Abstract: Although chronic lymphocytic leukemia (CLL) has been consistently at the forefront of genomic discovery, complete characterization of its genomic landscape has been limited by sample size and cohort diversity. To address this challenge, we assembled and generated new genomic data from CLL samples from ~1100 patients ('CLL-1100'). In total, we analyzed 984 whole-exome sequences (WES), 177 whole-genome sequences (WGS), RNA-sequencing of 717 cases, and 758 methylome profiles. With our large dataset, we had increased sensitivity to detect candidate drivers even with frequency less than 1%. By applying MutSig2CV to the WES data, we identified 89 putative cancer driver genes (q & lt;0.1), 46 of which were novel. New candidate driver genes highlighted cellular pathways including metabolism (e.g. GPS2, CHKB, CD36) and protein synthesis/stability (e.g. RPS16, EEF1A1,USP8), thus expanding our knowledge of the processes contributing to CLL leukemogenesis. Analysis of somatic copy number alterations (CNAs) using GISTIC2 confirmed both high frequency and rarely reported arm-level events, as well as identified 6 novel focal amplifications and 54 deletions (35 new). Many of these genomic regions primarily contained known CLL drivers but also novel drivers found based on somatic single nucleotide variants (e.g. DDX5), providing further evidence that these likely contribute to pathogenesis. Thus, by approximately doubling the previously reported number of driver genes in CLL, we are able to assign a putative driving event to & gt;92% of CLL samples within the cohort. The gain in power was most evident in our characterization of the two major molecular subtypes of CLL, those with mutated (M-CLL) or unmutated (U-CLL) IGHV. Separate WES analyses of 513 M-CLLs and 459 U-CLLs revealed numerous differences between these two subtypes: (i) Mutation analysis revealed 24 and 59 candidate driver genes in M-CLL and U-CLL, respectively (q & lt;0.1). Only a minority of genes were significant in both subgroups (n=13; e.g. TP53, SF3B1, NOTCH1), while most were significant in either M-CLL (n=11; e.g. MYD88, KLHL6, ITPKB) or U-CLL (n=46; e.g. XPO1, BCOR, KRAS). Moreover, IGHV subtype-specific analyses enabled further sensitivity to identify 13 novel putative drivers that were not identified in the pan-CLL analysis (e.g. DIS3 in M-CLL; CHKA in U-CLL); (ii) We found 37 and 46 putative focal CNA drivers specific to M-CLL and U-CLL; (iii) By evaluating mutation clustering in 3-D protein structures (using CLUMPS), we identified additional drivers enriched in M-CLL (e.g. DICER1) or U-CLL (e.g. RPS23, RAF1, MAP2K2) (q & lt;0.1); and finally (iv) inference of timing and order of mutation acquisition (by PhylogicNDT) also revealed distinct evolutionary trajectories between subtypes. Altogether, these results highlight the divergent genomic landscape of the IGHV subtypes. To further understand disease biology and to develop improved prognostic models for this heterogeneous disease, we performed transcriptomic analysis of 610 treatment-naive CLLs after correction for known and inferred covariates (e.g. PEER factors). We identified 8 expression clusters (ECs) that represent subgroups of U-CLL (n=2), M-CLL (n=5) or an intermediate methylation epigenetic subtype (n=1). The ECs were distinguishable based on association (q & lt;0.1) with genomic drivers (e.g. tri(12), SF3B1, XPO1), biological processes (e.g. B-cell differentiation, TNF- 𝜶 signaling, oxphos, migration, metabolism) and EC-defining marker genes (e.g. LPL, CTLA4, HCK, BCL7A, TOX2). Multivariable analysis including clinical features and IGHV subtype, revealed distinct outcomes, demonstrating their prognostic potential (OS p=0.013). Of note, ~10% of M-CLLs had U-CLL-like expression profiles and vice-versa. The known difference in clinical outcome between the IGHV subtypes was not observed within these non-canonical cases (OS log-rank p & gt;0.05; p & lt;0.01 for reduced OS difference in comparison to canonical M-CLL vs. U-CLL). Finally, we used machine-learning to robustly classify new samples into these ECs to demonstrate the potential for future clinical utility. Altogether, the CLL-1100 cohort facilitates novel genomic discovery with multiomic insights and cross-validation, showing the distinct molecular spectrum of a diverse patient population. This sets the stage for the development of comprehensive and more precise genome-based prognostic tools. Disclosures Nadeu: Janssen: Honoraria. Tausch:AbbVie: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Research Funding. Wiestner:Pharmacyclics LLC, an AbbVie Company, Acerta, Merck, Nurix, Verastem, and Genmab: Research Funding; NIH: Patents & Royalties: NIH. Burger:AstraZeneca: Consultancy; Gilead Sciences: Consultancy, Research Funding; Janssen Pharmaceuticals: Consultancy, Speakers Bureau; Beigene: Research Funding, Speakers Bureau; Pharmacyclics, an AbbVie company: Consultancy, Research Funding, Speakers Bureau; TG Therapeutics: Research Funding, Speakers Bureau. Kipps:Ascerta/AstraZeneca, Celgene, Genentech/F. Hoffmann-La Roche, Gilead, Janssen, Loxo Oncology, Octernal Therapeutics, Pharmacyclics/AbbVie, TG Therapeutics, VelosBio, and Verastem: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics/ AbbVie, Breast Cancer Research Foundation, MD Anderson Cancer Center, Oncternal Therapeutics, Inc., Specialized Center of Research (SCOR) - The Leukemia and Lymphoma Society (LLS), California Institute for Regenerative Medicine (CIRM): Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Oncternal Therapeutics, Inc.: Other: Cirmtuzumab was developed by Thomas J. Kipps in the Thomas J. Kipps laboratory and licensed by the University of California to Oncternal Therapeutics, Inc., which provided stock options and research funding to the Thomas J. Kipps laboratory, Research Funding; Genentech/Roche: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; VelosBio: Research Funding; Celgene: Honoraria, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Brown:Gilead, Loxo, Sun, Verastem: Research Funding; Abbvie, Acerta, AstraZeneca, Beigene, Invectys, Juno/Celgene, Kite, Morphosys, Novartis, Octapharma, Pharmacyclics, Sunesis, TG Therapeutics, Verastem: Consultancy; Janssen, Teva: Speakers Bureau. Neuberg:Celgene: Research Funding; Pharmacyclics: Research Funding; Madrigak Pharmaceuticals: Current equity holder in publicly-traded company. Stilgenbauer:Pharmacyclics: Consultancy, Honoraria, Other, Research Funding; Novartis: Consultancy, Honoraria, Other, Research Funding; Mundipharma: Consultancy, Honoraria, Other, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Other: travel support, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Other: travel support, Research Funding; Genzyme: Consultancy, Honoraria, Other: travel support, Research Funding; Genentech: Consultancy, Honoraria, Other: travel support, Research Funding; F. Hoffmann-LaRoche: Consultancy, Honoraria, Other: travel support, Research Funding; Celgene: Consultancy, Honoraria, Other: travel support, Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Other: travel support, Research Funding; Amgen: Consultancy, Honoraria, Other: travel support, Research Funding; AbbVie: Consultancy, Honoraria, Other: travel support, Research Funding. Wu:BionTech: Current equity holder in publicly-traded company; Pharmacyclics: Research Funding. Campo:NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.. Getz:Broad Institute: Patents & Royalties: MuTect, ABSOLUTE, MutSig, MSMuTect, MSMutSig, POLYSOLVER and TensorQTL; Pharmacyclics: Research Funding; IBM: Research Funding; Scorpion Therapeutics: Consultancy, Current equity holder in publicly-traded company, Other: Founder.

Abstract: Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous disease characterized by multiple low-frequency alterations including somatic mutations, copy number alterations (CNAs) and chromosomal rearrangements. We sought to identify previously unrecognized low-frequency genetic events, integrate recurrent alterations into comprehensive signatures and associate these signatures with clinical parameters. For these reasons, our multi-institutional international group assembled a cohort of 304 primary DLBCLs from newly diagnosed patients, 87% of whom were uniformly treated with state-of-the-art therapy (rituximab-containing CHOP regimen) and had long term followup. Tumors were subjected to whole exome sequencing with an extended bait set that included custom probes designed to capture recurrent chromosomal rearrangements. In this cohort, 47% of samples had available transcriptional profiling and assignment to associated disease subtypes. Analytical pipelines developed at the Broad Institute were used to detect mutations (MuTect), CNAs (Recapseq+Allelic Capseq) and chromosomal rearrangements (dRanger+Breakpointer) and assess clonality (Absolute). To analyze formalin-fixed paraffin-embedded tumors without paired normals we developed a method which utilized 8334 unrelated normal samples to stringently filter recurrent germline events and artifacts. Significant mutational drivers were identified using the MutSig2CV algorithm and recurrent CNAs were assessed with GISTIC2.0. In addition, we utilized a recently developed algorithm, CLUMPS2, to prioritize somatic mutations which cluster in 3-dimensional protein structure. With this approach, we identified 〉 90 recurrently mutated genes, 34 focal amplifications and 41 focal deletions, 20 arm-level events and 〉 200 chromosomal rearrangements in the DLBCL series. Of note, 33% of the mutational drivers were also perturbed by chromosomal rearrangements or CNAs, underscoring the importance of a comprehensive genetic analysis. In the large DLBCL series, we identified several previously unrecognized but potentially targetable alterations including mutations in NOTCH2 (8%) and TET2 (5%). The majority of identified chromosomal rearrangements involved translocations of potent regulatory regions to intact gene coding sequences. The most frequently rearrangements involved Ig regulatory elements which were translocated to BCL2, MYC, BCL6 and several additional genes with known roles in germinal center B-cell biology. After identifying recurrent somatic mutations, CNAs and chromosomal rearrangements, we performed hierarchical clustering and identified subsets of DLBCLs with comprehensive signatures comprised of specific alterations. A large subset of tumors shared recurrent alterations previously associated with follicular lymphoma including mutations of chromatin modifiers such as CREBBP, MLL2, and EZH2 in association with alterations of TNFRSF14 and GNA13 and translocations of BCL2. This cluster was enriched in GCB-type DLBCLs and contained a subset with select genetic alterations associated with an unfavorable outcome. An additional cohort of tumors was characterized by alterations perturbing B-cell differentiation including recurrent BCL6 translocations or alterations of PRDM1. A subset of these DLBCLs had alterations of NOTCH2 and additional pathway components or mutations of MYD88 in association with TNFAIP3, CD70 and EBF1, a master regulator of B-cell differentiation. An additional group of DLBCLs exhibited frequent MYD88 mutations in association with alterations of CD79B, PIM1, TBL1XR1 and ETV6 and BCL2 copy gain; these tumors were highly enriched for ABC-type DLBCLs. This coordinate signature and additional alterations of p53 pathway components were associated with outcome. We explored bases for the identified genetic alterations in DLBCL by performing an in silico mutational signature analysis. The most frequent mutational signatures were those of spontaneous deamination (aging) and AID with rare cases of microsatellite instability. We also assessed the clonality of identified genetic features to define cancer cell fraction and establish the timing of specific genetic events. The comprehensive genetic signatures of clinically annotated DLBCLs provide new insights regarding approaches to targeted therapy. Disclosures Link: Kite Pharma: Research Funding; Genentech: Consultancy, Research Funding. Rodig:Perkin Elmer: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding. Pfreundschuh:Boehringer Ingelheim, Celegene, Roche, Spectrum: Other: Advisory board; Roche: Honoraria; Amgen, Roche, Spectrum: Research Funding. Shipp:Gilead: Consultancy; Sanofi: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees; Bayer: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract: This article reports metabolic consequences of JAK2-mutant myeloproliferative neoplasms (MPNs) with a therapeutic translational impact: expression of mutant JAK2 induces abnormal metabolic activity of MPN cells, resulting in hypoglycemia, adipose tissue atrophy, and early mortality.