Fitzgibbon, Jude

SummaryDespite the clinical and molecular heterogeneity of follicular lymphoma (FL), there remains a lack of biomarker‐directed therapeutic approaches in routine clinical practice, with the notable exception of the EZH2 inhibitor tazemetostat in EZH2‐mutant FL. Here we examined whether gene mutation status predicts response to clinical mTOR inhibitors (mTORi) in FL, by performing targeted mutational profiling of biopsies from 21 relapsed/refractory FL patients treated with mTORi everolimus or temsirolimus within clinical trials. We observed an enrichment of mutations within the catalytic histone acetyltransferase (HAT) domain of CREBBP in mTORi‐responders, and describe distinct transcriptional characteristics and co‐occurring mutations of FL harbouring these mutations; reinforcing the growing appreciation of CREBBPHAT mutation as a key biological determinant and its promise as a therapeutic biomarker in FL.

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 Despite the effectiveness of immuno-chemotherapy, 40% of patients with diffuse large B-cell lymphoma (DLBCL) experience relapse or refractory disease. Longitudinal studies have previously focused on the mutational landscape of relapse but fell short of providing a consistent relapse-specific genetic signature. In our study, we have focused attention on the changes in GEP accompanying DLBCL relapse using archival paired diagnostic/relapse specimens from 38 de novo patients with DLBCL. COO remained stable from diagnosis to relapse in 80% of patients, with only a single patient showing COO switching from activated B-cell–like (ABC) to germinal center B-cell–like (GCB). Analysis of the transcriptomic changes that occur following relapse suggest ABC and GCB relapses are mediated via different mechanisms. We developed a 30-gene discriminator for ABC–DLBCLs derived from relapse-associated genes that defined clinically distinct high- and low-risk subgroups in ABC–DLBCLs at diagnosis in datasets comprising both population-based and clinical trial cohorts. This signature also identified a population of <60-year–old patients with superior PFS and OS treated with ibrutinib–R-CHOP as part of the PHOENIX trial. Altogether this new signature adds to the existing toolkit of putative genetic predictors now available in DLBCL that can be readily assessed as part of prospective clinical trials.

Background: Although diffuse large B cell lymphoma (DLBCL) can be cured using immuno-chemotherapy, 40% of patients experience relapse or refractory disease. Large-scale profiling studies have mainly focused on DLBCL at diagnosis, resolving different outcome groups based on gene expression (e.g. cell-of-origin (COO) or molecular high grade), MYC/BCL2 translocations (double-hit lymphoma) or gene mutations and copy number aberrations (Schmitz et al, NEJM 2018; Chapuy et al, NatureMedicine 2018). In comparison, longitudinal studies have been hindered by the limited availability of sequential biopsy samples. To date, the relapse-specific gene mutations identified are limited and inconsistent across studies. In our study, we have focussed attention on the changes in gene expression profile (GEP) accompanying DLBCL relapse. Methods: We retrospectively collected archival paired diagnostic/relapse formalin fixed paraffin embedded tumor biopsies from 38 de novo DLBCL patients collected from multiple UK sites treated with rituximab-based immuno-chemotherapy, where partial or complete remission was reported following treatment. COO classification was performed by the Lymph2Cx assay on NanoString to distinguish activated B-cell-like (ABC) and germinal center B-cell-like (GCB) subtypes. The Ion AmpliSeq™ Transcriptome Human Gene Expression Kit was used to measure the expression levels of > 20,000 genes on the paired samples. Results: COO remained stable from diagnosis to relapse in 17 ABC-ABC pairs, 11 GCB-GCB pairs and 4 unclassified (UNC)-UNC pairs. Frank COO switching was observed in 6 cases (1 ABC-GCB, 2 ABC-UNC, 2 GCB-UNC, 1 UNC-ABC). Pairs with stable COO were taken forward for further analysis. Gene expression analysis using the limma R package identified 163 and 136 genes as differentially expressed (DE) (p <= 0.01 and absolute log2FC > 1) between the diagnostic and relapse biopsies in ABC and GCB tumors respectively, with only a one gene overlap. Gene Set Enrichment Analysis further suggested that ABC and GCB relapses are mediated via different mechanisms, with tumor growth and proliferation signatures enriched in ABC relapses, whilst adaptive immunity-related signatures accompanied GCB relapses. Next, we aimed to utilise our relapse-specific genes to identify outcome predictors at diagnosis using publicly available GEP datasets. In order to increase our discovery power and accuracy, a larger set of DE genes from the paired differential analysis (796 genes in ABC pairs and 387 from GCB pairs) were selected (p <= 0.05) and subsequently used in a training cohort (GEP from Reddy et al, Cell 2017). The Prediction Analysis for Microarrays R (PAMR) algorithm identified a 30-gene signature within DE genes from ABC pairs (Fig1.A), capable of separating the 249 ABC cases into 136 low and 113 high-risk cases with significantly inferior overall survival (Hazard Ratio (HR)=1.89, log-rank p=0.0017, measure of goodness-of-fit C-index=0.71; Fig1.B). No equivalent signature was found in the GCB cases using this approach. The prognostic significance of this 30-gene discriminator was successfully validated using a linear predictor in two independent GEP datasets: 1) a population-based cohort (Lenz et al, NEJM 2008) with 93 R-CHOP-treated ABC cases identifying 47 low and 46 high-risk cases (HR=1.92, p=0.046, C-index=0.77; Fig1.C) and 2) a clinical trial dataset (REMoDL-B, Davies et al, Lancet Oncol 2019) with 255 ABC cases identifying 110 low and 145 high-risk ABC cases (HR=1.95, p=0.0051, C-index=0.70; Fig1.D). Conclusions: Here we describe a 30-gene discriminator in ABC-DLBCL, derived from genes differentially expressed between diagnosis and relapse, that allowed the definition of clinically distinct high and low risk subgroups in ABC-DLBCLs at diagnosis. The clinical translation of such a tool may be useful to guide therapy for this unfavourable subgroup of ABC-DLBCLs. Validation of this signature is currently underway in additional datasets and further study is required to understand the contribution of these genes in DLBCL pathology. Disclosures Korfi: Roche: Consultancy. Burton:Celgene: Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees. Rule:TG Therapeutics: Consultancy, Honoraria; Napp: Consultancy; Kite: Consultancy; Pharmacyclics: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Astra-Zeneca: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Crosbie:Janssen: Honoraria. Scott:Celgene: Consultancy; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding; Roche/Genentech: Research Funding. Rimsza:NanoSting: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution]. Davies:Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding; Bayer: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Research Funding; Karyopharma: Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Research Funding; Acerta Pharma: Honoraria, Research Funding; ADCT Therapeutics: Honoraria, Research Funding; BioInvent: Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; MorphoSys AG: Honoraria, Membership on an entity's Board of Directors or advisory committees. Gribben:Abbvie: Consultancy, Honoraria, Research Funding; Acerta/Astra Zeneca: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Okosun:Gilead Sciences: Honoraria, Research Funding. Johnson:Epizyme: Honoraria, Research Funding; Novartis: Honoraria; Kite: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Boehringer Ingelheim: Honoraria; Takeda: Honoraria; Genmab: Honoraria; Celgene: Honoraria; Incyte: Honoraria. Fitzgibbon:Epizyme: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Speakers Bureau.

Abstract Background: It has been known for approximately 19 years that germline mutations in RUNX1, lead to familial platelet disorder with predisposition to myeloid malignancy (FPD-MM, OMIM 601399). Since that time researchers have identified a broad range of different RUNX1 mutations, in over 100 families. In large families, the diagnosis of malignancy shows variable penetrance among family members with the same mutation; some carriers of RUNX1 mutations do not develop malignancy. The causes of this heterogeneity are currently not known, complicating counselling and risk analysis for individual carriers. Recent advances in genetic sequencing technology applied by many FPD-MM research groups around the world have highlighted their value in understanding the somatic genetic changes that are associated with development of malignancies in germline RUNX1 mutation carriers. Collectively this information could lead to powerful insights essential for more precise risk assessment, monitoring, and therapeutic intervention. Specifically, a growing catalogue of somatic mutations associated with germline RUNX1 malignancy offers the opportunity for informed monitoring of asymptomatic RUNX1 carriers for additional high-risk somatic mutations, in turn providing the possibility for early therapeutic intervention to arrest the leukemic process. The challenge in advancing these goals for FPD-MM is the relative rarity of the disorder in individual populations. Global data sharing in a highly interactive FPD-MM research community offers a solution to this problem that benefits all patients world-wide. Aims: To create a global RUNX1 network through identifying and contacting researchers and clinicians with known and novel germline RUNX1 families, seeking their collaboration to share genomics data. To create a RUNX1.db portal to collectively house and analyse genomics data from germline RUNX1 carriers, with associated phenotype and clinical information, such that researchers have an ongoing means by which to combine their data with those generated by other groups around the world. Methods: RUNX1 network : Through existing collaborative networks, a systematic review of the literature, and referrals from initial contacts, we have identified a global network of researchers managing FPD-MM cases and families. RUNX1.db: We have adapted a custom-built variant analysis platform, VariantGrid, that is a visual web application and database designed to help scientists manage and analyse DNA variants that can be used to aggregate and analyse multiple datasets. Results: Preliminary analysis of aggregated data from the literature suggests there are features of germline RUNX1 syndrome that can be ascertained. These include frequent somatic mutation of RUNX1 in malignancy development, as well as mutations in genes associated with clonal hematopoiesis that may precede development of overt leukemia. This analysis also suggests that different types of germline RUNX1 mutations may be associated with different combinations of somatic mutations in the tumour. To further this analysis, we have identified over 70 groups internationally that either manage RUNX1 families or have identified potential germline carriers through genomics initiatives. This represents a large and growing resource for both scientific studies and clinical programs to benefit individuals with FPD-MM. Many of these groups have generated NGS data sets from patient samples which will be available for analysis through this portal. Further details and activities of the network, and results from the genomics aggregation database will be presented. Conclusion: We have created a global RUNX1 network, aggregated their data, and generated a RUNX1.db genomics portal for the continuous curation of genomics data from germline RUNX1 carriers. A preliminary analysis has already identified specific features of germline RUNX1 mutated malignancies that have clinical importance. Ongoing scientific and clinical studies through the RUNX1 network will enhance the power of aggregated data analysis, with RUNX1.db providing a central link, driving new insights that benefit patients. Disclosures Natsoulis: Imago BioSciences, Inc.: Consultancy, Equity Ownership. Guzman:Cellectis: Research Funding. DiNardo:Bayer: Honoraria; Karyopharm: Honoraria; Celgene: Honoraria; Agios: Consultancy; Medimmune: Honoraria; Abbvie: Honoraria. Borate:Novartis: Consultancy; Agios: Consultancy. Wei:Amgen: Honoraria, Other: Advisory committee, Research Funding; Pfizer: Honoraria, Other: Advisory committee; Celgene: Honoraria, Other: Advisory committee, Research Funding; Abbvie: Honoraria, Other: Advisory board, Research Funding, Speakers Bureau; Servier: Consultancy, Honoraria, Other: Advisory committee, Research Funding; Novartis: Honoraria, Other: Advisory committee, Research Funding, Speakers Bureau. Dokal:MRC, Bloodwise, Telomerase Activator Sciences: Research Funding; The Gary Woodward Dyskeratosis Congenita Trust: Membership on an entity's Board of Directors or advisory committees; Action Medical Research, European School of Haematology: Membership on an entity's Board of Directors or advisory committees; Barts and The London School of Medicine and Dentistry, Queen Mary University of London,: Employment, Research Funding; Telomerase Activator Sciences: Research Funding; Barts and The London, Queen Mary University of London: Employment; Gary Woodward Dyskeratois Congenita Trust: Membership on an entity's Board of Directors or advisory committees. Hiwase:Novartis: Research Funding; Celgene: Research Funding. Branford:Cepheid: Honoraria; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Qiagen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Kramer:Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Bayer: Research Funding; Daiichi Sankyo: Consultancy. Owen:Merck: Honoraria; Teva: Honoraria; AbbVie: Research Funding; Pharmacyclics: Research Funding; Janssen: Honoraria, Research Funding; Celgene: Research Funding; AstraZeneca: Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Honoraria, Research Funding. Fitzgibbon:Epizyme: Consultancy, Research Funding; Gilead: Consultancy. Rienhoff:Imago BioSciences, Inc.: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Kurokawa:Astellas Pharma: Research Funding; Sumitomo Dainippon Pharma: Research Funding; Nippon Sinyaku: Honoraria, Research Funding; Kyowa Hakko Kirin: Honoraria, Research Funding; Eizai: Research Funding; MSD: Honoraria, Research Funding; Ono Pharmaceutical: Honoraria, Research Funding; Pfizer: Research Funding; Takeda Pharmaceutical: Research Funding; Otsuka Pharmaceutical: Research Funding; Teijin Pharma: Research Funding; Chugai Pharmaceutical: Research Funding.

Background:With an expanding array of novel treatment options in follicular lymphoma (FL), we largely lack effective biomarkers to predict response in this molecularly heterogeneous disease. Activating mutations focused on components of the nutrient‐sensing arm of the mTORC1 pathway (RRAGC, ATP6V1B2, ATP6AP1), are particularly enriched in FL, occurring in ∼30% of cases. Meanwhile, clinical mTOR inhibitors (mTORi) have shown some promise, with response rates of 50–60% in relapsed/refractory FL.Aims:We therefore sought to determine whether gene mutation status ‐ particularly in genes regulating the mTOR pathway – may represent biomarkers of mTORi‐response in FL.Methods:We retrospectively analyzed pre‐treatment tumor samples from relapsed/refractory FL patients treated on two phase II clinical trials with single agent mTOR inhibitors, everolimus (NCT00436618) or temsirolimus (NCT00290472), with well characterized clinical outcomes. In total, 21 patients had available biopsies, consisting of 15 everolimus‐ and 6 temsirolimus‐treated cases.Tumor DNA extracted from formalin fixed paraffin embedded (FFPE) tissue was subjected to targeted sequencing using a 22 gene panel comprising genes recurrently mutated in FL, and PI3K/AKT/mTOR pathway genes mutated in germinal center lymphomas. Libraries were prepared using capture‐based target enrichment (Nonacus), and sequenced on the NextSeq550 (Illumina) with a mean coverage depth of x700. A stringent bioinformatic pipeline was adopted with variants called with VarScan2, and a 10% variant allele frequency (VAF) threshold was employed to filter out sequencing artefacts due to the FFPE material. 100% (15/15) of a selection of variants were validated by Sanger sequencing. Staining for pS6 was undertaken on tissue slides to examine downstream mTOR activation by immunohistochemistry.Results:Overall response rate (CR and PR) was 48% (10/21). Mutational analysis showed no significant association between clinical response and mTORC1‐pathway mutations (mut) taken individually or collectively; although, absolute numbers of mutations in these genes were low, including RRAGC (responder: 0/10 mut vs non‐responder: 1/11 mut), ATP6AP1 (responder: 1/10 vs non‐responder: 1/11), and ATP6V1B2 (responder: 1/10 vs non‐responder 3/11). Notably, no difference in pS6 staining was seen between responders and non‐responders.However, we found mutations in the epigenetic regulator CREBBP to be enriched in the responder group (100% (10/10) responders vs 54.5% (6/11) non‐responders, p = 0.04). This effect was more pronounced when considering only mutations within the catalytic histone acetyltransferase (HAT) domain of CREBBP, with HAT mutations seen in 100% (10/10) responders, and 27.3% (3/11) non‐responders (p = 0.001).Summary/Conclusion:Mutations in the mTOR pathway did not predict for response to mTOR inhibition in our study. The enrichment of CREBBP mutations in responders, and particularly those affecting the catalytic HAT domain, points to CREBBP as a potential biomarker of response which warrants validation in trials of drugs modulating the PI3K/AKT/mTOR axis. More broadly our data may lend support to a distinct clinical and biological behavior of CREBBP HAT domain‐mutant disease that also warrants further evaluation. Taken together, our findings highlight the potential opportunities afforded by undertaking correlative studies, and underlines the need to incorporate prospective biomarker discovery into clinical trials in order to help focus future therapeutic strategies more rationally.