Citations

Abstract Programmed death 1 (PD-1) is a T cell co-inhibitory receptor with two ligands, PD-L1 and PD-L2. In B-cell malignancies, this pathway plays a major role in immune resistance in the tumor environment by promoting the differentiation of regulatory T-cells and inducing T-cell exhaustion. Recent data have shown that blockade of this pathway can enhance antitumor immune responses. While interactions between PD-1 and its ligands have been studied in various lymphoid tissues, little data exist regarding these interactions in the bone marrow, particularly in patients with Waldenstrom macroglobulinemia (WM). The goal of this study was therefore to determine the expression of PD-1 and its ligands in the bone marrow of patients with WM and to assess the functional role of PD-1 signaling in this disease. Using immunohistochemistry, the expression of PD-1, PD-L1 and PD-L2 in bone marrow (BM) specimens from patients with WM (n=6) was compared to normal control BM. PD-1 expression was modest and the pattern of staining in WM was similar to normal BM. In contrast however, intense staining for PD-L1 and PD-L2 was seen in WM compared to controls. When analyzed by flow cytometry, PD-L1 and PD-L2 expression was seen on malignant B-cells and also on dendritic cells, monocytes and macrophages isolated from the bone marrow. To determine the functional effect of PD-1 signaling in WM, we stably transfected PD-L1 and PD-L2 into the HEK-293 cell line. The WM cell lines, MWCL-1, BCWM.1 and RPCI-WM1 as well as patient specimens, were then cocultured with either the PD-L1 or PD-L2 expressing HEK-293 cells. When compared to cells expressing an empty vector control, proliferation and viability of WM cells was increased when they were cocultured with cells expressing PD-L1 or PD-L2. Addition of blocking antibodies abrogated the increase in proliferation. These results show that PD-L1 and PD-L2 are highly expressed on both malignant B-cells and non-malignant cells within the BM microenvironment in WM and promote malignant B-cell growth. Inhibition of PD-1 signaling may therefore be a promising therapeutic strategy in patients with WM. Disclosures: No relevant conflicts of interest to declare.

Abstract Background: The results of the primary endpoint of the E2906 North American Intergroup phase 3 trial - demonstrating significantly inferior OS after single agent clofarabine versus standard intensive daunorubicin & cytarabine induction and consolidation - strongly support the use of intensive therapy for patients age ≥60 years with newly-diagnosed AML who are fit for treatment. This result was achieved despite similar CR rates (including CRi - CR with incomplete blood count recovery) and similar early (30- & 60-day) induction mortality between study arms, raising the question as to the importance of achieving CR as an endpoint. Therefore, we performed a follow-up analysis to address the factors that contribute to early mortality, the necessity for 2nd induction cycle to achieve CR, and to assess the survival impact of the quality of remission. Methods: E2906 design, study population and results for the primary objective were reported previously (ASH 2015, abstr. #217a). We performed this updated analysis to evaluate clinical risk factors for early mortality and re-induction, and to assess the impact of response quality on OS. Univariate comparisons were made with Fisher's exact test (category) and t-test (continuous variable), and logistic regression models were used to examine risk factors associated with early mortality, and with requiring a 2nd cycle of induction therapy. We performed a landmark analysis (beginning Day 60 after initiation of therapy) to determine the impact of response quality (CR/CRi, morphologic leukemia-free-state (MLFS), and treatment failure - i.e. residual/refractory AML) on OS. Survival comparisons were performed with log-rank test. Results: A total of n=727 patients were registered to E2906, the median age is 68 years (range 60-86) and the median follow-up of surviving patients is now 18.3 months. Adjusting for treatment, cytogenetic risk group, FAB subtype, WBC count, and secondary AML, increasing age (p=0.06) and performance status (PS) >1 (p=0.05) were associated with 30-day mortality and only PS >1 (p=0.06) with 60-day mortality. Treatment arm (p=0.003), adverse cytogenetic risk group (p=0.02), increasing age (p=0.03) and baseline WBC <10K (p=0.03) were each independently associated with higher risk of receiving 2nd cycle induction, but there was no difference in CR/CRi (44.2% vs. 42.2%, p=0.58) or in median OS (13.8 versus 12.0 months, p=0.11) for those receiving 1 vs. 2 induction cycles, respectively. We next performed a landmark analysis (day 60, n=608 evaluable patients) to evaluate OS in relation to the quality of response (Table). We observed an advantage in achieving CR and CR/CRi, although the benefit of CRi diminished greatly after 12 months, and OS after MLFS appeared more similar to treatment failure (Figure, p<0.001). The relative adverse impact of CRi and MLFS (vs. CR) was most pronounced for patients treated with clofarabine, where median OS was shorter for those achieving CRi (12.2m vs. 22.6m standard therapy, p=0.007) and MLFS (6.6m vs. 13.4m standard therapy, p=0.15). Conclusion: This follow-up analysis confirms the importance of CR regardless of the number of cycles of induction therapy required to achieve remission, and identifies risk factors associated with early mortality and with requiring re-induction. At longer follow-up the OS after CRi appears to be inferior to true CR, particularly after clofarabine. We hypothesize that this may be due to higher rates of minimal residual disease in CRi, and studies to determine this are being performed. MLFS is not associated with a better overall survival than frank treatment failure (i.e. residual disease) and therefore its value as a response category is uncertain. These results highlight the role of standard intensive remission induction therapy with the intent of achieving CR, which remains the standard of care for fit older adults. Table. Table. Figure 1. Figure 1. Disclosures Foran: karyopharm: Honoraria; novartis: Honoraria; medscape: Honoraria; Millennium Pharmaceuticals, Inc.: Research Funding; pfizer: Honoraria; boehringer ingelheim: Research Funding; agios: Research Funding; Cellerant: Research Funding. Melnick:Janssen: Research Funding. Altman:Novartis: Honoraria; BMS: Honoraria; Janssen: Honoraria; Syros: Honoraria. Al-Kali:Novartis: Research Funding; Celgene: Research Funding.

Abstract Background We have previously reported on the high prevalence and severity of insomnia amongst a large international cohort of MPN patients (Emanuel JCO 2012). We sought to further analyze the relationships between insomnia and the MPN disease features (in particular splenomegaly, status of blood counts), individual MPN symptom prevalence and severity, language, and overall quality of life. Methods Data was collected among an international cohort of patients with MPNs. Subjects completed the BFI, MPN-SAF, and EORTC QLQ-C30 instruments. Surveyed symptoms on the MPN-SAF included the patient’s perceptions of common MPN-related symptoms and overall quality of life (QOL) on a 0 (absent) to 10 (worst imaginable) scale. Specifically, the MPN-SAF insomnia item asked about “difficulty sleeping”. Total symptom score (TSS) was computed based on 10 symptom items using the published scoring algorithm on a 0 (all reported symptoms absent) to 100 (all reported symptoms worst imaginable) scale. Pairwise associations between the MPN-SAF insomnia item and continuous and categorical covariates were investigated using Pearson correlations and analysis of variance/t-tests, respectively. Multivariate regression models were used to investigate impact of groups of covariates on the insomnia item with the final multivariate model selected using forward regression. Results Demographics A total of 1992 MPN patients (essential thrombocythemia=834, polycythemia vera=703, myelofibrosis=449, unknown=6) completed the insomnia item. Participants were of typical age (median=61, range-15-94) and gender (female=54%). Overall, 1307 subjects endorsed the MPN insomnia item (score >0) with an overall mean symptom score of 3.0 (median=2.0, SD=3.1. range=0-10); 603/1992 (30%) of patients had severe insomnia related complaints (score >4). Univariate Analysis Among QLQ-C30 functioning scales, emotional functioning most highly correlated with the MPN-SAF insomnia item (r=-.47, p<0.001) with all other domains also having statistically significant but slightly weaker correlation (all p<0.001). Among QLQ-C30 symptom scales, insomnia (r=.79, p<0.001) and fatigue (r=.45, p<0.001) most highly correlated with the MPN-SAF insomnia item with all other QLQ-C30 symptoms having correlations between .13 and .37 (all p<.001). Among MPN-SAF items, the MPN-SAF insomnia item correlated with all MPN-SAF items (all p<0.001) including the TSS (r=0.55, p<0.001) and most highly with depression (r=.52, p<0.001), concentration problems (r=.43, p<0.001), overall QOL (r=.41, p<0.001), night sweats (r=.41, p<0.001), and extremity tingling (r=.40, p<0.001). MPN-SAF insomnia significantly differed by gender (means: M 2.4, F 3.4; p<0.001), language (means ranged from 2.6 [Italian] to 3.6 [German]; p=0.01), anemia (means: absent 2.8, present 3.5; p<0.001), prior hemorrhage (means: no 2.9, yes 3.7; p=0.01), and requiring red blood cell transfusion (means: no 2.9, yes 3.6; p=0.03), with a trend for a difference by MPN type (ET mean=2.7, PV mean=3.0, MF mean=3.2; p=0.06). Multivariate Analysis In a multivariate model of MPN-SAF insomnia containing all QLQ-C30 functioning scales, physical, emotional, and cognitive functioning along with global health status/QOL were all significant (all p<0.001). Numerous symptoms were also significant in a multivariate model of MPN-SAF insomnia containing all other MPN-SAF symptoms (all p<0.05: headaches, extremity tingling, depression, sexual problems, night sweats, pruritus, fever, and QOL). The final multivariate model based on forward regression starting with all demographics, clinical variables, and patient-reported QLQ-C30 scales and MPN-SAF items found age, gender, QLQ-C30 emotional functioning and MPN-SAF items to be significant. Conclusions Insomnia is highly prevalent and severe in MPN patients and closely correlates with most other MPN-related symptoms and functional domains bearing a multi-faceted impact on overall quality of life. Correlations between insomnia and emotional, cognitive, and physical complaints including depression/sad mood, concentration problems, night sweats, and numbness/tingling in the extremities suggest that the cause of MPN-related sleep complaints is likely complex. Future studies should evaluate the impact of interventions on MPN associated insomnia as well as its biological underpinnings. Disclosures: Etienne: novartis: Consultancy, Membership on an entity’s Board of Directors or advisory committees; Bristol Myers Squibb: Consultancy, Membership on an entity’s Board of Directors or advisory committees; Pfizer: Membership on an entity’s Board of Directors or advisory committees; Ariad: Membership on an entity’s Board of Directors or advisory committees. Roy:Novartis, BMS: Honoraria. Harrison:Novartis: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sanofi: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; YM Bioscience: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Celgene: Honoraria; Shire: Speakers Bureau; S Bio: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Gilead: Honoraria, Membership on an entity’s Board of Directors or advisory committees. Birgegard:Vifor Pharma: Honoraria.

Abstract Introduction We have previously developed a primary human bone marrow model in CLL which allows us to study marrow derived mesenchymal stroma cells (MSC) and mimic in vivoMSC-leukemic interactions in CLL (Ding, Blood, 2010) These interactions proved to be bidirectional with functional implications for both cell types. However the biologic and clinical implications of these bilateral cellular interactions in relation to MSC function in CLL patients have not been completely studied. MSC are clearly established as an essential component in forming supportive marrow niches for hematopoiesis. Our focus in this study thus was to further investigate on the status of CLL MSC function in comparison with normal MSC and the impact of the leukemic CLL B cell on MSC function and its role in forming marrow niches in CLL. Methods Bone marrow (BM) aspirates of CLL patients or normal age-matched subjects were used to generate MSC and these MSC were then assessed for various functions. Specifically we assessed the growth, differentiation capacity, gene expression, cytokine secretion profile and transcriptome analysis of CLL and normal MSC using colony forming unit (CFU) assay, MSC differentiation assay, Affymetrix U133 2.0 plus array and RNA sequencing respectively. To determine MSC CFU frequency, fixed number of nucleated cells (5 or 10 million) from BM aspirates were added in MSC growth medium for 10 days to form CFU. CFU frequency was then calculated by dividing the number of MSC colonies by the fixed number of inputted nucleated cells. In order to test the specific gene changes that occurred in MSC after their interaction with CLL leukemic cells, normal MSC were co-cultured with CLL cells for 1 week and subsequently followed by cell growth, gene expression analysis with RNA sequencing and cytokine profiles using a multiplex assay. Results CLL MSC generated significantly lower CFU colonies compared to normal subjects (CLL [n=24] vs normal [n=6] mean: 2.2 vs. 22 CFU per million nucleated cells, p=0.01). In order to test if the lower number of CLL MSC CFU was due to their reduced growth capacity or lower frequency, we then performed the CFU assay using identical numbers of CLL and normal MSC at the start of culture. CLL MSC was found to have significantly lower CFU capacity compared to normal MSC (mean: 2.1 [CLL] vs 4.5 [normal] CFU/10 input cell, n=7 in each group, p=0.03). To investigate the mechanism(s) for the reduced growth capacity of CLL MSC, we compared the gene expression profiles of non-stimulated CLL vs. normal MSC (n=10 for each group) with the following outcomes: CLL MSC had increased expression of cell cycle inhibitor: p16(Ink4a) and p57, both key markers of cell senescence (Baker, Nature, 2011); CLL MSC overexpressed homeobox B cluster of transcription factors, key regulator for cell development and differentiation. Wnt inhibitors DKK1/DKK2 and non-canonical Wnt 5b known to be associated with aging were found to be 10 and 2 fold more elevated in CLL MSC. In addition, MSC abundantly produced a milieu of the cytokines MCP-1/IL-8/IL-6/IL-1Ra after interaction with CLL leukemic cells. These cytokines are associated with a senescent associated secretory phenotype (SASP). Co-culture experiments of normal MSC with CLL Leukemic cells revealed significant impact of leukemic cells on normal MSC functions. Co-culture with a low density of CLL leukemic cells (CLL to MSC ratio: ≤10,000/1) increased MSC growth (1.2 fold). However, high density co-culture of CLL cells with MSC (CLL to MSC ratio of 100,000/1) inhibited MSC growth (0.8 fold). Transcriptome analysis of normal MSC before and after one week of co-culture with CLL leukemic cells showed that normal MSC had alteration of ~1500 genes. Many of the modified genes (CDKN2B, DKK2, LIF, HGF, FOXQ1 etc) are known to be involved in regulation of cell growth and senescence. Conclusion Collectively, these results demonstrated that bone marrow derived CLL MSC have decreased proliferative potential and possess senescent phenotypes. Importantly these senescent features were inducible in normal MSC after their interaction with CLL leukemic cells implying that leukemic B cells can educate MSC to become senescent. The implications of the CLL MSC senescence status are multiple and include: defective hematopoietic niches due to dysfunctional MSC, immune dysregulation and the enhanced nurturing of CLL B cell by these MSC. We are now investigating several of these latter features in our current work. Disclosures Shanafelt: Genentech: Research Funding; GlaxoSmithKline: Research Funding; Celegene: Research Funding; Cephalon: Research Funding; Pharmacyclics/Jannsen: Research Funding; Hospira: Research Funding; Polyphenon E Int'l: Research Funding. Kay:Genetech: Research Funding; Pharmacyclics: Research Funding; Hospira: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees.

Abstract Background. A recent meta-analysis of 9 case-control and 5 cohort studies reported a positive association of transfusion history with risk of NHL (RR=1.20; 95% CI 1.07-1.35), which was only evident in cohort (RR=1.25) and not case-control (RR=1.05) studies (Castillo et al., Blood 2010;116:2897-2907). Risk was similar in men and women, and for transfusions before or after 1992. In subset analyses, elevated risk was only apparent for chronic lymphocytic leukemia (CLL) and not diffuse large B-Cell lymphoma (DLBCL) or follicular lymphoma, but power was low. To further investigate these findings, particularly from studies conducted after 1990, better assess confounding, and address heterogeneity by NHL subtypes, we conducted an individual-level, pooled analysis of 13 case-control studies in the InterLymph Consortium (including 11 studies conducted after 1990; 8 studies were not included in the published meta-analysis). Methods. There were a total of 10,805 cases and 14,026 controls with transfusion data from 13 studies conducted in Europe, North America, and Australia. Transfusion history and other risk factors were self-reported in interviewer-administered or self-administered questionnaires. All risk factor data were harmonized centrally, and cases were grouped into NHL subtypes according to the WHO classification using guidelines from the InterLymph Pathology Working Group. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression, adjusted for age, sex, and study center. Results. The median age at diagnosis was 60 years for cases (range, 18-97) and 59 years for controls (range, 16-97). The overall prevalence of a history of any transfusion in controls was 15.5%, was higher in women (18.6%) than men (13.0%), and increased with age, but was not associated with race/ethnicity (Asian, Black, Hispanic, White, other) or geographic region after adjusting for age and sex. Among whites, history of any transfusion was inversely associated with NHL risk among men (OR=0.74; 95% CI 0.65-0.83) but not women (OR=0.92; 95% CI 0.83-1.03); there were no significant results for other race/ethnicity groups, and ORs were highly variable and imprecise due to small sample sizes. Thus analyses were restricted to white men, where there was no trend with the number of transfusions, time since first transfusion, age at first transfusion, or decade of first transfusion. Further adjustment for socioeconomic status, body mass index, smoking, alcohol use or hepatitis C virus (HCV) seropositivity did not alter these results. The associations were stronger in hospital-based (OR=0.56; 95% CI 0.45-0.70) than population-based (OR=0.84; 95% CI 0.72-0.98) studies, and were stronger in studies from Southern Europe (OR=0.53; 95% CI 0.36-0.79) than northern Europe (OR=0.67; 95% CI 0.53-0.83) or North America (OR=0.82; 95% CI 0.70-0.98). For NHL subtypes, statistically significant inverse associations were observed for follicular lymphoma (OR=0.70; 95% CI 0.56-0.88), DLBCL (OR=0.72; 95% CI 0.59-0.87), and CLL/SLL (OR=0.67; 95% CI 0.52-0.87), whereas weaker and non-statistically significant associations were observed for mantle cell (OR=0.81; 95% CI 0.54-1.23), marginal zone (OR=0.78; 95% CI 0.54-1.15), lymphoplasmacytic (OR=0.82; 95% CI 0.47-1.42) and peripheral T-cell (OR=0.83; 95% CI 0.49-1.40) lymphomas. Conclusion. Contrary to earlier results, transfusion history was inversely associated with risk of NHL and the common subtypes of follicular lymphoma, DLBCL and CLL/SLL among white men, whereas associations were null among white women and other racial/ethnic groups. These results were not explained by confounding by lifestyle factors or HCV seropositivity, era of first transfusion, hospital versus population-based study design, or geographic location. Despite dramatic changes in transfusion practice over the past 40 years, results were similar for decade of first transfusion, suggesting secular trends are a less likely explanation. Our results are unexpected and bias cannot be ruled out. Further studies, particularly cohort studies, are needed to clarify the role of transfusion history in NHL risk. Disclosures No relevant conflicts of interest to declare.

Abstract DNA methylation at cytosine position 5 (5mC) is a genetic modification that regulates gene expression and is critical for cancer initiation and development. The methylcytosine dioxygenase TET2 participates in active DNA demethylation by converting 5mC to 5-hydroxymethylcytosine (5hmC) and its subsequent intermediates thereby regulating gene expression. TET2 gene is frequently mutated in hematological disorders, including 15-25% of myelodysplastic syndrome (MDS) cases. Loss of TET2 function leads to DNA hypermethylation and subsequent dysregulated gene expression in hematopoietic stem cells, and has been considered as an initial step of myeloid malignant transformation including MDS and acute myeloid leukemia (AML). While enzymatic activity of TET2 is well studied, little is known about post-translational modifications (PTMs) that regulate its activity in hematopoietic cells. Lysine acetylation, one of the most crucial PTMs, occurs in a variety of proteins and modulates protein-protein or protein-nucleic acids interactions. Here, we first observed that ectopic expression of histone acetyltransferase EP300 or CREB binding protein (CBP) increased the endogenous TET2 acetylation in 293T cells. Mass spectrometry analysis of TET2 identified several conserved acetylated lysine residues located on the exterior surface of its catalytic domain (CD), which is predicted to be essential for the interaction of TET2 with DNA. Modeling of TET2/DNA interaction using x-ray crystal structure (PDB code: 4NM6) indicates acetylated TET2 interferes with DNA binding thereby impairing the catalytic activity of the enzyme. Like other acetylated proteins, TET2 modification is reversible, since ectopic expression of the protein deacetylase Sirtuin1 (SIRT1) significantly decreases acetylation of TET2. A domain mapping analysis revealed that SIRT1 preferentially interacts with TET2 CD, further supporting the regulatory role of SIRT1 on TET2. To explore the role of SIRT1 mediated deacetylaion of TET2 in more physiological condition, SIRT1 knockdown (KD) MDS-L cells as well as SIRT1 knockout (KO) murine hematopoietic c-kit+ cells were used. In MDS-L cells derived from a MDS patient, SIRT1 KD promoted hyperacetylation of endogenous TET2 which is associated with 50% decrease in 5hmC levels compared to control (p=0.03, n=3). Similarly, SIRT1 KO murine c-Kit+ cells showed TET2 hyperacetylation and 62% decrease in 5hmC compared to wildtype (WT) counterpart (p=0.009, n=5). Phenotypically, the transforming ability of SIRT1 shRNA transduced MDS-L cells was evaluated in vitro through serial replating assay. In contrast to first plating which showed no difference between two groups, the number of colonies derived from SIRT1 KD cells was 2.39 fold higher than that from the control shRNA transduced group after two rounds of replating (p=0.0002, n=3). Importantly, we tested the in-vivo effect of SIRT1 KD on MDS-L cells engrafted in immunodeficient NSGS mice. SIRT1 KD significantly enhanced MDS-L cell engraftment compared to control shRNA (50±5% of human CD45+ cells in SIRT1 KD group vs. 19±4% human CD45+ cells in control group, p=0.003, n=6). Interestingly, increased transformation capacity of SIRT1 KD MDS-L cells was associated with decreased expression of TET2 regulated tumor suppressor genes. For example, expression levels of Mtss1 and Dusp6 were significantly decreased in SIRT1 KD MDS-L cells compared to control shRNA counterpart (Mtss1, 49±5% decrease compared to control, p=0.005; Dusp6, 25±2% decrease compared to control, p=0.01). Similar results were observed in SIRT1 KO cells. The validation of physical binding of TET2 to its targets is ongoing. Moreover, the effect of an SIRT1 allosteric activator-SRT1720 in MDS-L cells is similar to that of Vitamin C, a known TET2 activator. Specifically, SRT1720 significantly increased Mtss1 expression in MDSL cells (p=0.0005, n=3), indicating that SIRT1 agonist may lead to activation of TET2 downstream tumor suppressor genes. In summary, our data demonstrate that TET2 activity can be functionally modified by acetylation and may be enhanced in MDS patients that do not harbor loss-of-function mutations through the SIRT1 mediated deacetylation. These results support further exploration of molecular mechanisms inducing TET2 acetylation, and evaluation of SIRT1 activation as a potential therapeutic approach in MDS. Disclosures No relevant conflicts of interest to declare.

Abstract Background We have previously reported on the significant, but heterogeneous baseline MPN symptom burden among an international sample of MPN patients (including essential thrombocythemia (ET), polycythemia vera (PV), and myelofibrosis (MF)) utilizing the MPN Symptom Assessment Form (MPN-SAF) and the derivative Total Symptom Score (MPN-SAF TSS). Recent clinical trials have sought to determine optimal MPN symptom response criteria, such as absolute 10 point improvement in MPN SAF TSS for ET/PV (ELN Criteria, Barosi et. al. Blood 2013) and 50% reduction in MPN-SAF TSS for MF (IWG-MRT, Tefferi et. al. Blood 2013). We sought to determine the role of improvement in MPN-SAF TSS quartiles as potential thresholds to assess symptomatic response to therapy. Methods Utilizing prospectively gathered MPN-SAF TSS (Emanuel et. al. JCO 2012) in patients we assessed potential thresholds of response by evaluating quartile thresholds for severity of symptom burden. The MPN-SAF TSS was scored as the average of 10 symptoms (individual symptoms scores of 0-10, with a total score of 0 (best) to 100 (worst)). MPN-SAF TSS quartiles were identified by the percentage of scores between 0-24% (quartile 1 (Q1)), 25-49% (quartile 2 (Q2)), 50-74% (quartile 3 (Q3)), 75-100% (quartile 4 (Q4)). Results MPN-SAF TSS Quartiles: MPN-SAF TSS quartiles were identified among 1858 MPN patients (ET N=775, PV N=654, and MF N=423). Overall MPN-SAF TSS scores of 0 - 7 were designated as Q1, 8 - 17 as Q2, 18 - 31 as Q3, and ≥ 32 was as Q4. MPN-SAF TSS scores were significantly different between clusters (p<0.001). Associations Between Quartiles and Demographic/ Disease Factors: As quartiles increased, the proportion of PV and ET patients diminished and MF increased (Table 1, p<0.001). Cytopenias and transfusion dependence increased in prevalence in the higher quartiles (p<0.001). A history of prior thrombosis was also significantly more prevalent in the quartiles with highest symptom burden (p<0.001). The prevalence of women was significantly higher among the more symptomatic quartiles females 48.9% Q1, 49.4% Q2, 58.4% Q3, and 60.1% Q4; p<0.001). Associations Between Individual Symptoms and MPN-SAF TSS Quartiles: All individual symptoms measured in the MPN-SAF TSS were significantly worse in quartiles as they increased (p<0.0001). Evaluation of Prognostic Scoring and MPN-SAF TSS Quartiles: Comparison of each patients individual risk score (IPSET, PV, DIPSS for MF) and worsening symptom quartile showed the highest correlation with MF patients (DIPSS) (Table 1). However, ET and PV risk scores were not surrogates for symptom burden by quartile. Conclusions Distribution of MPN patient symptomatic burden by MPN-SAF TSS quartiles provides an easy-to-calculate method to cluster and analyze MPN patients of similar burden. Although MF patients are most prevalent in the most severe quartile of MPN symptomatology it is notable that Q4 has many patients with PV and ET. Future prospective efforts are ongoing to assess the potential of using changes in quartile (i.e. improving from Q3 to Q1) as potential symptomatic response thresholds. Disclosures: Etienne: novartis: Consultancy, Membership on an entity’s Board of Directors or advisory committees; Bristol Myers Squibb: Consultancy, Membership on an entity’s Board of Directors or advisory committees; Pfizer: Membership on an entity’s Board of Directors or advisory committees; Ariad: Membership on an entity’s Board of Directors or advisory committees. Roy:Novartis, BMS: Honoraria. Harrison:Gilead: Honoraria, Membership on an entity’s Board of Directors or advisory committees; S Bio: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Shire: Speakers Bureau; Celgene: Honoraria; YM Bioscience: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; Novartis: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding, Speakers Bureau. Vannucchi:Novartis: Honoraria, Membership on an entity’s Board of Directors or advisory committees. Birgegard:Vifor Pharma: Honoraria.

Abstract BACKGROUND: Most cancer patients with bone metastases report significant pain and substantial impairment in their ability to function. In particular, patients with MM are susceptible to bone pain because of bone damage. Patient-reported outcomes such as a general health outcome measure and a legacy pain instrument may provide valuable information in determining the impact of this condition. The goal of this study was to provide a descriptive profile of health status for cancer patients using the EQ-5D-3L (EQ-5D), a commonly used tool to measure health utility scores. Another goal is to evaluate the predictive information provided by the Brief Pain Inventory (BPI), a self-report pain assessment tool designed to capture pain severity and interference in patients. These information may be useful in estimating the health status of patients where the EQ-5D was not administered. METHODS: Data was pooled across three denosumab registrational trials '20050136', '20050103', and '20050244'. Patients completed the EQ-5D and the BPI at baseline. Eligible patients had histologically confirmed advanced cancers, radiographic evidence of at least one bone metastasis (or lytic bone lesion from multiple myeloma), ECOG of 2 or better and adequate organ function. Using data from patients with MM (N=168), descriptive statistics were used to present summary information on health-related quality of life states and utility scores. Linear regressions were used to examine how BPI severity and interference subscale scores relate with EQ-5D utility scores. Ordinal regressions were used to evaluate how well BPI items predict EQ-5D individual items. Bonferroni adjustments were made when evaluating the relationships of BPI items to individual EQ-5D items. These analyses were repeated using data across several groups of cancer patients to determine if similar results can be obtained (breast cancer, N=2,044, prostate cancer, N=1,819 and others, N=1,509). RESULTS: About 9% of MM patients reported perfect health compared with 11% of all cancer patients. Of the 5 dimensions measured by the EQ-5D, the MM cohort rated pain (80%) the highest with moderate to extreme problems. This was followed by usual activities (68%), mobility (63%), anxiety/depression (49%), and self-care (36%). Similar order was observed across all cancer groups, but with slightly lower percentages for most items: pain (78%), usual activities (58%), mobility (55%), anxiety/depression (57%), and self-care (26%). Although pain interference subscale score explained more of the variability in the EQ-5D utility scores compared with pain severity items in the MM cohort (39% vs 31%) and for all patients (41% vs 34%), model fit was less than ideal (mean squared error=0.23 - 0.25). Hence, BPI items were fitted into individual EQ-5D items. Ordinal regression models fitting BPI items into individual EQ-5D items for the MM cohort showed good predictive power as measured by the concordance index c for mobility (86%), self-care (80%), usual activities (83%), pain (90%) and anxiety/depression (78%). For all patients, similar model fit were obtained for mobility (83%), self-care (78%), usual activities (81%), pain (90%) and anxiety/depression (72%). Further examination of the ordinal regression models across all groups showed that three BPI pain severity items, 'pain at its worst', 'average pain' and 'pain now' in addition to interference with activity and interference with work significantly predicted the EQ-5D pain item. Five interference items, activity, walking ability, work, sleep and enjoyment of life significantly predicted the EQ-5D usual activities item. Finally, 'pain now' and four interference items, relationship with others, enjoyment of life, mood, and activity significantly predicted the EQ-5D anxiety/depression item. CONCLUSIONS: Patients with MM reported several functional limitations on the EQ-5D. Majority of the patients reported moderate to extreme problems in all EQ-5D dimensions except self-care. Model fit of ordinal regression models relating BPI items with EQ-5D items are reasonable underscoring the benefit of using the BPI for planning patient care and health status evaluation. This consistency was also found across cancer groups that primarily include breast and prostate. The resultant model demonstrates the significant contribution of pain severity and interference in determining health status in this patient population. Disclosures Mendoza: Amgen Inc.: Consultancy. Shi:Amgen Inc.: Consultancy. Ma:Amgen Inc.: Employment. Zhang:Amgen Inc.: Employment. Qian:Amgen Inc.: Employment. Cleeland:Amgen Inc.: Consultancy.

Abstract T-cell prolymphocytic leukemia (T-PLL) is a rare disease with an aggressive clinical course and a median overall survival of less than three years. Although almost 75% of T-PLL patients are reported to harbor translocations causing the activation of the proto-oncogene TCL1A, T-PLL is genetically heterogenous: most T-PLL patients also have mutations or deletions in the ATM gene and the genes involved in the JAK-STAT pathway are mutated in 76% of cases. There is an urgent need for more rational based therapies, but clinical trials are difficult to perform due to the rareness of the disease. Here, we systematically explored the diversity of drug responses in T-PLL patient samples ex vivo using a drug sensitivity and resistance testing (DSRT) system including 306 oncology drugs (approved or investigational). We also aimed to determine any associations between the genetic aberrations and drug sensitivities in T-PLL patients. Primary mononuclear cells were gathered from 30 T-PLL patients for drug testing. Cells were plated in 384-well plates and subjected to the 306 substances using a 10,000-fold concentration range. After 72 hours, cell viabilities were measured, the results were depicted as dose-response curves for each compound, and differential drug sensitivity scores (sDSS), representing leukemia-specific responses, were computed by comparing patient samples to healthy donors. Drug response profiles across patients were clustered and visualized by hierarchical clustering. The subgroups resulting from the clustering were statistically compared using a two-sample t-test to understand which drug classes were driving the grouping. To delineate heterogeneous pathway dependencies, drug sensitivities were correlated with somatic genetic variants and recurrent chromosomal aberrations. Genetic characterization was performed by targeted amplicon sequencing of tumor cells to profile known recurrent genetic variants (STAT5b, IL2RG, JAK1, JAK3, ATM). Information on chromosomal aberrations (TCL1A translocations, ATM deletions) was derived from parallel clinicopathologic databases. Amplicon sequencing revealed that 70% of T-PLL patients (21/30) harbored a mutation in genes involved in the JAK-STAT pathway (JAK1, JAK3, STAT5b or IL2RG). The most prevalent mutation led to an M511I amino acid exchange in the JAK3 protein (26% of patients). Interestingly, the STAT5b mutations (5/30) did not coexist with any of the JAK mutations in our cohort. Based on DSRT analysis, all T-PLL samples were sensitive to the CDK-inhibitor SNS-032 and the anti-cancer antibiotic actinomycin D. Next, we clustered patients using sDSS values for all 306 different substances, and this showed that patient samples could be divided into 3 main groups, based on their drug responses (Figure). According to two-sample t-test, the grouping was driven by the selective sensitivities of Groups II and III to HDAC inhibitors (belinostat, panobinostat, quisinostat, CUDC-101 and vorinostat) and the selective sensitivity of Group III to PI3K/AKT/mTOR inhibitors (AZD-8055, MK-2206, apitolisib, dactolisib, PF-04691502, ZSTK474, and omipalisib), HSP90 inhibitors (BIIB021, luminespib, alvespimycin, and tanespimycin) as well as JAK inhibitors (ruxolitinib, momelotinib, tofacitinib, gandotinib). Group I samples were on the other hand relatively resistant to these classes of drugs. Surprisingly, despite the prevalence of the signature event of activation of TCL1 (the established AKT coactivator) in nearly all cases, only a subset of cases (group III) responded to PI3K/AKT/mTOR inhibitors. Strikingly, the grouping of selective responses to HDAC, JAK, PI3K/mTOR/Akt and HSP90 inhibitors did not link to the presence of JAK/STAT mutations, TCL1A translocations, or ATM deletion status. Ex vivo drug screening of primary T-PLL samples revealed heterogenous selective drug responses in specific drug classes (such as HDAC-, JAK-, HSP90- and PI3K/Akt/mTOR-inhibitors). Surprisingly, the drug response patterns did not correlate with known recurrent genetic aberrations suggesting that sequencing for recurrent genetic biomarkers cannot easily be turned into effective therapeutic strategies in T-PLL, and that further elucidation of the biological pathways driving T-PLL is needed. Figure 1. Mutation status and clustering of HDAC-, PI3K/mTOR/Akt-, HSP90-, and JAK-inhibitor responses in PLL patients based on sDSS values Figure 1. Mutation status and clustering of HDAC-, PI3K/mTOR/Akt-, HSP90-, and JAK-inhibitor responses in PLL patients based on sDSS values Disclosures Koschmieder: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel reimbursement for scientific conferences, Research Funding; Novartis Foundation: Research Funding; Baxalta/CTI: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen Cilag: Other: Travel reimbursement for scientific conferences ; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel reimbursement for scientific conferences. Wennerberg:Pfizer: Honoraria, Research Funding. Ding:Merek: Research Funding. Mustjoki:Pfizer: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding.