Hagemeister, Fredrick B.

Abstract Introduction: MYC+BCL2+ double expression (DE) is a biomarker for poor prognosis in diffuse large B-cell lymphoma (DLBCL), likely due to the cooperation between MYC and BCL2 oncoproteins in tumor cells. However, as generally MYC and BCL2 are separately assessed on two different slides by immunohistochemistry (IHC), MYC+ and BCL2+ results are from different cells. With the WHO-recommended cutoffs, ≥40% for MYC and ≥50% for BCL2 (sum < 100%), there is chance that the so-called DE comes from non-overlapping regions of the tumor (not single-cell DE). Moreover, tumor expression scores based on morphology assessment often vary among pathologists. In this study, we performed fluorescent multiplex IHC (fmIHC) using a MultiOmyxTM immunofluorescence platform (NeoGenomics Laboratories, Inc.) to determine single-cell MYC and BCL2 co-expression for prognostic analysis in DLBCL. Patients and Methods: Co-expression of MYC, BCL2, and 11 immunophenotypic markers by fmIHC was digitally quantified for 547 patients with DLBCL. Percentage of cells with MYC/BCL2 double or single expression was calculated for various cell types. Prognostic analysis was performed for de novo DLBCL cases, including 108 patients treated CHOP chemotherapy, and 356 patients treated with rituximab (R)-CHOP. Results: First, although MYC and BCL2 were expressed in multiple cell types, the vast majority (>90%) of MYC+BCL2+ DE cells were lymphoma cells. Frequencies of MYC and BCL2 co-expression were consistent with random distribution of independent MYC/BCL2 expression in positive cases. The activated B-cell-like subtype compared with the germinal center B-cell-like subtype had a significantly higher mean percentage of MYC+BCL2+ DE, but not single BCL2 or MYC expression, in PAX5+ cells. Second, in both the R-CHOP and CHOP cohorts, high percentages of DE in PAX5+ cells and in all DAPI+ cells were associated with significantly poorer survival of DLBCL patients. Very high percentage of single BCL2 expression in PAX5+ cells was also associated with poorer survival, however, only in a small number of patients in both cohorts. Only in the R-CHOP cohort, high single MYC expression in PAX5+ cells (in a significant proportion of the cohort) was associated with significantly poorer overall survival. In the R-CHOP cohort, eight cases had MYC/BCL2 double hit by FISH, including 3 cases with MYC/IGH fusions (DE) and 5 cases with MYC/non-IGH rearrangements (only one DE). The exclusion of these double hit cases did not impact the significance of DE and single MYC+ expression. Summary: True MYC+BCL2+ double protein expression at the single cell level is predominantly in lymphoma cells, and associated with significantly poor survival of DLBCL patients. Our results suggest high cutoffs for common MYC/BCL2 IHC to identify true double expressor lymphoma. Citation Format: Zijun Yidan Xu-Monette, Yong Li, Qingyan Au, Harry Nunns, Wenyu Shi, Alexandar Tzankov, Carlo Visco, Govind Bhagat, Eric Hsi, Xiaoxian X. Zhao, Karen Dybkaer, April Chiu, Wayne Tam, Youli Zu, Fredrick B. Hagemeister, Andrew Song, Michele Pellegrino, Heounjeong Go, Maurilio Ponzoni, Andrés Ferreri, Michael B. Møller, Benjamin Parsons, J. Han van Krieken, Miguel A. Piris, Jane N. Winter, Mingzhi Zhang, Bing Xu, Ken H. Young. Single-cell double expression of MYC and BCL2 proteins by fluorescent multiplex IHC is mainly in lymphoma cells with significant prognostic impact in large B-cell lymphoma while suggesting high cutoffs for routine IHC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6418.

Background: DNA mismatch repair (MMR) deficiency (dMMR), which leads to genomic and microsatellite instability, is a biomarker that predicts response to immunotherapies and has variable prognostic effects for chemotherapies in solid tumors. The dMMR can be detected using gene sequencing or immunohistochemistry for four essential MMR proteins: MSH6, MSH2, MLH1, and PMS2. Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive lymphoma. Previous studies have suggested the role of MMR gene variants in DLBCL lymphomagenesis, yet the prognostic role of dMMR in DLBCL has not been well studied. Methods: We performed targeted next-generation sequencing and immunohistochemistry for MSH6, MSH2, MLH1, and PMS2 in a large cohort of DLBCL patients treated with standard chemoimmunotherapy. Gene expression profiling (GEP) was performed using the Affymetrix GeneChip Human Genome HG-U133 Plus 2.0 microarray (data in GSE31312). Fluorescent multiplex immunohistochemistry (mIHC) was performed using MultiOmyx multiplexing immunofluorescence staining protocols and antibodies against 13 immune markers. We investigated the frequencies of dMRR and MMR protein expression and correlated the mutation status and expression levels with patient survival and DLBCL biology, including the number of mutated genes, GEP data, previously analyzed DLBCL biomarkers, and immune cell immunophenotypes. Results: MMR gene mutations and loss of MMR protein expression were infrequent in DLBCL (Figure A) and did not show a significant prognostic impact. MMR proteins were commonly expressed in DLBCL samples and the germinal centers of reactive tonsil controls (Figure B), with higher mean and median percentages of tumor cells expressing MSH6 and MLH1 proteins than in the solid tumor samples used for comparison. High expression of MMR proteins was associated with Ki-67, MYC, and p53 overexpression as determined by immunohistochemistry. GEP analysis identified significantly upregulated genes involved in the mitotic cell cycle and DNA metabolism and prominent downregulated immune gene signatures in DLBCL with high MMR protein expression. Fluorescent mIHC confirmed the associations with decreased T cell abundance in MSH6/MSH2/MLH1/PMS2 highly expressing DLBCL (Figure C) independent of p53 and MYC expression status, whereas MSH6/ MLH1 mutations were associated with increased T cell frequencies. High versus low expression of MSH6, MLH1, and PMS2 showed significant unfavorable prognostic effects in DLBCL when the optimal cutoffs were used for high expression. However, when the median percentages were used as cutoffs, the prognostic effects were not significant; nonetheless, MSH6 and PMS2 high expression showed significant adverse prognostic effects in the MYC¯ DLBCL subset. Interestingly, when we used Ki-67, MYC + or BCL2 + percentages in DLBCL assessed by immunohistochemistry to subtract MMR protein percentages and then correlated the differences to survival, we found significant favorable prognostic impact by higher percentage expression differences between MMR proteins and BCL2, or by intermediately higher differences between MMR proteins and MYC. For MSH2/MLH1/PMS2, the higher percentages compared with MYC/BCL2 showed no significant correlations with T cell infiltration levels, whereas the higher differences between MSH6 and MYC/BCL2 were associated with significantly lower T cell frequencies (Figure D). Conclusions: This study revealed that high expression of MMR proteins is a common feature of DLBCL associated with lower tumor-infiltrating T cells, MYC and p53 overexpression, and context-dependent prognostic effects. In contrast, dMMR and loss of MMR proteins are infrequent and have no significant prognostic effects in DLBCL treated with standard chemoimmunotherapy. These results may have implications for understanding DLBCL biology and the low efficacy of PD-1 blockade immunotherapy in DLBCL.

Abstract Purpose: Tumor-infiltrating B lymphocytes (TIL-B) have demonstrated prognostic and predictive significance in solid cancers. In this study, we aimed to distinguish TIL-Bs from malignant B-cells in diffuse large B-cell lymphoma (DLBCL) and determine the clinical and biological significance. Experimental Design: A total of 269 patients with de novo DLBCL from the International DLBCL R-CHOP Consortium Program were studied. Ultra-deep sequencing of the immunoglobulin genes was performed to determine B-cell clonotypes. The frequencies and numbers of TIL-B clonotypes in individual repertoires were correlated with patient survival, gene expression profiling (GEP) data, and frequencies of DLBCL-infiltrating immune cells quantified by fluorescent multiplex IHC at single-cell resolution. Results: TIL-B abundance, evaluated by frequencies of normal B-cell clonotypes in the immunoglobulin repertoires, remarkably showed positive associations with significantly better survival of patients in our sequenced cohorts. DLBCLs with high versus low TIL-B abundance displayed distinct GEP signatures, increased pre-memory B-cell state and naïve CD4 T-cell state fractions, and higher CD4+ T-cell infiltration. TIL-B frequency, as a new biomarker in DLBCL, outperformed the germinal center (GC) B-cell–like/activated B-cell–like classification and TIL-T frequency. The identified TIL-B–high GEP signature, including genes upregulated during T-dependent B-cell activation and those highly expressed in normal GC B cells and T cells, showed significant favorable prognostic effects in several external validation cohorts. Conclusions: TIL-B frequency is a significant prognostic factor in DLBCL and plays a crucial role in antitumor immune responses. This study provides novel insights into the prognostic determinants in DLBCL and TIL-B functions with important therapeutic implications.

Abstract Introduction: Multiple studies have demonstrated that diffuse large B-cell lymphoma (DLBCL) can be divided into subgroups based on their biology. However, these biological subgroups overlap clinically. While R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) remains the standard of care for treating patients with DLBCL, predicting which patients will not benefit from such therapy is important so that alternative therapy or clinical trials can be considered. Most of the studies stratifying patients select biomarkers first, then explore how these biomarkers can stratify patients based on outcome. We explored the potential of using machine learning to first group patients with DLBCL based on survival, then isolating the biomarkers necessary for predicting these survival subgroups. Methods: RNA was extracted from tissue paraffin blocks from 379 R-CHOP treated patients with de novo DLBCL, and from 247 patients with extranodal DLBCL. A targeted hybrid capture RNA panel of 1408 genes was used for next generation sequencing (NGS). Sequencing was performed using an Illumina NextSeq 550 System platform. Ten million reads per sample in a single run were required, and the read length was 2 × 150 bp. An expression profile was generated from the sequencing coverage profile of each individual sample using Cufflinks. A machine learning system was developed to classify patients into four groups based on their overall survival. This machine learning approach based on Naïve Bayesian algorithm was also used to discover the relevant subset of genes with which to classify patients into each of the four survival groups. To eliminate the underflow problem commonly associated with the standard Naïve Bayesian classifiers, we applied Geometric Mean Naïve Bayesian (GMNB) as the classifier to predict the survival group for each patient. Results: Using machine learning, patients were first divided into two groups: short survival (S) and long survival (L). To refine this model, we used the same approach and divided the patients in each group into two subgroups, generating four groups: long survival in the long group (LL), short survival in the long group (LS), long survival in the short group (SL), and short survival in the short group (SS). The hazard ratio for this model was 0.174 (confidence interval: 0.120-0.251), and P-value <0.0001. After defining these four groups, a machine learning algorithm was used to discover the biomarkers from the expression data of the 1408 genes from NGS data. To reduce the effects of noise and avoid overfitting, we employed a 12-step cross validation to obtain a robust measure. For an individual gene, a generalized Naïve Bayesian classifier was constructed on the training of one of the 12 subsets and tested on the other 11 testing subsets. This allowed us to limit the prediction process to 60 genes for each separation step. Using the selected biomarkers, we classified the patients in the original set (379 patients) into LL, LS, SL, and SS groups and then evaluated the survival pattern of these groups. As shown in Fig. 1A, the selected biomarkers predicted survival as expected in the overall survival groups prior to biomarker selection. For additional validation of the system, we used the selected biomarkers to classify a completely new set of 247 samples of patients with extranodal DLBCL. As shown in Fig. 1B, these selected biomarkers successfully predicted the overall survival in this group of patients with an HR of 0.530 (confidence interval: 0.234-1.197, P=0.005). This classification correlated with cell of origin classification, TP53 mutation status, MYC expression, and IRF4 expression. However, in a multivariate analysis, only TP53 mutation was independent in predicting prognosis (P=0.005) and age (below or over 60) (P=0.01) along with the survival grouping (P<0.000001). Conclusions: Using a novel machine learning approach with the expression levels of 180 genes, we developed a model that can reliably stratify patients with DLBCL treated with R-CHOP into four survival subgroups. This model can be used to identify patients who may not respond well to R-CHOP to be considered for alternative therapy and clinical trials. Figure 1 Figure 1. Disclosures Hsi: AbbVie Inc, Eli Lilly: Research Funding. Ferreri: Ospedale San Raffaele srl: Patents & Royalties; BMS: Research Funding; Pfizer: Research Funding; Beigene: Research Funding; Hutchison Medipharma: Research Funding; Amgen: Research Funding; Genmab: Research Funding; ADC Therapeutics: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; PletixaPharm: Membership on an entity's Board of Directors or advisory committees; x Incyte: Membership on an entity's Board of Directors or advisory committees; Adienne: Membership on an entity's Board of Directors or advisory committees. Piris: Millenium/Takeda, EUSA, Jansen, NanoString, Kyowa Kirin, Gilead and Celgene.: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Winter: BMS: Other: Husband: Data and Safety Monitoring Board; Actinium Pharma: Consultancy; Janssen: Other: Husband: Consultancy; Agios: Other: Husband: Consultancy; Gilead: Other: Husband: Consultancy; Epizyme: Other: Husband: Data and Safety Monitoring Board; Ariad/Takeda: Other: Husband: Data and Safety Monitoring Board; Merck: Consultancy, Honoraria, Research Funding; Novartis: Other: Husband: Consultancy, Data and Safety Monitoring Board; Karyopharm (Curio Science): Honoraria.

8523 Background: ISIS 481464 is a synthetic bicyclic nucleic acid-containing antisense oligonucleotide that is complementary to the mRNA for signal transducer and activator of transcription 3 (STAT3). Methods: Primary objective of the dose-escalation study (3+3 design) was to establish the maximum tolerated dose (MTD) and recommended phase II dose (RP2D). Secondary objectives included safety, tumor response, pharmacokinetics (PK), and pharmacodynamics (PD) using IL-6 and tumor markers. Patient (pt) eligibility included : >18 yrs old, solid tumors or lymphomas refractory to at least 1 prior systemic therapy. ISIS 481464 was administered IV as a loading dose on Days 1, 3, and 5 and then weekly. Results: 15 pts were dosed (4 at 2 mg/kg and 11 at 4 mg/kg). 6 pts had advanced lymphoma (3 DLBCL, 2 Hodgkin’s lymphoma, 1 mantle cell lymphoma) and 9 pts solid tumors. There was one dose limiting toxicity (DLT), a possibly related thrombotic microangiopathy at 4 mg/kg. Treatment emergent thrombocytopenia was observed with an average reduction of approximately 70% from baseline. Three pts, 1 at 2 mg/kg and 2 at 4 mg/kg, experienced nadirs in platelet count below 50x109/L (range 16 to 33x109/L). MTD was not reached; however, given the thrombocytopenia at 4mg/kg, the RP2D was 2mg/kg. Partial responses were observed in 2/3 DLBCL pts. The 1st DLBCL pt (2 mg/kg) with 10 prior treatments had a durable 55% reduction in tumor size and is ongoing treatment at 11 months. This pt had a 76% reduction in IL-6. The 2nd DLBCL pt (4 mg/kg) with 2 prior treatments had a 65% reduction for 4 months and was able to undergo autologous stem cell transplantation. There were no responses in the solid tumor pts. PKs revealed increased plasma trough levels (indicative of tissue concentrations) with increased dose. Conclusions: ISIS 481462 was well-tolerated and the RP2D was determined to be 2 mg/kg. Initial tumor activity was observed in DLBCL pts and a dose expansion in advanced lymphomas is ongoing. Clinical trial information: NCT01563302.