ALBERT

Description: Anaplastic Large Cell Lymphoma (ALCL) is a T-cell malignancy predominantly driven by a hyperactive Anaplastic Lymphoma Kinase (ALK) fusion protein. ALK inhibitors such as crizotinib provide alternatives to standard chemotherapy with reduced toxicity and side effects. Children with lymphomas driven by NPM1-ALK fusion proteins achieved an objective response rate to ALK inhibition therapy of 54-90% in clinical trials. However, a subset of patients progress within the first 3 months of treatment. The mechanism for the development of ALK inhibitor resistance is unknown. Through genome-wide CRISPR activation and knockout screens in ALCL cell lines combined with RNA-seq data derived from ALK inhibitor relapsed patient tumors, we show that resistance to ALK inhibition by crizotinib in ALCL can be driven by aberrant upregulation of IL10RA. Elevated IL10RA expression rewires the STAT3 signaling pathway bypassing otherwise critical phosphorylation by NPM1-ALK. IL10RA expression does not correlate with response to standard chemotherapy in pediatric patients suggesting that combination of crizotinib with chemotherapy could prevent ALK-inhibitor resistance-specific relapse. Trials registered as NCT01979536/NCT02034981/UMIN000028075.

Description: Background: Twenty percent of patients (pts) with high-tumor burden follicular lymphoma (FL) develop progression/relapse of disease within 24 months of frontline immune-chemotherapy (POD24). Those ultra-high-risk cases are at 50% risk of dying within 5-years since the POD event. Unmet need is to identify such pts at the time of initial treatment. The traditional approach used for building predictive scores (such as FLIPI, PRIMA-PI) is multivariable logistic regression (LR). LR is the tool of choice in case of many predictors (continuous or categorical) and a single binary (yes/no) outcome. Bayesian network (BN) offer an alternative strategy which may overcome several drawbacks of LR (risk of overfitting, missing data handling, problems of odds ratio interpretation), brings more insight into the complex relations among the variables, and offer an individualized prediction. Aim: The goal was to build a model to predict the risk of POD24 from the parameters known at diagnosis and compare LR to BN approach. Methods: The study (ClinicalTrials.gov No NCT03199066) comprised 1394 FL (grade I-IIIA) patients from the Czech Lymphoma Study Group registry treated with frontline rituximab-containing regimen and diagnosed between 10. 4. 2000 and 28. 12. 2016. The following parameters were analyzed: gender, age at diagnosis, clinical stage, lymphoma grade, no. of LNs regions, bone marrow involvement, no. of extranodal localizations, longest tumor diameter, systemic symptoms, performance status, LDH, beta-2-microglobulin, hemoglobin, and leucocyte, lymphocyte, and thrombocyte counts, induction regime, radiotherapy, ASCT, maintenance application, response to treatment, and OS, PFS and POD24 as outcome parameters. POD24 was defined as relapse, progression, change of therapy for 24 months since the induction started. Only parameters known at diagnosis were used for the prediction of POD24. Results: The median age was 59 yrs (range 26-89 yrs) with female predominance (59.2%), advanced disease stage (III/IV) was seen in 85.9% of the cases and FLIPI risk groups distribution was as follows: low (18.8%), intermediate (30.9%) and high (50.3%). The most frequent regime used was R-CHOP (76.8%), followed by R-CVP (12.4%), R-bendamustine (4.7%), intensive protocols (3.3), and fludarabine-based (2.8%). Consolidative IF-radiotherapy was applied in 5.1% and up-front ASCT in 2.9% of the pts. Maintenance immunotherapy was given in 67.1% of the pts. Response to therapy was known in all but 28 pts (98%) with CR/CRu 67.9%, PR 26.6%, SD 1.8%, and PD in 3.2% of the cases. After a median follow-up of 7.64 yrs, 484 (34.7%) of the pts progressed or relapsed and 316 (22.6%) have died. POD24 was recorded in 266 (19.0%) of the pts. The 5-year OS reached 86.4% and 5-year PFS 64.2%. LR model (PFS) building strategy included testing for significance as this model performed better than the model with all parameters. Overfitting was prevented by splitting the data into training (75%) and testing (25%) set. The performance of the model was assessed using the AUC criterion computed on the ROC curve. The LR model reached AUC of 0.69, and at 80% specificity, it reached about 51% sensitivity. Next, the BN (Augmented Naïve Bayes Classifier) was trained. Links of all predictors to POD24 were forced and all links to age and gender were forbidden, otherwise the network structure was inferred from the data. The performance of the BN was similar to the LR - AUC of 0.67 and about 50% sensitivity at the specificity of 80%. Both these models were compared to the standard PRIMA-PI risk classifier and were found to better stratify the population into risk groups (Table 1). An example of a patient is presented who was low-risk according to PRIMA-PI but actually experienced the POD24 event. The BN estimated the probability of the event to 91% (Figure 1). Conclusion: Lymphoma-related death following POD24 remains the most frequent cause of mortality in FL patients. BN modelling is a non-inferior prognostic tool compared to LR in term of POD24 prediction. Unlike LR, it also allows visualisation of complex relations among the predictors and individualized prediction of the patient's POD24 risk, even if some of the predictors are unknown. Both "ad hoc" trained LR and BN were found to better stratify the population into risk groups with respect to POD24 event than the traditional PRIMA-PI score. Acknowledgement: MZ Czech Republic DRO grant (FNOL, 00098892). Disclosures Procházka: F. Hoffmann-La Roche AG: Consultancy, Honoraria; Takeda Pharmaceuticals, Inc: Consultancy, Research Funding. Belada:Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel expenses, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel expenses, Research Funding; Celgene: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel expenses, Research Funding. Trněný:Janssen: Consultancy, Honoraria, Other: Travel Expenses; Gilead: Consultancy, Honoraria, Other: Travel Expenses; Takeda: Consultancy, Honoraria, Other: Travel Expenses; Bristol-Myers Squibb Company: Consultancy, Honoraria, Other: Travel Expenses; Amgen: Honoraria; Abbvie: Consultancy, Honoraria, Other: Travel Expenses; Roche: Consultancy, Honoraria, Other: Travel Expenses; MorphoSys: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Celgene: Consultancy.

Description: B cell receptor (BCR) signaling and T cell interactions play a pivotal role in chronic lymphocytic leukemia (CLL) pathogenesis and disease aggressiveness. CLL cells can utilize microRNAs (miRNAs) and their targets to modulate microenvironmental interactions in the lymph node niches. To identify miRNA expression changes in the CLL microenvironment, we performed complex profiling of short non-coding RNAs in this context by comparing CXCR4/CD5 intraclonal cell subpopulations (CXCR4dimCD5bright vs. CXCR4brightCD5dim cells). This identified dozens of differentially expressed miRNAs including several that have previously been shown to modulate BCR signaling (miR-155, miR-150, and miR-22), but also other candidates for a role in microenvironmental interactions. Notably, all three miR-29 family members (miR-29a, miR-29b, miR-29c) were consistently down-modulated in the immune niches, and lower miR-29(a/b/c) levels associated with an increased relative responsiveness of CLL cells to BCR ligation, and significantly shorter overall survival of CLL patients. We identified Tumor-Necrosis Factor Receptor-Associated Factor 4 (TRAF4) as a novel direct target of miR-29s and revealed that higher TRAF4 levels increase CLL responsiveness to CD40 activation and downstream NFkB signaling. In CLL, BCR-represses miR-29 expression via MYC, allowing for concurrent TRAF4 upregulation and stronger CD40-NFkB signaling. This regulatory loop is disrupted by "BCR inhibitors" (BTK inhibitor ibrutinib or PI3K inhibitor idelalisib). In summary, we showed for the first time that a miRNA-dependent mechanism acts to activate CD40 signaling/T-cell interactions in a CLL microenvironment and described a novel miR-29-TRAF4-CD40 signaling axis modulated by the BCR activity.

Description: Anaplastic large cell lymphoma (ALCL), an aggressive CD30-positive T-cell lymphoma, comprises systemic anaplastic lymphoma kinase (ALK)-positive, and ALK-negative, primary cutaneous and breast implant-associated ALCL. Prognosis of some ALCL subgroups is still unsatisfactory, and already in second line effective treatment options are lacking. To identify genes defining ALCL cell state and dependencies, we here characterize super-enhancer regions by genome-wide H3K27ac ChIP-seq. In addition to known ALCL key regulators, the AP-1-member BATF3 and IL-2 receptor (IL2R)-components are among the top hits. Specific and high-level IL2R expression in ALCL correlates with BATF3 expression. Confirming a regulatory link, IL-2R-expression decreases following BATF3 knockout, and BATF3 is recruited to IL2R regulatory regions. Functionally, IL-2, IL-15 and Neo-2/15, a hyper-stable IL-2/IL-15 mimic, accelerate ALCL growth and activate STAT1, STAT5 and ERK1/2. In line, strong IL-2Rα-expression in ALCL patients is linked to more aggressive clinical presentation. Finally, an IL-2Rα-targeting antibody-drug conjugate efficiently kills ALCL cells in vitro and in vivo. Our results highlight the importance of the BATF3/IL-2R-module for ALCL biology and identify IL-2Rα-targeting as a promising treatment strategy for ALCL.