Ansell, Stephen M.

We recently defined event‐free survival at 24 months (EFS24) as a clinically relevant outcome for patients with DLBCL. Patients who fail EFS24 have very poor overall survival, while those who achieve EFS24 have a subsequent overall survival equivalent to that of the age‐ and sex‐matched general population. Here, we develop and validate a clinical risk calculator (IPI24) for EFS24. Model building was performed on a discovery dataset of 1,348 patients with DLBCL and treated with anthracycline‐based immunochemotherapy. A multivariable model containing age, Ann Arbor stage, normalized serum LDH, ALC, ECOG performance status, bulky disease, and sex was identified. The model was then applied to an independent validation dataset of 1,177 DLBCL patients. The IPI24 score estimates the probability of failing to achieve the EFS24 endpoint for an individual patient. The IPI24 model showed superior discriminatory ability (c‐statistic = 0.671) in the validation dataset compared to the IPI (c‐statistic = 0.649) or the NCCN‐IPI (c‐statistic = 0.657). After recalibration of the model on the combined dataset, the median predicted probability of failing to achieve EFS24 was 36% (range, 12–88%), and the IPI24 showed an EFS24 gradient in all IPI groups. The IPI24 also identified a significant percentage of patients with high risk disease, with over 20% of patients having a 50% or higher risk of failing to achieve EFS24. The IPI24 provides an individual patient level probability of achieving the clinically relevant EFS24 endpoint. It can be used via electronic apps. Am. J. Hematol. 91:179–184, 2016. © 2015 Wiley Periodicals, Inc.

Hodgkin lymphoma (HL) is a B-cell malignancy that typically has a favorable prognosis when treated with chemotherapy, often in combination with radiation therapy. The prognosis for patients whose disease relapses or is refractory, however, is far less favorable and novel therapies are needed for these patients. The unique cellular composition of HL provides a number of opportunities to target either the malignant Reed-Sternberg cell or the inflammatory tumor microenvironment. Antibody-drug conjugates targeting CD30, small molecule inhibitors of cell signaling, and antibodies that inhibit immune checkpoints, have all demonstrated activity in HL. Current and future trials are exploring the use of these agents in combination with each other and with standard chemotherapy.

Abstract Background: Excess adiposity has been associated with lymphomagenesis, possibly mediated by increased cytokine production causing a chronic inflammatory state. The relationship between obesity, cytokine polymorphisms, and selected mature B-cell neoplasms is reported. Method: Data on 4,979 cases and 4,752 controls from nine American/European studies from the InterLymph consortium (1988–2008) were pooled. For diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), joint associations of body mass index (from self-reported height and weight) and 12 polymorphisms in cytokines IL1A (rs1800587), IL1B (rs16944, rs1143627), IL1RN (rs454078), IL2 (rs2069762), IL6 (rs1800795, rs1800797), IL10 (rs1800890, rs1800896), TNF (rs1800629), LTA (rs909253), and CARD15 (rs2066847) were investigated using unconditional logistic regression. BMI-polymorphism interaction effects were estimated using the relative excess risk due to interaction (RERI). Results: Obesity (BMI ≥ 30 kg/m2) was associated with DLBCL risk [OR = 1.33; 95% confidence interval (CI), 1.02–1.73], as was TNF-308GA+AA (OR = 1.24; 95% CI, 1.07–1.44). Together, being obese and TNF-308GA+AA increased DLBCL risk almost 2-fold relative to those of normal weight and TNF-308GG (OR = 1.93; 95% CI, 1.27–2.94), with a RERI of 0.41 (95% CI, −0.05–0.84; Pinteraction = 0.13). For FL and CLL/SLL, no associations with obesity or TNF-308GA+AA, either singly or jointly, were observed. No evidence of interactions between obesity and the other polymorphisms were detected. Conclusions: Our results suggest that cytokine polymorphisms do not generally interact with BMI to increase lymphoma risk but obesity and TNF-308GA+AA may interact to increase DLBCL risk. Impact: Studies using better measures of adiposity are needed to further investigate the interactions between obesity and TNF-308G>A in the pathogenesis of lymphoma. Cancer Epidemiol Biomarkers Prev; 24(7); 1061–70. ©2015 AACR.

Abstract Background: Fusion genes, transcripts, and proteins are key drivers of hematopoietic oncogenesis and can serve as effective therapeutic targets. Among peripheral T-cell lymphomas (PTCLs), little is known about fusion genes except for those involving ALK. Discovery of fusion genes may provide therapeutic targets for PTCLs, which have poor outcomes with conventional therapy. We have developed methods for detecting candidate fusions using (1) mate-pair DNA sequencing (MPseq), an approach that spans the entire genome at a fraction of the cost of traditional whole-genome sequencing, and (2) RNA sequencing (RNAseq). Each technique has strengths, limitations, and false discovery rates. Here, we integrated results of both methods to discover and orthogonally validate expressed fusion genes in PTCLs. Methods: DNA and RNA were extracted from 49 frozen, OCT-embedded clinical PTCL specimens, including 25 anaplastic large cell lymphomas; 16 PTCLs, not otherwise specified; and 8 other PTCLs. MPseq and RNAseq were performed using Illumina library protocols and a HiSeq 2000. Detection of fusion genes and transcripts followed our published methods (Blood 2012;120:2280 and Nucleic Acids Res 2011;39:e100, respectively). Functional annotation of genes involved in fusions was performed using DAVID. Results: Of 2818 candidate chromosomal rearrangements identified by MPseq and 90 candidate fusion transcripts identified by RNAseq, 45 events were present in both datasets (mean/case, 0.9; range, 0-7). Fusions were inter-chromosomal in 16 and intra-chromosomal in 29. Annotation clusters with the highest enrichment scores related to SH2 domain-containing proteins and tyrosine kinases (including FER and MAP2K3). Seven genes were recurrently involved in fusions, including known fusion partners such as ALK and previously unreported fusion partners such as PPP1R8, a phosphatase inhibitor important for the activity of Polycomb group proteins such as EZH2. Detection of candidate events only by MPseq could be explained in part by breakpoints mapping to non-genic regions (79% of events). Detection only by RNAseq could be explained in part by unannotated transcripts spanning neighboring named genes (median intra-chromosomal distance, 0.09 MB vs. 12.7 MB for intra-chromosomal candidates identified by MPseq; p<0.0001, Wilcoxon test). Conclusions: Integrated DNA/RNA sequencing is an effective, clinically feasible tool for simultaneous discovery and orthogonal validation of expressed fusion genes. This approach yielded fusions in PTCLs involving genes with key functions in lymphocytes, including novel and recurrent fusions, some of which might be targetable with compounds currently in clinical trial. Candidate intra-chromosomal fusion transcripts not identified by MPseq may represent unrecognized isoforms or the results of novel read-through mechanisms, and merit further study. Citation Format: Andrew L. Feldman, George Vasmatzis, Yan W. Asmann, Sarah H. Johnson, Bruce W. Eckloff, Sumit Middha, Jaime I. Davila, Paul J. Kurtin, Brian K. Link, Stephen M. Ansell, James R. Cerhan. Integrated DNA/RNA sequencing for discovery and orthogonal validation of expressed fusion genes in peripheral T-cell lymphomas. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5585. doi:10.1158/1538-7445.AM2014-5585

Abstract Interferon regulatory factor-4 (IRF4) is a tightly-regulated transcription factor involved in growth and differentiation of normal lymphocytes. IRF4 is expressed in multiple lymphoid malignancies and its expression drives tumor growth. Thus, characterization of the molecular events regulating IRF4 levels is key to design any targeting strategy. Here, we define a novel regulatory mechanism controlling IRF4 expression in peripheral T-cell lymphoma (PTCL), an aggressive non-Hodgkin lymphoma with poor overall survival rates and high levels of this transcription factor. In normal T cells, IRF4 was induced upon external activation of protein kinase C (PKC) by phorbol myristate acetate and ionomycin, an effect reversed by the PKC inhibitor, enzastaurin. Unlike normal T cells, PTCL cells constitutively expressed IRF4 in the absence of external stimulation, and this expression was resistant to enzastaurin. To identify regulators of IRF4 expression in PTCL, we performed a pharmacological screen using inhibitors that targeted PKC-associated pathways, including mitogen-activated protein kinases, PI3K/AKT/mTOR, and NF-κB. Of the inhibitors tested, only the proteasome inhibitor, bortezomib, showed a decrease in IRF4 expression in a dose- and time-dependent manner. To confirm this result we used a more specific NF-κB inhibitor blocking IκB kinase, BMS-345541. This inhibitor dramatically reduced IRF4 expression by 95.6% (P<0.0001). We used cell-based assays to investigate further the role of NF-κB in the transcriptional regulation of IRF4. A reporter assay for the IRF4 promoter demonstrated reduced promoter activity by siRNA knockdown of RelB and p52 NF-κB subunits to 31.4% and 36.9% of control (P=0.009). IRF4 promoter activity also was inhibited 67.9% by IκBαΔN, a dominant negative inhibitor of NF-κB activity (P=0.002), and was increased 71% by siRNA knockdown of IκBα (P<0.05). Chromatin immunoprecipitation assays confirmed the occupancy of NF-κB subunits in the IRF4 promoter, and this interaction was diminished in the presence of BMS-345541. Finally, knockdown of RelB and p52 subunits had a tendency to decrease IRF4 gene expression by 24.4% and 27.3% (P=0.1). Taken together, these data demonstrate transcriptional regulation of IRF4 by the NF-κB family in PTCL, and suggest the NF-κB pathway may represent a therapeutic target for PTCLs with concurrent IRF4 and NF-κB expression. Citation Format: Rebecca L. Boddicker, N. Sertac Kip, Luciana L. Almada, Julie C. Porcher, Deanna M. Grote, Stephen M. Ansell, Martin E. Fernandez-Zapico, Andrew L. Feldman. Interferon regulatory factor-4 is transcriptionally regulated by NF-κB in peripheral T-cell lymphomas. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2323. doi:10.1158/1538-7445.AM2014-2323

Key Points The mTOR pathway is constitutively activated in the TCL cells and is responsible for TCL proliferation. This is first trial to demonstrate that mTORC1 inhibitors (everolimus) have substantial antitumor activity (44% overall response rate) in patients with relapsed TCL.

Key PointsThe NF-κB subunits p52 and RelB increase IRF4 promoter activity and expression in PTCL cells. A positive feedback loop involving CD30, NF-κB, and IRF4 drives PTCL cell proliferation and can be blocked by NF-κB inhibitors.

Abstract Purpose: Waldenström macroglobulinemia (WMG) is a lymphoproliferative disorder characterized by good initial responses to standard therapeutics, but only a minority of patients achieve complete remissions, and most inevitably relapse, indicating a need for novel agents. B-cell receptor signaling has been linked to clonal evolution in WMG, and Spleen tyrosine kinase (Syk) is overexpressed in primary cells, suggesting that it could be a novel and rational target. Experimental Design: We studied the impact of the Syk inhibitor fostamatinib on BCWM.1 and MWCL-1 WMG-derived cell lines both in vitro and in vivo, as well as on primary patient cells. Results: In WMG-derived cell lines, fostamatinib induced a time- and dose-dependent reduction in viability, associated with activation of apoptosis. At the molecular level, fostamatinib reduced activation of Syk and Bruton's tyrosine kinase, and also downstream signaling through MAPK kinase (MEK), p44/42 MAPK, and protein kinase B/Akt. As a single agent, fostamatinib induced tumor growth delay in an in vivo model of WMG, and reduced viability of primary WMG cells, along with inhibition of p44/42 MAPK signaling. Finally, fostamatinib in combination with other agents, including dexamethasone, bortezomib, and rituximab, showed enhanced activity. Conclusions: Taken together, these data support the translation of approaches targeting Syk with fostamatinib to the clinic for patients with relapsed and possibly even newly diagnosed WMG. Clin Cancer Res; 21(11); 2538–45. ©2015 AACR.

SummaryDeubiquitinase enzymes (DUBs) of the proteasomal 19S regulatory particle are emerging as important therapeutic targets in several malignancies. Here we demonstrate that inhibition of two proteasome‐associated DUBs (USP14 and UCHL5) with the small molecule DUB inhibitor b‐AP15, results in apoptosis of human Waldenström macroglobulinaemia (WM) cell lines and primary patient‐derived WM tumour cells. Importantly, b‐AP15 produced proteotoxic stress and apoptosis in WM cells that have acquired resistance to the proteasome inhibitor bortezomib. In silico modelling identified protein residues that were critical for the binding of b‐AP15 with USP14 or UCHL5 and proteasome enzyme activity assays confirmed that b‐AP15 does not affect the proteolytic capabilities of the 20S proteasome β‐subunits. In vitro toxicity from b‐AP15 appeared to result from a build‐up of ubiquitinated proteins and activation of the endoplasmic reticulum stress response in WM cells, an effect that also disrupted the mitochondria. Focused transcriptome profiling of b‐AP15‐treated WM cells revealed modulation of several genes regulating cell stress and NF‐κB signalling, the latter whose protein translocation and downstream target activation was reduced by b‐AP15 in vitro. This is the first report to define the effects and underlying mechanisms associated with inhibition of USP14 and UCHL5 DUB activity in WM tumour cells.