Abstract: CLL with deletion 17p (17p-) or refractory to fludarabine (F)-based regimens is characterized by poor prognosis. The cooperative French/German CLL2O study aimed at achieving deep and durable response in this population by combining alemtuzumab (A) and dexamethasone (D) induction, followed by consolidation with A maintenance or allogeneic stem-cell transplantation (allo-SCT). Induction treatment consisted of subcutaneous A (30mg, 3x weekly) combined with oral D (40 mg days 1-4 and 15-18), both at 28 day cycles, and prophylactic pegfilgrastim 6 mg on days 1 and 15. If at least SD was achieved after 3 cycles, consolidation was scheduled with either allo-SCT or A maintenance (30mg every 2 weeks for up to 2 years), at discretion of pt and physician. Between January 2008 and December 2011, 131 eligible pts were enrolled at 26 centers. Pts were generally subdivided for this analysis into three cohorts: 17p- 1st line, 17p- relapsed (not refractory) and refractory (i.e. no response or relapse within 6 months) to F-based or similar (i.e. pentostatin, cladribine, bendamustine) therapy. All three cohorts where characterized by high-risk baseline disease features (detailed in Table). During induction, a total of 467 non-hematologic AEs were recorded, predominantly (79%) of minor grade, while 36%, 43%, and 50% of pts in the 3 cohorts had at least one event of grade 3 or higher (Table). ORR (best response) was high in all three cohorts, but CRs were rarely observed outside the 17p- 1st line cohort (Table). Correspondingly, there were marked differences in PFS and OS between the three cohorts with far better outcome in the 17p- 1st line group (see Table and Figure 1). Consolidation treatment was performed as A maintenance (median duration 42 weeks, range 2 – 112.4) in 37%, and allo-SCT in 25%, with a median age of 69 and 57 y in these subgroups. The main reasons for going off-study without consolidation were death due to infection in 19 patients (15%), largely from the F-refractory cohort (n=16), with the majority being non-responders to study treatment (n=11); CLL progression (10%), and other toxicity (9%). Five pts who did not receive immediate consolidation treatment per protocol later underwent allo-SCT, 2 of these have died (sepsis, GvHD). During A maintenance, grade 3/4 toxicity consisted of neutropenia in 47% and thrombocytopenia in 12%. Serious (grade 3/4) non-CMV infection occurred in 17%, 10%, 13% in the 3 cohorts. When comparing PFS between A maintenance and allo-SCT, there were 41 (84%) and 16 (48%) events, respectively, significantly favoring SCT (Figure 2). Six pts who started A maintenance later underwent allo-SCT, 4 of them after relapse. After median follow up of 20 months from allo-SCT, 12 pts have died, 7 because of non-relapse mortality and 5 subsequent to CLL progression. In conclusion, the combination of A and D, followed by A maintenance or allo-SCT showed high response rates in ultra high-risk CLL with expected toxicity. For 17p- 1st line treatment, the results compare favorably to FCR (CLL8: ORR 68%, median PFS 11.3 mo). On the other hand, in F-refractory and 17p- relapsed CLL, the high ORR did not translate into prolongation of PFS. Allo-SCT appears to offer superior disease control in eligible patients despite prior A exposure. Overall, this mature trial may serve as a historical benchmark for comparison of novel agents in ultra high-risk CLL. Table 1 Parameter 17p- 1st line 17p- relapsed F-refractory Number of patients 42 28 61 Median age (yrs) 66.5 64 66 Binet C (%) 45 57 77 B symptoms (%) 40 32 31 ECOG 1/2 (%) 38 39 56 Median thymidine kinase (U/l) 35 48.1 27.6 Median β2MG (mg/dl) 3.8 5.1 4.7 Unmutated IGHV (%) 90 93 87 17p- (%) 100 100 49 Prior lines (median) n.a. 2 3 Prior rituximab (%) n.a. 71 93 AEs during induction (grade 3/4) Table 2 All AEs (%) 36 43 50 Neutropenia (%) 24 36 67 Anemia (%) 14 36 21 Thrombocytopenia (%) 12 39 31 Non-CMV infection (%) 19 36 36 CMV infection (%) 7 0 2 Efficacy (median follow-up 41.3 mo) Table 3 ORR (%) 97 79 69 CR (%) 21 4 3 Median PFS (mo) 32.8 10.3 9.7 Median OS (mo) 〉 60.0 21.4 17.3 Figure 1 Figure 1. Figure 2 Figure 2. Disclosures Stilgenbauer: Amgen: Honoraria, Research Funding; Genzyme: Honoraria, Research Funding.

Abstract: Despite considerable treatment advances with targeted therapies for patients with chronic lymphocytic leukemia (CLL) deemed high-risk [del(17p) and/or TP53 mutation], the outcome is still inferior compared with other CLL patients. Combining multiple agents with distinct mechanisms of action may further improve outcomes. CLL2-GIVe is an open-label, multicenter trial which enrolled patients with previously untreated CLL with del(17p) and/or TP53 mutation. Patients received induction therapy with obinutuzumab (GA-101), ibrutinib, and venetoclax (GIVe) for cycles 1 through 6 and consolidation therapy with venetoclax and ibrutinib for cycles 7 through 12. Ibrutinib monotherapy was continued for cycles 13 through 36 in patients not reaching a complete response (CR) with serial undetectable minimal residual disease (uMRD) after consolidation. The primary endpoint was CR rate at cycle 15 (final restaging). Secondary endpoints included MRD, survival, and safety. All 41 patients enrolled between September 2016 and August 2018 received study treatment and were included in efficacy and safety populations. With a CR rate of 58.5% at cycle 15, the primary endpoint was met (95% CI: 42.1-73.7; P & lt; .001). At final restaging, 78.0% of patients had uMRD in peripheral blood (PB); 65.9% of patients had uMRD in bone marrow (BM). Estimated progression-free survival (PFS) and overall survival (OS) rates at 24 months were both 95.1%. Adverse events were reported in all patients; most were low grade (grade ≥3: 23.9%). Two deaths were reported (cardiac failure and ovarian carcinoma), neither related to study treatment. The CLL2-GIVe treatment regimen has a manageable safety profile and is a first-line treatment of good efficacy for patients with high-risk CLL.

Abstract: Bruton tyrosine kinase (BTK) inhibitors are highly active drugs for the treatment of chronic lymphocytic leukemia (CLL). To understand the response to BTK inhibitors on a molecular level, we performed (phospho)proteomic analyses under ibrutinib treatment. We identified 3466 proteins and 9184 phosphopeptides (representing 2854 proteins) in CLL cells exhibiting a physiological ratio of phosphorylated serines (pS), threonines (pT), and tyrosines (pY) (pS:pT:pY). Expression of 83 proteins differed between unmutated immunoglobulin heavy-chain variable region (IGHV) CLL (UM-CLL) and mutated IGHV CLL (M-CLL). Strikingly, UM-CLL cells showed higher basal phosphorylation levels than M-CLL samples. Effects of ibrutinib on protein phosphorylation levels were stronger in UM-CLL, especially on phosphorylated tyrosines. The differentially regulated phosphopeptides and proteins clustered in pathways regulating cell migration, motility, cytoskeleton composition, and survival. One protein, myristoylated alanine-rich C-kinase substrate (MARCKS), showed striking differences in expression and phosphorylation level in UM-CLL vs M-CLL. MARCKS sequesters phosphatidylinositol-4,5-bisphosphate, thereby affecting central signaling pathways and clustering of the B-cell receptor (BCR). Genetically induced loss of MARCKS significantly increased AKT signaling and migratory capacity. CD40L stimulation increased expression of MARCKS. BCR stimulation induced phosphorylation of MARCKS, which was reduced by BTK inhibitors. In line with our in vitro findings, low MARCKS expression is associated with significantly higher treatment-induced leukocytosis and more pronounced decrease of nodal disease in patients with CLL treated with acalabrutinib.

Abstract: Genetic parameters are established prognostic factors in chronic lymphocytic leukemia (CLL) treated with chemoimmunotherapy, but are less well studied with novel compounds. We assessed immunoglobulin heavy variable chain (IGHV) mutation status, common genomic aberrations, and gene mutations in 421 untreated patients within the CLL14 trial (NCT02242942), comparing obinutuzumab+chlorambucil (GClb) vs obinutuzumab+venetoclax (VenG). The incidences of genomic aberrations considering the hierarchical model were del(17p) 7%, del(11q) 18%, +12 18%, and del(13q) 35%, whereas IGHV was unmutated in 60% of patients. NOTCH1 mutations were most common (23%), followed by SF3B1 (16%), ATM (13%), and TP53 (10%). Although the overall response rate (ORR) for GClb was lower in patients with del(17p), del(11q), mutated TP53, ATM, and BIRC3, none of these parameters reduced complete remission (CR) rate and ORR with VenG. At a median follow-up of 28 months, del(17p) and mutated TP53 were the only abnormalities with an effect on progression-free survival (PFS) for both treatment groups: GClb (hazard ratio [HR], 4.6 [P & lt; .01]; HR, 2.7 [P & lt; .01], respectively) and VenG (HR, 4.4 [P & lt; .01]; HR, 3.1 [P & lt; .01], respectively). No other factors affected outcome with VenG, whereas for GClb del(11q), BIRC3, NOTCH1, and unmutated IGHV were associated with shorter PFS. Multivariable analysis identified del(17p), del(11q), unmutated IGHV, and mutated TP53, BIRC3, and SF3B1 as independent prognostic factors for PFS with GClb, whereas for VenG, only del(17p) was significant. VenG was superior to GClb across most genetic subgroups. Patients with adverse genetic markers had the strongest benefit from VenG, particularly subjects with unmutated IGHV, which was identified as a predictive factor in a multivariable treatment-interaction analysis.

Abstract: The field of cancer genomics has been empowered by increasingly sophisticated inference tools to distinguish driver mutations from the vastly greater number of passenger mutations. Epigenetic alterations such as promoter DNA hypermethylation have been shown to drive cancer through inactivation of tumor suppressor genes (TSGs), but growing malignant populations also accrue pervasive stochastic epigenetic changes in DNA methylation (DNAme), most of which likely carry little functional impact. Unlike with somatic mutations, we have limited ability to robustly differentiate driver DNAme changes (DNAme drivers) from stochastic, passenger DNAme changes. To address this challenge, we developed MethSig, a statistical inference framework that accounts for the varying stochastic hypermethylation rates across the genome and between samples. MethSig estimates expected background DNAme changes, thereby allowing the identification of epigenetically disrupted loci, where observed hypermethylation significantly exceeds expectation, potentially reflecting positive selection (Fig. 1a). We applied MethSig to reduced representation bisulfite sequencing (RRBS) data of chronic lymphocytic leukemia (CLL) cohorts, which include 304 CLLs collected in a prospective clinical trial (CLL8) and 103 CLLs in a previously published study (CLL-DFCI, Landau et al., 2014), as well as other malignancies where RRBS data is available, including ductal carcinoma in situ (Abba et al., 2015) and multiple myeloma. Area under the receiver operating characteristic curve (AUROC) was used to evaluate sensitivity and specificity of methods in the inference of likely DNAme drivers. We identified two key features that are likely to be strongly associated with true candidate DNAme drivers: gene silencing in relation to promoter hypermethylation and association with clinical outcome. MethSig qualitatively improved ROC across those clinical and biological read outs (0.955 of MethSig, 95% confidence interval [CI] 0.945 - 0.965, versus 0.703 of benchmarked methods, 95% CI 0.669 - 0.737, Fig. 1b used CLL8 as an example). We identified 189 candidate DNAme drivers in CLL, which include known TSGs, and are enriched in genes hypermethylated or inactivated across cancer types. To further validate MethSig's inferences, selected CLL candidate DNAme drivers (DUSP22, RPRM) underwent CRISPR/Cas9 knockout (KO) in CLL cells and stable KO clones were generated through single-cell cloning to eliminate genetic heterogeneity effect. The RPRM and DUSP22 KO clones showed faster growth without treatment (Fig. 1c) and superior fitness in ibrutinib/fludarabine treatment compared with controls (Fig. 1d). Notably, we observed a gene dose effect in the RPRM KO clones (Fig. 1c-d, greater growth of the bi-allelic compared to mono-allelic KO). Elastic net regression with a Cox proportional hazards model was used to evaluate DNAme drivers' contribution to the prediction of failure-free survival after treatment (FFS; failure defined as retreatment or death) and a rigorous training (CLL8) and validation (an independent cohort CLL-DFCI) cohort study design was implemented to safeguard from overfitting and poor generalizability. DNAme drivers were found to be associated with shorter FFS in independent CLL cohorts (Fig. 1e-f). A regression model including established CLL risk indicators (IGHV unmutated status, del[17p] or TP53 mutation) showed an adjusted hazard ratio of 2.3 (95% CI 1.6 - 3.3, P = 2 × 10-6) in CLL8 cohort and 3.2 (95% CI 1.2 - 8.8, P = 0.02) in CLL-DFCI cohort for patients with high risk. Application of MethSig to CLL relapsed after chemoimmunotherapy further identified relapse-specific DNAme drivers, enriched in TP53 targets as well as DNA damage pathway, which indicates that CLL relapse after chemotherapy may follow an alternative path compared to CLL progression in the absence of therapy, offering novel insights for therapeutic strategies to address drug-resistant or relapsed cancer. Collectively, our data support a novel framework for the analysis of DNAme changes in cancer to specifically identify DNAme drivers of disease progression and relapse, empowering the discovery of epigenetic mechanisms that enhance cancer cell fitness. This work addressed a central gap between cancer epigenetics and cancer genetics, where such tools have had a transformative impact in precision oncology and cancer gene discovery. Disclosures Tausch: Janssen-Cilag: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding. Fink:AbbVie: Other: travel grants; Janssen: Honoraria; Celgene: Research Funding. Fischer:AbbVie: Honoraria; F. Hoffmann-La Roche: Honoraria, Other: travel grants. Gnirke:FL67 Inc.: Consultancy. Moreaux:Diag2Tec: Consultancy. Hallek:Celgene: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Gilead: Consultancy, Research Funding; Mundipharma: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Roche: Consultancy, Research Funding. Stilgenbauer:Janssen-Cilag: Consultancy, Honoraria, Other: travel support, Research Funding; Genentech: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Other: travel support, Research Funding; Genzyme: Consultancy, Honoraria, Other: travel support, Research Funding; Pharmacyclics: Consultancy, Honoraria, Other, 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; GlaxoSmithKline: Consultancy, Honoraria, Other: travel support, Research Funding; Novartis: Consultancy, Honoraria, Other, Research Funding; Mundipharma: Consultancy, Honoraria, Other, Research Funding. Wu:BionTech: Current equity holder in publicly-traded company; Pharmacyclics: Research Funding. Elemento:Acuamark: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; OneThree Biotech: Current equity holder in private company, Other: Cofounder; Owkin: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Sanofi: Research Funding; Eli Lilly: Research Funding; Volastra Therapeutics: Current equity holder in private company, Other: Cofounder; Freenome: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Genetic Intelligence: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding. Landau:Bristol Myers Squibb: Research Funding; Illumina: Research Funding.

Abstract: Background: The MYC proto-oncogene encodes a DNA-binding factor that can induce widespread changes in gene expression profiles (GEP). Activation of MYC is a hallmark of aggressive lymphomas and frequently observed in Richter transformation of CLL. In contrast, the role of MYC-related pathogenic networks is less clearly defined in untransformed CLL. Aims: We hypothesized that MYC activation in CLL could lead to specific GEP associated with aggressive disease. We combined the analysis of genomic copy number alterations (CNA) and GEP involved in MYC pathway activation on specimens from patients registered on the CLL8 trial (front line therapy FC vs. FCR). Methods: GEP were derived from CD19-enriched CLL samples (n=337, Human Exon 1.0 ST, Affymetrix) and analysis of CNA was performed based on availability of DNA (n=309, Human SNP Arrays 6.0, Affymetrix). Sample work-up upon trial registration included FISH and TP53 mutation analysis. Results: Genomic gains involving the MYC locus on 8q24.21 were observed in 4.5% of cases. To test the hypothesis of specific GEP associated with MYC activation, we explored the distribution of cases with MYC gain using an unsupervised approach on GEP. After consensus clustering (k=6 clusters) of variably expressed genes (SD 〉 0.5), cases with MYC gain were non-randomly distributed and showed a characteristic pattern. Preferential enrichment was observed in one cluster ("MYC-CNA" group, comprising 40% of all cases) with 64% of MYC gains. Gene set enrichment analysis (GSEA) confirmed overrepresentation of MYC target genes (gene set: HALLMARK_MYC_TARGETS_V1, FDR 〈 0.05) in MYC-CNA and a second cluster, denoted as MYC endogenous activation cluster ("MYC-EA" group, 16% of cases). Conversely, a large cluster, which was most distant to MYC-CNA, did not show significant enrichment in GSEA for MYC target genes or for CNA and was defined as "MYC-silent" reference cluster (comprising 30% of cases). Other potential elements contributing to the regulation of MYC networks, included enrichment of TP53 alterations in both MYC clusters compared to the MYC-silent cluster (17.5% vs. 6%, p=0.015, Fisher`s exact test). We also observed frequent gains of chromosome 2p, involving NMYC on 2p24.3, in both MYC clusters. Losses of the MYC repressors MNT on 17p13.3, MGA on 15q15.1 and PRDM1 on 6q21 also constituted frequent events in the MYC-CNA cluster. Overall, CNA affecting MYC, NMYC and the MYC repressors were more frequent in MYC-CNA (41 in 127 cases) compared to MYC-silent cluster (15 in 93 cases) (p=0.03, Mann Whitney). In addition, expression of the MYC repressor BCL6 was downregulated in MYC-CNA compared to the MYC-silent cluster (fold change 1.5, q 〈 1e-07). MYC protein overexpression was observed by Western blot densitometry in cases without the described CNA, both in MYC-CNA (n=11 cases tested) and MYC-EA (n=7 cases tested), confirming independent activation. Activation of PI3K-AKT and RAS-ERK-signaling was a prominent feature in both MYC clusters. Strong discrepancy between both MYC clusters was observed for cell cycle regulation with changes implicating either increased proliferation in MYC-CNA or cell cycle arrest in MYC-EA. PFS was different when comparing both treatment arms in MYC-CNA (HR 0.55 (95%CI 0.37-0.82), p=0.003) and MYC-EA (HR 0.30 (95%CI 0.15-0.60), p 〈 0.001) with PFS rates at 5 years of 15% (FC) vs. 38.6% (FCR) for MYC-CNA and 17.9% (FC) vs. 57.6% (FCR) for MYC-EA. In contrast, the MYC-silent cluster showed a better outcome compared to the MYC clusters when treated with FC and no benefit from the addition of rituximab with PFS rates at 5 years of 43.1% (FC) vs. 42.9% (FCR) (p=0.56). Median OS was significantly different for treatment arms in MYC-EA and, compared to all other clusters, showed shortest median OS for FC treatment with OS rates at 5 years of 47.9% and strongest benefit for the addition of rituximab with 80.5% (FCR) (HR 0.32 (95%CI 0.13-0.79), p=0.009). Conclusion: MYC pathway alterations were frequently observed in treatment-naive CLL and may involve various mechanism such as CNA affecting MYC and its repressors, TP53 defect or sole transcriptional changes. Cases with MYC activation may be segregated based on cell cycle checkpoint deregulation and consecutive proliferative capacity. Clusters with MYC activation had an inferior clinical course when treated with FC but, when adding rituximab, both MYC-CNA and MYC-EA showed a significant improvement for outcome. Disclosures Bahlo: Roche: Honoraria, Other: Travel Grants. Humphrey:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Wenger:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership, Other: Ownership interests PLC. Tausch:AbbVie: Consultancy, Other: Travel grants; Celgene: Consultancy, Other: Travel grants; Gilead: Consultancy, Other: Travel grants. Bullinger:Bayer Oncology: Research Funding; Pfizer: Speakers Bureau; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Speakers Bureau; Sanofi: Research Funding, Speakers Bureau; Bristol-Myers Squibb: Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Fischer:Roche: Other: Travel support. Hallek:Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Mundipharma: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Boehringer Ingelheim: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Stilgenbauer:Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Hoffmann La-Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Mundipharma: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmcyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genzyme: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract: Background Oncogenic proteins can be stabilized either via genetic mutations or via defects in the ubiquitin ligating- and degradation machinery. NOTCH1 protein stability is affected by genetic mutations in approximately 10% of chronic lymphocytic leukemia (CLL) patients and mutations are associated with a worse prognosis. Yet, even in the absence of NOTCH1 mutations, NOTCH1 is activated in almost half of all CLL patients. Aims In order to shed light on NOTCH1 activation in CLL, we analyzed the impact of its modulator, the E3-ubiquitin ligase FBXW7 and the deubiquitinase USP28 that is a negative regulator of FBXW7 and is located in chromosomal band 11q23. Methods FBXW7 mutation analysis was performed via targeted next generation sequencing from a total of 905 patients. In silico modeling of potential substrate binding to the mutated FBXW7 was performed by the use of PolyPhen-2 and validated via co-immunoprecipitation of overexpressed mutated FBXW7 and NOTCH1 wild type proteins. Accumulation of FBXW7 substrates was tested via Western blot in CRISPR/Cas9 induced FBXW7 mutated HG-3 CLL cell lines and in FBXW7 mutated primary CLL cells, identifying the transcription factor NOTCH1 as FBXW7 target. Expression of NOTCH1 target genes were analyzed in FBXW7 mutated CLL cases via gene expression profiling (n=4) and RT-qPCR (n=19). In an independent cohort, USP28 and NOTCH1 target gene expression was analyzed in a total of 285 patients via gene expression profiling. Results Heterozygous FBXW7 mutations were identified in 41/905 (4.5%) CLL patients. The majority were missense mutations (78%) that mostly affected the WD40 substrate binding domain, while an additional 10% of mutations were located on the first exon of the abundantly expressed FBXW7 α-isoform. We identified substrate targets of FBXW7 in CLL via the generation of a truncation of the WD40 domain of FBXW7 in the CLL cell line HG-3 using CRISPR/Cas9, identifying NOTCH1 as an FBXW7 target. In silico modeling of FBXW7 mutations on protein binding predicted that novel mutations within the WD40 domain affected substrate recognition capacity of FBXW7. Interestingly, modeling predicted W425C and a new hotspot mutation G423V (found in 3/905 of CLL cases) to ablate NOTCH1 binding while the mutation A503V was predicted not to impair binding of NOTCH1 to FBXW7. The in silico modeling was confirmed by co-immunoprecipitation experiments of overexpressed NOTCH1 and FBXW7 and further revealed that mutations within the α-isoform specific N-terminus T15VR and V154I still enabled NOTCH1 binding. Intriguingly, in primary CLL cells FBXW7 mutations correlated with an increase in NOTCH1 levels that remained stable even upon inhibition of translation, underlining the enhanced protein stabilization by FBXW7 mutations. Furthermore, FBXW7 mutations in CLL resulted in an increased NOTCH1 target gene expression. FBXW7 activity is not only modulated by gene mutations, but also by the deubiquitinase USP28 which is localized in the recurrently deleted region 11q22-q23 close to the ATM tumor suppressor gene. We hypothesized that USP28 would impact on FBXW7 activity and thus on NOTCH1 stability and activity. In line with this concept we found that in primary cells from a cohort of 285 CLL patients, low USP28 expression significantly correlated with increased NOTCH1 target gene expression, independent of the 11q deletion status of the patients where USP28 is localized. Discussion In CLL patient cells we have identified novel mutations within the WD40 binding domain of FBXW7 in addition to the common hot spot mutations (R465, R479, R505). Amongst these novel mutations, G423V and W425C are recurrent and result in decreased binding of the FBXW7 substrate NOTCH1 and hence in an accumulation and induction of NOTCH1 activity. Furthermore, expression of USP28, the negative regulator of FBXW7, significantly correlated with increased NOTCH1 target gene expression. Hence, our findings uncover modulation of NOTCH1 in CLL via the FBXW7-USP28-NOTCH1 axis (Figure 1) in addition to genomic NOTCH1 modification, thus explaining the high proportion of CLL cases that harbor an activation of NOTCH1 leading to more aggressive disease. Disclosures Tausch: AbbVie: Consultancy, Other: Travel grants; Celgene: Consultancy, Other: Travel grants; Gilead: Consultancy, Other: Travel grants. Döhner:AbbVie: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Astex Pharmaceuticals: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Pfizer: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Celator: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; AROG Pharmaceuticals: Research Funding; Astellas: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Agios: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Pfizer: Research Funding. Stilgenbauer:Novartis: Consultancy, Honoraria, Other: travel support, Research Funding; Roche: Consultancy, Honoraria, Other: travel support, Research Funding; Genetech: Consultancy, Honoraria, Other: travel support, Research Funding; Amgen: Consultancy, Honoraria, Other: travel support, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Other: travel support, Research Funding; Pharmacyclics: Consultancy, Honoraria, Other: travel support, Research Funding; Celgene: Consultancy, Honoraria, Other: travel support, Research Funding; AbbVie: Consultancy, Honoraria, Other: travel support, Research Funding; Janssen: Consultancy, Honoraria, Other: travel support, Research Funding; Mundipharma: Consultancy, Honoraria, Other: travel support, Research Funding.

Abstract: Richter's syndrome (RS) arising from chronic lymphocytic leukemia (CLL) is a striking example of an aggressive malignant histology that emerges from indolent cancer. A major barrier to disease control in CLL, RS is associated with poor clinical outcomes and limited survival. The genetic basis of RS is poorly understood and its relationship to antecedent CLL remains incompletely characterized. Notable challenges to the genomic study of RS includes those of sample acquisition, the distinction between true tumor events rather than sequence artifacts in archival fixed tissue, and the limitations of available computational techniques for deconvoluting admixtures of CLL and RS DNA within the same biopsy specimen. To address these challenges and characterize the genetic profile of RS, we performed whole-exome sequencing (WES) on samples collected from 42 patients with RS of diffuse large B cell lymphoma (DLBCL) histology. For this genomic characterization, samples from 37 patients were analyzed as 'trios' (matched germline, CLL and RS tissue DNA) and those from 5 as 'duos' (matched CLL and RS DNA). CLL diagnosis preceeded RS diagnosis by a median of 60.6 months (range 0.1-234.5). The median number of prior CLL-directed therapies was 2 (range 0-10). 8 patients had no prior CLL-directed therapy, while 9 were exposed to novel agents. The median time from most proximal CLL sampling to RS was 2.7 months (range: 82.2 months pre- to 3.8 months post RS diagnosis). Critical analytic innovations applied to this dataset included addressing contamination of CLL DNA in the germline sample (through the tool DeTIN) and generating the ability to discriminate between clones arising from RS or from CLL, even while both histologies were commonly co-existing within originating biopsies (via the tool PhylogicNDT). From this discovery cohort of 42 cases, 36 (86%) revealed RS and CLL to be clonally-related based on WES analysis, with a distinct RS clone emerging from an existing CLL subclone. Of the 6 (14%) cases determined to be clonally unrelated by WES, 4 had been previously examined by IGHV sequencing; only 1 of 4 was categorized as clonally unrelated, likely due to CLL and RS admixture. RS displayed mutational signatures reflecting aging (CpG), canonical AID, and non-canonical AID processes. Through deconvoluting clonal composition using PhylogicNDT in related sample trios (n=31), we established several notable differences compared to antecedent CLL. First, RS clones presented higher rates of additional mutations than the ancestral CLL clones from which they developed (2.47 vs. 0.86 Mut/Mb, p & lt;0.0001). Second, the frequency of CLL-associated driver mutations in the RS clones was altered:TP53 mutation (n=21, 50%), NOTCH1 mutation (n=17, 40%) NFKBIE (n=5, 12%), EGR2 (n=6, 14%), XPO1 (n=5, 12%), and RPS15 (n=3, 7%). Third, the clonal transition to RS was marked by a diversity of additional driver mutations and particularly increased copy number variants (CNVs). RS biopsies had recurrent arm level events, including del(17p) in 44%, del(4p) in 27%, del(4q) in 27%, del(9p) in 22%, del(17q) in 22% and del(9q) in 20% (Q & lt;0.05, GISTIC). The top focal alterations in RS biopsies, as identified by tool GISTIC included (Q value & lt;= 0.05): amp(7q21.2) - CDK6,amp(8q24.3) - RECQL4, amp(13q31.3) - ERCC5, amp(19p13.3), amp(19q13.42), del(8p12), del(17p13.1) - TP53, del(13q14.3), del(7q35), and del(16q12.2). Finally, whole genome doubling was observed in 6 cases upon transition to RS. To further investigate RS and CLL clonal evolution at high resolution, we performed single-cell RNA-sequencing (10x Genomics), on biopsies at the time of RS diagnosis in 5 individuals with clonally related transformation. Data analysis and clustering was conducted using Seurat(v3) with doublet removal (DoubletFinder). We identified CNV in single-cell transcriptomes that matched the WES copy-number profiles of individual subclones of the RS and CLL populations and thus linked subclones identified by WES to single-cell expression clusters and states, revealing CLL, RS and intermediate evolutionary cell states. In conclusion, we identify that RS arises from CLL subclones through distinct mutational trajectories. Further molecular subclassification of RS, including genetic characterization of additional cases, and linking mutational data with clinical outcomes is ongoing and has potential to alter clinical classification and prognostication of RS. Disclosures Guieze: abbvie: Honoraria, Other: advisory board, travel funds; janssen cilag: Honoraria, Other: advisory board, travel funds; roche: Other: travle funds; gilead: Honoraria, Other: travel funds; astrazanecka: Honoraria, Other: advisory board. Leshchiner:PACT Pharma, Inc.: Consultancy. Tausch:Roche: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Research Funding. Davids:Genentech: Consultancy, Research Funding; Janssen: Consultancy; Gilead Sciences: Consultancy; Novartis: Consultancy, Research Funding; MEI Pharma: Consultancy, Research Funding; Surface Oncology: Research Funding; AbbVie: Consultancy; Adaptive Biotechnologies: Consultancy; Merck: Consultancy; Pharmacyclics: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Verastem: Consultancy, Research Funding; Syros Pharmaceuticals: Consultancy; Sunesis: Consultancy; Zentalis: Consultancy; AstraZeneca: Consultancy, Research Funding; Ascentage Pharma: Consultancy, Research Funding; Eli Lilly: Consultancy; Research to Practice: Honoraria; Celgene: Consultancy; BeiGene: Consultancy; Bristol Myers Squibb: Research Funding. Elagina:AbbVie: Current Employment. Jain:TG Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Precision Bioscienes: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Research Funding; Pfizer: Research Funding; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Fate Therapeutics: Research Funding; Verastem: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding; Cellectis: Research Funding; BeiGene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Aprea Therapeutics: Research Funding; Genentech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; ADC Therapeutics: Research Funding; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Kipps: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; Celgene: Honoraria, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Genentech/Roche: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; VelosBio: Research Funding; 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; 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. Broséus:Novartis: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria; Gilead: Honoraria. Kay:MEI Pharma: Research Funding; Cytomx: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees. Purroy:AstraZenica: Current Employment. Utro:IBM: Current Employment. Rhrissorrakrai:IBM: Current Employment. Levovitz:IBM: Current Employment. Parikh:GlaxoSmithKline: Honoraria; Pharmacyclics: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; MorphoSys: Research Funding; TG Therapeutics: Research Funding; Merck: Research Funding; AbbVie: Honoraria, Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; Verastem Oncology: Honoraria. Brown:Abbvie, Acerta, AstraZeneca, Beigene, Invectys, Juno/Celgene, Kite, Morphosys, Novartis, Octapharma, Pharmacyclics, Sunesis, TG Therapeutics, Verastem: Consultancy; Gilead, Loxo, Sun, Verastem: Research Funding; Janssen, Teva: Speakers Bureau. Parida:IBM: Current Employment. Neuberg:Madrigak Pharmaceuticals: Current equity holder in publicly-traded company; Pharmacyclics: Research Funding; Celgene: Research Funding. Stilgenbauer:Novartis: Consultancy, Honoraria, Other, Research Funding; Mundipharma: Consultancy, Honoraria, Other, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Other: travel support, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Other: travel support, Research Funding; Genentech: Consultancy, Honoraria, Other: travel support, Research Funding; Genzyme: Consultancy, Honoraria, Other: travel support, Research Funding; Pharmacyclics: Consultancy, Honoraria, Other, Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Other: travel support, Research Funding; Celgene: Consultancy, Honoraria, Other: travel support, Research Funding; F. Hoffmann-LaRoche: Consultancy, Honoraria, Other: travel support, Research Funding; Amgen: Consultancy, Honoraria, Other: travel support, Research Funding; AbbVie: Consultancy, Honoraria, Other: travel support, Research Funding. Getz:Scorpion Therapeutics: Consultancy, Current equity holder in publicly-traded company, Other: Founder; IBM: Research Funding; Pharmacyclics: Research Funding; Broad Institute: Patents & Royalties: MuTect, ABSOLUTE, MutSig, MSMuTect, MSMutSig, POLYSOLVER and TensorQTL. Wu:Pharmacyclics: Research Funding; BionTech: Current equity holder in publicly-traded company.

Abstract: Genomic abnormalities have strong prognostic impact in chronic lymphocytic leukemia (CLL). However, clonal evolution has been studied in a limited number of cases and not within the setting of current standard therapy. It was therefore our aim to study changes in the composition of copy number alterations (CNA) over time with and without the influence of chemo(immuno)therapy. Sequential samples of 92 patients enrolled on the CLL8 trial of the GCLLSG were analyzed by Affymetrix® 6.0 single nucleotide polymorphism (SNP) arrays. Since procurement of a relapse sample was a prerequisite for this study, the cohort was not representative for the CLL8 trial [21% CR (N=19), 63% PR (N=58), 13% non response (N=12), 3% missing response (N=3)]. 48 patients received Fludarabine / Cyclophosphamide (FC), 44 patients FC plus Rituximab (FCR). Samples were taken at 3 time points: pre-treatment [N=27] , time of first treatment in CLL8 [N=92] and post treatment at relapse / progressive disease [N=74] . The median observation period between samples was 35 months [range: 6-127] for the pre-treatment vs. first treatment and 41 months [range: 5-87] for the first treatment vs. post treatment (relapse) comparisons. The majority of cases maintained genomic stability over time. This applied in particular for the comparison between pre-treatment and first treatment [N=21 of 27; 78%] but also for the comparison between first treatment and relapse [N=49 of 74; 66%] . The cohort was characterized by a high proportion of high-risk genomic abnormalities [30% del(11)(q22.3), 22% TP53 loss and/or mutation in the pre-treatment cohort; 36% del(11)(q22.3), 24% TP53 loss and/or mutation in the post treatment cohort]. The acquisition of novel clonal CNAs was associated with these: In the pre-treatment to first treatment comparison [N=27] , only 6 [22%] cases had novel CNAs emerging over time and all of them carried an ATM loss by del(11)(q22.3). Eight cases with ATM and/or TP53 alteration and all cases without high-risk genomic aberrations [N=13] showed no evidence of clonal evolution. In the first treatment to relapse comparison [N=74], 25 [34%] cases had newly acquired CNAs at relapse and 20 of them [80%] carried high-risk genomic abnormalities [44% del(11)(q22.3), 36% TP53 loss and/or mutation] . Only 5 cases lacking ATM or TP53 alteration had newly acquired CNAs. In contrast, genomic stability was observed in 25 cases with high-risk genomic abnormalities [15 cases with del(11)(q22.3), 10 with TP53 loss and/or mutation) and 24 cases without high-risk abnormalities. No statistically significant increased incidence of clonal evolution was observed in IGHV unmutated cases [N=66 of 92] [24 (80%) cases with clonal evolution vs. 42 (70%) cases without clonal evolution, p=0.3] . Nine patients had samples available from all 3 time points. While mainly genomic stability could be observed prior to treatment, 3 cases acquired 3 novel CNAs each after therapy. Comparing both treatment arms in the post treatment cohort [N=74] revealed a higher incidence of clonal evolution after treatment with FCR [FCR: N=16 of 35, 46%; FC: N=9 of 39, 23%; p=0.04] at a similar median observation period [36 and 35 months, respectively]. Also, the mean number of newly acquired CNAs at relapse was higher in the FCR treated group [3.3 vs. 2.6] . With regard to response no statistically significant differences were observed between cases with and without clonal evolution [cases with clonal evolution: 6 (24%) CR, 17 (64%) PR, 2 (8%) non-response; without: 8 (17%) CR, 31 (66%) PR, 8 (17%) non-response, p=0.5]. Loss of clonal lesions was rare, occurring only under the selection pressure of therapy: 16 CNAs in 11 cases were not observed anymore at relapse. 3 of these CNAs were subclonal at time of first treatment [10-20% allelic burden] and might not yet have re-emerged after relapse. 5 CNAs in 4 cases were lost at relapse. The remaining 8 CNAs were del(13q) [N=5] and del(11q) [N=3] that were lost for a probably more advantageous del(13q) / del(11q) clone. The appearance of a more advantageous del(13q) / del(11q) clone was linked to a larger deletion size [N=3] or a larger discontinuous deletion very likely resulting from chromothripsis [N=3]. The results of this study support previous data of a high genomic stability in CLL cases lacking alterations of TP53 and/or ATM. However, application of chemo(immuno)therapy did slightly increase the number of cases acquiring novel clonal CNAs. Disclosures Stilgenbauer: Pharmacyclics, Janssen: Honoraria, Research Funding.

Abstract: Apoptosis is controlled by the expression levels and interplay of pro- and anti-apoptotic BCL-2 family proteins. The specific BCL-2 inhibitor Venetoclax (VEN) showed high efficiency in BCL-2 dependent cancers like chronic lymphocytic leukemia (CLL) or mantle cell lymphoma (MCL). Despite its high efficiency in CLL and MCL, refractory disease can develop. BCL-2 mutations have been described to mediate resistance in CLL cases, however these mutations are only found in a proportion of VEN resistant cases and in a fraction of cells. In order to design alternative therapeutic strategies to overcome drug resistance, a better understanding of the mechanisms mediating resistance to VEN is necessary. VEN-resistant (VEN-R) MCL cell lines (MINO and MAVER-1) were generated by chronic exposure to increasing amounts of VEN (up to 3µM). A significant and stable upregulation of BCL-XL mRNA and protein was seen in the MINO and MAVER-1 resistant cell lines (2 and 4 fold increase in mRNA and 2.6 and 4.5 fold increase in protein, respectively). We used BH3 profiling in combination with VEN treatment for 4h to investigate the differences in anti- and pro-apoptotic signaling in parental and VEN-R cell lines. Additionally, sensitivity to VEN was restored upon shRNA-mediated knockdown of BCL-XL. These results confirmed the importance of BCL-XL upregulation in mediating resistance. Furthermore, we did not detect mutations in BCL-2 upon resistance to VEN via targeted NGS, which is in contrast to results obtained in VEN-R CLL patients (Blombery et al., Cancer Discovery 2019 and Tausch et al., Hematologica 2019). However, the results obtained by dynamic BH3-profiling (VEN treatment in combination with BH3 Profiling) suggest that increase in BCL-XL is most likely not the only alteration necessary to render cells resistant to VEN. In addition, reduced activation of pro-apoptotic proteins like BAX and BAK might contribute to resistance to VEN. In order, to investigate if VEN resistance can be overcome by drug mediated inhibition of BCL-XL we used different therapeutic approaches. Combinational treatment with the BCL-XL inhibitor A-1331852 and VEN or the single treatment with Navitoclax, a combined inhibitor of BCL-2, BCL-W and BCL-XL for 48h reduced cell viability in VEN-R MINO and MAVER-1 cell lines. Furthermore, BDA-366, a BH4 domain BCL-2 inhibitor effectively reduced the cell viability after 48h of treatment in a dose dependent manner in both parental and VEN-R cell lines. The binding of BDA-366 to the anti-apoptotic BCL-2 protein leads to a conformational change into a pro-apoptotic molecule by the exposure of the BH3 domain of the protein. Despite mediating apoptosis in a TP53-independent manner, VEN treatment in CLL has been associated with inferior outcome in the presence of TP53 aberrations. In order to address the role of TP53 dysfunction in mediating resistance to VEN, we generated p53 knock out cell lines (N=2) by CRISPR/Cas9 gene editing. This significantly decreased the sensitivity to VEN compared to p53 WT cell lines. Additionally, the sensitivity to BDA-366 was significantly reduced upon knockout of p53, suggesting an interference of p53 downstream of BCL-2. Overall, VEN resistance is mediated by a permanent increase in BCL-XL mRNA and protein level in MCL. Importantly, BDA-366, which converts the anti-apoptotic BCL-2 molecule into a BAX-like death molecule, could be a potential alternative treatment strategy for BCL-2 dependent cancers even when resistant to VEN. Despite mediating apoptosis in a p53 independent manner, VEN seems to be less effective in p53 deficient cells, underlining the importance of further investigations of treatment combinations in these groups. Disclosures Tausch: Roche: Consultancy, Honoraria, Speakers Bureau; AbbVie: Consultancy, Honoraria, Other: travel support, Speakers Bureau. Döhner:AbbVie, Agios, Amgen, Astellas, Astex, Celator, Janssen, Jazz, Seattle Genetics: Consultancy, Honoraria; AROG, Bristol Myers Squibb, Pfizer: Research Funding; Celgene, Novartis, Sunesis: Honoraria, Research Funding. Stilgenbauer:Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; Hoffmann La-Roche: Consultancy, Honoraria, Research Funding, Speakers Bureau; Pharmacyclics: Other: Travel support; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Research Funding, Speakers Bureau; AstraZeneca: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria, Research Funding, Speakers Bureau. Schneider:Celgene: Other: travel grant.