Lasho, Terra

Abstract Introduction: CMML is a heterogeneous malignancy characterized by peripheral monocytosis and a propensity for AML transformation. Given the low incidence of CMML and its broad range complexity, a large disease-specific data set is necessary to discern independent co-variates predictive of disease behavior. Several prognostic models derived from smaller data sets have been developed to stratify CMML patients into distinct groups that are predictive for OS. However, the validity of these models in a large international data set has never been investigated. Here, we present the largest International CMML data base established to date and report key baseline characteristics predictive for disease outcome. We externally validate and perform a detailed statistical comparison between the International Prognostic Scoring System (IPSS), Revised (R)-IPSS, Global MD Anderson Scoring System (MDASC), MD Anderson Prognostic Score (MDAPS), Dusseldorf Score (DS), Mayo, and Spanish Scoring Systems (CPSS). Methods: Data were abstracted by each contributing institution and deposited for central data review at the Moffitt Cancer Center. Manual review of cases was performed to ensure data quality prior to analysis. Only WHO defined CMML was included. The primary objective of this study was to establish an international CMML data set and validate the above models calculated at the time of presentation to each center. All prognostic models were calculated as previously described. The Kaplan–Meier (KM) method was used to estimate median OS and the log rank test was used to compare KM survival estimates with SPSS version 21.0. Random Forest Survival (RSF) and ROC analysis was done with R. Results: Between July 1981 and June 2014, 1832 CMML patients were captured in the International CMML database. Median age at diagnosis was 70 (16-93) years with a male (67%) predominance. By the WHO classification, the majority of patients had CMML-1 (79.9% vs. 20.1%) and most patients were evenly subcategorized as MPN-CMML (49.8%) versus MDS-CMML (50.2%) by FAB criteria. Splenomegaly was demonstrable in 25%. Most patients had favorable cytogenetics by both IPSS (70%) and CPSS (67.6%) classification schemas. Mean BM blast % was 5.6 and mean monocyte count was 4.85x103/dL. Median OS of the entire data set was 31.6 months. All tested prognostic models were valid and able to predict OS (p<0.0001). To compare relative model performance, 1013 complete cases with sufficient data to calculate all risk models were compared using time dependent receiver operator characteristic (ROC) curves and their area under the curves (AUC). ROC curves were calculated for OS at 36 months. The R-IPSS model had the highest AUC (0.694) while the DS model had the lowest (0.635). The difference in AUC between the R-IPSS and DS models was statistically significant (p = 0.003) whereas there was no significant difference from other models tested. To determine which models were most vulnerable to reclassification from low-risk to higher risk, we calculated a vulnerability score defined by the number of models able to up-stage low-risk disease in more than 15% of cases. Using this metric, the Mayo and MDASC scores were least vulnerable to up-staging by other models. Lastly, we used an orthogonal method for determination of variable importance (RSF for OS at 36 months). RSF is an ensemble method of classification and regression tree methodology. Ranking of variables by their weighted importance determined by this procedure identified the top five variables were hemoglobin, circulating blasts, platelet count, number of cytopenias, and karyotype. A new risk model was developed using the results of the RSF with an AUC of 0.720, which was comparable but not significantly different than other modern scoring systems. Conclusions: This represents the largest international CMML-specific data set derived from eight unique centers of excellence. All modern prognostic models were valid and performed comparably. Despite novel strategies for variable importance discovery, an improved model could not be constructed. This data suggest that the power of clinical variables has reached an asymptote and highlights the need for incorporation of molecular and other novel biological features. This data set is currently being populated with molecular data and is being leveraged to test published CMML molecular prognostic models which will be disclosed at the time of presentation. Disclosures Garcia-Manero: Epizyme, Inc: Research Funding. Fenaux:Celgene, Janssenm, Novartis: Research Funding. Kantarjian:ARIAD, Pfizer, Amgen: Research Funding. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen Corp: Membership on an entity's Board of Directors or advisory committees; Boehringer-Ingelheim Corp: Membership on an entity's Board of Directors or advisory committees.

Abstract Abstract 925 Diffuse large B-cell lymphomas (DLBCL) consists of biologically distinct subtypes: Germinal Center B-cell (GCB)–like and Activated B-cell (ABC)-like. Studies to date suggest that patients with tumors that have ABC features have an inferior survival; therefore, it is important to develop new therapies specifically for ABC-type DLBCL based on mechanistic differences. It has been shown that the ABC-DLBCL has high levels of total and phosphorylated STAT3 (pSTAT3) protein and this STAT3 activity may play a role in the survival of ABC-DLBCL cells. Indeed, when ABC and GCB cell were incubated with the novel JAK2 inhibitor TG101348 (TargeGen, San Diego, CA) we found potent cytotoxicity (LD50 2μM) in ABC DLBCL but not in GCB DLBCL. This provides further rationale to study the regulation of STAT3 in the survival of ABC type DLBCL cells. In studies of HDAC expression in ABC DLBCL cells, we found over-expression of the class 1 histone deacetylases, specifically HDAC1 and HDAC3. We then performed co-immunoprecipitation experiments to learn the functional interaction between STAT3 and HDACs. We found that STAT3 formed complexes with HDAC1 to a greater extent than HDAC3. We also showed that STAT3 did co-precipitate with HDAC1 suggesting a reciprocal relationship between these two proteins. These results suggested that HDAC1 (but not HDAC3) might be involved in the regulation of STAT3. The HDAC inhibitor LBH589 (LBH, Novartis Pharm) was more cytotoxic to ABC (LD50, 10-20nM) than GCB (LD50, 50-100nM) and was shown to dephosphorylate STAT3. These results led to experiments designed to determine the effect of LBH on STAT3 acetylation. When ABC cells were incubated with LBH, co-immunoprecipitation data showed a dose-dependent increased in acetylation of STAT3 without significant change on the levels of STAT3 immunoprecipitated. Next, we asked that how LBH is dephosphorylating STAT3. One potential mechanism is activation of a protein phosphatase. Immunoprecipitation of protein phosphatase 2A (PP2A) in the lysates of LBH-treated cells followed by western blotting of STAT3 demonstrated a positive correlation between LBH dose and amount of STAT3 co-immunoprecipitated with PP2A. Our data show that when LBH is incubated with ABC cells, the LBH increases binding of PP2A to STAT3 and the increased phosphatase activity turns off STAT3 signaling. Since both HDAC inhibitor (LBH) and the JAK2 inhibitor (TG) had selective cytotoxic effects on ABC cells, and since both agents dephosphorylate STAT3, we combined the two drugs. We found that the combination exhibited enhanced inhibitory effects on the growth of ABC cells and was able to alter the association of STAT3 with HDAC1 and subsequently dephosphorylate STAT3 to greater extent than either agent alone. Furthermore, we knocked down HDAC1 expression (through siRNA) in OCILy10 (ABC) cells and showed that inhibition of HDAC1 inhibits constitutively activated STAT3. This data suggests that inhibiting HDAC1 expression results in STAT3 dephosphorylation. In summary, we have demonstrated that a key consequence of HDAC expression in ABC cells is continuous activation of STAT3. These data indicate that HDACs activate STAT3 and that PP2A may be important in maintaining STAT3 in the activated state in the ABC cells. This study describes a new mechanism by which STAT3 mediates ABC cell survival and provides the rationale for targeting ABC type DLBCL by simultaneously inhibiting HDAC activity and STAT3 activation by pharmacologic grade inhibitors such as LBH589 and TG101348, which are currently in clinical trial. A phase 1 and 2 trial of JAK2 inhibitor, TG101348 for ABC/GCB type DLBCL is planned. Disclosures: No relevant conflicts of interest to declare.