complexity that was characterized by frequent loss or mutation of tumor suppressor genes targeting the CDKN2A/B-TP53 axis and PTEN-PI3K pathways. Co-occurring gains/amplifications of STAT3 and MYC occurred in PTCL-GATA3. Several CNAs, in particular loss of CDKN2A, exhibited prognostic significance in PTCL-NOS as a single entity and in the PTCL-GATA3 subgroup. The PTCL-TBX21 subgroup had fewer CNAs, primarily targeting cytotoxic effector genes, and was enriched in mutations of genes regulating DNA methylation. CNAs affecting metabolic processes regulating RNA/protein degradation and T-cell receptor signaling were common in both subgroups. AITL showed lower genomic complexity compared with other PTCL entities, with frequent co-occurring gains of chromosome 5 (chr5) and chr21 that were significantly associated with IDH2R172 mutation. CN losses were enriched in genes regulating PI3K–AKT–mTOR signaling in cases without IDH2 mutation. Overall, we demonstrated that novel GEP-defined PTCL subgroups likely evolve by distinct genetic pathways and provided biological rationale for therapies that may be investigated in future clinical trials.

Description: Abstract 2658 Background: Peripheral T-cell lymphomas (PTCL) carry a poorer prognosis compared to their B-cell counterparts and the molecular pathogenesis of PTCL is still largely unknown. The aims of this study are to characterize the molecular signatures and identify signaling pathways involved in the different subsets of PTCL and NKTCL. Materials and Methods: RNA was extracted from tumors of 60 patients with newly diagnosed PTCL and NKTCL: 21 with angioimmunoblastic T-cell lymphoma (AITL), 12 anaplastic large-cell lymphoma (ALCL), 15 peripheral T-cell lymphoma not-otherwise-specified (PTCL-NOS) and 12 with natural-killer T-cell lymphoma (NKTCL). Comparisons were made using published gene expression data files of normal T and NK T-cells. Gene expression profiling was performed using the Affymetrix HG-U133 Plus 2.0 GeneChip platform. Results: The Affymetrix expression profiling distinguishes the 48 PTCL samples from normal T-cell controls (p

Description: Abstract 679 Background: Peripheral T-cell lymphoma (PTCL) represents approximately 10–12% of all non-Hodgkin lymphoma (NHL) in the Western world, with a higher incidence in Asian populations. The World Health Organization classification recognizes a number of distinctive subtypes of PTCL including angioimmunoblastic T-cell lymphoma (AITL), anaplastic large cell lymphoma (ALCL), adult T-cell leukemia/lymphoma (ATLL), extranodal NK/T-cell lymphoma of nasal type (ENKTCL), and many other rare entities that present mainly as extranodal PTCL. However, with current immunophenotypic and molecular markers, about 30–50% of PTCL cases are not classifiable and are categorized as PTCL-not otherwise specified (PTCL-NOS). With the exception of ALK(+)ALCL, the PTCLs generally have a poor outcome and, thus a better understanding of the biology of these diseases is greatly needed to improve the long-term survival of these patients. Methods: In the current study, we performed gene expression profiling analysis on a large and well- characterized series of PTCL and ENKTCL cases (n=372) from the Lymphoma Leukemia Molecular Profiling Project (LLMPP), the International Peripheral T-cell Lymphoma Project (IPTCL) and other major institutions to define robust molecular classifiers, oncogenic pathways and prognosticators for the more common PTCL entities, as well as unique molecular and prognostic subgroups within PTCL-NOS. Molecular signatures for diagnosis and prognosis were generated in training data sets and validated in separate cohorts. Results: Robust molecular classifiers for AITL, two types of systemic ALCL (ALK(+) and ALK(-)), ATLL and ENKTCL were identified (Figure 1). These classifiers reflect the pathobiology of the tumor cells, as well as their microenvironment, and represent a refinement of what we reported previously (Iqbal et.al Blood, 2010; Iqbal et.al Leukemia. 2011). Importantly, ALK(-)ALCL can be differentiated from ALK(+)ALCL and PTCL-NOS with a unique gene expression signature. Approximately 14% of PTCL-NOS were re-classified as ALK(-)ALCL and showed expression of CD30 protein, TIA-1 or granzyme B by immunohistochemistry. ENKTCL can be separated molecularly into NK-cell lymphoma and gd-PTCL, the latter of which was also identified in 9% of PTCL-NOS. The remaining PTCL-NOS cases could be separated into two major subgroups related to T-cell differentiation and characterized by either high expression of GATA3 (30%) or TBX21(T-BET) (45%) and many of the corresponding target genes (Figure 2). Cases with high expression of GATA3 had poor overall survival and showed enriched Wnt and mTOR pathways, but no prominent microenvironment signature. The high TBX21 subgroup had a remarkably good outcome for patients with a high plasma cell-like gene expression signature, but poor overall survival when expressing a high cytotoxic signature (Figure 3). The molecular prognosticator for AITL largely reflected the role of the tumor microenvironment, with the presence of a high B-cell signature correlating with favorable outcome, whereas high dendritic cell/monocyte signatures were associated with inferior survival. Conclusion: We have organized the most comprehensive molecular profiling study of PTCL, and have not only refined the molecular diagnostic and prognostic signatures for the common subtypes of PTCL, but also segregated PTCL-NOS in meaningful biological and prognostic subtypes. Molecular diagnostic and prognostic signatures of PTCL frequently include components of the tumor-host interactions, highlighting the importance of the microenvironment in PTCL biology. This study provides an important framework for additional analysis to identify novel therapeutic targets to improve the outcome of patients with PTCL. Disclosures: No relevant conflicts of interest to declare.

Description: Peripheral T-cell lymphoma (PTCL) is a group of clinically and pathologically heterogeneous non-Hodgkin lymphomas (NHL). Using gene expression profiling (GEP), we have defined molecular classifiers for PTCL subtypes reflecting their pathobiology and oncogenic pathways (Iqbal et al. 2014). We have also shown associations of specific mutations with the molecular subgroups (Wang et al. 2015). Although genomic information is increasing, the pathogenetic mechanisms of PTCLs remain largely unknown. Therefore, we analyzed copy number variation (CNV) and GEP to identify unique genetic abnormalities in the defined PTCL molecular subgroups. CNV data were generated on fresh frozen or formalin-fixed paraffin-embedded genomic DNA (n=114) on 3 Affymetrix platforms (SNP 6.0, 250K SNP, and OncoScan). Two published cohorts (PTCL-NOS, Hartmann et al. 2010; ALCL, Boi et al. 2013) were included for validation. The gene expression analysis, morphological review and clinical characteristics of these cases have been included in previous studies (Iqbal et al. 2010, 2014). Angioimmunoblastic T-cell lymphoma (AITL) represents 20% of all PTCL cases. The most recurrent CNV in AITL was chromosome (chr) 5 gain (39%), followed by chr 21 gain (21%). Interestingly, chr 21 gain co-occurred with chr 5 gain (p=0.003). No recurrent losses (≥20%) were identified among these cases. Molecularly re-classified AITL cases from morphologically classified PTCL-NOS cases showed concordant results with bonafide AITL cases. Of the commonly mutated genes, DNMT3A, IDH2, RHOA and TET2, only IDH2R172Kshowed a significant association (p=0.012) with chr 5 gain. GEP showed enrichment of gene signatures associated with oxidative phosphorylation (PGC-1α target genes) in cases with chr 5 gain. PTCL, not otherwise specified (PTCL-NOS) is the most common PTCL subtype and cannot be further sub-classified using conventional approaches; however, we have identified 2 molecular subgroups within PTCL-NOS, the GATA3 and TBX21 subgroups which are related to 2 distinct T-helper subsets (Iqbal et al. 2014), by employing GEP. Consistent with earlier observations (Hartmann et al. 2010), PTCL-NOS showed remarkably varied CNVs with nearly 50% of cases showing high CNV frequencies. When correlated with molecular subgroups, distinctive CNVs were observed in the molecular GATA3 and TBX21 subgroups. The GATA3 subgroup displayed a large assortment of CNVs. Complete or partial gain of chr 7 (57%) was the most recurrent gain in these cases. Losses affecting 17p, 10q and 9p21, encompassing tumor suppressors such as TP53 (57%), PTEN (43%) and CDKN2A (43%), were frequent in the GATA3 subgroup. The TBX21 subgroup had significantly fewer CNVs, as none were recurring (≥20%); but gains of 5p or 11p were observed in 14%. Additionally, PTCL-NOS cases with ≥10% abnormal genome had significantly poorer overall survival (p=0.012) compared to those with fewer abnormalities. This finding validates the GEP molecularly defined subgroups, as the GATA3 subgroup displayed more CNVs and has been associated with a worse prognosis compared to the TBX21 subgroup (Iqbal et al. 2014). We were able to distinguish CNVs characteristic of the different entities, including the co-occurrence of chr 5 and 21 gains specific in AITL. Gain of 1q (complete or partial) was identified in the GATA3 subgroup of PTCL-NOS and anaplastic lymphoma kinase (ALK) (-) ALCL with equal frequencies (~ 36%), but only 16% in ALK(+) ALCL. Complete or partial gain of chr 7 was also observed in ALCL, but at a considerably lower frequency than in the GATA3 subgroup. Additionally, gain of chr 18 or regions of 17q, and loss of 5q or regions on both arms of chr 9, were more frequent in the GATA3 subgroup compared to other entities. The TBX21 subgroup was primarily differentiated from the GATA3 subgroup by presence of fewer CNVs. Our analysis provides a framework for future investigations into the molecular pathogenesis of PTCL, and highlights potential candidate oncogenes and tumor suppressors deregulated by copy number aberrations. Comparative analysis revealed that certain chromosomal abnormalities are entity-specific. AITL cases with IDH2R172K also had trisomy 5 suggesting that these oncogenic events cooperate in malignant transformation. Thus, the complexity of PTCL is finally becoming clearer with the integration of high resolution molecular techniques for global genomic analysis. Disclosures No relevant conflicts of interest to declare.

Description: Key Points Diagnostic signatures for PTCL subtypes and 2 novel subgroups with distinct oncogenic pathway and prognostic importance in PTCL-NOS were identified. Demonstrated that ALK(–) ALCL is a distinct molecular entity and the tumor microenvironment has prognostic significance in AITL patients.

Description: Key Points Alterations in JAK/STAT signaling pathway are highly prevalent in PTCL and NKTL, where STAT3 and TP53 are the most frequently mutated genes. STAT3 activation drives PD-L1 expression in NKTL, providing a rationale to combine STAT3 inhibitors with immune checkpoint inhibitors.