ALBERT

Description: Background: Immunocompromised patients have higher risk for virally-driven lymphomas associated with pathogens including Epstein-Barr Virus (EBV), Kaposi Sarcoma Herpesvirus (KSHV), HTLV-1, and HIV-1. Within this high-risk patient population, early cancer detection remains a critically unmet clinical need. Recently, analysis of viral cell-free DNA (cfDNA) has shown promise as a predictive biomarker for both immune status and cancer risk. In solid organ transplant recipients, immunosuppression is associated with expansion of a circulating family of viruses called Anelloviridae (De Vlaminck I, Cell, 2013). In screening for EBV-driven nasopharyngeal carcinomas (NPC), EBV cfDNA fragment length distributions distinguish normal adults with transient viremia from those with high risk of NPC (Lam WK, PNAS, 2018). We developed VirCAPP-Seq (Viral Cancer Personalized Profiling by Deep Sequencing) as a clinical virome capture approach for enriching and deeply sequencing circulating viral nucleic acids to elucidate virome composition, fragment length distribution, host genome integration sites, and viral polymorphisms. These features of viral cfDNA may clarify patient risk for malignancy and immunosuppression. Method: 180 viral species from 15 families were selected on the basis of 3 criteria: (1) Known oncoviruses (eg, EBV, Human Papillomavirus (HPV), Hepatitis B Virus (HBV)); (2) Commensal viruses associated with immune state (eg, Anelloviridae); (3) Common clinically relevant viruses (Adenovirus, CMV, BK, etc.). Viral reference genomes were segmented into continuous sliding 50mer windows, and compared to hg19 and a pan-viral reference database for homology using BLASTN. Non-unique regions were excluded. Remaining regions were clustered using CD-HIT at 85% homology to minimize redundant probes (figure 1A). We applied VirCAPP-Seq to plasma samples of patients with known levels of EBV viremia. To evaluate possible interactions of VirCAPP-Seq with human probes, we applied the viral panel alone and in combination with a CAPP-Seq lymphoma panel (Kurtz DM, JCO, 2018). Reads were aligned to a composite reference genome consisting of 180 viral reference genomes and hg19. For each targeted virus, plasma (GE) were estimated by computing the ratio of unique viral depth to human depth, and multiplying by the measured plasma DNA concentration and plasma volume. We correlated the sequencing-based GE estimate to viral titers determined by a clinical RT-PCR assay measured in a CLIA laboratory. Viral integration sites were evaluated with Virus-Clip (Ho DW, Oncotarget, 2015). Results: The final VirCAPP-Seq design consists of 2349 target regions across 180 species, spanning 2.097 Mb. A median of 95.9% of each targeted virus was covered by the panel (IQR 85.1% - 99.0%). Sequence-based phylogenetic analysis demonstrated clear relationships between members of each viral family. However, following in silico masking of non-unique regions, these phylogenetic relationships were no longer discernible, demonstrating that our design avoids targeting regions with interspecies ambiguity (figure 1B). Surprisingly, addition of VirCAPP-Seq to a human capture panel did not significantly impact the human on-target rate compared to human-only capture of lymphoma CAPP-Seq targets (Kurtz et al 2018 JCO), suggesting minimal non-specific interaction between viral probes and host DNA (figure 1C). Across EBV-positive samples, VirCAPP-Seq enriched EBV cfDNA a median of 214,000x compared to off-target EBV abundance in human-only capture (IQR 55,100x - 277,600x) (figure 1D). EBV-positive samples achieved a median EBV depth of 1015x (IQR 210x - 2802x) after enrichment. Additionally, viral GE estimates from read counts were highly correlated with viral titer estimates by clinical RT-PCR (r = 0.92, p 〈 0.001, n=9) (figure 1E). We observed several significant correlations between virome measurements across a range of immunosuppression states and lymphoma subtypes, with details to be presented at the meeting. Conclusions: VirCAPP-Seq enables simultaneous enrichment of clinically relevant viral and host cfDNA from plasma over several orders of magnitude. This framework holds promise for monitoring diverse features of viral cfDNA that capture risks for malignancy and immunosuppression, facilitating personalized diagnostic and therapeutic interventions. Disclosures Kurtz: Roche: Consultancy. Advani:Janssen: Research Funding; Kura: Research Funding; Merck: Research Funding; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cell Medica, Ltd: Consultancy; Kyowa Kirin Pharmaceutical Developments, Inc.: Consultancy; Forty-Seven: Research Funding; Agensys: Research Funding; Bayer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Consultancy, Research Funding; AstraZeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Celmed: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead Sciences, Inc./Kite Pharma, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity Pharma: Research Funding; Millennium: Research Funding; Regeneron: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Stanford University: Employment, Equity Ownership; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees. Diehn:AstraZeneca: Consultancy; BioNTech: Consultancy; Quanticell: Consultancy; Novartis: Consultancy; Roche: Consultancy.

Description: Background: Diffuse large B cell lymphoma (DLBCL) exhibits significant clinical and biological heterogeneity, in part due to cell-of-origin subtypes, somatic alterations, and diverse stromal constituents within the tumor microenvironment (TME). Several immunologically-active lymphoma therapies are known to rely on innate and adaptive anti-tumor responses occurring within this dynamic TME, including agents that are approved (e.g., rituximab, lenalidomide, CART19, ibrutinib) or emerging (e.g., anti-CD47, checkpoint inhibitors). We hypothesized that a large-scale characterization of the cellular heterogeneity in DLBCL might reveal previously unknown biological variation in the TME linked to tumor subtypes and genotypes, therapeutic responses and clinical outcomes, with implications for future personalization of immunotherapy. Methods: Using a combination of lymphoma single-cell RNA sequencing (scRNA-seq) and bulk tumor transcriptome deconvolution (CIBERSORTx; Newman et al., Nat Biotech, 2019), we developed a new machine learning framework for identifying cellular states and ecosystems that reflect fundamental TME subtypes and distinctions in tumor biology (Fig. 1). Specifically, using CIBERSORTx, we purified the transcriptomes of B cells and 12 different TME cell types, including immune and stromal subsets, from 1,279 DLBCL tumor biopsies profiled in 3 prior studies (Reddy et al., Cell 2017; Schmitz et al., NEJM 2018; Chapuy et al., Nat Med 2018). Then, we defined distinct transcriptional states for each of the 13 cell types, which we validated at single-cell resolution, using a combination of two scRNA-seq techniques (Smart-Seq2 and 10x Chromium 5' GEP, BCR and TCR) to profile primary DLBCL, FL, and human tonsils, as well as leveraging multiple scRNA-seq datasets from previous studies. We identified robust co-associations between cell states that form tumor cellular ecosystems, which we validated in independent datasets of bulk DLBCL tumor gene expression profiles. Finally, we related TME ecosystems to defined tumor subtypes, including genotype classes, and to clinical outcomes. Results: By systematically characterizing the landscape of cellular heterogeneity in nearly 1,300 DLBCL tumors, we defined an atlas of 49 distinct transcriptional states across 13 major cell types. These novel cell states spanned diverse innate and adaptive immune effector cells of the lymphoid and myeloid lineages, as well as tumor-associated fibroblasts. Remarkably, 94% of these states (46 of 49) could be validated in a compendium of ~200,000 single-cell transcriptomes derived from lymphomas, healthy control tonsils, and other tissue types. Moreover, single cells from DLBCL, FL and tonsils best mirrored these newly discovered cell states. We next characterized the biology and potential clinical utility of each cell state. We observed clear distinctions in the transcriptional programs of immune and stromal elements between germinal center and activated B cell DLBCL, as well as between known mutational subtypes. Importantly, many cell states reflected novel phenotypic groupings, and the majority were significantly associated with overall survival (P

Description: Vascular endothelial growth factor (VEGF)-mediated signaling has at least two potential roles in diffuse large B cell lymphoma: potentiation of angiogenesis, and potentiation of proliferation and/or survival induced by autocrine VEGF receptor-mediated signaling by lymphoma cells. We have recently shown that diffuse large B cell lymphomas expressing high levels of VEGF protein also express high levels of VEGF receptors 1 and 2. We have now assessed a larger multi-institutional cohort of patients with de novo diffuse large B cell lymphoma treated with anthracycline-based therapy to address whether either tumor vascularity as assessed by microvessel density counting, or expression of VEGF protein and its receptors as assessed by immunohistochemistry, contribute to patient outcomes. Increased tumor vascularity (Figure 1a, b, c -- increasing microvessel density) is associated with poor overall survival (p=0.047), and is independent of the international prognostic index (Figure 1d). In contrast, high expression of VEGFR1 by lymphoma cells is associated with improved overall survival (p=0.044) and a trend toward improved progression-free survival (p=0.054). High expression of VEGF by lymphoma cells is also associated with a trend toward improved overall survival (p=0.089). The concordant trend toward improved survival with increased lymphoma cell expression of VEGF and its receptor VEGFR1, together with their coordinate overexpression in a subset of diffuse large B cell lymphomas (p=0.00025, chi value 21.5), suggests the presence of an autocrine VEGF-VEGFR1-mediated feedback loop in these lymphomas. Indeed the combination of high VEGF and VEGFR1 protein expression identifies a subgroup of patients with improved overall (p=0.003) and progression-free (p=0.026) survival; these findings are independent of the international prognostic index (Figure 2). The presence of improved survival in a cohort of patients whose lymphomas potentially depend on autocrine signaling via VEGFR1 suggests that dependence on this pathway may render patients susceptible to the effects of anthracycline-based therapy; indeed, downregulation of VEGF expression at the mRNA level by anthracyclines and other chemotherapeutic agents has been demonstrated in a variety of non-hematolymphoid neoplasms. The relative importance of autocrine VEGF-mediated signaling versus vascularity should certainly be taken into account in clinical trials of anti-VEGF/VEGF receptor therapy in diffuse large B cell lymphoma. Figure Figure Figure Figure

Description: Key Points Brentuximab vedotin serves as an effective therapy for PEL. Brentuximab vedotin led to cytotoxic effects in PEL cell lines and extended survival of xenograft mice.

Description: Recent effort in the molecular characterization of diffuse large B-cell lymphoma (DLBCL) has led to the recognition that patients with DLBCL of germinal center origin exhibit a better overall survival. Thus, identification and characterization of markers of germinal center derivation are of importance in dissecting prognostic subclasses of DLBCL. The VICKZ (Vg1 RBP/Vera, IMP1, 2, 3, CRD-BP, KOC, ZBP-1) family members are RNA-binding proteins that recognize specific RNA targets and have been implicated in diverse cellular functions including cell polarity, migration, proliferation and tumorigenesis/metastasis. We generated an antibody that recognizes all three isoforms of VICKZ protein and characterized its expression in normal lymphoid tissue and in lymphoma subtypes. In normal tonsils, VICKZ protein showed a germinal center-specific pattern of expression with staining localized to the cytoplasm. Among 868 non-Hodgkin and Hodgkin lymphomas tested by immunohistochemistry on tissue microarrays, staining for VICKZ protein was present in 76% (126/165) of follicular lymphoma, 78% (155/200) of DLBCL, 90% (9/10) of mediastinal large B-cell lymphoma, and 100% (2/2) of Burkitt lymphoma. A subset of mantle cell lymphoma (11%, 2/19), extranodal (8%, 2/25), and nodal (20%, 1/5) marginal zone lymphoma and lymphoblastic lymphoma (25%, 4/13), showed VICKZ staining. The majority of lymphocyte predominant Hodgkin (92%, 12/13) and classical Hodgkin (94%, 101/108) lymphoma were found to be positive. Among T cell lymphoma, anaplastic large cell lymphoma were positive (75%, 6/9). Additional work is in progress to correlate VICKZ protein expression with other germinal center markers such as HGAL, BCL6 and CD10 as well as with prognostic subclasses of DLBCL. The differential expression pattern of VICKZ protein in lymphoma subtypes suggests a potential utility for VICKZ in the identification of subgroups of DLBCL associated with different prognoses.

Description: Several gene-expression signatures predict survival in diffuse large B-cell lymphoma (DLBCL), but the lack of practical methods for genome-scale analysis has limited translation to clinical practice. We built and validated a simple model using one gene expressed by tumor cells and another expressed by host immune cells, assessing added prognostic value to the clinical International Prognostic Index (IPI). LIM domain only 2 (LMO2) was validated as an independent predictor of survival and the “germinal center B cell–like” subtype. Expression of tumor necrosis factor receptor superfamily member 9 (TNFRSF9) from the DLBCL microenvironment was the best gene in bivariate combination with LMO2. Study of TNFRSF9 tissue expression in 95 patients with DLBCL showed expression limited to infiltrating T cells. A model integrating these 2 genes was independent of “cell-of-origin” classification, “stromal signatures,” IPI, and added to the predictive power of the IPI. A composite score integrating these genes with IPI performed well in 3 independent cohorts of 545 DLBCL patients, as well as in a simple assay of routine formalin-fixed specimens from a new validation cohort of 147 patients with DLBCL. We conclude that the measurement of a single gene expressed by tumor cells (LMO2) and a single gene expressed by the immune microenvironment (TNFRSF9) powerfully predicts overall survival in patients with DLBCL.

Description: We previously developed a multivariate model based on the RNA expression of 6 genes (LMO2, BCL6, FN1, CCND2, SCYA3, and BCL2) that predicts survival in diffuse large B-cell lymphoma (DLBCL) patients. Since LMO2 emerged as the strongest predictor of superior outcome, we generated a monoclonal anti-LMO2 antibody in order to study its tissue expression pattern. Immunohistologic analysis of over 1200 normal and neoplastic tissue and cell lines showed that LMO2 protein is expressed as a nuclear marker in normal germinal-center (GC) B cells and GC-derived B-cell lines and in a subset of GC-derived B-cell lymphomas. LMO2 was also expressed in erythroid and myeloid precursors and in megakaryocytes and also in lymphoblastic and acute myeloid leukemias. It was rarely expressed in mature T, natural killer (NK), and plasma cell neoplasms and was absent from nonhematolymphoid tissues except for endothelial cells. Hierarchical cluster analysis of immunohistologic data in DLBCL demonstrated that the expression profile of the LMO2 protein was similar to that of other GC-associated proteins (HGAL, BCL6, and CD10) but different from that of non-GC proteins (MUM1/IRF4 and BCL2). Our results warrant inclusion of LMO2 in multivariate analyses to construct a clinically applicable immunohistologic algorithm for predicting survival in patients with DLBCL.

Description: Sinus histiocytosis with massive lymphadenopathy (SHML or Rosai-Dorfman disease) is a rare histiocytic proliferation of unknown etiology. There is a known association between SHML and immune disorders. Recently, histologic changes of SHML have been found in lymph nodes of patients with autoimmune lymphoproliferative syndrome (ALPS), a disorder most commonly associated with mutations in the TNFRSF6 gene that encodes the Fas antigen. We retrospectively analyzed tissue from 22 patients with SHML for TNFRSF6 gene mutations using isolated genomic DNA from paraffin-embedded tissue followed by screening of PCR products for the promoter regions and all exons (1–9) of the gene for possible mutation by high performance liquid chromatography. Mutations were confirmed by direct sequencing. We identified six patients (27%) with SHML and mutations of the TNFRSF6 gene as listed below, including three cases (14%) with potentially significant mutations (*) involving promotor and splice donor regions, and frameshift mutations. The samples with mutations had a 4:2 male:female ratio with a mean/median age of 39/43 years (range 7–68 years) compared to a 9:7 male:female ratio, mean/median age of 42/43 years (range 12–76 years) for the non-mutated samples. No differences in site of disease were identified in the mutated versus non-mutated groups. None of the samples had morphologic features to suggest ALPS. These results suggest that at least a subset of cases of SHML are associated with disruption of the Fas apoptotic pathway. Additional study of other components of the apoptotic pathway may be warranted in this disease. Cases with TNFRSF6 mutations. Case No. Nucleotide Change Localization Codon Amino acid change **Numbering for the promoter sequence, according to www.mutationdiscovery.com. All other numbering according to GeneBank accession number M67454. 1 c217+34A〉G Intron 7 c217+40A〉G Intron 7 2 T779C Exon 7 195 Val --〉 Ala 3 c217+1G〉A Intron 7 Splice defect* T763C Exon 7 190 Val --〉 Ala c217+182A〉G Intron 7 c217+183A〉G Intron 7 C1425T Exon 9II 3′UTR * 4 597del T Exon 4 135 Frameshift* 5 T/C 4656** Promoter * c189+4A〉T Intron 6 5′ consensus splice donor site* C729T Exon 6 179 Leu --〉 Phe 6 c218-84A〉G Intron 7