Abstract: Fc γ receptor IIB (FcγRIIB) is an inhibitory molecule capable of reducing antibody immunotherapy efficacy. We hypothesized its expression could confer resistance in patients with diffuse large B-cell lymphoma (DLBCL) treated with anti-CD20 monoclonal antibody (mAb) chemoimmunotherapy, with outcomes varying depending on mAb (rituximab [R]/obinutuzumab [G] ) because of different mechanisms of action. We evaluated correlates between FCGR2B messenger RNA and/or FcγRIIB protein expression and outcomes in 3 de novo DLBCL discovery cohorts treated with R plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) reported by Arthur, Schmitz, and Reddy, and R-CHOP/G-CHOP-treated patients in the GOYA trial (NCT01287741). In the discovery cohorts, higher FCGR2B expression was associated with significantly shorter progression-free survival (PFS; Arthur: hazard ratio [HR], 1.09; 95% confidence interval [CI] , 1.01-1.19; P = .0360; Schmitz: HR, 1.13; 95% CI, 1.02-1.26; P = .0243). Similar results were observed in GOYA with R-CHOP (HR, 1.26; 95% CI, 1.00-1.58; P = .0455), but not G-CHOP (HR, 0.91; 95% CI, 0.69-1.20; P = .50). A nonsignificant trend that high FCGR2B expression favored G-CHOP over R-CHOP was observed (HR, 0.67; 95% CI, 0.44-1.02; P = .0622); however, low FCGR2B expression favored R-CHOP (HR, 1.58; 95% CI, 1.00-2.50; P = .0503). In Arthur and GOYA, FCGR2B expression was associated with tumor FcγRIIB expression; correlating with shorter PFS for R-CHOP (HR, 2.17; 95% CI, 1.04-4.50; P = .0378), but not G-CHOP (HR, 1.37; 95% CI, 0.66-2.87; P = .3997). This effect was independent of established prognostic biomarkers. High FcγRIIB/FCGR2B expression has prognostic value in R-treated patients with DLBCL and may confer differential responsiveness to R-CHOP/G-CHOP.

Abstract: Background: The anti-CD20 monoclonal antibody (mAb), obinutuzumab (G), has shown improved outcomes versus rituximab (R) in indolent lymphomas; however, no improvement was seen in diffuse large B-cell lymphoma (DLBCL), and the molecular basis is unclear. The inhibitory Fc gamma receptor IIB (Fc γRIIB), expressed on lymphoma cells, can impair the effects of direct targeting mAbs, such as R, by binding and internalizing them, reducing opsonization and limiting FcγR-mediated killing. We hypothesized that FcγRIIB expression on cellular effectors and/or the lymphoma confers treatment resistance in some patients (pts) and evaluated if outcomes differ for therapies involving a non-internalized mAb (G). Methods: We evaluated correlates between FCGR2B mRNA and/or FcγRIIB protein expression and pt outcomes in two discovery cohorts of de novo DLBCL treated with R-CHOP (Arthur et al. 2018, n=372; Schmitz et al. 2018, n=234), and the phase III GOYA trial (NCT01287741; n=552), which compared R-CHOP with G-CHOP in pts with previously untreated DLBCL. FCGR2B mRNA expression was assessed by RNA-Seq, and protein expression was assessed in evaluable cohorts by immunohistochemistry, using tissue microarrays with macrophages identified by CD68. FCGR2B expression was also measured by a NanoString assay (Arthur cohort). Cox regression analyzed the impact of FcγRIIB/FCGR2B expression on progression-free survival (PFS), with univariate and multivariate models adjusted for International Prognostic Index (IPI), cell of origin (COO), and BCL2 protein expression. Results: In the discovery cohorts, a higher FCGR2B expression was significantly associated with shorter PFS (Arthur: HR 1.09 [95% CI: 1.01–1.19], P=0.036; Schmitz: HR 1.13 [95% CI: 1.02–1.26] , P=0.0243). Expression by NanoString strongly correlated with RNA-Seq, confirming the association with shorter PFS (HR 1.13 [95% CI: 1.04–1.23], P=0.0048). In GOYA, a significant association between PFS and FCGR2B was observed in the R arm (HR 1.26 [95% CI: 1.00–1.58] , P=0.0455), with no prognostic effect observed for G (HR 0.91 [95% CI: 0.69–1.20], P=0.5). Pts with high FCGR2B expression appeared to benefit more from G than R (HR 0.67 [95% CI: 0.44–1.02] , P=0.0622), in contrast to pts with low FCGR2B expression (HR 1.58 [95% CI: 1.00–2.50], P=0.0503). In both Arthur and GOYA cohorts, FCGR2B expression by RNA-Seq was associated with FcγRIIB on the tumor, which correlated with a shorter PFS for R (HR 2.17 [95% CI: 1.04–4.50] , P=0.03), but not G (HR 1.37 [95% CI: 0.66–2.87], P=0.4). This prognostic effect on PFS was independent of established prognostic biomarkers, IPI, COO and BCL2. Conclusion: High FcγRIIB/FCGR2B expression in pts with DLBCL has prognostic value in those treated with R and may confer differential responsiveness to R or G. Citation Format: Laura K. Hilton, Malgorzata Nowicka, Margaret Ashton-Key, Chantal E. Hargreaves, Chern Lee, Russell Foxall, Matthew J. Carter, Stephen A. Beers, Kathleen N. Potter, Christopher R. Bolen, Christian Klein, Andrea Knapp, Farheen Mir, Matthew Rose-Zerilli, Cathy Burton, Wolfram Klapper, David W. Scott, Laurie H. Sehn, Umberto Vitolo, Maurizio Martelli, Marek Trneny, Graham W. Slack, Pedro Farinha, Jonathan C. Strefford, Mikkel Z. Oestergaard, Ryan D. Morin, Mark S. Cragg. Prognostic significance of Fc gamma receptor IIB expression in the response of previously untreated diffuse large B-cell lymphomas to anti-CD20 monoclonal antibodies: Differing impact of rituximab and obinutuzumab [abstract]. In: Proceedings of the AACR Virtual Meeting: Advances in Malignant Lymphoma; 2020 Aug 17-19. Philadelphia (PA): AACR; Blood Cancer Discov 2020;1(3_Suppl):Abstract nr PO-26.

Abstract: Rhodococcus sp. RHA1 (RHA1) is a potent polychlorinated biphenyl-degrading soil actinomycete that catabolizes a wide range of compounds and represents a genus of considerable industrial interest. RHA1 has one of the largest bacterial genomes sequenced to date, comprising 9,702,737 bp (67% G+C) arranged in a linear chromosome and three linear plasmids. A targeted insertion methodology was developed to determine the telomeric sequences. RHA1's 9,145 predicted protein-encoding genes are exceptionally rich in oxygenases (203) and ligases (192). Many of the oxygenases occur in the numerous pathways predicted to degrade aromatic compounds ( 30 ) or steroids ( 4 ). RHA1 also contains 24 nonribosomal peptide synthase genes, six of which exceed 25 kbp, and seven polyketide synthase genes, providing evidence that rhodococci harbor an extensive secondary metabolism. Among sequenced genomes, RHA1 is most similar to those of nocardial and mycobacterial strains. The genome contains few recent gene duplications. Moreover, three different analyses indicate that RHA1 has acquired fewer genes by recent horizontal transfer than most bacteria characterized to date and far fewer than Burkholderia xenovorans LB400, whose genome size and catabolic versatility rival those of RHA1. RHA1 and LB400 thus appear to demonstrate that ecologically similar bacteria can evolve large genomes by different means. Overall, RHA1 appears to have evolved to simultaneously catabolize a diverse range of plant-derived compounds in an O 2 -rich environment. In addition to establishing RHA1 as an important model for studying actinomycete physiology, this study provides critical insights that facilitate the exploitation of these industrially important microorganisms.

Abstract: Introduction: Among the tumor immune escape mechanisms described to date, alterations in the expression of major histocompatibility complex (MHC) molecules play a crucial role in the development of diffuse large B-cell lymphoma (DLBCL). Although the frequency of loss of MHC expression differs between ABC- and GCB-DLBCL cell of origin (COO) subtypes, distinct genetic alterations and molecular features that affect MHC expression and the composition of immune cells in the tumor microenvironment remain ill-defined. Here, we aimed to uncover the biologic and genomic basis underlying acquired loss of MHC expression. Method: We analyzed biopsies from 347 patients newly diagnosed with de novo DLBCL and uniformly treated with R-CHOP in British Columbia. We performed targeted resequencing, SNP6.0 array and RNAseq for genetic analyses. Immunohistochemical (IHC) staining of MHC-I and -II was performed on tissue microarrays (n=332). COO was assigned by the Lymph2Cx assay in 323 cases (183 GCB, 104 ABC and 36 unclassifiable). Immune cell composition was assessed by IHC, flow cytometry and gene expression profiling (GEP)-based deconvolution of cellular signatures. To experimentally confirm decreased MHC expression induced by EZH2 mutation, we measured surface MHC-I and -II expression on tumor B cells using EZH2Y641/BCL2 mouse model which was previously established (Beguelin et al, Cancer Cell 2013). We also treated human DLBCL cells harboring EZH2 mutation and wild type using EZH2 inhibitor (EPZ-6438), and evaluated their surface MHC-I and -II expression. Results: Loss of MHC-I and -II expression was observed in 43% and 28% of DLBCL cases, respectively. MHC-II loss of expression was significantly associated with the reduction of tumor-infiltrating lymphocytes (TILs), especially CD4 positive T-cells (FOXP3+ cells, PD-1+ cells, and CD4+ naïve and memory T-cells), and cytolytic activity (GZMB and PRF1 mRNA expression) in GCB-DLBCL (all; p 〈 0.001), but not in ABC-DLBCL. MHC-II-negativity was associated with unfavorable prognosis only in GCB-DLBCL (5-year time-to-progression; 59% vs 79%, p=0.007), whereas there was no prognostic impact of MHC-I expression in either subtype, suggesting a link between loss of MHC-II expression and reduced immune surveillance leading to poor prognosis, specifically in GCB-DLBCL. We next performed GEP using RNAseq separately in each COO subtype. Interestingly, only four genes (HLA-DMA, DRA, DPA1 and CD74) were differentially expressed according to MHC-II expression (FDR 〈 0.001) in ABC-DLBCL. By contrast, a total of 641 genes were differentially expressed in GCB-DLBCL. Of importance, a dark zone (DZ) B-cell signature was strongly enriched in MHC-II-negative GCB-DLBCL cases (FDR 〈 0.001), suggesting that MHC-II deficiency defines the tumor originated from DZ of the germinal center. Correlative genetic analysis revealed that, as expected, mutations of CIITA and RFXAP were detected more frequently in MHC-II-negative GCB-DLBCL (p=0.01 and 0.003, respectively). Strikingly, CD83 mutations, which elevate and stabilize MHC-II expression in centrocytes of the light zone (LZ), were significantly enriched in MHC-II positive GCB-DLBCL (p= 0.008), suggesting that these mutations affecting the antigen presentation machinery are selectively acquired in GCB-DLBCL tumors to further reduce and increase the surface MHC-II expression. Genetic analysis also highlighted that EZH2 mutations were most significantly enriched in MHC-II-negative as well as MHC-I-negative GCB-DLBCL cases (both, p 〈 0.001). Indeed, 77% of EZH2 mutated cases demonstrated loss of either MHC-I and/or MHC-II expression on the tumor cells. Notably, we found significantly lower MHC-I and MHC-II expression in high-grade lymphomas of EZH2 mutant Vav-BCL2 transgenic mice compared to EZH2 wildtype control tumors. Furthermore, of potential clinical relevance, in-vitro EZH2 inhibition significantly restored MHC-I and MHC-II gene expression as well as protein expression in EZH2-mutated human DLBCL cells, but not EZH2 wild type tumor cells. Conclusion: Our findings provide important implications for understanding the cancer biology underlying acquired loss of MHC expression. The restoration of MHC expression by EZH2 inhibitors suggests a novel approach of epigenetically enhancing tumor recognition and eradication in combination with immune therapies. Disclosures Sehn: Abbvie: Consultancy, Honoraria; Roche/Genentech: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria. Connors:Roche Canada: Research Funding; Takeda: Research Funding; Merck: Research Funding; F Hoffmann-La Roche: Research Funding; Cephalon: Research Funding; Seattle Genetics: Honoraria, Research Funding; Amgen: Research Funding; Bayer Healthcare: Research Funding; Bristol Myers-Squibb: Research Funding; Lilly: Research Funding; NanoString Technologies: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Janssen: Research Funding; Genentech: Research Funding. Gascoyne:NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies. Scott:Roche: Research Funding; Janssen: Research Funding; NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Celgene: Consultancy, Honoraria. Steidl:Juno Therapeutics: Consultancy; Roche: Consultancy; Seattle Genetics: Consultancy; Nanostring: Patents & Royalties: patent holding; Bristol-Myers Squibb: Research Funding; Tioma: Research Funding.

Abstract: A significant proportion of diffuse large B-cell lymphoma (DLBCL) patients treated with immunochemotherapy containing rituximab (R-CHOP) exhibit either primary or acquired treatment resistance. The advancement of therapeutics in the relapse setting has likely been encumbered by our limited understanding of the molecular features that underlie resistance to R-CHOP. Unfortunately, our knowledge of DLBCL genetics is mostly limited to analyses conducted on diagnostic tissue biopsies, which have not been exposed to the selective pressures imposed by therapy. Identifying genetic alterations that contribute to treatment resistance may reveal additional treatment options and lead to biomarkers allowing patients to be paired with appropriate treatments. Genetic subgroups are gaining popularity as a new strategy to implement precision medicine in DLBCL (1). The relevance of these and other biomarkers in the relapse setting remains unclear due to limited genetic exploration of relapsed and refractory DLBCL (rrDLBCL). Progress has been limited, in part, by the requirement of tissue biopsies collected after relapse. It is well established that quantitative genomic techniques such as digital PCR and targeted sequencing can be used to determine the proportion of tumor DNA in plasma from lymphoma patients (2). With a sufficiently broad panel, sequencing affords additional opportunities including the ability to identify subclonal structure and population dynamics over time. This presentation will discuss our recent analysis of a large collection of ctDNA primarily comprising DLBCL patients on various clinical trials (3). Targeted sequencing of these samples and comparison to exome data from a meta-cohort of previously characterized untreated DLBCL biopsies revealed six genes significantly enriched for mutations upon relapse. We found both TP53 and KMT2D were mutated in the majority of rrDLBCLs, and these mutations persisted in the dominant clone following relapse, suggesting a role in primary treatment resistance. By inferring subclonal dynamics, we observed recurrent patterns of clonal expansion and contraction following rituximab-based therapy, with MS4A1 mutations representing the only example of consistent clonal expansion. MS4A1 missense mutations within the transmembrane domains led to loss of CD20 expression in vitro, and patient tumors harboring these mutations lacked CD20 protein expression. Our analysis nominates TP53 and KMT2D mutation status as novel prognostic factors that may facilitate the identification of high-risk patients prior to therapy. Moreover, we have demonstrated the potential to identify tumors with loss of CD20 surface expression stemming from MS4A1 mutations. Implementation of noninvasive assays to detect such features of acquired treatment resistance may allow timely transition to more effective treatment regimens. In certain scenarios whole-exome sequencing (WES) or whole-genome sequencing (WGS) can be successfully applied to ctDNA, thereby allowing the identification of mutations, structural variation, and copy number changes. Low-pass sequencing of shotgun libraries can also be used to ascertain course estimates of ctDNA levels as well as the copy number landscape (4). Given the importance of copy number and structural alterations in the inference of genetic subgroups, these methods may allow the exploration of these groups and their stability over time. Through a series of illustrative examples, this presentation will explore the benefits of each of these techniques in the study of tumor evolution and acquired treatment resistance in DLBCL. References: 1. Morin RD, Scott DW. DLBCL subclassification: Divide and conquer? Blood 2020;135:1722–4. 2. Rossi D et al. The development of liquid biopsy for research and clinical practice in lymphomas: Report of the 15-ICML workshop on ctDNA. Hematol Oncol 2020;38:34–7. 3. Rushton CK et al. Genetic and evolutionary patterns of treatment resistance in relapsed B-cell lymphoma. Blood Adv 2020;4:2886–98. 4. Adalsteinsson VA et al. Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors. Nat Commun 2017;8:1324. Citation Format: Nicole Thomas, Laura K. Hilton, Neil Michaud, Kevin Bushell, Ryan Rys, Michael Jain, Lois Shepherd, Marco A. Marra, John Kuruvilla, Michael Crump, Koren Mann, Sarit Assouline, Christian Steidl, Mark S. Cragg, David W. Scott, Nathalie Johnson, Ryan D. Morin, Christopher K. Rushton, Sarah E. Arthur, Miguel Alcaide, Matthew Cheung, Aixiang Jiang, Krysta M. Coyle, Kirstie L. S. Cleary. Detecting and quantifying mutations associated with treatment resistance in aggressive lymphomas using ctDNA [abstract]. In: Proceedings of the AACR Virtual Meeting: Advances in Malignant Lymphoma; 2020 Aug 17-19. Philadelphia (PA): AACR; Blood Cancer Discov 2020;1(3_Suppl):Abstract nr IA42.

Abstract: Introduction Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma and is characterized by its genetic and clinical heterogeneity. Patients can develop DLBCL de novo or as a transformation from other lymphoid malignancies, most commonly follicular lymphoma. For patients with relapsed/refractory DLBCL (rrDLBCL), prognosis is extremely poor with 2-year overall survival of 20-40%. While numerous treatments are under investigation to improve patient outcomes, the success of these treatments has been limited as the genetic mechanisms underpinning treatment resistance are largely unknown. Identifying genomic alterations which contribute to relapse may improve salvage therapy for patients with rrDLBCL or allow patients to be stratified prior to frontline treatment. Methods To identify genomic alterations which contribute to R-CHOP resistance, we previously collected samples from patients enrolled in four clinical trials exploring candidate salvage therapies for patients with rrDLBCL as well as a retrospective rrDLBCL cohort, totalling 193 cases (133 de-novo DLBCL, 60 transformed). Plasma samples were collected from each patient upon relapse along with diagnostic tissue biopsies where available. A combination of exome sequencing and target-panel sequencing of lymphoma associated genes was performed on circulating tumour DNA and tissue biopsies (if available). Mutations implicated in R-CHOP resistance were identified through two complimentary strategies. First, the mutation frequency of recurrently mutated genes across de novo rrDLBCL samples was compared to a cohort of unrelated diagnostic DLBCL cases (n=1691) to identify genes enriched for mutations. Second, the genomic landscape and tumor clonal structure was compared prior to and following R-CHOP to identify mutations in each patient that underwent clonal expansion following therapy. Anti-CD20 antibody binding affinity of MS4A1 mutants was evaluated using flow cytometry on transfected CHO-S cells. Results We have identified five genes enriched for mutations in our rrDLBCL cohort relative to diagnostic DLBCL: KMT2D (Mutated in 49%, Q=0.0385), TP53 (47%, Q=1.07x10-9), FOXO1 (11%, Q=0.0727), NFKBIE (11%, Q=0.0385), and MS4A1 (8%, Q=0.0522). Consistent with its characterization as a poor prognostic marker, mutations in TP53 were typically present at diagnosis and remained stable following R-CHOP therapy for both de novo and transformed DLBCL (23/27 cases, 85%). Recurrent mutations affecting Arg248 of TP53 (6.8%, Q=0.0413) were also clonally stable and have previously been associated with poor overall survival across several cancer types. The histone methyltransferase KMT2D is dominated by nonsense and frameshift mutations which were stable or underwent clonal expansion following R-CHOP (17/19, 89%). Recurrent missense mutations in MS4A1 targeted the small loop and adjacent transmembrane domains of CD20, including several patients with a Tyr86 mutation. Transfected cells carrying Tyr86Cys or Leu66Arg mutations were not bound by rituximab or other anti-CD20 antibodies including obinituzumab and ofatumumab. Subclonal populations containing MS4A1 mutations underwent clonal expansion (6 cases) or were stable (1 case) following treatment, including one case with multiple MS4A1 mutations in distinct subclonal populations which both underwent clonal expansion. In another unique case, a series of ctDNA samples were available prior to and following R-CHOP and salvage therapy, where we again observed convergent evolution of two mutually exclusive clonal subpopulations containing MS4A1 mutations. The first subpopulation underwent clonal expansion following frontline therapy but was extinguished following salvage therapy, while the other subpopulation underwent clonal expansion following salvage therapy and harboured a transmembrane domain mutation. Conclusion Mutations in TP53 and truncating mutations in KMT2D are generally present prior to treatment and will be investigated as biomarkers of treatment failure. Additional mutations are not always present at diagnosis, but their emergence can be detected in ctDNA and relapsed tissue, specifically mutations in MS4A1. As mutations in MS4A1 attenuate rituximab binding and are recurrently associated with clonal expansion, they likely impart a selective advantage and lead to resistance against anti-CD20 antibodies. Disclosures Michaud: Epizyme: Employment. Daigle:Epizyme: Employment. Jain:Kite/Gilead: Consultancy. Kuruvilla:Roche: Honoraria; Astra Zeneca: Honoraria; Novartis: Honoraria; Merck: Honoraria; Karyopharm: Honoraria; Gilead: Honoraria; Celgene: Honoraria; BMS: Honoraria; Amgen: Honoraria; Seattle Genetics: Consultancy; Roche: Consultancy; Merck: Consultancy; Karyopharm: Consultancy; Gilead: Consultancy; Janssen: Research Funding; Roche: Research Funding; BMS: Consultancy; Abbvie: Consultancy; Seattle Genetics: Honoraria; Janssen: Honoraria. Assouline:Abbvie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria, Speakers Bureau. Scott:NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding; Celgene: Consultancy; Roche/Genentech: Research Funding; Janssen: Consultancy, Research Funding. Johnson:BD Biosciences: Other: Provided a significant proportion of the antibodies used in this project free of cost.; Merck: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Abbvie: Consultancy, Employment, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Employment, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel fees, gifts, and others, Research Funding; Seattle Genetics: Honoraria; Lundbeck: Employment, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel fees, gifts, and others, Research Funding.