ALBERT

Description: Background: Diffuse large B-cell lymphoma (DLBCL) is the most common form of adult lymphoma. Although comprehensively investigated, it remains a prominently heterogeneous disease. The standard of care for DLBCL is a combination chemo-immunotherapy RCHOP regimen. The 3-year progression free survival (PFS) rate is 70%. Relapses normally occur within 2-3 years and treatment options for relapsed and refractory DLBCL are limited with only 10% of patients achieving a 3-year PFS. Global mRNA expression analysis has been used to further classify DLBCL into molecularly distinct subtypes (GCB and ABC) which display remarkably different outcomes to current therapeutics, with GCB having a better prognostic outcome. Multiple attempts at further restratification of DLBCL cases based on next generation sequencing have only confirmed the striking heterogeneity of the disease; providing little direction for clinical practices. Therefore, further analysis of DLBCL with the intent to stratify patients for clinical response is needed. We utilized whole exome sequencing to reveal alterations in the genome that are associated with relapse and chemotherapeutic resistance in DLBCL. Current literature has focused on DLBCL as an entity without stratification into relapsed/refractory and de novo DLBCL. In addition, published studies have had a clear focus on diagnostic sampling. By discovering and prioritizing somatic mutations associated with relapse and chemotherapeutic resistance, we aim to provide a novel analysis of the mutational heterogeneity of DLBCL to identify new biomarkers for improved stratification of patients for clinical treatment. Method: DLBCL samples from 37 cases (45 biopsies) were collected with normal matched blood (germline). Of these, 17 cases never relapsed (median observation time 3.9 yrs). Whereas, 20 cases relapsed from RCHOP or related therapy (median observation time 4.8 yrs). Of these, 15 biopsies were taken at diagnosis and 13 were taken at relapse including 8 cases with serial biopsies. We performed whole exome capture and paired-end sequencing using the Illumina HiSeq2000 platform. Reads of each sample were mapped with BWA-mem to the human reference genome (build b37 with an added decoy contig). Marking of duplicates was performed with Picard tools; GATK tools were used for two‐step local realignment and base‐quality recalibration. Somatic single nucleotide variant (SNV) detection was performed with MuTect and Strelka. Strelka alone was used for insertion/deletion (InDel) detection. Results: We achieved 288X mean coverage of targeted exonic regions in tumor samples and 125X in normal blood. After application of our bioinformatics pipeline, we identified 44,297 variants in the cohort. The mean mutational SNV burden was 944 and the mean InDel burden was 40 variants per case. In serial biopsies there was a higher mean mutational burden at relapse than diagnosis (1001 to 772, respectively). After filtering synonymous, UTR, non-coding, and low confidence variant calls, we identified 11,743 coding variants corresponding to 6,399 genes (Figure 1). In order to define potential recurrent driver mutations in DLBCL associated with relapse and survival, we applied the Oncodrive algorithm (IntOgen) to the total cohort and subgroups classified by relapse status, survival and subtype. We also applied the Oncocluster algorithm (IntOgen) to the total cohort to identify genes with significant hotspots and clustering which may suggest potential cancer driver mutations. Using a corrected q-value of

Description: In a retrospective cohort, seven patients with multiple myeloma carrying the BRAF V600E mutation had significantly shorter overall survival and higher prevalence of extramedullary disease than 251 BRAF wild type (wt) controls (Andrulis et al Cancer Discov 2013). Three case reports are in concordance with this view (Bohn et al and Sharman et al, Clin Lymphoma Myeloma Leuk, 2014). We conducted this study to further investigate the clinical and biological implications of this mutation in multiple myeloma. We used mutation-specific quantitative real-time PCR (qPCR) to screen biopsies from 209 myeloma patients, of which 185 were taken prior to first relapse. The BRAF V600E mutation was detected in 13 (6.2 %) of the patients. 10 of them also expressed the corresponding protein as evaluated by immunohistochemistry (IHC) using the BRAF V600E specific VE1 antibody, and 2 patients had simultaneous mutations in BRAF and NRAS/KRAS. RAS mutations are of particular interest because in vitro studies indicate that their presence may imply a paradoxical effect of BRAF inhibitors (Lohr et al Cancer Cell 2014). Whole exome sequencing (WES) was carried out in three BRAF V600E positive patients from whom we had stored purified myeloma cells. Among the top 11 recurrently mutated genes listed in Lohr et al (Cancer Cell 2014), we found mutations only in BRAF, NRAS, and KRAS. Clonal fraction of BRAF V600E mutated plasma cells as evaluated by IHC and WES varied from 4 to 100 %. There was agreement between detection methods in the patient with a dominating V600E mutated clone, but less so in the patients with small clones. Estimates of BRAF V600E clone size and RAS mutation analysis in 13 patients positive for BRAF V600E by qPCR Table 1 IHC (clone size, %) WES (clone size, %) Sanger sequencing NRAS / KRAS mutation 75-100 86 + negative 75-100 negative negative 75-100 + negative 50-75 + negative 50-75 + negative 25-50 negative negative 25-50 negative negative

Description: Introduction Multiple myeloma (MM) is a malignant plasma cell disorder of which the prognosis has significantly improved since the introduction of proteasome inhibitors (PIs) and immune modulatory drugs (IMiDs) in standard-of-care treatment protocols. Despite this progress, many patients still suffer from progressive disease, of which the underlying biological mechanisms are mainly unknown. To elucidate these, we have studied the genomic evolution of MM tumor samples in 29 patients before and after receiving a PI-based and/or IMiD-based treatment, using whole exome sequencing (WES) and mRNA sequencing (RNA-Seq). Methods Patient samples were selected from the Norwegian Biobank for Multiple Myeloma and the HOVON-87/NMSG-18 MM and EMN-02/HOVON-95 MM studies. Tumor DNA was isolated from CD138-positive MM cells with control DNA from peripheral blood samples. WES libraries were prepared using the SureSelectXTsample prep kit and the SureSelectXT Human All Exon V5 target 50 Mb kit (Agilent), followed by paired-end sequencing on a HiSeq2500 instrument (Illumina). Somatic, non-synonymous variants (SNSVs) were called using MuTect and Strelka. Copy number aberrations (CNAs) were estimated using Sequenza. RNA-Seq libraries were generated using the TruSeq® Stranded mRNA kit (Illumina).DESeq2 paired analysis was performed in R Studio to find differentially expressed genes. RNA-Seq expression data from diagnosis/relapse pairs from patients treated with a PI and/or IMiD were selected from the CoMMpass IA10 release database and used as validation cohort. Results We obtained 21 diagnosis/relapse pairs, as well as 8 relapse/relapse pairs, with a median time between samples of 21 months, respectively 16 months. In addition, for 3 of the patients, we had a 3rd sample included. We found a median of 54 SNSVs in our cohort, with an increase in mutational load from the first to the second sample (median 44 to 61). Three different patterns of tumor evolution were observed, confirming previous reports:stable evolution (29% of patients), where the tumor had no or minor changes;linear evolution (29% of patients), where there were acquired mutations and/or CNAs at relapse;differential clonal response (42% of patients), where there was a disappearance of certain mutations/CNAs at relapse and appearance of new ones, suggesting a shift in dominance of different clones. Of interest, of the 7 relapse-relapse tumor pairs that were included in the analysis, 5 were defined to have a differential clonal response, while the remaining 2 had linear evolution, suggesting that the tumors are more prone to genomic change later in the disease course.Tumors shifting their clonal dominance tended to select for a clone with more high-risk features later in the disease course, as illustrated by the appearance of a deletion of chromosome 17p, TP53 mutations and a gain of chromosome 1q. There was a shorter average time interval between sample 1 and 2 for those having a stable evolution pattern (average 12 months, range [5-16]), than those having a differential clonal response (19 months [5-70]), and the highest interval was in patients with linear evolution patters (29 months [15-50]). Tumors having a differential clonal response and linear evolution, showed more often a deeper treatment response (43% CR/nCR, 40% VGPR and 22% CR/nCR, 56% VGPR, respectively) compared to those with stable evolution patterns (14% VGPR), suggesting that tumors that respond well to treatment are more prone to evolve. RNA-Seq data showed a higher expression of genes involved in G2M checkpoint, E2F targets and mitotic spindle at relapse. In line with this, relapsed tumors were found to have an increased proliferation index (GEP; Zhan et al, Blood, 2006). This was confirmed in RNA-Seq data from 27 diagnosis-relapse samples from the CoMMpass dataset. Conclusion This study has performed a comprehensive genomic and transcriptomic analysis of the clonal evolution of MM tumors after treatment with PIs and IMIDs. Our data suggest that clones with high-risk factors and increased expression of genes involved in proliferation and cell cycle regulation are selected for under the pressure of these treatment regimens. The data also suggest that there is a relation between the pattern of genomic evolution and the obtained depth of response, which deserves further investigation. Disclosures Sonneveld: Janssen: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Karyopharm: Honoraria, Research Funding; BMS: Honoraria, Research Funding.

Description: Introduction: Follicular lymphoma (FL) is an indolent malignancy, characterized by multiple relapses during the disease course. Annually around 2-3% of patients experience transformation to aggressive disease (tFL), most commonly to diffuse large B-cell lymphoma (DLBCL). Both transformation and progression of disease within 2 years (POD24) are associated with poor prognosis, yet the molecular events underlying these processes are not well understood. The existence of common progenitor cells (CPCs) has been inferred from genetic analyses of longitudinal biopsies. Improved characterization of genetic alterations associated with CPCs in cases with transformation and POD24 may improve our understanding of disease progression, and reveal molecular markers for high-risk disease. Methods: We performed whole-exome sequencing of 97 serial tumor biopsies and matched normal samples purified from peripheral blood from 44 FL patients. An average sequencing coverage of 700X was achieved for both tumor and normal samples, which ensured high data quality and ability to detect SNVs and InDels using our bench-marked bioinformatics pipeline. SNP6.0 data was available for 93 sequenced tumors and used to infer allele-specific copy number alterations. Several computational tools were applied to identify potential cancer driver genes (MutSig2CV, 2020plus), mutational signatures (MutationalPatterns), and to study clonal evolution (PyClone, ClonEvol). Results: Twenty-two of the 44 FL patients experienced relapses without transformation (referred to as the nFL group), and 22 patients experienced transformation (the tFL group). Nineteen patients (including both groups) experienced POD24. Both transformation and POD24 were associated with inferior overall survival. The median non-synonymous mutational burden was 96 per biopsy (range 10-326). Pre-treatment FL biopsies from the tFL group had significantly higher mutational burden compared to the nFL group (p

Description: Introduction Relapses of diffuse large B-cell lymphoma typically occur within 2-3 years and only 10% of these patients reach a 3-year progression-free survival compared to 65% at diagnosis. Our ability to distinguish patients at risk for relapse remains based on clinical staging. We hypothesized that identifying genetic alterations in serial tumour biopsies at diagnosis and relapse would improve our ability to identify high-risk patients, make therapeutic selections and reveal molecular markers for chemo-immunotherapy resistant tumours. However, relatively few relapsed/refractory biopsies have been sequenced. A unique, clinically annotated, Nordic DLBCL cohort was used to identify significantly mutated genes, assess potential driver genes, comprehensively examine clonal evolution, and gauge the importance of clinical relapsed sampling. Methods To address the lack of information on the molecular foundations of relapsed/refractory DLBCL, we performed whole exome sequencing (WES) on 42 DLBCL cases, with 34% representing relapsed/refractory biopsies and 13 serially sample cases. Enriched with relapsed/refractory diffuse large B-cell lymphoma cases, we performed multiple computational analyses to identify significantly mutated genes (MutSig2CV), mutational signatures (NMF and DeConstructsSig), driver genes (IntOgen and CADD), clonal evolution architecture (SciClone and ClonEvol), druggable gene analysis (DGIdb), and HLA-inference and mutation calling (Polysolver). Results Clonal evolution analysis of 13 paired diagnostic and relapsed biopsies revealed that relapsed/refractory biopsies have remarkable similarities to diagnostic biopsies and often present with late divergent clonal evolution of the tumor. Mutational analysis of 18 serially sampled tumors determined that in the majority of cases druggable oncogenic variants do arise at relapse. In addition, time to relapse correlated with divergence of mutations from the diagnostic biopsy. In addition to being identified as a significantly mutated gene, mutations in HLA-A had an increased incidence in cases that ultimately relapsed. This result led to an in-depth investigation into the mutational prevalence, timing, impact on prognosis, and loss of heterozygosity in the human leukocyte antigen (HLA) haplotypes of relapsed/refractory DLBCL. HLA-A mutagenesis and loss of heterozygosity was discovered as mechanisms of immune evasion in cases that go on to relapse from R-CHOP like therapies (Figure 1). Conclusions Our results yield insight into the development of chemo-immunotherapy resistant diffuse large B-cell lymphoma, and highlight the clinical importance of sampling relapsed biopsies. Analysis of immune evasion through MHC Class I/II, specifically HLA-A, may provide better characterization of patients for relapse prediction. In the age of personalized medicine it will be instrumental to determine if relapsed biopsies offer additional insight for salvage therapy treatment. Divergence of biopsies, as characterized by shared genomic mutations, increase with time and the majority of cases present with new alterations in druggable genes post-therapy. Disclosures Leppa: Roche: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy; Bayer: Research Funding. Holte:Novartis: Honoraria, Other: Advisory board.