Cancer treatment has been transformed by checkpoint blockade therapies, with the highest anti-tumor activity of anti-programmed death 1 (PD-1) antibody therapy seen in Hodgkin lymphoma (HL). Disappointingly, response rates have been low in the non-Hodgkin lymphomas (NHLs), with no activity seen in relapsed/refractory (R/R) chronic lymphocytic leukemia (CLL) with PD-1 blockade. Thus, identifying more powerful combination therapy is required for these patients. Here, we pre-clinically demonstrate enhanced anti-CLL activity following combinational therapy with anti-PD-1 or anti-PD-1 ligand (PD-L1) and avadomide, a cereblon E3 ligase modulator (CELMoD). Avadomide induced type I and II interferon (IFN) signaling in patient T cells, triggering a feedforward cascade of reinvigorated T cell responses. Immune modeling assays demonstrated that avadomide stimulated T cell activation, chemokine expression, motility and lytic synapses with CLL cells, as well as IFN-inducible feedback inhibition through upregulation of PD-L1. Patient-derived xenograft tumors treated with avadomide were converted to CD8+ T cell-inflamed tumor microenvironments (TMEs) that responded to anti-PD-L1/PD-1-based combination therapy. Notably, clinical analyses showed increased PD-L1 expression on T cells, as well as intratumoral expression of chemokine signaling genes in B cell malignancy patients receiving avadomide-based therapy. These data illustrate the importance of overcoming a low inflammatory T cell state to successfully sensitize CLL to checkpoint blockade-based combination therapy.

Let K be an imaginary quadratic field, and fix a prime p > 3 that does not divide the class number of K. In this paper we prove that Iwasawa's λ-invariant for the cyclotomic Zp-extension of K is greater than 1 if and only if the number of points on a certain reduced elliptic curve is divisible by p 2 .

PURPOSE 60-70% of newly diagnosed diffuse large B-cell lymphoma (DLBCL) patients avoid events within 24 months of diagnosis (EFS24) and the remainder have poor outcomes. Recent genetic and molecular classification of DLBCL has advanced our knowledge of disease biology, yet were not designed to predict early events and guide anticipatory selection of novel therapies. To address this unmet need, we used an integrative multiomic approach to identify a signature at diagnosis that will identify DLBCL at high risk of early clinical failure. PATIENTS AND METHODS Tumor biopsies from 444 newly diagnosed DLBCL were analyzed by WES and RNAseq. A combination of weighted gene correlation network analysis and differential gene expression analysis followed by integration with clinical and genomic data was used to identify a multiomic signature associated with high risk of early clinical failure. RESULTS Current DLBCL classifiers are unable to discriminate cases who fail EFS24. We identified a high risk RNA signature that had a hazard ratio (HR, 18.46 [95% CI 6.51-52.31] P < .001) in a univariate model, which did not attenuate after adjustment for age, IPI and COO (HR, 20.8 [95% CI, 7.14-61.09] P < .001). Further analysis revealed the signature was associated with metabolic reprogramming and a depleted immune microenvironment. Finally, WES data was integrated into the signature and we found that inclusion of ARID1A mutations resulted in identification of 45% of cases with an early clinical failure which was validated in external DLBCL cohorts. CONCLUSION This novel and integrative approach is the first to identify a signature at diagnosis that will identify DLBCL at high risk for early clinical failure and may have significant implications for design of therapeutic options.