Despite the effectiveness of immuno-chemotherapy, 40% of patients with diffuse large B-cell lymphoma (DLBCL) experience relapse or refractory disease. Longitudinal studies have previously focused on the mutational landscape of relapse but fell short of providing a consistent relapse-specific genetic signature. In our study, we have focused attention on the changes in GEP accompanying DLBCL relapse using archival paired diagnostic/relapse specimens from 38 de novo patients with DLBCL. COO remained stable from diagnosis to relapse in 80% of patients, with only a single patient showing COO switching from activated B-cell-like (ABC) to germinal center B-cell-like (GCB). Analysis of the transcriptomic changes that occur following relapse suggest ABC and GCB relapses are mediated via different mechanisms. We developed a 30-gene discriminator for ABC-DLBCLs derived from relapse-associated genes that defined clinically distinct high-and low-risk subgroups in ABC- DLBCLs at diagnosis in datasets comprising both population-based and clinical trial cohorts. This signature also identified a population of <60-year-old patients with superior PFS and OS treated with ibrutinib-R-CHOP as part of the PHOENIX trial. Altogether this new signature adds to the existing toolkit of putative genetic predictors now available in DLBCL that can be readily assessed as part of prospective clinical trials.

Introduction: Diffuse large B-cell lymphomas (DLBCLs) with a non-germinal center B cell-like (non-GCB) cell-of-origin are frequently driven by genetic alterations that culminate in constitutive B-cell receptor (BCR) signaling, which has inspired the exploration of Bruton's tyrosine kinase inhibitors (BTKi) in these lymphomas. However, the phase III PHOENIX study that randomized untreated, non-GCB DLBCL patients to R-CHOP plus placebo or ibrutinib failed to meet its primary endpoint of event-free survival (Younes et al. 2019), which suggests that cell-of-origin alone is an insufficient biomarker to predict BTKi sensitivity in DLBCL. More recently, a DLBCL genetic classifier termed LymphGen has identified distinct subtypes (MCD and N1) of non-GCB DLBCL that benefit from the addition of BTKi to R-CHOP (Wilson et al. 2021). However, genetic classifiers are complex and difficult to implement in routine clinical settings and may fail to capture all DLBCLs that benefit from BTKi. Therefore, we sought to identify a straightforward biomarker of BTKi responsiveness in DLBCL with greater precision than cell-of-origin but with broader inclusivity than current genomic platforms, such as LymphGen. We hypothesized that CD5 - a surrogate marker of BCR activation - may effectively identify BCR-driven, non-GCB DLBCLs that are sensitive to BTKi therapy, and evaluated the extent to which CD5 protein expression and a transcriptionally defined CD5 gene signature could accurately identify BCR-activated DLBCLs with potential susceptibility to BTKi-based therapies. Methods: CD5 immunohistochemistry (IHC) was performed on a cohort of 406 diagnostic DLBCL samples, which were considered CD5+ if >=30% of lymphoma cells exhibited unequivocal membranous staining. A majority of DLBCL samples had available RNA-sequencing and targeted mutational sequencing data. A comparison of differentially expressed genes between CD5+ and CD5- DLBCLs was performed in order to construct a 60-gene CD5 signature (CD5sig), which was applied to large genomic DLBCL datasets, including pre-treatment biopsies from patients enrolled on PHOENIX (n = 584) to evaluate the utility of the CD5sig in identifying DLBCLs that benefitted from the addition of ibrutinib to R-CHOP. Results: Twenty-six of 406 DLBCLs were identified as CD5+ by IHC (6% of all DLBCLs; 12% of non-GCB DLBCLs). CD5 IHC+ DLBCLs were majority non-GCB cell-of-origin and were associated with inferior progression-free survival (PFS) to R-CHOP (50% 3-year PFS), compared with CD5 IHC- DLBCLs, consistent with previous reports. Gene set enrichment analysis revealed that CD5 IHC+ DLBCLs exhibited transcriptional features of BCR activation, and mutational analysis demonstrated that CD5 IHC+ DLBCLs were enriched for CD79B BCR-activating mutations known to correlate with BTKi sensitivity. Many CD5 IHC+ DLBCLs, however, lacked canonical BCR-activating mutations or were classified as “Other” by LymphGen. A CD5 gene signature (CD5sig; Figure 1A) was developed that recapitulated these findings in independent DLBCL datasets (NCI, Duke), where ~13% of non-GCB DLBCLs were classified as CD5sig+. Together, these results suggest that CD5 signature expression captures DLBCLs with both a genetic and non-genetic basis for BCR dependence. Supporting this notion, CD5sig+ DLBCL patients (< 60 years) derived a selective and striking event-free and overall survival advantage from the addition of ibrutinib to R-CHOP in the PHOENIX study ( Figure 1B), independent of LymphGen classification. Conclusions: We demonstrate that CD5 IHC and a novel CD5 gene signature identify high-risk, BCR-driven DLBCLs. Importantly, the CD5 signature also identifies DLBCL patients with a selective survival advantage to BTK inhibitor-based therapy, independent of LymphGen classification. In conclusion, the CD5 signature expands upon LymphGen classification as a biomarker of BTKi response by accurately identifying DLBCLs with both genetic and non-genetic bases for BTKi response. The CD5 signature and/or CD5 IHC should be prospectively evaluated in BTKi-based clinical trials for non-GCB DLBCLs.

Introduction: Gene expression profiling has identified DLBCLs that bear transcriptional similarity to either non-malignant germinal center B-cells (GCB-DLBCL) or activated B-cells (ABC-DLBCL, i.e. non-GCB-DLBCL). This cell-of-origin (COO) classification has guided precision medicine strategies, including the use of ibrutinib, a BTK inhibitor (BTKi), with ABC-DLBCLs thought to be sensitive to BTKi due to their constitutive activation of NF-kB downstream of the B-cell receptor (BCR). However, the phase III Phoenix trial testing the addition of ibrutinib to R-CHOP chemoimmunotherapy surprisingly failed to demonstrate a survival benefit in non-GCB-DLBCLs. By employing a newly defined genetic classification algorithm (LymphGen), distinct genetic DLBCL subtypes that benefit from this regimen were identified. However, LymphGen is not utilized in the clinic and fails to classify >40% of DLBCLs. To overcome these challenges, we sought to identify a straightforward biomarker of BTKi sensitivity. CD5 was selected as a potential candidate, given its role as a negative regulator of BCR signaling and expression in other BTKi-responsive B-cell lymphomas. Methods: CD5 IHC was performed on a cohort of 405 DLBCLs, most with paired RNA and targeted mutational sequencing. Comparison of the transcriptomes of CD5+ and CD5− DLBCLs was used to construct a 60-gene CD5 signature (CD5sig), which was applied to large genomic DLBCL datasets, including pre-treatment biopsies from the Phoenix trial (n = 584) to evaluate its utility in predicting improved response to R-CHOP + ibrutinib. Results: Twenty-seven DLBCLs were identified as CD5+ by IHC (6% of cases; 12% of non-GCB). Consistent with previous reports, CD5+ DLBCLs were enriched for a non-GCB COO and exhibited inferior progression-free survival to R-CHOP. CD5+ DLBCLs upregulated genes related to BCR signaling and had a significantly higher incidence of CD79B BCR-activating mutations. A CD5 signature (CD5sig) was created from differentially expressed genes between CD5 IHC+ and CD5 IHC− non-GCB-DLBCLs. When applied to an external dataset of 349 non-GCB-DLBCLs, CD5sig+ DLBCLs (15% of cases) were enriched for BCR-activating mutations and were majority MCD (MYD88 and CD79B) or unclassified by LymphGen. CD5sig+ DLBCLs were largely devoid of BCL10 activating mutations known to drive BTKi resistance. When applied to the Phoenix study, CD5sig+ DLBCLs selectively benefitted from R-CHOP + ibrutinib by event-free and overall survival. This survival difference was preserved even among LymphGen-unclassified DLBCLs. Conclusions: Here, we identify CD5 expression as a simple and useful biomarker to identify high-risk, BCR-driven DLBCLs beyond those identified through genetic classification. Based upon unique transcriptional features of CD5 IHC+ DLBCLs, we developed a novel CD5 signature that identifies DLBCLs vulnerable to BTKi therapy. Citation Format: Alan Cooper, Sravya Tumuluru, Kyle Kissick, Girish Venkataraman, Nikita Kotlov, Aleksander Bagaev, Andrew Lytle, Gerben Duns, David W. Scott, Christian Steidl, Brendan Hodkinson, Srimathi Srinivasan, Justin Kline, James Godfrey. A CD5 signature identifies diffuse large B-cell lymphomas (DLBCLs) sensitive to Bruton’s tyrosine kinase (BTK) inhibition. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4330.

Diffuse large B-cell lymphoma (DLBCL), with high coexpression of BCL2 and MYC proteins (DE lymphoma), is considered an adverse prognostic indicator associated mostly with nongerminal center B-cell-like (non-GCB) DLBCL. BCL2/MYC overexpression is associated with B-cell receptor (BCR) pathway activation; consequently, DE DLBCL may be sensitive to BCR inhibitors. We assessed whether high BCL2/MYC coexpression by RNA sequencing could identify a patient subset responsive to ibrutinib using baseline biopsies from the PHOENIX trial, which evaluated the addition of ibrutinib to rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) in untreated non-GCB DLBCL. BCL2/MYC RNA expression was correlated with lower event-free survival (EFS) and overall survival (OS) using Kaplan-Meier estimates with Cox regression and log-rank testing. In total, 234 of 766 (30.5%) patients had high BCL2/MYC coexpression: 123 of 386 (31.9%) received ibrutinib plus R-CHOP and 111 of 380 (29.2%) received R-CHOP. EFS was superior with ibrutinib plus R-CHOP compared with R-CHOP alone in patients with high BCL2/MYC coexpression, but there was no significant impact on OS. However, EFS and OS showed clinically meaningful improvement with ibrutinib plus R-CHOP over R-CHOP alone in patients aged <60 years with high BCL2/MYC coexpression. We observed a significant association between high BCL2/MYC coexpression and activated B-cell-like and MYD88(L265P)/CD79B-mutated subtypes of DLBCL. Consequently, high BCL2/MYC coexpression identified a subset of non-GCB DLBCL that may be preferentially responsive to ibrutinib and warrants further investigation. This trial was registered at www.clinicaltrials.gov as #NCT01855750.

In this post hoc subgroup analysis of 200 patients enrolled in China from the phase III PHOENIX trial ( N = 838, NCT01855750), addition of ibrutinib to rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisone (R‐CHOP) did not improve event‐free survival (EFS) versus placebo+R‐CHOP in the intent‐to‐treat (ITT; n = 200, hazard ratio [HR] = 0.83, 95% confidence interval [CI]: 0·509–1.349; p = 0.4495) or activated B‐cell‐like (ABC; n = 141 [based on available gene‐expression profiling data], HR = 0.86, 95% CI: 0.467–1.570; p = 0.6160) subpopulations. However, ibrutinib+R‐CHOP improved EFS (HR = 0·50, 95% CI: 0.251–1.003) and progression‐free survival (PFS; HR = 0.48, 95% CI: 0.228–1.009) versus placebo+R‐CHOP in patients aged <60 but not ≥60 years. Grade ≥3 serious treatment‐emergent adverse events occurred more with ibrutinib+R‐CHOP (45·6% vs. 31·3%). The percentage of patients receiving ≥6 cycles of R‐CHOP was similar across treatment arms in those <60 years. A numerical trend was seen towards improved EFS and PFS with ibrutinib+R‐CHOP versus placebo+R‐CHOP in patients with MYC ‐high/ BCL2 ‐high co‐expression. In this slightly younger Chinese subgroup, ibrutinib+R‐CHOP did not improve EFS in the ITT and ABC subpopulations but improved outcomes with manageable safety in patients <60 years, consistent with overall PHOENIX study outcomes.

Mantle cell lymphoma (MCL) is a rare, incurable lymphoma subtype characterized by heterogeneous outcomes. To better understand the clinical behavior and response to treatment, predictive biomarkers are needed. Using residual archived material from patients enrolled in the MCL3001 (RAY) study, we performed detailed analyses of gene expression and targeted genetic sequencing. This phase III clinical trial randomized patients with relapsed or refractory MCL to treatment with either ibrutinib or temsirolimus. We confirmed the prognostic capability of the gene expression proliferation assay MCL35 in this cohort treated with novel agents; it outperformed the simplified MCL International Prognostic Index in discriminating patients with different outcomes. Regardless of treatment arm, our data demonstrated that this assay captures the risk conferred by known biological factors, including increased MYC expression, blastoid morphology, aberrations of TP53 , and truncated CCND1 3 ′ untranslated region. We showed the negative impact of BIRC3 mutations/deletions on outcomes in this cohort and identified that deletion of chromosome 8p23.3 also negatively impacts survival. Restricted to patients with deletions/alterations in TP53 , ibrutinib appeared to abrogate the deleterious impact on outcome. These data illustrate the potential to perform a molecular analysis of predictive biomarkers on routine patient samples that can meaningfully inform clinical practice.

We assessed the concordance between immunohistochemistry (IHC) and gene expression profiling (GEP) for determining diffuse large B-cell lymphoma (DLBCL) cell of origin (COO) in the phase III PHOENIX trial of rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) with or without ibrutinib. Among 910 of 1114 screened patients with non-germinal centre B cell-like (non-GCB) DLBCL by IHC, the concordance with GEP for non-GCB calls was 82·7%, with 691 (75·9%) identified as activated B cell-like (ABC), and 62 (6·8%) as unclassified. Among 746 of 837 enrolled patients with verified non-GCB DLBCL by IHC, the concordance with GEP was 82·8%, with 567 (76·0%) identified as ABC and 51 (6·8%) unclassified; survival outcomes were similar regardless of COO or treatment, whereas among patients with ABC DLBCL aged <60 years, the overall and event-free survival were substantially better with ibrutinib versus placebo plus R-CHOP [hazard ratio (HR) 0·365, 95% confidence interval (CI) 0·147-0·909, P = 0·0305; HR 0·561, 95% CI 0·326-0·967, P = 0·0348, respectively]. IHC and GEP showed high concordance and consistent survival outcomes among tested patients, indicating centralised IHC may be used to enrich populations for response to ibrutinib plus R-CHOP.

In diffuse large B cell lymphoma (DLBCL), tumors belonging to the ABC but not GCB gene expression subgroup rely upon chronic active B cell receptor signaling for viability, a dependency that is targetable by ibrutinib. A phase III trial ("Phoenix;" ClinicalTrials.gov: NCT01855750) showed a survival benefit of ibrutinib addition to R-CHOP chemotherapy in younger patients with non-GCB DLBCL, but the molecular basis for this benefit was unclear. Analysis of biopsies from Phoenix trial patients revealed three previously characterized genetic subtypes of DLBCL: MCD, BN2, and N1. The 3-year event-free survival of younger patients (age ≤60 years) treated with ibrutinib plus R-CHOP was 100% in the MCD and N1 subtypes while the survival of patients with these subtypes treated with R-CHOP alone was significantly inferior (42.9% and 50%, respectively). This work provides a mechanistic understanding of the benefit of ibrutinib addition to chemotherapy, supporting its use in younger patients with non-GCB DLBCL.

Abstract Background The single‐arm DAWN trial (NCT01779791) of ibrutinib monotherapy in patients with relapsed/refractory follicular lymphoma (FL) showed an overall response rate (ORR) of 20.9% and a median response duration of 19.4 months. This biomarker analysis of the DAWN dataset sought to determine genetic classifiers for prediction of response to ibrutinib treatment. Methods Whole exome sequencing was performed on baseline tumor samples. Potential germline variants were excluded; a custom set of 1216 cancer‐related genes was examined. Responder‐ versus nonresponder‐associated variants were identified using Fisher's exact test. Classifiers with increasing numbers of genes were created using a greedy algorithm that repeatedly selected genes, adding the most nonresponders to the existing “predicted nonresponders” set and were evaluated with 10‐fold cross‐validation. Results Exome data were generated from 88 patient samples and 13,554 somatic mutation variants were inferred. Response data were available for 83 patients (17 responders, 66 nonresponders). Each sample showed 100 to >500 mutated genes, with greater variance across nonresponders. The overall variant pattern was consistent with previous FL studies; 75 genes had mutations in >10% of patients, including genes previously reported as associated with FL. Univariate analysis yielded responder‐associated genes FANCA, HISTH1B, ANXA6, BTG1, and PARP10, highlighting the importance of functions outside of B‐cell receptor signaling, including epigenetic processes, DNA damage repair, cell cycle/proliferation, and cell motility/invasiveness. While nonresponder‐associated genes included well‐known TP53 and CARD11, genetic classifiers developed using nonresponder‐associated genes included ATP6AP1, EP400, ARID1A, SOCS1, and TBL1XR1, suggesting resistance to ibrutinib may be related to broad biological functions connected to epigenetic modification, telomere maintenance, and cancer‐associated signaling pathways (mTOR, JAK/STAT, NF‐κB). Conclusion The results from univariate and genetic classifier analyses provide insights into genes associated with response or resistance to ibrutinib in FL and identify a classifier developed using nonresponder‐associated genes, which warrants further investigation. Trial registration: NCT01779791.

Phylogenetic diversification is a precursor to speciation, but the underlying patterns and processes are not well‐studied in lichens. Here we investigate what factors drive diversification in two tropical, morphologically similar macrolichens that occupy a similar range but differ in altitudinal and habitat preferences, testing for isolation by distance (IBD), environment (IBE), and fragmentation (IBF).

AbstractTo advance the use of circulating tumor DNA (ctDNA) applications, their broad clinical validity must be tested in different treatment settings, including targeted therapies. Using the prespecified longitudinal systematic collection of plasma samples in the phase 1/2a LYM1002 trial (registered on www.clinicaltrials.gov as NCT02329847), we tested the clinical validity of ctDNA for baseline mutation profiling, residual tumor load quantification, and acquisition of resistance mutations in patients with lymphoma treated with ibrutinib+nivolumab. Inclusion criterion for this ancillary biological study was the availability of blood collected at baseline and cycle 3, day 1. Overall, 172 ctDNA samples from 67 patients were analyzed by the LyV4.0 ctDNA Cancer Personalized Profiling Deep Sequencing Assay. Among baseline variants in ctDNA, only TP53 mutations (detected in 25.4% of patients) were associated with shorter progression-free survival; clones harboring baseline TP53 mutations did not disappear during treatment. Molecular response, defined as a >2-log reduction in ctDNA levels after 2 cycles of therapy (28 days), was achieved in 28.6% of patients with relapsed diffuse large B-cell lymphoma who had ≥1 baseline variant and was associated with best response and improved progression-free survival. Clonal evolution occurred frequently during treatment, and 10.3% new mutations were identified after 2 treatment cycles in nonresponders. PLCG2 was the topmost among genes that acquired new mutations. No patients acquired the C481S BTK mutation implicated in resistance to ibrutinib in CLL. Collectively, our results provide the proof of concept that ctDNA is useful for noninvasive monitoring of lymphoma treated with targeted agents in the clinical trial setting.

We analyzed potential biomarkers of response to ibrutinib plus nivolumab in biopsies from patients with diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and Richter's transformation (RT) from the LYM1002 phase I/IIa study, using programmed death ligand 1 (PD-L1) immunohistochemistry, whole exome sequencing (WES), and gene expression profiling (GEP). In DLBCL, PD-L1 elevation was more frequent in responders versus nonresponders (5/8 [62.5%] vs. 3/16 [18.8%]; p = 0.065; complete response 37.5% vs. 0%; p = 0.028). Overall response rates for patients with WES and GEP data, respectively, were: DLBCL (38.5% and 29.6%); FL (46.2% and 43.5%); RT (76.5% and 81.3%). In DLBCL, WES analyses demonstrated that mutations in RNF213 (40.0% vs. 6.2%; p = 0.055), KLHL14 (30.0% vs. 0%; p = 0.046), and LRP1B (30.0% vs. 6.2%; p = 0.264) were more frequent in responders. No responders had mutations in EBF1, ADAMTS20, AKAP9, TP53, MYD88, or TNFRSF14, while the frequency of these mutations in nonresponders ranged from 12.5% to 18.8%. In FL and RT, genes with different mutation frequencies in responders versus nonresponders were: BCL2 (75.0% vs. 28.6%; p = 0.047) and ROS1 (0% vs. 50.0%; p = 0.044), respectively. Per GEP, the most upregulated genes in responders were LEF1 and BTLA (overall), and CRTAM (germinal center B-cell–like DLBCL). Enriched pathways were related to immune activation in responders and resistance-associated proliferation/replication in nonresponders. This preliminary work may help to generate hypotheses regarding genetically defined subsets of DLBCL, FL, and RT patients most likely to benefit from ibrutinib plus nivolumab.

A phase 1/2a study (LYM1002 [EudraCT 2014-005191-28]) of ibr (560 mg once daily) + nivo (3 mg/kg on a 14-day cycle) demonstrated acceptable safety and promising efficacy vs single-agent ibr in Richter’s transformation (RT), follicular lymphoma (FL), and diffuse large B-cell lymphoma (DLBCL). We examined potential biomarkers of treatment (tx) response using archived biopsy samples. GEP was used for DLBCL subtyping and to assess proportions of 22 distinct immune cells. Exome data were generated from 72 formalin-fixed paraffin-embedded samples, and sequencing analysis was used to identify mutations in genes of interest and assess somatic mutation burden. The correlations of immune cell proportions and gene variants were evaluated by investigator-assessed responses in each histology and by ongoing responses in DLBCL patients (pts; progression-free survival [PFS] > 24 months, n = 7 vs not, n = 20). In pts with available GEP and response data, overall response rates were 29.6% (8/27) for DLBCL, 43.5% (10/23) for FL and 81.3% (13/16) for RT. Proportions of CD8 and follicular helper T cells, M1 macrophages, and resting dendritic cells were higher in DLBCL responders vs nonresponders, while the proportion of regulatory T cells was decreased. These subsets did not differ by response in FL although an increase of CD4 memory resting T-cells was noted in responders. The trend toward increased follicular helper T cell and resting dendritic cell proportions in DLBCL pts was also associated with longer survival (PFS > 24 months) vs not. Gene variant data and responder status were available for 26 pts with DLBCL, 26 with FL, and 17 with RT. Comparison between responders and nonresponders showed that DLBCL pts with RNF213 (4/10 [40.0%] vs 1/16 [6.2%]) and KLHL14 (3/10 [30.0%] vs 0/16) mutations were more likely to respond to ibr + nivo. Conversely, nonresponders were associated with variants in EBF1, ADAMTS20, AKAP9, SOCS1, TP53, and genes in BCR pathways such as TNFRSF14, MYD88, and NFKB1B. BCL2 mutation in FL (9/12 [75.0%] vs 4/14 [28.6%]) and ROS1 mutation in RT (0/13 vs 2/4 [50.0%]) were associated with response; both are involved in the NF-kB pathway. In DLBCL, the most frequent gene mutations were RNF213, NBPF1, and BCL2 in pts who had PFS > 24 months (3/7 [42.9%] each), and KMT2D (8/20 [40.0%]) and CSMD3 (8/20 [40.0%]) in pts who did not. Somatic mutation burden was lower in responders vs nonresponders, especially in germinal center B-cell-DLBCL, and in DLBCL pts with PFS > 24 months vs not. In conclusion, we report gene variations among DLBCL, FL, and RT pts associated with response or durable PFS with ibr + nivo. While ibr inhibits Bruton’s tyrosine kinase-dependent pathways, we identify alternative gene pathway variants that may impact tx outcomes. Immune cell infiltration into the microenvironment relates to differential tx response with this immune combination and is histology dependent. Citation Format: Brendan Hodkinson, Michael Schaffer, Joshua Brody, Wojciech Jurczak, Cecilia Carpio, Dina Ben-Yehuda, Irit Avivi, Rao Saleem, Muhit Özcan, John Alvarez, Rob Ceulemans, Nele Fourneau, Sriram Balasubramanian, Anas Younes. Phase 1/2a LYM1002 study of ibrutinib (ibr) + nivolumab (nivo): Exome and gene expression profiling (GEP) analyses by histology and responder status [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4024.

Background Preclinical studies have shown synergistic antitumour effects between ibrutinib and immune-checkpoint blockade. The aim of this study was to assess the safety and activity of ibrutinib in combination with nivolumab in patients with relapsed or refractory B-cell malignant diseases. Methods We did a two-part, open-label, phase 1/2a study at 21 hospitals in Australia, Israel, Poland, Spain, Turkey, and the USA. The primary objective of part A (dose escalation) was to assess the safety of daily oral ibrutinib (420 mg or 560 mg) in combination with intravenous nivolumab (3 mg/kg every 2 weeks) to ascertain a recommended phase 2 dose in patients with relapsed or refractory high-risk chronic lymphocytic leukaemia or small lymphocytic lymphoma (del17p or del11q), follicular lymphoma, or diffuse large B-cell lymphoma. Dose optimisation was investigated using a modified toxicity probability interval design. The primary objective of the part B expansion phase was to establish the preliminary activity (the proportion of patients who achieved an overall response) of the combination of ibrutinib and nivolumab in four cohorts: relapsed or refractory high-risk chronic lymphocytic leukaemia or small lymphocytic lymphoma (del17p or del11q), follicular lymphoma, diffuse large B-cell lymphoma, and Richter's transformation. All participants who received at least one dose of treatment were included in the primary analysis and analyses were done by disease cohort. Findings Between March 12, 2015, and April 11, 2017, 144 patients were enrolled in the study. Three patients died before receiving study treatment; thus, 141 patients were included in the analysis, 14 in part A and 127 in part B. One dose-limiting toxicity (grade 3 hyperbilirubinaemia) was reported at the 420 mg dose in the diffuse large B-cell lymphoma cohort, which resolved after 5 days. The combination of ibrutinib and nivolumab led to overall responses in 22 (61%) of 36 patients with high-risk chronic lymphocytic leukaemia or small lymphocytic lymphoma, 13 (33%) of 40 patients with follicular lymphoma, 16 (36%) of 45 patients with diffuse large B-cell lymphoma, and 13 (65%) of 20 patients with Richter's transformation. The most common all-grade adverse events were diarrhoea (47 [33%] of 141 patients), neutropenia (44 [31%]), and fatigue (37 [26%]). 11 (8%) of 141 patients had adverse events leading to death; none were reported as drug-related. The most common grade 3-4 adverse events were neutropenia (40 [28%] of 141 patients) and anaemia (32 [23%]). The incidence of grade 3-4 neutropenia ranged from eight (18%) of 45 patients with diffuse large B-cell lymphoma to 19 (53%) of 36 patients with chronic lymphocytic leukaemia or small lymphocytic lymphoma; incidence of grade 3-4 anaemia ranged from five (13%) of 40 patients with follicular lymphoma to seven (35%) of 20 patients with Richter's transformation. The most common serious adverse events included anaemia (six [4%] of 141 patients) and pneumonia (five [4%]). The most common grade 3-4 immune-related adverse events were rash (11 [8%] of 141 patients) and increased alanine aminotransferase (three [2%]). Interpretation The combination of ibrutinib and nivolumab had an acceptable safety profile and preliminary activity was similar to that reported with single-agent ibrutinib in chronic lymphocytic leukaemia or small lymphocytic lymphoma, follicular lymphoma, and diffuse large B-cell lymphoma. The clinical response in patients with Richter's transformation was promising and supports further clinical assessment. Copyright (C) 2019 Elsevier Ltd. All rights reserved.

The Basidiomycota constitutes a major phylum of the kingdom Fungi and is second in species numbers to the Ascomycota. The present work provides an overview of all validly published, currently used basidiomycete genera to date in a single document. An outline of all genera of Basidiomycota is provided, which includes 1928 currently used genera names, with 1263 synonyms, which are distributed in 241 families, 68 orders, 18 classes and four subphyla. We provide brief notes for each accepted genus including information on classification, number of accepted species, type species, life mode, habitat, distribution, and sequence information. Furthermore, three phylogenetic analyses with combined LSU, SSU, 5.8s, rpb1, rpb2, and ef1 datasets for the subphyla Agaricomycotina, Pucciniomycotina and Ustilaginomycotina are conducted, respectively. Divergence time estimates are provided to the family level with 632 species from 62 orders, 168 families and 605 genera. Our study indicates that the divergence times of the subphyla in Basidiomycota are 406–430 Mya, classes are 211–383 Mya, and orders are 99–323 Mya, which are largely consistent with previous studies. In this study, all phylogenetically supported families were dated, with the families of Agaricomycotina diverging from 27–178 Mya, Pucciniomycotina from 85–222 Mya, and Ustilaginomycotina from 79–177 Mya. Divergence times as additional criterion in ranking provide additional evidence to resolve taxonomic problems in the Basidiomycota taxonomic system, and also provide a better understanding of their phylogeny and evolution.

Introduction: Sequencing studies identified mutational drivers in diffuse large B cell lymphoma (DLBCL), capturing outcome difference in previously unrecognized patient subsets. However, the lack of routine-applicable genomic approaches limits translation of such information to the clinic. Currently, molecular prognostication consists in cell of origin (COO) determination by the Lymph2Cx NanoString assay. We recently developed two independent prognostic signatures incorporating genes reflecting the COO, the activation of pivotal oncogenic pathways, and the composition of tumor microenvironment (TME). We aimed this study at examining the prognostic strength of a model combining the performance of each signature and developing a comprehensive NanoString assay rapidly transferable to the clinic for prognostic purposes. Methods: The expression of the genes was measured by the NanoString nCounter Analysis System using customized probes for 73 genes, including 15 COO genes, 6 additional oncogenic genes (MYC, BCL-2, NFKBIA, PIK3CA, PTEN, STAT3), 47 TME genes, and 5 housekeeping genes. The analysis was performed on 175 newly diagnosed, nodal DLBCL, homogeneously selected from the RHDS0305 and DLCL04 trials. Patients had comparable clinical features and double-hit cases were excluded. Heatmaps, Kaplan–Meier survival estimator, tree-based survival model, and P values were produced by ‘R’ statistical software. Long-rank test was used to compare overall survival (OS) and progression-free survival (PFS) among groups. Multivariate analysis was constructed through the Cox proportional hazards regression model. Results: Based on the expression of the COO and oncogenic genes, a tree-based survival model stratified patients into subgroups showing significantly different survival, with MYC, BCL-2 and NFKBIA holding additional prognostic power based on their high (H) or low (L) expression. The TME panel identified a lower gene expression cluster (C3) with significantly worse survival than those at intermediate (C2) and higher expression (C1). Integration of COO-, TME-, and MYC/BCL-2/NFKBIA-based data produced a new survival risk categorization of DLBCL. The high-risk category, showing the worst outcomes, includes ABC/H/C1-2-3, ABC/L/C3 and GCB/H/C3 cases; the intermediate-risk category comprises ABC/L/C2, GCB/H or L/C1 and UN/H or L/C1 or C3 cases; whereas the low-risk category contains GCB/H or L/C2, GCB/L/C3, UN/H/C1 or C2 and UN/L/C2 or C3 cases, with longer survival. An unsupervised clustering analysis was also performed based on the expression of the entire 74-gene panel and stratified cases into four clusters with significantly different OS (p=0.011) and PFS (p=0.009). In particular, cluster 1 and 4 showed significantly worse survival than cluster 2 and 3 (Figure 1), and a multivariate Cox analysis indicated that the prognostic performance of the panel overcomes the IPI score. Finally, such model was also validated “in silico” using a gene expression profiling dataset (GSE10846 and GSE98588) relative to a cohort of 146 DLBCL patients uniformly selected according to R-CHOP treatment. Conclusions: This study supports the idea that DLBCL heterogeneity involves both tumor and TME, resulting in diverse transcriptional subtypes with distinct outcomes and, putatively, diverse biology. Our integrative analysis prompts the development of a new survival categorization outperforming current prognostic risk-assessment. Moreover, the applicability of a unique Nanostring-based assay to routine biopsies may facilitate the stratification of patients at diagnosis and their inclusion in future trials exploring novel therapeutic approaches.