Translational Oncology 14 (2021) 100977 Contents lists available at ScienceDirect Translational Oncology journal homepage: www.elsevier.com/locate/tranon Biomarkers of response to ibrutinib plus nivolumab in relapsed diffuse large B-cell lymphoma, follicular lymphoma, or Richter’s transformation ✩,✩✩ Brendan P. Hodkinson a, Michael Schaffer a, Joshua D. Brody b, Wojciech Jurczak c, Cecilia Carpio d, Dina Ben-Yehuda e, Irit Avivi f, Ann Forslund g, Muhit Özcan h, John Alvarez a, Rob Ceulemans i, Nele Fourneau i, Anas Younes j,1, Sriram Balasubramanian a,∗ a Oncology Translational Research, Janssen Research & Development, Spring House, PA 19477, United States b Division of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, United States c Department of Clinical Oncology, Maria Sklodowska-Curie National Research Institute of Oncology, Krakow, 31-115, Poland d Department of Hematology, University Hospital Vall d’Hebron, Department of Medicine. Universitat Autònoma de Barcelona (UAB), Vall d’Hebron Institut of Oncology (VHIO), Barcelona, Spain e Department of Hematology, Hadassah-Hebrew University Medical Center, Jerusalem 91120, Israel f Department of Hematology and Bone Marrow Transplantation, Tel Aviv Sourasky Medical Center and Sackler Faculty of Medicine, Tel Aviv 6997801, Israel g Oncology Biomarkers, Bristol-Myers Squibb, Lawrenceville, NJ 08543, United States h Department of Hematology, Ankara University School of Medicine, Ankara 06100, Turkey i Translational Medicine, Janssen Research & Development, Beerse 2340, Belgium j Lymphoma Department, Memorial Sloan Kettering Cancer Center, New York, NY 10065, United States a r t i c l e i n f o a b s t r a c t Keywords: We analyzed potential biomarkers of response to ibrutinib plus nivolumab in biopsies from patients with diffuse Ibrutinib large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and Richter’s transformation (RT) from the LYM1002 Nivolumab phase I/IIa study, using programmed death ligand 1 (PD-L1) immunohistochemistry, whole exome sequencing Non-hodgkin’s lymphoma (WES), and gene expression profiling (GEP). In DLBCL, PD-L1 elevation was more frequent in responders versus Biomarkers nonresponders (5/8 [62.5%] vs. 3/16 [18.8%]; p = 0.065; complete response 37.5% vs. 0%; p = 0.028). Overall Phase I/II trial 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. Introduction lymphoma (NHL) [1–9] leading to approval of ibrutinib in the United States and Europe for the treatment of adult B-cell malignancies, and Among novel targeted therapies for the treatment of B-cell malig- also for chronic graft versus host disease (cGVHD) [10,11]. nancies, ibrutinib, a first-in-class, oral, covalent inhibitor of Bruton’s Ibrutinib is an investigational therapy for diffuse large B-cell lym- tyrosine kinase (BTK), improved clinical outcomes in randomized trials phoma (DLBCL), follicular lymphoma (FL), and Richter’s transforma- in patients with treatment-naive or relapsed/refractory non-Hodgkin’s tion (RT), and responses have been observed in phase I/II studies in patients with treatment-naive [12] and relapsed/refractory disease [13– 15]. However, the prognosis for patients with relapsed disease remains ✩ Congress Presentation ✩✩ Part of the results was presented at the American Association for Cancer Research 2019 Meeting in Atlanta, GA, USA, March 29–April 3, 2019. ∗ Corresponding author. E-mail address: sbalas14@ITS.JNJ.com (S. Balasubramanian). 1 Dr. Younes’s affiliation during the time this study was conducted, and the manuscript developed. His current affiliation is Oncology R&D at AstraZeneca, USA. https://doi.org/10.1016/j.tranon.2020.100977 Received 24 August 2020; Received in revised form 11 November 2020; Accepted 25 November 2020 1936-5233/© 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) B.P. Hodkinson, M. Schaffer, J.D. Brody et al. Translational Oncology 14 (2021) 100977 poor [16], and the synergistic antitumor activity of ibrutinib combined nists). Biomarker analyses presented herein were conducted in patients with other novel agents is currently being investigated as an approach with DLBCL, FL, and RT for whom tumor tissue samples were available. to improve long-term outcomes. Nivolumab is a fully human immunoglobulin G4 monoclonal anti- Assessments body that blocks interaction between the programmed death 1 (PD-1) receptor and its ligands, PD-L1 and PD-L2, and augments antitumor ac- DLBCL subtyping tivity of T cells [17]. High expression of PD-L1 in solid tumors and lym- DLBCL subtyping, based on the Wright et al. classification al- phomas is generally thought to be related to greater response to anti- gorithm [31], was conducted in the R software environment using PD-1 therapy, but the results from clinical trials are conflicting [17,18]. MAS5-normalized (affy v1.48.0, Bioconductor) baseline formalin-fixed Based on data from a phase II study [19], nivolumab was approved in the paraffin-embedded (FFPE) biopsy GEP data (GeneChip Human Genome United States for the treatment of classic Hodgkin’s lymphoma [20] and U133 Plus 2.0 Array; Affymetrix, Santa Clara, CA, USA). has been investigated as monotherapy in DLBCL and FL [21,22], and in combination with ibrutinib in RT [23]. Treatment response and survival outcomes The phase I/IIa LYM1002 study (NCT02329847) evaluated the ef- Preliminary activity and clinical response to treatment were evalu- ficacy and safety of ibrutinib plus nivolumab in 141 patients with re- ated by radiological assessments every five cycles for the first 15 months lapsed/refractory B-cell malignancies [24]. Safety was consistent with and every 12 cycles thereafter until disease progression, at the end of that reported for single-agent ibrutinib or nivolumab. The overall re- treatment, and every 6 months during the follow-up period for patients sponse rate (ORR) was 22/36 (61%) for patients with chronic lympho- who had not progressed while on therapy and did not start subsequent cytic leukemia/small lymphocytic lymphoma CLL/SLL (including pa- therapy. Response was assessed per Lugano Classification by Cheson for tients with del17p/del11q), 13/40 (33%) for FL, 16/45 (36%) for DL- DLBCL, FL, and RT [32]. For calculation of ORR, responders were de- BCL, and 13/20 (65%) for RT. Response to ibrutinib plus nivolumab in fined as patients who achieved complete response (CR) or partial re- RT was high; historically, these patients have had poor outcomes with sponse (PR) by investigator assessment. Progression-free survival (PFS) chemotherapy [25] or single-agent ibrutinib [26]. and overall survival (OS) were estimated using the Kaplan-Meier method Biomarker analyses can enhance the efficacy of molecularly tar- and log-rank tests were performed to assess significance. geted therapies by improving rational combinations and identifying pa- tients most likely to benefit from the therapies. Whole genome or ex- Biomarker analyses and correlation with clinical outcome ome sequencing studies have identified the spectrum of mutations in genes known to be functionally relevant in DLBCL [27,28], and re- PD-L1 expression vealed mutations driving initiation and progression of FL (CREBBP, PD-L1 expression as a predictive biomarker for clinical outcomes was EZH2, KMT2D, EBF1, MYD88, TNFAIP3) [29] and RT (MYC, BCL2, evaluated by IHC from baseline tissue biopsies. PD-L1 levels were as- CDKN2A,TP53, TNFRSF14, TNFSF9) [30]. Some gene mutations, includ- sessed by IHC as the percentage of tumor cells demonstrating plasma ing CD79B, TP53, CARD11, MYD88, EZH2, KMT2D, TNFRSF14, BTG1, membrane PD-L1 staining of any intensity in a minimum of 100 evalu- MEF2B, and GNA13, have been implicated in the pathogenesis of DLBCL able tumor cells using the Dako PD-L1 IHC 28–8 pharmDx assay (Agilent [27]. Exploration of gene variants that may impact response to ibrutinib Technologies, Glostrup, Denmark). PD-L1 elevation was defined as ex- therapy in NHL (such as BCR and MYD88 pathway mutations in DLBCL pression in ≥5% of tumor cells. Kaplan-Meier survival probability with and CARD11 mutations in DLBCL and FL) [13,14] is limited and requires response or survival endpoints was calculated for patients with elevated further examination. or nonelevated PD-L1 subgroups with DLBCL, FL, and RT. The associ- This analysis evaluated the associations between response to ibruti- ation of PD-L1 with clinical response was assessed using Fisher’s exact nib plus nivolumab and a variety of biomarkers including PD-L1 expres- test. sion by immunohistochemistry (IHC), DNA exome sequencing, and gene expression profiling (GEP), including pathway analyses. Analyses were DNA sequence analyses performed using biopsy samples collected at baseline or before start of Exome data were generated from FFPE samples, each from treatment from patients with DLBCL (including subtypes), FL, and RT a different patient at baseline. Raw Illumina FASTQ files were enrolled in the LYM1002 study. processed as follows on the DNAnexus platform (DNAnexus Inc; https://www.dnanexus.com/) using a custom exome analysis workflow: quality was assessed using FastQC 1.0.0, sequences were aligned to the Methods hs37d5 genome build using the BWA-MEM algorithm in BWA Software Package 0.5.9, alignments were recalibrated with the GATK 3.5 Exome Patients and study design Pipeline, variants were annotated with MuTect 1.1.7, and annotations were made with both SnpEff 4.2 (using the GRCh37.75 database and Detailed methodology for the LYM1002 study (NCT02329847) was dbNSFP 3.4c) and GEMINI 0.20.0 (modified by using “non-TCGA” gno- published previously; the study was approved by an independent ethics mAD and ExAC references). committee, and all patients provided written informed consent [24]. Mutation analysis was performed on a set of cancer-related genes of Briefly, this nonrandomized, open-label phase I/IIa study enrolled adult interest (n = 1742), including those from DLBCL-associated genes (ie, ac- patients with NHL who received intravenous nivolumab (3 mg/kg) tivated B-cell–like [ABC]/germinal center B-cell–like [GCB] discriminat- once per 14-day cycle combined with oral ibrutinib 420 mg or 560 mg ing genes, genes used to discriminate between four recently defined sub- once daily. Key eligibility criteria were histologically confirmed re- types, genes predicted as hypermutated in DLBCL) [33], and genes pre- lapsed/refractory CLL/SLL (with del17p or del11q), DLBCL, FL, or RT viously identified from ibrutinib studies, focusing on nonsynonymous (transformation from CLL/SLL only), ≥1 prior systemic therapy (≥2 for single-nucleotide variants that are likely to be somatic based on a set of FL) but no more than four prior lines of treatment, Eastern Coopera- defined criteria (Supplementary Figure S1). A number of variant filters tive Oncology Group (ECOG) performance status ≤2, measurable dis- were used to reduce the likelihood of incorporating sequencing artifacts ease, and no prior ibrutinib or anti-PD-1 therapy. Patients were excluded and germline variants into the analyses. for (a) having major surgery within 4 weeks of the first dose of ibruti- The significance of variant frequency differences between treat- nib, (b) getting diagnosed or treated for malignancies other than the ment responders (CR + PR) versus nonresponders (no response or sta- indication under study, or (c) requiring treatment with either strong ble disease [SD] + progressive disease [PD]), and between patients with CYP3A inhibitors or warfarin (including equivalent vitamin K antago- durable responses (PFS >24 months) versus those with PFS ≤24 months, B.P. Hodkinson, M. Schaffer, J.D. Brody et al. Translational Oncology 14 (2021) 100977 Table 1 Responses in Patients with DLBCL, FL, and RT who had GEP and WES Data. GEP Data Set Total DLBCLa FL RT N = 66 Alln = 27 ABCn = 5 GCBn = 18 n = 23 n = 16 ORR (CR + PR), n (%) 31 (47.0) 8 (29.6) 2 (40.0) 6 (33.3) 10 (43.5) 13 (81.3) CR, n (%) 9 (13.6) 4 (14.8) 2 (40.0) 2 (11.1) 3 (13.1) 2 (12.5) PR, n (%) 22 (33.3) 4 (14.8) 0 4 (22.2) 7 (30.4) 11 (68.8) Nonresponders, n (%) 35 (53.0) 19 (70.4) 3 (60.0) 12 (66.7) 13 (56.5) 3 (18.8) No response or SD, n (%) 10 (15.2) 4 (14.8) 0 2 (11.1) 6 (26.1) 0 PD, n (%) 25 (37.9) 15 (55.6) 3 (60.0) 10 (55.6) 7 (30.4) 3 (18.8) WES Data Set Total DLBCL FL RT N = 69 Alln = 26 ABCn = 4 GCBn = 16 n = 26 n = 17 ORR (CR + PR), n (%) 35 (50.7) 10 (38.5) 2 (50.0) 6 (37.5) 12 (46.2) 13 (76.5) CR, n (%) 10 (14.5) 5 (19.2) 2 (50.0) 2 (12.5) 3 (11.5) 2 (11.8) PR, n (%) 25 (36.2) 5 (19.2) 0 4 (25.0) 9 (34.6) 11 (64.7) Nonresponders, n (%) 34 (49.3) 16 (61.5) 2 (50.0) 10 (62.5) 14 (53.8) 4 (23.5) No response or SD, n (%) 12 (17.4) 4 (15.4) 0 2 (12.5) 8 (30.8) 0 PD, n (%) 22 (31.9) 12 (46.2) 2 (50.0) 8 (50.0) 6 (23.1) 4 (23.5) a All DLBCL patient set also includes patients with unclassified and/or transformed DLBCL not outlined in the Table.ABC, activated B-cell–like; CR, complete response; DLBCL, diffuse large B-cell lymphoma; FL, follicular lymphoma; GCB, germinal center B-cell–like; GEP, gene expression profiling; NHL, non- Hodgkin’s lymphoma; ORR, overall response rate; PD, progressive disease; PR, partial response; PRL, partial response with lymphocytosis; RT, Richter’s transformation; SD, stable disease; WES, whole exome sequencing. were examined gene-by-gene using Fisher’s exact test (no adjustments n = 19, del11q n = 17), DLBCL (n = 45), FL (n = 40), and RT (n = 20). At for multiple hypothesis testing). Patients with no response data were the time of clinical cutoff on October 10, 2017, 35/141 (25%) patients not included in the analyses. Differences in tumor mutational burden remained on treatment (13 with CLL/SLL, 9 with DLBCL, 7 with FL, (TMB), calculated by dividing the number of inferred somatic mutations and 6 with RT). The most common reasons for treatment discontinua- in each sample by 30 Mb (the approximate size of the whole exome), tion in all patients were progressive disease or relapse (39%) and ad- were assessed using the Wilcoxon rank sum test. verse events (28%). Median age was 65 years (interquartile range [IQR] For patients with DLBCL, mutations were examined in terms of func- 54.0–71.0), 87 (62%) patients were male, 130 (93%) had an ECOG per- tional groupings by tying mutations in particular genes to potential dys- formance status of 0 to 1, and 68 (48%) had bulky disease (≥5 cm). The regulation of certain pathways and counting the number of patients with median number of prior lines of treatment was three. Median follow-up such mutations. Supplementary Table S1 shows which genes were cho- for patients included in this analysis was 18.4 months (IQR 14.8–19.4) sen and the functional groups to which they were assigned. for DLBCL, 19.6 months (IQR 14.1–20.7) for FL, and 8.7 months (IQR 6.5–12.1) for RT. Gene expression analyses DLBCL subtyping Gene expression microarray data were generated from baseline FFPE biopsy samples using the GeneChip Human Genome U133 Plus 2.0 Ar- Twenty-eight patients with DLBCL were evaluable for subtyping us- ray. CEL files were processed and analyzed for DGE and DLBCL sub- ing the GEP microarray method; most (19/28) had the GCB subtype, typing using the R software environment. Raw data were prepared for five had the ABC subtype, and four were unclassified. DGE analyses by Robust Multichip Average normalization (affy v1.48.0, Bioconductor) and annotation with the University of Michigan BrainAr- Treatment responses ray CDF (hgu133plus2hsentrezgcdf, v20.0.0); DGE analyses were per- formed with empirical Bayes moderation (limma v3.40.6, Bioconductor) Of 70 patients (DLBCL + FL + RT) who had GEP data, 66 were evalu- and resulting p values were adjusted using the Benjamini-Hochberg false able for response. ORRs were 47.0% (31/66) for all patients, 29.6% discovery rate-controlling method for multiple hypothesis testing. Gene (8/27) for DLBCL, 33.3% (6/18) for GCB DLBCL, and 43.5% (10/23) set enrichment analyses were performed to assess enrichment of canon- for FL. ORR was highest for patients with RT (81.3%; 13/16) (Table 1). ical pathways from the C2 collection of gene sets from mSigDB. Genes CRs were reported in four patients with DLBCL (two with GCB and two were preranked according to log FC values (from aforementioned DGE with ABC), three with FL, and two with RT. results) and analyzed using the Java-based application gsea2–2.2.0.jar Of 72 patients who had WES data, 69 were evaluable for response. with default parameters. ORRs were 50.7% (35/69) for all patients, 38.5% (10/26) for DLBCL, 37.5% (6/16) for GCB DLBCL, 46.2% (12/26) for FL, and 76.5% (13/17) Results for RT (Table 1). CRs were reported in five patients with DLBCL (two with GCB, two with ABC, and 1 with unclassified DLBCL), three with Patients and treatment FL, and two with RT (Table 1). Baseline demographics and primary efficacy and safety results for Clinical outcome analyses by biomarker LYM1002 have been reported previously [24]. Briefly, between March 12, 2015 and April 11, 2017, 141 patients were enrolled and treated PD-L1 expression with daily oral ibrutinib (420 mg or 560 mg) plus intravenous nivolumab Twenty-six patients with DLBCL, 25 with FL, and 15 with RT had (3 mg/kg every 2 weeks): relapsed/refractory CLL/SLL (n = 36; del17p IHC-based PD-L1 data available for analysis. Because only 1 of 25 pa- B.P. Hodkinson, M. Schaffer, J.D. Brody et al. Translational Oncology 14 (2021) 100977 Fig. 1. PFS and OS by IHC-based PD-L1 expression in patients with DLBCL (A and B) and GCB DLBCL (C and D). The numbers below the X-axis depict patients at risk of progression who had elevated PD-L1 and those who did not have elevated PD-L1. DLBCL, diffuse large B-cell lymphoma; GCB, germinal center B-cell–like; IHC, immunohistochemistry; OS, overall survival; PD-L1, programmed death ligand 1; PFS, progression-free survival. tients with FL had PD-L1 elevation (≥5% tumor cells by IHC), this anal- Exome analyses ysis focused on patients with DLBCL and RT. Among the 26 patients with DLBCL who had IHC data, 18 patients had PD-L1 expression <5% Responders versus nonresponders (range 0–2%) and 8 patients had PD-L1 expression ≥5% (range 5–95%), Exome and response data were available for 26 patients with DLBCL with the mean (standard deviation [SD]) of 9.6 (21.6)% (Supplementary (ORR 38.5%; 10 responders [5 CR, 5 PR], 16 nonresponders), 16 with Figure S2). Of the 8 patients with elevated PD-L1, three had a CR and GCB DLBCL (ORR 37.5%; 6 responders [2 CR, 4 PR], 10 nonresponders), two had PRs. Of the 26 DLBCL patients with IHC data, 24 also had GEP- 26 with FL (ORR 46.2%; 12 responders [3 CR, 9 PR], 14 nonresponders), based subtyping calls, with six (25.0%) having elevated PD-L1; among and 17 with RT (ORR 76.5%; 13 responders [2 CR, 11 PR], 4 nonrespon- these patients, four had GCB DLBCL (one CR, two PRs, and one SD), one ders). had ABC DLBCL (PD), and one was unclassified (PD) (Supplementary DLBCL responders versus nonresponders were more likely to have Table S2). Based on the IHC analysis, elevated PD-L1 in DLBCL (≥5% mutations in RNF213 (4/10 [40.0%] vs. 1/16 [6.2%]), KLHL14 (3/10 tumor cells positive for PD-L1) was observed more frequently in respon- [30.0%] vs. 0/16), LRP1B (3/10 [30.0%] vs. 1/16 [6.2%]), and OS- ders versus nonresponders (62.5% [5/8] vs. 18.8% [3/16]; p = 0.065) BPL10 (3/10 [30.0%] vs. 1/16 [6.2%]) (Table 2, Fig. 2). The difference and was significantly associated with CR (37.5% [3/8] vs. 0% [0/16]; in expression between responders and nonresponders was highest for p = 0.028). There was a trend toward improved PFS and OS in patients KLHL14 (p = 0.046) Fig. 2 is a heatmap of the frequently occurring mu- with DLBCL or GCB DLBCL who had elevated PD-L1 (Fig. 1). In RT, 3/15 tations from the gene set of interest occurring in patients with DLBCL (20.0%) patients with available IHC data had elevated PD-L1; all three by responder and nonresponder status, sorted by p values within the re- had PRs with durable PFS and OS. At study closure, two of the three pa- sponder gene block (top four genes) and the nonresponder gene block tients with elevated PD-L1 had not progressed, and all three were alive, (all other genes). DLBCL nonresponders commonly had variants in EBF1, but no significant correlation could be established because of the small ADAMTS20, and AKAP9. Mutations in the BCR pathway (TNFRSF14, number of patients. NFKB1B), epigenetic modifiers (CREBBP, KMT2D), and other signaling B.P. Hodkinson, M. Schaffer, J.D. Brody et al. Translational Oncology 14 (2021) 100977 Table 2 Frequent Differentially Mutated Genes between Responders and Nonresponders in Diffuse Large B-Cell Lymphoma (Occurring in at Least Three Patients in Either Group). Gene Responders(n = 10) Nonresponders(n = 16) Odds Ratio (95% CI) p Value Mutations more frequent in responders KLHL14 3 (30.0%) 0 (0.0%) Inf (0.730–Inf) 0.046 RNF213 4 (40.0%) 1 (6.2%) 9.053 (0.711–522.371) 0.055 LRP1B 3 (30.0%) 1 (6.2%) 5.950 (0.397–358.476) 0.264 OSBPL10 3 (30.0%) 1 (6.2%) 5.950 (0.397–358.476) 0.264 Mutations more frequent in nonresponders EBF1 0 (0.0%) 4 (25.0%) 0.000 (0.000–2.304) 0.136 ADAMTS20 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 AKAP9 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 CHD8 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 CSDE1 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 EML4 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 GPR124 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 KIAA1109 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 KLF2 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 MDC1 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 MEF2C 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 SOCS1 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 SPTA1 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 TNFRSF14 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 TP53 0 (0.0%) 3 (18.8%) 0.000 (0.000–3.825) 0.262 CREBBP 1 (10.0%) 5 (31.2%) 0.257 (0.005–2.940) 0.352 KMT2D 2 (20.0%) 6 (37.5%) 0.430 (0.034–3.353) 0.42 BCL7A 1 (10.0%) 4 (25.0%) 0.346 (0.006–4.350) 0.617 HIST1H1C 1 (10.0%) 4 (25.0%) 0.346 (0.006–4.350) 0.617 HIST1H1E 1 (10.0%) 4 (25.0%) 0.346 (0.006–4.350) 0.617 SGK1 1 (10.0%) 4 (25.0%) 0.346 (0.006–4.350) 0.617 CSMD3 3 (30.0%) 7 (43.8%) 0.564 (0.068–3.754) 0.683 CI, confidence interval. Fig. 2. Diffuse large B-cell lymphoma gene-level mutation heatmap showing variants from panel of interest occurring in at least three patients, by responder status. Each vertical column represents an individual patient. pathways were also observed (Table 2, Fig. 3). Mutations in HIST1H1C, observed in nonresponders, with 10% (1/10) of responders and 50% BCL7A, and SGK1 were reported in both responders and nonresponders (8/16) of nonresponders having mutations associated with BCR signal- but were generally more frequent in nonresponders (Table 2). ing (p = 0.087). Gene mutations implicated in the pathogenesis of DLBCL [27] were In the GCB DLBCL subset, there were no gene variants that reached generally more frequent in nonresponders (Supplementary Table S2). significance between responders and nonresponders (Supplementary Ta- None of the DLBCL responders had mutations in TP53, MYD88, GNA13, ble S3). The most differentially expressed gene mutations were more and TNFRSF14, while frequency of these mutations in nonresponders frequent in nonresponders versus responders: CSMD3 (5/10 [50%] vs. ranged from 12.5% to 18.8%. Of note, there were two mutations in 0/6 [0%], p = 0.093); BCL2 (6/10 [60.0%] vs. 1/6 [16.7%], p = 0.145); MYD88 (both in nonresponders) and one in CARD11 (in a responder). KMT2D (6/10 [60.0%] vs. 1/6 [16.7%], p = 0.145); CREBBP, EBF1, and In DLBCL, a trend toward more BCR pathway–associated mutations was SGK1 (all 4/10 [40.0%] vs. 0/6 [0%], p = 0.234). B.P. Hodkinson, M. Schaffer, J.D. Brody et al. Translational Oncology 14 (2021) 100977 pathways related to the extracellular matrix (ECM) processing (eg, gly- coproteins, collagen, ECM organization, and general matrisome activity; Table 5). The most enriched pathways in responders and nonresponders with DLBCL, FL, and RT are summarized in Supplementary Tables S7, S8, and S9. The pathways with greater activation in the DLBCL nonresponders were predominantly related to cell cycle, DNA replication, and RNA splicing/processing/metabolism (Supplementary Table S7). The respon- ders with FL had enrichment of activity in pathways related to RNA splicing/processing/metabolism (Supplementary Table S8). Discussion Reliable disease subtype identification in patients receiving novel therapies is an important step toward personalizing treatment for pa- tients with relapsed/refractory B-cell malignancies, who have limited options for achieving durable responses. Further, biomarker analyses can help identify patients most likely to benefit from molecularly tar- geted therapies. This analysis evaluated several potential biomarkers of Fig. 3. Functional groups of mutated genes in patients with diffuse large B-cell response to combined treatment with ibrutinib and nivolumab in pa- lymphoma. The pie chart shows the number of patients (N = 52) with somatic tients with DLBCL (subtyped using GEP and HTG methods), FL, and RT, mutations in ≥1 gene representing the associated functional grouping. using data from the primary LYM1002 phase I/IIa study. Among patients who had both GEP and response data, good re- Mutation frequencies differing for responders versus nonresponders sponses to treatment were noted in all cohorts, with the highest re- in FL and RT, respectively, were in BCL2 (9/12 [75.0%] vs. 4/14 sponse rate in RT (81.3%). Patients with DLBCL had an ORR of 29.6%. [28.6%]; p = 0.047) and ROS1 (0/13 vs. 2/4 [50.0%]; p = 0.044). No ma- Responses were more frequent in patients with the GCB subtype (6/18 jor differences were observed in overall TMB between responders and [33.3%]), which is in contrast to the ORR of 5% reported previously nonresponders with DLBCL (p = 0.215), FL (P = .899), or RT (p = 1.000); for single-agent ibrutinib [13]. These results, with the caveat of limited however, in GCB DLBCL, TMB was substantially lower for responders sample size and no central review of GCB status, suggest that ibrutinib in (p = 0.003) (Supplementary Figure S3A-D). combination with nivolumab may have increased efficacy in this patient population. PFS >24 versus ≤24 months in DLBCL PD-L1 expression was investigated in various solid tumors treated In DLBCL, RNF213 (3/7 [42.9%]), NBPF1 (3/7 [42.9%]), KLHL14 with nivolumab, using the definition of PD-L1 positivity as ≥5% cell (2/7 [28.6%]), and LRP1B (2/7 [28.6%]) variants were more often seen membrane staining of any intensity [34]. DLBCL tumors often express in patients with PFS >24 months. In patients with PFS ≤24 months, PD-L1 [35–38], and analyzing expression of PD-L1 in DLBCL using the most common variants included KMT2D (8/20 [40.0%]), CREBBP biopsy samples and a 5% threshold for PD-L1 positivity reported vary- (6/20 [30.0%]), HIST1H1E (5/20 [25.0%]), EP400 (4/20 [20.0%]), and ing percentages of PD-L1–positive DLBCL, ranging from 11% to 49% PDE4DIP (6/20 [30.0%]), all of which are involved in chromatin struc- [35,37,38]. In this study, approximately 30% of patients with DLBCL ture; EBF1 (4/20 [20.0%]), CD79B, TP53, ADAMTS20, AKAP9, and TN- (including the GCB and ABC subtypes) had elevated PD-L1 expression FRSF14 (all 3/20 [15.0%]) variants were also seen (Table 3). The TMB by IHC. Studies in large groups of patients suggest that non-GCB DL- was substantially lower in DLBCL patients with PFS >24 versus ≤24 BCL is more commonly associated with PD-L1 expression, although it months (p = 0.0288) (Supplementary Figure S3E). is observed within both GCB and ABC subtypes [35,36]. Patients with DLBCL and PD-L1 elevation showed a trend toward improved response Gene expression profiling analysis rates and prolonged survival with ibrutinib and nivolumab, with statis- tical significance reached for the association between PD-L1 expression Differential gene expression and CR (p = 0.028). These results are promising, particularly as PD-L1 Gene expression and response data were available for 66 patients. positivity in tumor cells has been associated with poor outcomes (partic- The 20 most common genes that were differentially expressed in re- ularly OS) to rituximab, cyclophosphamide, doxorubicin vincristine, and sponders versus nonresponders (all increased in responders) are listed prednisone (R-CHOP) or R-CHOP–based regimens in DLBCL [35,36]. All in Table 4. LEF1 and BTLA were the most upregulated genes in respon- three patients with RT and elevated PD-L1 achieved PRs and none of ders for all patients included in this analysis (DLBCL + FL + RT). The top them experienced PD during the course of the study. However, mean- 20 genes upregulated and downregulated in responders with DLBCL, FL, ingful correlations between PD-L1 status and RT outcome were not pos- and RT are summarized in Supplementary Tables S4, S5, and S6. In GCB sible due to the small sample size. Only one patient with FL had PD-L1 DLBCL, CRTAM was a top gene upregulated (2.25-fold) in the responder elevation; previous research indicates that PD-L1 expression is rare in group. this malignancy [39,40]. In a recent phase II study, nivolumab showed very limited activity in relapsed/refractory FL (ORR 4%), and no corre- Pathway-level gene set enrichment analysis lation between PD-1 or PD-L1 expression and response was noted [22]. Among all patients included in this analysis, pathway enrichment re- In view of this result, the high response in FL observed in our study sults were available for 41 ibrutinib plus nivolumab responders and 37 (43.5%) might have been driven mostly by ibrutinib, consistent with nonresponders. Among various histologies, responder and nonrespon- single-agent ibrutinib achieving ORR of 37.5% in a phase II study in der results, respectively, were available for 8 and 19 patients with DL- relapsed/refractory FL [14]. BCL, 10 and 13 patients with FL, and 13 and 3 patients with RT. Over- Further investigation of the combination of BTK and PD-L1 inhibitor all, pathways upregulated in responders to ibrutinib plus nivolumab re- therapy is ongoing in B-cell malignancies and could help identify his- lated mostly to RNA translation/metabolism, IL-12 signaling, TCR sig- tologies for which this treatment strategy is likely to be most benefi- naling, IFN-gamma signaling, cytokine/chemokine activity, and general cial. Ongoing phase I/II studies are evaluating the safety and efficacy immune activation (Table 5). Nonresponders had enriched activity in of ibrutinib combined with nivolumab (NCT02420912, NCT02940301) B.P. Hodkinson, M. Schaffer, J.D. Brody et al. Translational Oncology 14 (2021) 100977 Table 3 Frequent Differentially Mutated Genes Between Patients with PFS >24 versus ≤24 Months in Diffuse Large B-Cell Lymphoma (Occurring in at Least Three Patients Overall). Gene PFS >24 Months(n = 7) PFS ≤24 Months(n = 20) Odds Ratio (95% CI) p Value Mutations more frequent in patients with PFS >24 months RNF213 3 (42.9%) 2 (10.0%) 6.147 (0.527–97.903) 0.091 KLHL14 2 (28.6%) 1 (5.0%) 6.889 (0.303–469.371) 0.156 LRP1B 2 (28.6%) 2 (10.0%) 3.398 (0.200–58.569) 0.269 TRIO 2 (28.6%) 2 (10.0%) 3.398 (0.200–58.569) 0.269 NBPF1 3 (42.9%) 4 (20.0%) 2.863 (0.298–26.744) 0.328 MEF2B 2 (28.6%) 3 (15.0%) 2.190 (0.145–25.665) 0.580 SGK1 2 (28.6%) 3 (15.0%) 2.190 (0.145–25.665) 0.580 IGLL5 2 (28.6%) 4 (20.0%) 1.571 (0.111–15.591) 0.633 BCL2 3 (42.9%) 6 (30.0%) 1.712 (0.191–14.078) 0.653 Mutations more frequent in patients with PFS <24 months CREBBP 0 (0.0%) 6 (30.0%) 0.000 (0.000–2.315) 0.155 PDE4DIP 0 (0.0%) 6 (30.0%) 0.000 (0.000–2.315) 0.155 HIST1H1E 0 (0.0%) 5 (25.0%) 0.000 (0.000–3.101) 0.283 KMT2D 1 (14.3%) 8 (40.0%) 0.261 (0.005–2.854) 0.363 ADAMTS20 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 AKAP9 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 ANK3 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 CD79B 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 CHD8 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 CSDE1 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 EML4 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 EP400 0 (0.0%) 4 (20.0%) 0.000 (0.000–4.440) 0.545 GPR124 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 HIST1H2AC 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 KIAA1109 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 KLF2 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 MAP3K1 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 MDC1 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 MEF2C 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 SF3A1 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 SLC4A5 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 SPEN 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 SPTA1 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 SPTAN1 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 TET2 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 TNFRSF14 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 TP53 0 (0.0%) 3 (15.0%) 0.000 (0.000–7.204) 0.545 BTG1 0 (0.0%) 4 (20.0%) 0.000 (0.000–4.440) 0.545 DCC 0 (0.0%) 4 (20.0%) 0.000 (0.000–4.440) 0.545 EBF1 0 (0.0%) 4 (20.0%) 0.000 (0.000–4.440) 0.545 EP400 0 (0.0%) 4 (20.0%) 0.000 (0.000–4.440) 0.545 MUC17 0 (0.0%) 4 (20.0%) 0.000 (0.000–4.440) 0.545 NRG1 0 (0.0%) 4 (20.0%) 0.000 (0.000–4.440) 0.545 CSMD3 2 (28.6%) 8 (40.0%) 0.611 (0.047–4.995) 0.678 CI, confidence interval; PFS, progression-free survival. or pembrolizumab (NCT03153202, NCT03514017, NCT03204188, melanoma and an association with response to PD-1 blockade has been NCT02332980, NCT03204188) in NHL or classic Hodgkin’s lymphoma. reported[48]. Exome analyses were aimed at identifying gene mutations enriched DLBCL nonresponders commonly had mutations in EBF1, in patients who responded versus those who did not respond to treat- ADAMTS20, and AKAP9 genes generally involved in tumor initia- ment with ibrutinib plus nivolumab. In DLBCL, the top three gene mu- tion/proliferation [49-51]. It has been suggested that mutations of tations more frequently mutated in responders versus nonresponders in- CARD11 (another gene implicated in NF-𝜅B pathway activation down- cluded KLHL14 (p = 0.046), RNF213 (p = 0.055), and LRP1B (p = 0.264). stream of BTK) predict lack of response to ibrutinib in DLBCL and FL KLHL14 belongs to the Kelch-like family of proteins that can serve as [13,14]. In our analyses of patients with DLBCL, nonresponders were subunits of Cullin-RING ubiquitin ligase complex [41] highly expressed more likely to have mutations in genes involved in alternate BCR path- in B cells, promoting B1a but suppressing B1b cell development in ways converging on NF-𝜅B, such as TNFRSF14, MYD88, and NFKB1B, mice, and thus revealing a role in controlling B cell differentiation [42]. which are among the genes implicated in the pathogenesis of DLBCL KLHL14 is frequently mutated in ABC DLBCL cells [43], and recent in and recurrent in refractory disease [27,28]. Notably, none of the DLBCL vitro data have highlighted involvement of KLHL14 in BCR-dependent responders had mutations in TP53, MYD88, and TNFRSF14. Other gene NF-𝜅B activation [44]. Mutations in RNF213, the Moyamoya disease variants occurred frequently but were not linked to response, such as gene product and an E3 ligase, have been reported in liver cancers CSMD3, BCL2, and NBPF1. [45] and RNF213-ALK fusion has been described in anaplastic large cell As mentioned, ibrutinib plus nivolumab had an unexpectedly high lymphoma [46]. In HER2+ breast cancer cells, RNF213 was uncovered antitumor activity in GCB DLBCL, emphasizing the clinical benefit of to be a substrate for the protein-tyrosine phosphatase PTP1B, and both adding nivolumab to ibrutinib. However, overall TMB was lower in re- proteins were required for survival of HER2+ breast cancer in the hy- sponders with GCB DLBCL and in DLBCL patients with PFS >24 versus poxic tumor microenvironment[47] Mutations in LRP1B are frequent in ≤24 months, contrary to previous reports in non–small-cell lung car- B.P. Hodkinson, M. Schaffer, J.D. Brody et al. Translational Oncology 14 (2021) 100977 Table 4 The Top 20 Genes Differentially Expressed Between Responders and Nonresponders to Ibrutinib plus Nivolumab Among All Patients with Non-Hodgkin’s Lymphomaa . Gene Description Log FC Adjusted p Value Genes upregulated in the responder group LEF1 Lymphoid enhancer-binding 1.058 0.001 factor 1 BTLA B and T lymphocyte associated 1.095 0.001 PATL2 Protein associated with 1.111 0.003 topoisomerase II homolog 2 (yeast) SIDT1 SID1 transmembrane family, 0.872 0.015 member 1 PYHIN1 Pyrin and HIN domain family, 1.261 0.016 member 1 L3MBTL3 l(3)mbt-like 3 (Drosophila) 0.982 0.028 FAM114A2 Family with sequence similarity 0.545 0.028 114, member A2 TBC1D15 TBC1 domain family, member 15 0.400 0.028 LEPROTL1 Leptin receptor overlapping 0.817 0.028 transcript-like 1 SACS Sacsin molecular chaperone 0.905 0.028 LMBRD1 LMBR1 domain containing 1 0.808 0.028 GCLC Glutamate-cysteine ligase, 1.150 0.028 catalytic subunit APOL3 Apolipoprotein L, 3 0.946 0.028 SRBD1 S1 RNA binding domain 1 0.658 0.028 TIGIT T cell immunoreceptor with Ig 0.562 0.032 and ITIM domains CCL4 Chemokine (C–C motif) ligand 4 0.697 0.032 MDM1 Mdm1 nuclear protein 0.725 0.032 SUB1 SUB1 homolog, transcriptional 0.850 0.032 regulator FCMR Fc fragment of IgM receptor 1.378 0.032 GMFG Glia maturation factor, gamma 0.547 0.035 Genes downregulated in the responder group C5orf66 Chromosome 5 open reading –0.503 0.053 frame 66 PAPPA Pregnancy-associated plasma –0.442 0.056 protein A, pappalysin 1 CCDC120 Coiled-coil domain containing –0.331 0.061 120 SOX9 SRY (sex determining region –1.061 0.066 Y)-box 9 STS Steroid sulfatase (microsomal), –0.421 0.067 isozyme S LYPD6B LY6/PLAUR domain containing –0.573 0.075 6B ARR3 Arrestin 3, retinal (X-arrestin) –0.497 0.076 LMOD1 Leiomodin 1 (smooth muscle) –0.328 0.081 LOC102546294 Uncharacterized LOC102546294 –0.427 0.085 BAIAP2L1 BAI1-associated protein 2-like 1 –0.472 0.085 SPINK2 Serine peptidase inhibitor, Kazal –0.545 0.090 type 2 (acrosin-trypsin inhibitor) FGF14 Fibroblast growth factor 14 –0.509 0.092 HMCN1 Hemicentin 1 –0.895 0.093 ATG9B Autophagy related 9B –0.432 0.095 ESRP2 Epithelial splicing regulatory –0.554 0.099 protein 2 CASC15 Cancer susceptibility candidate –0.472 0.103 15 (non-protein coding) ZFHX3 Zinc finger homeobox 3 –0.340 0.103 CLDN1 Claudin 1 –0.826 0.103 SLC1A1 Solute carrier family 1 –0.430 0.103 (neuronal/epithelial high affinity glutamate transporter, system Xag), member 1 LARGE-AS1 LARGE antisense RNA 1 –0.494 0.103 a Diffuse large B-cell lymphoma, follicular lymphoma, and Richter’s transformation. cinoma and melanoma linking higher mutational burden with greater of these results in larger patient samples is warranted to fully understand effectiveness of immune checkpoint blockade therapy [52,53]. On the their clinical and biological significance. other hand, non–small-cell lung carcinoma and melanoma have a very In FL, BCL2 mutations were more frequent in responders (75% vs. high average mutational burden, unlike the relatively low average mu- 28.6% in nonresponders). It has been proposed that BCL2 mutations in tational burden in DLBCL [54], suggesting that factors other than TMB FL may be a surrogate for genomic instability triggered by activation- may be linked to the antitumoral immune response in DLBCL. Validation induced cytidine deaminase (AID) [55]. In FL, a significant association B.P. Hodkinson, M. Schaffer, J.D. Brody et al. Translational Oncology 14 (2021) 100977 Table 5 Most Enriched Pathways in Responders and Nonresponders to Ibrutinib plus Nivolumab among Patients with Non-Hodgkin’s Lymphomaa . Pathway Name NES FDR pValue FWER pValue Responders Translationb 2.98 0.000 0.000 Metabolism of RNAb 2.93 0.000 0.000 SRP-dependent co-translational protein targeting to membraneb 2.88 0.000 0.000 IL12_2 pathwayc 2.80 0.000 0.000 HIV infectionb 2.79 0.000 0.000 Influenza life cycleb 2.79 0.000 0.000 Metabolism of mRNAb 2.78 0.000 0.000 Adaptive immune systemb 2.73 0.000 0.000 3UTR-mediated translational regulationb 2.71 0.000 0.000 Host interactions of HIV factorsb 2.71 0.000 0.000 Processing of capped intron containing pre-mRNAb 2.68 0.000 0.000 CD8 TCR pathwayc 2.68 0.000 0.000 TCR signalingb 2.67 0.000 0.000 Interferon signalingb 2.66 0.000 0.000 Respiratory electron transport ATP synthesis by chemiosmotic coupling and heat production by uncoupling proteinsb 2.66 0.000 0.000 TCA cycle and respiratory electron transportb 2.64 0.000 0.000 Interferon gamma signalingb 2.63 0.000 0.000 TCR pathwayc 2.60 0.000 0.000 Signaling by the BCR 2.59 0.000 0.000 Antiviral mechanism by IFN-stimulated genesb 2.59 0.000 0.000 Nonresponders Core matrisomed –2.92 0.000 0.000 Integrin 1 pathwayc –2.77 0.000 0.000 ECM glycoproteinsd –2.74 0.000 0.000 Cytochrome P450 arranged by substrate typeb –2.58 0.000 0.000 ECM receptor interactione –2.56 0.000 0.000 ECM organizationb –2.48 0.000 0.000 Phase 1 functionalization of compoundsb –2.48 0.000 0.000 Regulation of IGF activity by IGF-binding proteinsb –2.48 0.000 0.000 Cell-cell junction organizationb –2.41 0.000 0.000 Collagen formationb –2.41 0.000 0.000 A tetrasaccharide linker sequence is required for GAG synthesisb –2.38 0.000 0.000 ECM regulatorsd –2.38 0.000 0.000 Olfactory signaling pathwayb –2.35 0.000 0.000 Linoleic acid metabolisme –2.32 0.000 0.002 Avb3 integrin pathwayc –2.30 0.000 0.003 Collagensd –2.29 0.000 0.003 Tight junction interactionsb –2.27 0.000 0.004 Bile acid and bile salt metabolismb –2.25 0.000 0.009 Cell junction organizationb –2.24 0.000 0.009 Integrin 3 pathwayc –2.23 0.000 0.009 a Diffuse large B-cell lymphoma, follicular lymphoma, and Richter’s transformation.Databases: b REACTOME. c PID. d NABA. e KEGGFDR, false discovery rate; FWER, family-wise error rate; NES, normalized enrichment score. between risk and TMB (also often used as a proxy for genomic instabil- with ibrutinib plus nivolumab. The top genes upregulated in all patients ity) has been previously demonstrated [56]. The lack of a distinct an- who responded to ibrutinib plus nivolumab included LEF1 and BTLA. ticorrelation between TMB and response in the FL cohort of this study LEF1 is expressed at early stages of B-cell differentiation and is essen- (compared with DLBCL) may indicate that there is some degree of bene- tial for cell survival and proliferation. Overexpression of LEF1 is asso- fit being derived from ibrutinib plus nivolumab therapy in genomically ciated with poor prognosis and disease progression in CLL [57], and its unstable patients with high TMB FL. This is supported by the fact that presence here may reflect the contribution of ibrutinib to the response. the patients with ≥30 mutated cancer-related genes in the set examined BTLA is a lymphocyte inhibitory receptor that is expressed on Th1 but in this work (n = 1742) all had BCL2 mutations and a response rate of not Th2 cells [58]. Increased BTLA expression in ibrutinib-responding 75% (3/4; top two patients with the most mutations were responders), patients with NHL is consistent with the finding that ibrutinib can drive while the patients with response data who had <10 mutated genes of Th1- versus Th2 T-cell immunity [59]. Moreover, BTLA, TIGIT, and CCL4 interest had a 0% (0/2) response rate (neither had BCL2 mutations). are associated with T-cell exhaustion and tumor response to checkpoint CREBBP and KMT2D mutations were also frequent in FL, though not blockade [60,61]. Therefore, the fact that each of these genes is highly significantly associated with response. Longitudinal analyses had previ- upregulated in tumor tissue of responding patients suggests that the PD- ously identified CREBBP and KMT2D variants as early driver mutations 1 blockade was also a significant part of the clinical efficacy in these in chromatin regulator genes [29]. The mutational spectrum in RT in patients. this study was quite different than that observed in the other histolo- In GCB DLBCL, CRTAM was the most upregulated gene in the respon- gies. ROS1 was more frequent in RT nonresponders (2/4 vs. 0/13 in ders. CRTAM is expressed on CD8+ T-cells, especially during late-stage responders, p = 0.044); both ROS1 and BCL2 are involved in the NF-𝜅B activation, and aids in maintaining activated T-cell populations within pathway. lymph nodes [62]. A high level of CRTAM expression likely correlates Gene expression analyses uncovered several genes and pathways dif- with an immunologically active phenotype, potentially providing a ben- ferentially expressed in responders versus nonresponders to treatment efit for patients undergoing immune therapy for cancer. B.P. Hodkinson, M. Schaffer, J.D. Brody et al. Translational Oncology 14 (2021) 100977 Overall, pathways upregulated in responders to ibrutinib plus ing; Wojciech Jurczak: Formal Analysis, Investigation, Writing – Re- nivolumab were mostly related to RNA translation/metabolism, TCR, view & Editing; Cecilia Carpio: Investigation, Writing – Review & Edit- IL-12, IFN-gamma signaling, cytokine/chemokine activity, and general ing; Dina Ben-Yehuda: Investigation, Writing – Review & Editing; Irit immune activation; similar trends are seen with DLBCL and RT alone. Avivi: Investigation, Writing – Review & Editing; Ann Forslund: For- These results are consistent with studies reporting that PD-1 targets TCR mal Analysis, Investigation, Writing – Review & Editing; Muhit Özcan: signaling to inhibit functional T-cell activation [63], and anti-PD-1 ther- Investigation, Writing – Review & Editing; John Alvarez: Investigation, apy reduces this inhibition. Moreover, successful activation of T cells Writing – Review & Editing; Rob Ceulemans: Investigation, Writing – depends on a cross-talk between T cells and dendritic cells that involves Review & Editing; Nele Fourneau: Formal Analysis, Investigation, Writ- IL-12 and IFN-gamma signaling [64]. IL-12 and IFN-gamma are also as- ing – Review & Editing; Sriram Balasubramanian: Conceptualization, sociated with Th1 differentiation [65], and we have previously shown Investigation, Formal Analysis, Writing – Original Draft, Writing – Re- increased secretion of these proteins in ibrutinib responders in FL [66]. view & Editing; Anas Younes: Conceptualization, Investigation, Formal Based on two separate analyses in all patients and a subgroup of patients Analysis, Writing – Original Draft, Writing – Review & Editing. with DLBCL, our results suggest that patients showing high activity of these immune-related pathways may be more responsive to anti-PD-1 Declaration of Competing Interest agents in combination with ibrutinib. Pathways related to BCR signal- ing were also enriched in responders with FL, consistent with the mech- A. Younes received research funding from Novartis, Janssen, and anism of action of ibrutinib. Curtis and honoraria from Bayer, Merck, Bristol Myers Squibb, Celgene, Among all patients, nonresponders had enriched activity in pathways Incyte, Janssen, Sanofi, Seattle Genetics, and Takeda Millennium. W. Ju- related to the ECM processing. A recently published study identified a rczak has served as a consultant or in an advisory role for Janssen-Cilag, distinct set of ECM genes upregulated in cancer and correlated with poor Acerta Pharma, Sandoz-Novartis, Celltrion, MEI Pharma, Roche, and prognosis [67]. Transcriptional program dysregulation of these genes Gilead Sciences and has received research funding from Janssen-Cilag, was linked to the activation of TGF-beta signaling in cancer-associated Acerta Pharma, Merck, Gilead Sciences, TG Therapeutics, Pfizer, Incyte, fibroblasts and subsequent immunosuppression [67]. The pathways ac- Bayer HealthCare Pharmaceuticals, Sandoz-Novartis, Roche, Celltrion, tivated in the DLBCL nonresponders related mostly to cell cycle, DNA Takeda Pharmaceuticals, Affimed Therapeutics, and Epizyme. M. Özcan replication, and RNA splicing/processing/metabolism. These pathways has received research funding from Archigen, AbbVie, Novartis, Bayer, may represent resistance mechanisms because they can drive cancer sur- Roche, MSD, Janssen, Celgene, and Takeda and honoraria and travel vival or progression using mechanisms that are not affected by ibrutinib funding from Takeda, Bristol Myers Squibb, JAZZ, Sanofi, Abdi İbrahim, or nivolumab. Interestingly, some of the pathways enriched in respon- and Roche. JD Brody received research funding from Janssen, Merck, ders with FL appeared to be implicated in RNA metabolism or trans- Bristol Myers Squibb, Seattle Genetics, Takeda, Kite, Acerta, Celgene, lational regulation, possibly indicating high AID activity in responders. and Morphosys. A. Forslund is an employee of Bristol Myers Squibb and As discussed previously, responder-associated BCL2 mutations in FL may owns stock in the company. B. Hodkinson, M. Schaffer, N. Fourneau, J. serve as a proxy for AID-mediated genomic instability. The DNA muta- Alvarez, R. Ceulemans, and S. Balasubramanian are employees of the tor activity of AID, which can ultimately serve to increase neoantigen Janssen Pharmaceutical Companies of Johnson & Johnson. S. Balasub- presentation and thereby response to checkpoint inhibition, is regulated ramanian owns stock in Pharmacyclics/AbbVie. C. Carpio, I. Avivi, and by the RNA exosome complex, meaning that RNA processing could be D. Ben-Yehuda have nothing to disclose. related to the mechanism behind many FL-associated BCL2 mutations and genomic instability [68]. Acknowledgements In conclusion, there was a trend toward improved survival with ibru- tinib and nivolumab in patients with DLBCL with elevated PD-L1, al- The authors would like to thank all the patients who participated in though the differences did not reach statistical significance. We have this study, as well as the study investigators. identified several gene mutations, as well as differentially expressed genes and enriched signaling pathways, in patients with DLBCL, FL, and Funding RT who responded versus those who did not respond to treatment with ibrutinib plus nivolumab. The preliminary analyses reported herein may Sponsored by Janssen Research & Development, LLC. highlight some of the mechanisms involved in the action of this thera- peutic combination and help identify patients with B-cell malignancies Supplementary materials who are most likely to benefit from treatment with ibrutinib combined with an anti-PD-1/PD-L1 agent, which may represent a salvage therapy Supplementary material associated with this article can be found, in for patients with relapsed/refractory NHL. the online version, at doi:10.1016/j.tranon.2020.100977. Role of the funding source References Writing assistance was provided by Ewa Wandzioch and Liqing Xiao [1] J.C. Byrd, J.R. Brown, S. O’Brien, J.C. Barrientos, N.E. Kay, N.M. Reddy, et al., Ibru- of Parexel and funded by Janssen Global Services, LLC. tinib versus ofatumumab in previously treated chronic lymphoid leukemia, N. Engl. J. Med. 371 (3) (2014) 213–223. [2] S. O’Brien, R.R. Furman, S. Coutre, I.W. Flinn, J.A. Burger, K. Blum, et al., Sin- Data-sharing statement gle-agent ibrutinib in treatment-naive and relapsed/refractory chronic lymphocytic leukemia: a 5-year experience, Blood 131 (17) (2018) 1910–1919. [3] P.M. Barr, T. Robak, C. Owen, A. Tedeschi, O. Bairey, N.L. Bartlett, et al., Sus- The data in this publication will be available from the corresponding tained efficacy and detailed clinical follow-up of first-line ibrutinib treatment in author upon request. older patients with chronic lymphocytic leukemia: extended phase 3 results from RESONATE-2, Haematologica 103 (9) (2018) 1502–1510. [4] A. Chanan-Khan, P. Cramer, F. Demirkan, G. Fraser, R.S. Silva, S. Grosicki, et al., Author contributions (per CRediT) Ibrutinib combined with bendamustine and rituximab compared with placebo, ben- damustine, and rituximab for previously treated chronic lymphocytic leukaemia or Brendan P. Hodkinson: Conceptualization, Formal Analysis, Inves- small lymphocytic lymphoma (HELIOS): a randomised, double-blind, phase 3 study, tigation, Writing – Review & Editing; Michael Schaffer: Formal Analy- Lancet Oncol. 17 (2) (2016) 200–211. [5] A. Noy, V.S. de, C. Thieblemont, P. Martin, C.R. Flowers, F. Morschhauser, et al., sis, Investigation, Writing – Review & Editing; Joshua D. Brody: Con- Targeting Bruton tyrosine kinase with ibrutinib in relapsed/refractory marginal zone ceptualization, Formal Analysis, Investigation, Writing – Review & Edit- lymphoma, Blood 129 (16) (2017) 2224–2232. B.P. Hodkinson, M. Schaffer, J.D. Brody et al. Translational Oncology 14 (2021) 100977 [6] M.L. Wang, S. Rule, P. Martin, A. Goy, R. Auer, B.S. Kahl, et al., Targeting BTK with [34] J.F. Novotny Jr., J. Cogswell, H. Inzunza, C. Harbison, C. Horak, S Averbuch, Es- ibrutinib in relapsed or refractory mantle-cell lymphoma, N. Engl. J. Med. 369 (6) tablishing a complementary diagnostic for anti-PD-1 immune checkpoint inhibitor (2013) 507–516. therapy, Ann. Oncol. 27 (10) (2016) 1966–1969. [7] M.L. Wang, K.A. Blum, P. Martin, A. Goy, R. Auer, B.S. Kahl, et al., Long-term fol- [35] L.Y. Hu, X.L. Xu, H.L. Rao, J. Chen, R.C. Lai, H.Q. Huang, et al., Expression and low-up of MCL patients treated with single-agent ibrutinib: updated safety and effi- clinical value of programmed cell death-ligand 1 (PD-L1) in diffuse large B cell lym- cacy results, Blood 126 (6) (2015) 739–745. phoma: a retrospective study, Chin. J. Cancer 36 (1) (2017) 94. [8] J.A. Burger, A. Tedeschi, P.M. Barr, T. Robak, C. Owen, P. Ghia, et al., Ibrutinib as [36] J. Kiyasu, H. Miyoshi, A. Hirata, F. Arakawa, A. Ichikawa, D. Niino, et al., Expression initial therapy for patients with chronic lymphocytic leukemia, N. Engl. J. Med. 373 of programmed cell death ligand 1 is associated with poor overall survival in patients (25) (2015) 2425–2437. with diffuse large B-cell lymphoma, Blood 126 (19) (2015) 2193–2201. [9] S.P. Treon, C.K. Tripsas, K. Meid, D. Warren, G. Varma, R. Green, et al., Ibrutinib [37] D.J. Andorsky, R.E. Yamada, J. Said, G.S. Pinkus, D.J. Betting, J.M Timmerman, in previously treated Waldenstrom’s macroglobulinemia, N. Engl. J. Med. 372 (15) Programmed death ligand 1 is expressed by non-Hodgkin lymphomas and inhibits (2015) 1430–1440. the activity of tumor-associated T cells, Clin. Cancer Res. 17 (13) (2011) 4232–4244. [10] IMBRUVICA○R (ibrutinib) [prescribing information], Janssen Biotech, Inc., Horsham, [38] B.J. Chen, B. Chapuy, J. Ouyang, H.H. Sun, M.G. Roemer, M.L. Xu, et al., PD-L1 PA, USA, Pharmacyclics LLC, Sunnyvale, CA, USA, 2019. expression is characteristic of a subset of aggressive B-cell lymphomas and virus-as- [11] IMBRUVICA (ibrutinib) [summary of Product Characteristics], Janssen-Cilag Inter- sociated malignancies, Clin. Cancer Res. 19 (13) (2013) 3462–3473. national NV, Beerse, Belgium, 2019 [Internet]. [cited April 2, 2020]. Available from: [39] S. Vranic, N. Ghosh, J. Kimbrough, N. Bilalovic, R. Bender, D. Arguello, et al., PD-L1 https://www.ema.europa.eu/en/documents/product-information/imbruvica-epar- status in refractory lymphomas, PLoS One 11 (11) (2016) e0166266. product-information_en.pdf . [40] P.K. Panjwani, V. Charu, M. DeLisser, H. Molina-Kirsch, Y. Natkunam, S Zhao, Pro- [12] N.H. Fowler, L. Nastoupil, S. De Vos, M. Knapp, I.W. Flinn, R. Chen, et al., The grammed death-1 ligands PD-L1 and PD-L2 show distinctive and restricted patterns combination of ibrutinib and rituximab demonstrates activity in first-line follicular of expression in lymphoma subtypes, Hum. Pathol. 71 (2018) 91–99. lymphoma, Br. J. Haematol. 189 (4) (2020) 650–660. [41] X. Shi, S. Xiang, J. Cao, H. Zhu, B. Yang, Q. He, et al., Kelch-like proteins: physiolog- [13] W.H. Wilson, R.M. Young, R. Schmitz, Y. Yang, S. Pittaluga, G. Wright, et al., Tar- ical functions and relationships with diseases, Pharmacol. Res. 148 (2019) 104404. geting B cell receptor signaling with ibrutinib in diffuse large B cell lymphoma, Nat. [42] S. Li, J. Liu, Q. Min, T. Ikawa, S. Yasuda, Y. Yang, et al., Kelch-like protein 14 Med. 21 (8) (2015) 922–926. promotes B-1a but suppresses B-1b cell development, Int. Immunol. 30 (7) (2018) [14] N.L. Bartlett, B.A. Costello, B.R. LaPlant, S.M. Ansell, J.G. Kuruvilla, C.B. Reeder, 311–318. et al., Single-agent ibrutinib in relapsed or refractory follicular lymphoma: a phase [43] J. Zhang, V. Grubor, C.L. Love, A. Banerjee, K.L. Richards, P.A. Mieczkowski, et al., 2 consortium trial, Blood 131 (2) (2018) 182–190. Genetic heterogeneity of diffuse large B-cell lymphoma, Proc. Natl. Acad. Sci. U. S. [15] S.M. Jaglowski, J.A. Jones, V. Nagar, J.M. Flynn, L.A. Andritsos, K.J. Maddocks, A. 110 (4) (2013) 1398–1403. et al., Safety and activity of BTK inhibitor ibrutinib combined with ofatumumab in [44] J. Choi, J.D. Phelan, G.W. Wright, B. Haupl, D.W. Huang, A.L. Shaffer 3rd, et al., chronic lymphocytic leukemia: a phase 1b/2 study, Blood 126 (7) (2015) 842–850. Regulation of B cell receptor-dependent NF-kappaB signaling by the tumor suppres- [16] A. Galaznik, R. Huelin, M. Stokes, Y. Guo, M. Hoog, T. Bhagnani, et al., Systematic sor KLHL14, Proc. Natl. Acad. Sci. U. S. A. 117 (11) (2020) 6092–6102. review of therapy used in relapsed or refractory diffuse large B-cell lymphoma and [45] X. Li, W. Xu, W. Kang, S.H. Wong, M. Wang, Y. Zhou, et al., Genomic analysis of follicular lymphoma, Future Sci OA 4 (7) (2018) FSO322. liver cancer unveils novel driver genes and distinct prognostic features, Theranostics [17] M. Yi, D. Jiao, H. Xu, Q. Liu, W. Zhao, X. Han, et al., Biomarkers for predicting 8 (6) (2018) 1740–1751. efficacy of PD-1/PD-L1 inhibitors, Mol. Cancer 17 (1) (2018) 129. [46] J.A. van der Krogt, M.V. Bempt, J.F. Ferreiro, N. Mentens, K. Jacobs, U. Pluys, et al., [18] Z.Y. Xu-Monette, J. Zhou, K.H Young, PD-1 expression and clinical PD-1 blockade Anaplastic lymphoma kinase-positive anaplastic large cell lymphoma with the vari- in B-cell lymphomas, Blood 131 (1) (2018) 68–83. ant RNF213-, ATIC- and TPM3-ALK fusions is characterized by copy number gain of [19] A. Younes, A. Santoro, M. Shipp, P.L. Zinzani, J.M. Timmerman, S. Ansell, et al., the rearranged ALK gene, Haematologica 102 (9) (2017) 1605–1616. Nivolumab for classical Hodgkin’s lymphoma after failure of both autologous stem– [47] R.S. Banh, C. Iorio, R. Marcotte, Y. Xu, D. Cojocari, A.A. Rahman, et al., PTP1B cell transplantation and brentuximab vedotin: a multicentre, multicohort, single-arm controls non-mitochondrial oxygen consumption by regulating RNF213 to promote phase 2 trial, Lancet Oncol. 17 (9) (2016) 1283–1294. tumour survival during hypoxia, Nat. Cell Biol. 18 (7) (2016) 803–813. [20] Y.L. Kasamon, R.A. de Claro, Y. Wang, Y.L. Shen, A.T. Farrell, R Pazdur, FDA ap- [48] D.B. Johnson, G.M. Frampton, M.J. Rioth, E. Yusko, Y. Xu, X. Guo, et al., Targeted proval summary: nivolumab for the treatment of relapsed or progressive classical next generation sequencing identifies markers of response to PD-1 blockade, Cancer Hodgkin lymphoma, Oncologist 22 (5) (2017) 585–591. Immunol. Res. 4 (11) (2016) 959–967. [21] A.M. Lesokhin, S.M. Ansell, P. Armand, E.C. Scott, A. Halwani, M. Gutierrez, et al., [49] S. Kumar, N. Rao, R Ge, Emerging roles of ADAMTSs in angiogenesis and cancer, Nivolumab in patients with relapsed or refractory hematologic malignancy: prelim- Cancers 4 (4) (2012) 1252–1299. inary results of a phase Ib study, J. Clin. Oncol. 34 (23) (2016) 2698–2704. [50] D. Liao, Emerging roles of the EBF family of transcription factors in tumor suppres- [22] P. Armand, A.M. Janssens, G. Gritti, J. Radford, J.M. Timmerman, A. Pinto, sion, Mol. Cancer Res. 7 (12) (2009) 1893–1901. et al., Efficacy and safety results from CheckMate 140, a phase 2 study [51] Y.S. Jo, M.S. Kim, N.J. Yoo, S.H Lee, Frameshift mutations of AKAP9 gene in gastric of nivolumab for relapsed/refractory follicular lymphoma, Blood (2020), and colorectal cancers with high microsatellite instability, Pathol. Oncol. Res. 22 (3) doi:10.1182/blood.2019004753. (2016) 587–592. [23] N. Jain, A. Ferrajoli, U. Basu, T. P.A., J.A Burger, A phase II trial of nivolumab com- [52] N. Riaz, J.J. Havel, V. Makarov, A. Desrichard, W.J. Urba, J.S. Sims, et al., Tumor bined with ibrutinib for patients with Richter transformation, Blood 32 (Supplement and microenvironment evolution during immunotherapy with nivolumab, Cell 171 1) (2018) 296. (4) (2017) 934-49 e16. [24] A. Younes, J. Brody, C. Carpio, A. Lopez-Guillermo, D. Ben-Yehuda, B. Ferhanoglu, [53] P. Zarogoulidis, V. Papadopoulos, E. Maragouli, G. Papatsibas, C. Sardeli, Y.G. Man, et al., Safety and activity of ibrutinib in combination with nivolumab in patients et al., Nivolumab as first-line treatment in non-small cell lung cancer patients-key with relapsed non-Hodgkin lymphoma or chronic lymphocytic leukaemia: a phase factors: tumor mutation burden and PD-L1 ≥50, Transl. Lung Cancer Res. 7 (Suppl 1/2a study, Lancet Haematol. 6 (2) (2019) e67–e78. 1) (2018) S28–S30. [25] P. Jain, S. O’Brien, Richter’s transformation in chronic lymphocytic leukemia, On- [54] M.S. Lawrence, P. Stojanov, P. Polak, G.V. Kryukov, K. Cibulskis, A. Sivachenko, cology 26 (12) (2012) 1146–1152. et al., Mutational heterogeneity in cancer and the search for new cancer-associated [26] M. Tsang, T.D. Shanafelt, T.G. Call, W. Ding, A. Chanan-Khan, J.F. Leis, et al., The genes, Nature 499 (7457) (2013) 214–218. efficacy of ibrutinib in the treatment of Richter syndrome, Blood 125 (10) (2015) [55] C. Correia, P.A. Schneider, H. Dai, A. Dogan, M.J. Maurer, A.K. Church, et al., BCL2 1676–1678. mutations are associated with increased risk of transformation and shortened sur- [27] J.G. Lohr, P. Stojanov, M.S. Lawrence, D. Auclair, B. Chapuy, C. Sougnez, et al., vival in follicular lymphoma, Blood 125 (4) (2015) 658–667. Discovery and prioritization of somatic mutations in diffuse large B-cell lymphoma [56] T. Tsukamoto, M. Nakano, R. Sato, H. Adachi, M. Kiyota, E. Kawata, et al., High- (DLBCL) by whole-exome sequencing, Proc. Natl. Acad. Sci. U. S. A. 109 (10) (2012) -risk follicular lymphomas harbour more somatic mutations including those in the 3879–3884. AID-motif, Sci. Rep. 7 (1) (2017) 14039. [28] H.Y. Park, S.B. Lee, H.Y. Yoo, S.J. Kim, W.S. Kim, J.I. Kim, et al., Whole-exome and [57] F. Erdfelder, M. Hertweck, A. Filipovich, S. Uhrmacher, K.A Kreuzer, High lymphoid transcriptome sequencing of refractory diffuse large B-cell lymphoma, Oncotarget 7 enhancer-binding factor-1 expression is associated with disease progression and poor (52) (2016) 86433–86445. prognosis in chronic lymphocytic leukemia, Hematol Rep. 2 (1) (2010) e3. [29] J. Okosun, C. Bodor, J. Wang, S. Araf, C.Y. Yang, C. Pan, et al., Integrated genomic [58] N. Watanabe, M. Gavrieli, J.R. Sedy, J. Yang, F. Fallarino, S.K. Loftin, et al., BTLA is a analysis identifies recurrent mutations and evolution patterns driving the initiation lymphocyte inhibitory receptor with similarities to CTLA-4 and PD-1, Nat. Immunol. and progression of follicular lymphoma, Nat. Genet. 46 (2) (2014) 176–181. 4 (7) (2003) 670–679. [30] E. Chigrinova, A. Rinaldi, I. Kwee, D. Rossi, P.M. Rancoita, J.C. Strefford, et al., Two [59] J.A. Dubovsky, K.A. Beckwith, G. Natarajan, J.A. Woyach, S. Jaglowski, Y. Zhong, main genetic pathways lead to the transformation of chronic lymphocytic leukemia et al., Ibrutinib is an irreversible molecular inhibitor of ITK driving a Th1-selective to Richter syndrome, Blood 122 (15) (2013) 2673–2682. pressure in T lymphocytes, Blood 122 (15) (2013) 2539–2549. [31] G. Wright, B. Tan, A. Rosenwald, E.H. Hurt, A. Wiestner, L.M Staudt, A gene expres- [60] R.R. Ji, S.D. Chasalow, L. Wang, O. Hamid, H. Schmidt, J. Cogswell, et al., An im- sion-based method to diagnose clinically distinct subgroups of diffuse large B cell mune-active tumor microenvironment favors clinical response to ipilimumab, Can- lymphoma, Proc. Natl. Acad. Sci. U. S. A. 100 (17) (2003) 9991–9996. cer Immunol. Immunother. 61 (7) (2012) 1019–1031. [32] B.D. Cheson, R.I. Fisher, S.F. Barrington, F. Cavalli, L.H. Schwartz, E. Zucca, [61] X. Yu, K. Harden, L.C. Gonzalez, M. Francesco, E. Chiang, B. Irving, et al., The surface et al., Recommendations for initial evaluation, staging, and response assessment of protein TIGIT suppresses T cell activation by promoting the generation of mature Hodgkin and non-Hodgkin lymphoma: the Lugano classification, J. Clin. Oncol. 32 immunoregulatory dendritic cells, Nat. Immunol. 10 (1) (2009) 48–57. (27) (2014) 3059–3068. [62] A. Takeuchi, Y. Itoh, A. Takumi, C. Ishihara, N. Arase, T. Yokosuka, et al., CRTAM [33] R. Schmitz, G.W. Wright, D.W. Huang, C.A. Johnson, J.D. Phelan, J.Q. Wang, et al., confers late-stage activation of CD8+ T cells to regulate retention within lymph node, Genetics and pathogenesis of diffuse large B-cell lymphoma, N. Engl. J. Med. 378 J. Immunol. 183 (7) (2009) 4220–4228. (15) (2018) 1396–1407. B.P. Hodkinson, M. Schaffer, J.D. Brody et al. Translational Oncology 14 (2021) 100977 [63] R. Mizuno, D. Sugiura, K. Shimizu, T. Maruhashi, M. Watada, I.M. Okazaki, et al., [66] A.K. Gopal, S.J. Schuster, N.H. Fowler, J. Trotman, G. Hess, J.Z. Hou, et al., Ibrutinib PD-1 primarily targets TCR signal in the inhibition of functional T cell activation, as treatment for patients with relapsed/refractory follicular lymphoma: results from Front. Immunol. 10 (2019) 630. the open-label, multicenter, phase II DAWN study, J. Clin. Oncol. 36 (23) (2018) [64] C.S. Garris, S.P. Arlauckas, R.H. Kohler, M.P. Trefny, S. Garren, C. Piot, 2405–2412. et al., Successful anti-PD-1 Cancer immunotherapy requires T cell-dendritic cell [67] A. Chakravarthy, L. Khan, N.P. Bensler, P. Bose, D.D De Carvalho, TGF-beta-associ- crosstalk involving the cytokines IFN-gamma and IL-12, Immunity 49 (6) (2018) ated extracellular matrix genes link cancer-associated fibroblasts to immune evasion 1148-61 e7. and immunotherapy failure, Nat. Commun. 9 (1) (2018) 4692. [65] V. Athie-Morales, H.H. Smits, D.A. Cantrell, C.M Hilkens, Sustained IL-12 signaling [68] B. Laffleur, U. Basu, J Lim, RNA exosome and non-coding RNA-coupled mechanisms is required for Th1 development, J. Immunol. 172 (1) (2004) 61–69. in AID-mediated genomic alterations, J. Mol. Biol. 429 (21) (2017) 3230–3241.