Diffuse Large B-cell Lymphoma Patients Research Articles

Predictors of Survival, Treatment Modalities, and Clinical Outcomes of Diffuse Large B-Cell Lymphoma in Patients Older Than 70 Years Still an Unmet Medical Need in 2024 Based on Real-World Evidence

Background: Diffuse large B-cell lymphoma (DLBCL) especially affects the older population. Old (≥60 years) and very old age (≥80 years) DLBCL patients often present high-risk molecular alterations, lower tolerability to conventional immunochemotherapy, and poor clinical outcomes. In this scenario, attenuated therapeutic strategies, such as the R-MiniCHOP and R-MiniCHOP of the elderly regimens, have emerged for this particularly fragile population. However, the responses, clinical outcomes, and toxicities of these regimens currently remain poorly understood, mainly because these individuals are not usually included in controlled clinical trials. Methods: This retrospective, observational, and single-center real-world study included 185 DLBCL, NOS patients older than 70 years treated at the largest oncology center in Latin America from 2009 to 2020. We aimed to assess the outcomes, determine survival predictors, and compare responses and toxicities between three different primary therapeutic strategies, including the conventional R-CHOP regimen and the attenuated R-MiniCHOP and R-MiniCHOP of the elderly protocols. Results: The median age at diagnosis was 75 years (70–97 years), and 58.9% were female. Comorbidities were prevalent, including 19.5% with immobility, 28.1% with malnutrition, and 24.8% with polypharmacy. Advanced clinical stage was observed in 72.4%, 48.6% had bulky disease ≥7 cm, 63.2% had B-symptoms, and 67.0% presented intermediate–high/high-risk IPI. With a median follow-up of 6.3 years, the estimated 5-year OS and PFS were 50.2% and 44.6%, respectively. The R-MiniCHOP of the elderly regimen had a lower ORR (p = 0.040); however, patients in this group had higher rates of unfavorable clinical and laboratory findings, including hypoalbuminemia (p = 0.001), IPI ≥ 3 (p = 0.013), and NCCN-IPI ≥ 3 (p = 0.002). Although associated with higher rates of severe neutropenia (p = 0.003), the R-CHOP regimen promoted increased OS (p = 0.003) and PFS (p = 0.005) in comparison to the attenuated protocols. Additionally, age ≥ 75 years, high levels of LDH, B-symptoms, advanced clinical stage (III/IV), neutrophilia, and low lymphocyte/monocyte ratio were identified as poor prognostic factors in this cohort. Conclusions: In this large and real-life Latin American cohort, we demonstrated that patients with DLBCL, NOS older than 70 years still do not have satisfactory clinical outcomes in 2024, with half of cases not reaching 5 years of life expectancy after diagnosis. Although the conventional R-CHOP offers response and survival advantages over attenuated regimens, its myelotoxicity is not negligible. Therefore, the outcomes reported and the prognostic factors here identified may assist clinicians in the appropriate selection of therapeutic strategies adapted to the risk for old and very old DLBCL patients.

Artificial Intelligence, Lymphoid Neoplasms, and Prediction of MYC, BCL2, and BCL6 Gene Expression Using a Pan-Cancer Panel in Diffuse Large B-Cell Lymphoma

Background: Artificial intelligence in medicine is a field that is rapidly evolving. Machine learning and deep learning are used to improve disease identification and diagnosis, personalize disease treatment, analyze medical images, evaluate clinical trials, and speed drug development. Methods: First, relevant aspects of AI are revised in a comprehensive manner, including the classification of hematopoietic neoplasms, types of AI, applications in medicine and hematological neoplasia, generative pre-trained transformers (GPTs), and the architecture and interpretation of feedforward neural net-works (multilayer perceptron). Second, a series of 233 diffuse large B-cell lymphoma (DLBCL) patients treated with rituximab-CHOP from the Lymphoma/Leukemia Molecular Profiling Project (LLMPP) was analyzed. Results: Using conventional statistics, the high expression of MYC and BCL2 was associated with poor survival, but high BCL6 was associated with a favorable overall survival of the patients. Then, a neural network predicted MYC, BCL2, and BCL6 with high accuracy using a pan-cancer panel of 758 genes of immuno-oncology and translational research that includes clinically relevant actionable genes and pathways. A comparable analysis was performed using gene set enrichment analysis (GSEA). Conclusions: The mathematical way in which neural networks reach conclusions has been considered a black box, but a careful understanding and evaluation of the architectural design allows us to interpret the results logically. In diffuse large B-cell lymphoma, neural networks are a plausible data analysis approach.

Eukaryotic initiation factor 3a promotes the development of diffuse large B-cell lymphoma through regulating cell proliferation

BackgroundOne-third of diffuse large B-cell lymphoma (DLBCL) patients suffer relapse after standard treatment. Eukaryotic initiation factor 3a (eIF3a) is a key player in the initial stage of translation, which has been widely reported to be correlated with tumorigenesis and therapeutic response. This study aimed to explore the biological role of eIF3a, evaluate its prognostic and therapeutic potential in DLBCL.MethodsRNA-seq datasets from GEO database were utilized to detect the expression and prognostic role of eIF3a in DLBCL patients. Protein level of eIF3a was estimated by western blot and immunohistochemical. Next, DLBCL cells were transfected with lentiviral vector either eIF3a-knockdown or empty to assess the biological role of eIF3a. Then, samples were divided into 2 clusters based on eIF3a expression and differentially expressed genes (DEGs) were identified. Function enrichment and mutation analysis of DEGs were employed to detect potential biological roles. Moreover, we also applied pan-cancer and chemosensitivity analysis for deep exploration.ResultseIF3a expression was found to be higher in DLBCL than healthy controls, which was associated with worse prognosis. The expression of eIF3a protein was significantly increased in DLBCL cell lines compared with peripheral blood mononuclear cells (PBMCs) from healthy donors. eIF3a knockdown inhibited the proliferation of DLBCL cells and the expression of proliferation-related proteins and increase cell apoptosis rate. Besides, 114 DEGs were identified which had a close linkage to cell cycle and tumor immune. eIF3a and DEGs mutations were found to be correlated to chemosensitivity and vital signal pathways. Pan-cancer analysis demonstrated that high eIF3a expression was associated with worse prognosis in several tumors. Moreover, eIF3a expression was found to be related to chemosensitivity of several anti-tumor drugs in DLBCL, including Vincristine and Wee1 inhibitor.ConclusionsWe firstly revealed the high expression and prognostic role of eIF3a in DLBCL, and eIF3a might promote the development of DLBCL through regulating cell proliferation and apoptosis. eIF3a expression was related to immune profile and chemosensitivity in DLBCL. These results suggest that eIF3a could serve as a potential prognostic biomarker and therapeutic target in DLBCL.

Prediction of immunochemotherapy response for diffuse large B-cell lymphoma using artificial intelligence digital pathology.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous and prevalent subtype of aggressive non-Hodgkin lymphoma that poses diagnostic and prognostic challenges, particularly in predicting drug responsiveness. In this study, we used digital pathology and deep learning to predict responses to immunochemotherapy in patients with DLBCL. We retrospectively collected 251 slide images from 216 DLBCL patients treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP), with their immunochemotherapy response labels. The digital pathology images were processed using contrastive learning for feature extraction. A multi-modal prediction model was developed by integrating clinical data and pathology image features. Knowledge distillation was employed to mitigate overfitting on gigapixel histopathology images to create a model that predicts responses based solely on pathology images. Based on the importance derived from the attention mechanism of the model, we extracted histological features that were considered key textures associated with drug responsiveness. The multi-modal prediction model achieved an impressive area under the ROC curve of 0.856, demonstrating significant associations with clinical variables such as Ann Arbor stage, International Prognostic Index, and bulky disease. Survival analyses indicated their effectiveness in predicting relapse-free survival. External validation using TCGA datasets supported the model's ability to predict survival differences. Additionally, pathology-based predictions show promise as independent prognostic indicators. Histopathological analysis identified centroblastic and immunoblastic features to be associated with treatment response, aligning with previous morphological classifications and highlighting the objectivity and reproducibility of artificial intelligence-based diagnosis. This study introduces a novel approach that combines digital pathology and clinical data to predict the response to immunochemotherapy in patients with DLBCL. This model shows great promise as a diagnostic and prognostic tool for clinical management of DLBCL. Further research and genomic data integration hold the potential to enhance its impact on clinical practice, ultimately improving patient outcomes.

Abstract CT147: Phase I clinical study of Bruton’s tyrosine kinase inhibitor (BTKi) HBW-3220 capsules in patients with relapsed/refractory (R/R) B-cell non-Hodgkin lymphoma (B-NHL)

Abstract Purpose: This clinical study is to evaluate HBW-3220, a novel reversible BTK inhibitor (BTKi) with an improved in vitro profile than the existing non-covalent drugs pirtobrutinib (LOXO-305, approved) and MK-1026 (Phase III). HBW-3220 shows superior inhibition against BTK wild-type and several common mutants, such as C481S, C481R, T474I, T316A, and L528W (the one predominantly enriched in patients resistant to the newer-generation BTKis), and hematopoietic cell kinase (HCK), a key contributor to the development of ibrutinib resistance associated with kinase-defective BTK. Methods: This phase I clinical study was conducted in R/R B-NHL patients who had received two or more prior lines of treatments. The dose escalation study adopts accelerated titration and a "3+3" design, with a daily single dose of 15, 30, 60, 90, 120, or 150 mg. During the dose escalation phase, the sponsor and investigators determined whether to expand the cohort of the previous dose based on the existing data. Adverse events (AEs) were assigned according to NCI Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Response assessment was based on the iwCLL 2018 guidelines, the IWWM-7 consensus, or the Lugano 2014 guidelines, according to the respective disease type. Results: 28 patients have been enrolled so far, and the dose escalation study has been completed. No dose-limiting toxicity (DLT) occurred in any patient, implicating good tolerability. Adverse events (AEs), similar to other BTKis, were mostly Grade 1 or 2, including fever (38%), diarrhea (35%), headache (19%), anemia (42%), infectious pneumonia (23%), decreased neutrophils (42%), decreased platelet count (27%), increased alanine aminotransferase (23%), etc. Drug-related Grade 3 AEs included neutrophil count decreased (n=3, 11%), increased lymphocyte count (n=2, 7%), and infectious pneumonia (n=2, 7%). 21 patients underwent at least 1 response assessment (4 chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL); 4 marginal zone lymphoma (MZL); 5 mantle cell lymphoma (MCL); 3 diffuse large B-cell lymphoma (DLBCL); 5 other B-NHL), and the results are 1 complete response (CR), 6 partial response (PR), and 1 partial response with lymphocytosis (PR-L). The overall response rate (ORR) in CLL/SLL (all with prior irreversible BTKi treatment, and 2 of them with additional BCL2 inhibitor treatment), MZL, MCL, and DLBCL patients were 75% (3/4, including 1 PR-L), 50% (2/4), 40% (2/5) and 33% (1/3), respectively. Among the ORR (including CR, PR, and PR-L), 88% (7/8) were in the 90 mg and above dose group, regardless of previous BTKi treatment history or mutation status of p53 and BTK C481S. In the 90 mg and above dose group, the ORR is 47%. After oral administration, the drug exposures showed dose-dependent increases. The time to maximum plasma concentration (Tmax) was 2 hours, and the elimination half-life (T1/2) was 19 hours. Conclusions: The current data show that HBW-3220 is well tolerated, showing no DLT occurred at daily doses up to 150 mg, and has good efficacy in patients with CLL/SLL, MZL, and MCL. Citation Format: Ning Lee, Yingfu Li, Yong Mao, Guanfeng Liu, Jiang Li, Qingchun Liu. Phase I clinical study of Bruton’s tyrosine kinase inhibitor (BTKi) HBW-3220 capsules in patients with relapsed/refractory (R/R) B-cell non-Hodgkin lymphoma (B-NHL) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr CT147.

Real-world patient characteristics, treatment patterns, and treatment outcomes of patients with diffuse large B-cell lymphoma by line of therapy.

Although initial treatment of diffuse large B-cell lymphoma (DLBCL) with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) can be effective, up to 50% of patients will develop refractory or relapsed (R/R) disease. This study aimed to provide contemporary data on characteristics, treatment patterns, and outcomes for R/R-DLBCL. Patients with incident (January 2016 to March 2021) DLBCL age ≥18 years who initiated first-line (1L) therapy were identified from the COTA real-world database. Baseline characteristics, treatment patterns, and real-world outcomes, including time to next treatment (rwTTNT) and overall survival (rwOS), were assessed for the study population and by line of therapy (LOT). A total of 1347 eligible DLBCL patients were identified. Of these, 340 (25.2%) proceeded to receive 2L, of whom 141 (41.5%) proceeded to receive 3L, of whom 51 (36.2%) proceeded to receive 4L+. Most common treatments were R-CHOP in 1L (63.6%), stem cell transplant (SCT) in 2L (17.9%), polatuzumab vedotin, bendamustine, and rituximab (Pola-BR) in 3L (9.9%), and chimeric antigen receptor T-cell therapy (CAR-T) in 4L (11.8%). Treatment patterns were more variable in later LOTs. One- and 3-year rwOS from 1L initiation were 88.5% and 78.4%, respectively. Patients who received later LOTs experienced numerically lower 1- and 3-year rwOS (from 2L initiation: 62.4% and 46.4%, respectively). In this real-world analysis, 25.2% of patients experienced R/R-DLBCL after 1L with poor outcomes. Given the findings of this study, there is a high unmet need for novel, safe, and effective treatment options for patients with R/R DLBCL.

Development and validation of a novel prognostic nomogram for advanced diffuse large B cell lymphoma

Advanced diffuse large B cell lymphoma (DLBCL) is a common malignant tumor with aggressive clinical features and poor prognosis. At present, there is lack of effective prognostic tool for patients with advanced (stage III/IV) DLBCL. The aim of this study is to identify prognostic indicators that affect survival and response and establish the first survival prediction nomogram for advanced DLBCL. A total of 402 patients with advanced DLBCL were enrolled in this study. COX multivariate analysis was used to obtain independent prognostic factors. The independent prognostic factors were included in the nomogram, and the nomogram to predict the performance of the model was established by R rms package, C-index (consistency index), AUC curve and calibration curve. The training and validation cohorts included 281 and 121 patients. In the training cohort, multivariate analysis showed that Ki-67 (70% (high expression) vs ≤ 70% (low expression), p < 0.001), LDH (lactate dehydrogenase) (elevated vs normal, p = 0.05), FER (ferritin) (elevated vs normal, p < 0.001), and β2-microglobulin (elevated vs normal, p < 0.001) were independent predictors and the nomogram was constructed. The nomogram showed that there was a significant difference in OS among the low-risk, intermediate-risk and high-risk groups, with 5-year survival rates of 81.6%, 44% and 6%, respectively. The C-index of the nomogram in the training group was 0.76. The internal validation of the training group showed good consistency. In the internal validation cohort of the training group, the AUC was 0.828, and similar results were obtained in the validation group, with a C-index of 0.74 and an AUC of 0.803. The proposed nomogram provided a valuable individualized risk assessment of OS in advanced DLBCL patients.

Artificial intelligence-based assessment of PD-L1 expression in diffuse large B cell lymphoma

Diffuse large B cell lymphoma (DLBCL) is an aggressive blood cancer known for its rapid progression and high incidence. The growing use of immunohistochemistry (IHC) has significantly contributed to the detailed cell characterization, thereby playing a crucial role in guiding treatment strategies for DLBCL. In this study, we developed an AI-based image analysis approach for assessing PD-L1 expression in DLBCL patients. PD-L1 expression represents as a major biomarker for screening patients who can benefit from targeted immunotherapy interventions. In particular, we performed large-scale cell annotations in IHC slides, encompassing over 5101 tissue regions and 146,439 live cells. Extensive experiments in primary and validation cohorts demonstrated the defined quantitative rule helped overcome the difficulty of identifying specific cell types. In assessing data obtained from fine needle biopsies, experiments revealed that there was a higher level of agreement in the quantitative results between Artificial Intelligence (AI) algorithms and pathologists, as well as among pathologists themselves, in comparison to the data obtained from surgical specimens. We highlight that the AI-enabled analytics enhance the objectivity and interpretability of PD-L1 quantification to improve the targeted immunotherapy development in DLBCL patients.

New Insights into First-Line Therapy in Diffuse Large B-Cell Lymphoma: Are We Improving Outcomes?

Diffuse large B-cell lymphoma (DLBCL) is the most prevalent subtype of lymphoma, comprising heterogeneous patient subgroups with distinctive biological and clinical characteristics. The R-CHOP combination (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) has been the standard initial treatment, yielding prolonged remissions in over 60% of patients with advanced-stage disease. Several attempts to enhance the outcomes of this regimen over the last two decades have shown limited success. Various novel therapeutic approaches have recently emerged in lymphoma, demonstrating promising results. These include small molecules, novel monoclonal antibodies, antibody-drug conjugates (ADC), bispecific antibodies (BsAbs), and chimeric antigen receptor (CAR) T-cell therapy. This review explores recent advancements in therapeutic strategies for DLBCL and their potential impact on the initial management of DLBCL patients.

Abstract 2721: FF01: a novel humanized heavy chain antibody targeting endogenous retroviruses with anti-lymphoma activity

Abstract Background: Human endogenous retroviruses (HERVs) are transposable elements (TE) derived from retrovirus infections that occurred millions of years ago. Despite constituting 8% of our genome, their biological role still needs to be explored. HERV-K (HML-2), a subgroup of HERVs, represents the most recent retroviruses integrated into the human germline DNA. Members of the HML-2 subgroup retain complete ORF with coding potential and have garnered the most attention in disease-related studies. HERVs exhibit physiological expression in embryonic stem cells but are heavily methylated and remain almost silent in normal adult tissues. Although the mechanisms underlying HERV-K contribution to tumor cell growth and survival remain poorly understood, aberrant expression of HERVs has been demonstrated in various human tumor tissues and lymphoma. These findings led us to explore HERV-K as a potential therapeutic target in B cell lymphomas .Methods: RNA data were analyzed with Telescope. Validations were performed by qPCR, Western blot, flow cytometry, and ELISA. Env structure was obtained with AlphaFold and peptides were purchased from GeneScript. Antibody-dependent cellular cytotoxicity (ADCC) was performed with the ADCC Reporter Bioassay (Promega). Internalization was assessed using the Incucyte Fabfluor-pH Antibody labeling reagents. Results: We assessed the TE expression in RNA-seq datasets of diffuse large B cell lymphoma (DLBCL) and B cells from healthy individuals. An MDS plot showed that TEs could separate neoplastic from healthy samples, demonstrating that tumoral and normal specimens have distinct TE and HERV expression profiles. Focusing on tumor samples, DLBCLs were divided into four clusters with different prognoses. Similar results were obtained in a 47 B-cell lymphoma cell line panel. Focusing on the HML-2 family in lymphoma patients, we identified many of them upregulated in tumors. We validated RNA and protein expression of the HML-2 envelope (env) in seventeen lymphoma cell lines, and in two of them, we also proved the protein surface expression. Env-specific siRNA reduced env expression determined a decrease in cell proliferation, suggesting a contribution to lymphoma cell growth. In silico examination of the env identified four linear regions with potential for antibody binding, and peptides covering them were synthesized. We screened 150 lymphoma patients' serum samples for IgG antibodies binding to the peptides, and all peptides showed positive hits. We used a phage display screen to obtain one nanobody, FF01, binding one peptide. FF01 induced ADCC in the cell line with high surface env expression and not in a negative one. FF01 was internalized in an expressing cell, proving the principle for using it as a component of an antibody-drug conjugate. Conclusions: Our data demonstrate that HERVs are in DLBCL patients and propose FF01 as a new candidate to target HERV Env+ lymphomas. Citation Format: Filippo Spriano, Luciano Cascione, Jacopo Sgrignani, Nikolai Bendik, Sara Napoli, Giulio Sartori, Eleonora Cannas, Tao Gongo, Alberto J. Arribas, Davide Rossi, Davide F. Robbiani, Andrea Cavalli, Francesco Bertoni. FF01: a novel humanized heavy chain antibody targeting endogenous retroviruses with anti-lymphoma activity [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 2721.

Abstract 2356: NAV-006: A next-generation rituximab targeting CD20 for the treatment of B-cell lymphomas immunosuppressed by MUC16/CA125

Abstract Rituximab is a CD20-targeting antibody that is the standard-of-care for patients with Non-Hodgkin Lymphoma (NHL) cases. Rituximab’s mechanism of action includes complement-dependent cytotoxicity (CDC) and antibody-dependent cellular cytotoxicity (ADCC), herein referred to as Humoral Immuno-Oncology (HIO) mechanisms. Recent clinical evidence suggest that high serum levels of the MUC16 (CA125) protein inversely correlate with the effectiveness of rituximab clinical activity in 40-50% of follicular lymphoma (FL) as well as diffuse large B-cell lymphoma patients with newly diagnosed or relapsed/refractory (R/R) disease. In this study we demonstrated that CA125 binds to and suppresses the activity of rituximab, tafasitamab as well as the bispecific mosunetuzumab and glofitamab antibodies, which are approved for treating cases with indolent disease. These therapies have an overall response rate around 50-60%, suggesting the presence of a mechanism that allows lymphoma cells to escape these agents’ immune-mediated killing effects. CA125 may facilitate this immunosuppressive mechanism, and in fact, upon binding rituximab, CA125 reduces its affinity for the Fc receptor, CD16a, thus suppressing ADCC. Using a proprietary technology called Block-Removed Immunoglobulin Technology (BRITE) that employs randomized amino acid substitution and HIO effector function screening, we have identified a rituximab variant named NAV-006. NAV-006 is refractory to the immunosuppressive effects mediated by CA125 via its reduced CA125 interaction and increased HIO activity as compared to parent rituximab as well as the other antibodies used to treat R/R FL. In an in vivo model of human B-cell lymphoma, NAV-006 showed superior efficacy compared to parent rituximab. These data warrant further investigation of NAV-006 as a next generation anti-CD20 antibody that could improve upon the efficacy of antibody-mediated therapies used to treat NHL patients with high levels of CA125. Citation Format: Luigi Grasso, J. Bradford Kline, Nicholas C. Nicolaides. NAV-006: A next-generation rituximab targeting CD20 for the treatment of B-cell lymphomas immunosuppressed by MUC16/CA125 [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 2356.

Abstract 6326: Targeting PRDM1 to enhance CAR T cell efficacy against diffuse large B cell lymphoma (DLBCL)

Abstract CAR T cell therapy has shown remarkable success in treating patients with relapsed or refractory (r/r) DLBCL, but a majority (&amp;gt;60%) will experience disease progression. A key failure mechanism is the rapid terminal differentiation and exhaustion of CAR T cells, driven by persistent antigen exposure in vitro during manufacturing and in vivo in the DLBCL environment, which culminates in poor persistence and short-term effector functions. Recent studies have identified the transcriptional repressor PR/SET domain 1 (PRDM1) as a key regulator that drives differentiation of T cells toward these unwanted fates. Further, single cell transcriptomic profiling of r/r DLBCL biopsies has revealed PRDM1 enrichment in a cluster of exhausted-like CD8+ CAR T cells. These observations indicate that targeting PRDM1 could prevent or delay terminal differentiation/exhaustion in CAR T cells, thereby enhancing their persistence for lasting anti-tumor activity. Using CRISPR/Cas9 targeting, we have demonstrated that PRDM1-deficient CAR T cells exhibit enhanced proliferative capacity, memory characteristics, and resilience against exhaustion upon repeated stimulation. Moreover, genetic ablation of PRDM1 also promoted the in vivo expansion and persistence of CAR T cells, which led to significantly improved survival of lymphoma-bearing mice. Mechanistically, loss of PRDM1 leads to de-repression of PPARGC1A (PGC1α), a master regulator of mitochondrial biogenesis and antioxidant activity. This confers elevated tolerance to oxidative damage in CAR T cells lacking PRDM1, which showed increased capacity to buffer oxidative stress induced by mitochondrial uncouplers and constant stimulation. These findings suggest that PRDM1 loss may improve CAR T cell fitness through PGC1α upregulation and mitochondrial activation. From a translational perspective, we assessed the potential synergistic effects of PGC1α agonist, bezafibrate, with CAR T cells. Dual therapy with bezafibrate and CAR T cells mediated more robust expansion and anti-tumor immunity of CAR T cells without causing discernible adverse events. Importantly, bezafibrate alone had no direct tumoricidal effects, which indicates that bezafibrate suppressed tumor growth through modulating CAR T cell functions. Moving forward, we will uncover the previously uncharted role of PRDM1 in orchestrating the mitochondrial and metabolic activity of CAR T cells. Building upon a correlation between PRDM1 expression and CAR T cell dysfunction, we aim to pioneer the use of PRDM1 and/or its target genes as novel biomarkers for predicting clinical responses of r/r DLBCL patients to CAR T cell therapy. Our endeavors will shed light on the long-standing conundrum of CAR T cell dysfunction and offer solutions that may be applicable for improving T cell-based therapy against cancer in general. Citation Format: Sidney Wang, Lishi Xie, Xiufen Chen, Alan Cooper, Joanna Chorazeczewski, Justin Kline. Targeting PRDM1 to enhance CAR T cell efficacy against diffuse large B cell lymphoma (DLBCL) [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 6326.

Abstract 6418: 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 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 &amp;lt; 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 (&amp;gt;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.

Abstract 4911: PAIRWISE: Deep learning-powered personalized medicine approach identifies actionable drug combinations in B cell lymphoma

Abstract Combination drug therapies offer promise for improving cancer treatment. However, identifying actionable drug combinations for specific cancer subtypes and individual patients remains challenging due to the vast number of possibilities. Existing approaches like high-throughput screening (HTS) and rule-based drug additions have limitations in their ability to predict clinically translatable synergistic combinations. Therefore, advanced machine learning focused on patient-centric modelling have the potential to optimize combination therapies. PAIRWISE is a patient-centric deep learning-powered drug combination recommendation platform. Given gene expression along with chemical structures and targets from a set of two drugs being applied, the output is the binary combination outcome. PAIRWISE introduces a new approach of representing tumor genomics using the unsupervised pretraining design on 11K TCGA tumors. The power of PAIRWISE is derived from knowledge-guided transfer learning by learning from in vitro experiments with drug-drug-cell interactions and cellular heterogeneity. PAIRWISE can accurately predict combination synergy with area under the curve (AUC) &amp;gt; 0.85 across 10 tissue types in a large dataset of 200K in vitro drug combinations and significantly outperform all state-of-the-art methods. Diffuse large B cell lymphoma (DLBCL) is the most common B cell non-Hodgkin lymphoma and remains incurable in around 40% of patients. Finding optimal combination therapy for each DLBCL patient is a critical unmet need. As independent validation, we applied PAIRWISE to an external HTS study of Bruton Tyrosine Kinase inhibitor (BTKi) combinations (Griner et al., 2014), confirming the reproducibility and accuracy of high-confidence predictions (AUC = 0.72). PAIRWISE was also applied to transcriptomic data of 29 DLBCL cell lines (Bal et al., 2022) and predicted BTKi-containing combinations across ABC subtypes with higher synergy scores than GCB (P = 0.02). This is consistent with expected better overall efficacy of BTK inhibitors in ABC subtype (Younes et al., 2019; Davis et al., 2010; Wilson et al., 2015). To predict opportunities in DLBCL, PAIRWISE was used to identify BTKi partners for an additional 211 anti-cancer drugs using 562 published ex vivo DLBCL samples (Schmitz et al., 2018). PAIRWISE effectively identified novel DLBCL sub-population with significantly higher response scores for predicted BTKi combinations and favorable survival. Notably, patients predicted as responsive had significantly better outcomes upon first-line chemotherapy treatments than non-responsive ones (P &amp;lt; 0.0001). Collectively, we demonstrate that PAIRWISE is a highly efficient and generalizable framework that enables confident predictions of pairwise drug combinations at disease subtype level, with the potential of informing treatment options and clinical trial design. Citation Format: Chengqi Xu, Jake Cohen-Setton, Zhouyang Shen, Marta Milo, Ilkay US, Ben Sidders, Jude Fitzgibbon, Heng Pan, Olivier Elemento, Krishna Bulusu. PAIRWISE: Deep learning-powered personalized medicine approach identifies actionable drug combinations in B cell lymphoma [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 4911.

Characterization of primary small intestinal lymphoma: a retrospective study based on double balloon endoscopy

BackgroundThe diagnosis of primary small intestinal lymphoma (PSIL) is difficult. This study aimed to evaluate the clinical, radiological and endoscopic characteristics of PSIL and provide clue for diagnosis.MethodsA total of 30 patients diagnosed with PSIL who underwent double balloon endoscopy (DBE) in the First Affiliated Hospital of Zhejiang University were retrospectively analyzed. Clinical, radiological and endoscopic data were collected. Univariate analysis was used to determine significant indicators for differentiating three main subtypes of PSIL. Cox regression analysis was performed to assess the risk factors for survival.ResultsIn this study, 10 patients were pathologically diagnosed as diffuse large B-cell lymphoma (DLBCL), 11 were indolent B-cell lymphoma (BCL) and 9 were T-cell lymphoma (TCL). Compared with DLBCL patients, the body mass index (BMI) of TCL patients was significantly lower (p = 0.004). Meanwhile, compared with patients with DLBCL, the patients with indolent BCL had lower levels of C-reactive protein, lactate dehydrogenase (LDH), fibrinogen and D-Dimer (p = 0.004, p = 0.004, p = 0.006, and p = 0.002, respectively), and lower proportion of thicker intestinal wall and aneurysmal dilation in CT scan (p = 0.003 and p = 0.020, respectively). In terms of ulcer morphology, patients with DLBCL had significantly higher proportion of deep ulcers than patients with indolent BCL (p = 0.020, respectively). Cox regression analysis showed that drink (p = 0.034), concomitant colonic ulcers (p = 0.034) and elevated LDH (p = 0.043) are risk factors for mortality in patients with PSIL.ConclusionsThis study provides clinical characteristics of patients with PSIL. Thicker intestinal wall and aneurismal dilation detected on CT scan and deeper ulcer on DBE examination helps to establish a diagnosis of DLBCL.

Are changes in patient-reported outcomes prognostic for diffuse large B-Cell lymphoma survival? Results from the GOYA trial.

In this hypothesis-generating analysis, we examined whether longitudinal changes in patient-reported outcomes (PROs), such as symptoms, over time would be prognostic for progression-free survival (PFS) and overall survival (OS) in patients with diffuse large B-cell lymphoma (DLBCL) who were newly treated with obinutuzumab (G) in combination with CHOP (G-CHOP) or rituximab (R) with CHOP (R-CHOP), in the GOYA Phase 3 trial (NCT01287741). Our results show that from the study baseline to cycle 3day 1, every 1-point increase (worsening) in fever symptoms was associated with a 41% higher risk of death (hazard ratio [HR], 1.41; P = 0.01). Every 1-point increase (worsening) in lumps or swelling symptoms was associated with a 27% higher risk of disease progression or death (PFS events) (HR, 1.27; P = 0.01) and a 29% higher risk of death (OS events) (HR, 1.29; P = 0.02). No significant associations were observed between survival and changes in other symptoms, such as itching. Our study suggests that changes in some PROs are related to survival in DLBCL patients.

Prognostic mutation signature would serve as a potential prognostic predictor in patients with diffuse large B-cell lymphoma

The present study aimed to elucidate the prognostic mutation signature (PMS) associated with long-term survival in a diffuse large B-cell lymphoma (DLBCL) cohort. All data including derivation and validation cohorts were retrospectively retrieved from The Cancer Genome Atlas (TCGA) database and whole-exome sequencing (WES) data. The Lasso Cox regression analysis was used to construct the PMS based on WES data, and the PMS was determined using the area under the receiver operating curve (AUC). The predictive performance of eligible PMS was analyzed by time-dependent receiver operating curve (ROC) analyses. After the initial evaluation, a PMS composed of 94 PFS-related genes was constructed. Notably, this constructed PMS accurately predicted the 12-, 36-, and 60-month PFS, with AUC values of 0.982, 0.983, and 0.987, respectively. A higher level of PMS was closely linked to a significantly worse PFS, regardless of the molecular subtype. Further evaluation by forest plot revealed incorporation of international prognostic index or tumor mutational burden into PMS increased the prediction capability for PFS. The drug-gene interaction and pathway exploration revealed the PFS-related genes were associated with DNA damage, TP53, apoptosis, and immune cell functions. In conclusion, this study utilizing a high throughput genetic approach demonstrated that the PMS could serve as a prognostic predictor in DLBCL patients. Furthermore, the identification of the key signaling pathways for disease progression also provides information for further investigation to gain more insight into novel drug-resistant mechanisms.

Efficacy of intravenous high-dose methotrexate in preventing relapse to the central nervous system in R-CHOP(-like)-treated, high-risk, diffuse large B-cell lymphoma patients and its effect on mortality: a systematic review and meta-analysis.

To evaluate: 1) whether addition of prophylactic intravenous HD-MTX reduces the risk of CNS relapse in high-risk DLBCL patients treated with R-CHOP or similar and 2) whether HD-MTX prophylaxis confers an overall survival benefit, irrespective of CNS relapse. A systematic search of MEDLINE/PubMed and EMBASE on DLBCL patients at high risk of CNS relapse treated with R-CHOP or similar receiving HD-MTX as intervention and a comparator arm receiving no prophylaxis and/or IT prophylaxis. Risk of Bias was estimated using the ROBINS-I tool and the quality of the evidence by the GRADE approach. Finally, a meta-analysis based on the systematic review was conducted. A total of 1812 studies were screened. No RCT's were identified. Seven observational studies comprising 1661 patients met inclusion criteria. We found a statistically non-significant relative risk of 0.54 [0.27-1.07, 95% CI] of CNS relapse for patients receiving HD-MTX vs. controls. The meta-analysis investigating mortality demonstrated a relative risk of death of 0.70 [0.44-1.11, 95% CI] for HD-MTX treated vs. controls. The overall risk of bias was adjudged as "serious" and the quality of the evidence was rated as low. Our data indicate that HD-MTX does not prevent, or at best, only slightly reduces the risk of CNS relapse and confers no survival benefit.

[18F]FDG PET/CT for prognosis and toxicity prediction of diffuse large B-cell lymphoma patients with chimeric antigen receptor T-cell therapy.

Chimeric antigen receptor (CAR) T-cell therapy has been confirmed to benefit patients with relapsed and/or refractory diffuse large B-cell lymphoma (DLBCL). It is important to provide precise and timely predictions of the efficacy and toxicity of CAR T-cell therapy. In this study, we evaluated the value of [18F]fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG PET/CT) combining with clinical indices and laboratory indicators in predicting outcomes and toxicity of anti-CD19 CAR T-cell therapy for DLBCL patients. Thirty-eight DLBCL patients who received CAR T-cell therapy and underwent [18F]FDG PET/CT within 3 months before (pre-infusion) and 1 month after CAR T-cell infusion (M1) were retrospectively reviewed and regularly followed up. Maximum standardized uptake value (SUVmax), total lesion glycolysis (TLG), metabolic tumor volume (MTV), clinical indices, and laboratory indicators were recorded at pre-infusion and M1 time points, and changes in these indices were calculated. Progression-free survival (PFS) and overall survival (OS) were as endpoints. Based on the multivariate Cox regression analysis, two predictive models for PFS and OS were developed and evaluated the efficiency. Pre-infusion indices were subjected to predict the grade of cytokine release syndrome (CRS) resulting from toxic reactions. For survival analysis at a median follow-up time of 18.2 months, patients with values of international prognostic index (IPI), SUVmax at M1, and TLG at M1 above their optimal thresholds had a shorter PFS (median PFS: 8.1 months [IPI ≥ 2] vs. 26.2 months [IPI < 2], P = 0.025; 3.1 months [SUVmax ≥ 5.69] vs. 26.8 months [SUVmax < 5.69], P < 0.001; and 3.1 months [TLG ≥ 23.79] vs. 26.8 months [TLG < 23.79], P < 0.001). In addition, patients with values of SUVmax at M1 and ∆SUVmax% above their optimal thresholds had a shorter OS (median OS: 12.6 months [SUVmax ≥ 15.93] vs. 'not reached' [SUVmax < 15.93], P < 0.001; 32.5 months [∆SUVmax% ≥ -46.76] vs. 'not reached' [∆SUVmax% < -46.76], P = 0.012). Two novel predictive models for PFS and OS were visualized using nomogram. The calibration analysis and the decision curves demonstrated good performance of the models. Spearman's rank correlation (rs) analysis revealed that the CRS grade correlated strongly with the pre-infusion SUVmax (rs = 0.806, P < 0.001) and moderately with the pre-infusion TLG (rs = 0.534, P < 0.001). Multinomial logistic regression analysis revealed that the pre-infusion value of SUVmax correlated with the risk of developing a higher grade of CRS (P < 0.001). In this group of DLBCL patients who underwent CAR T-cell therapy, SUVmax at M1, TLG at M1, and IPI were independent risk factors for PFS, and SUVmax at M1 and ∆SUVmax% for OS. Based on these indicators, two novel predictive models were established and verified the efficiency for evaluating PFS and OS. Moreover, pre-infusion SUVmax correlated with the severity of any subsequent CRS. We conclude that metabolic parameters measured using [18F]FDG PET/CT can identify DLBCL patients who will benefit most from CAR T-cell therapy, and the value before CAR T-cell infusion may predict its toxicity in advance.

Identification of a prognostic signature based on five ferroptosis-related genes for diffuse large B-cell lymphoma.

Therapies for diffuse large B-cell lymphoma (DLBCL) are limited due to the diverse gene expression profiles and complicated immune microenvironments, making it an aggressive lymphoma. Beyond this, researches have shown that ferroptosis contributes to tumorigenesis, progression, and metastasis. We thus are interested to dissect the connection between ferroptosis and disease status of DLBCL. We aim at generating a valuable prognosis gene signature for predicting the status of patients of DLBCL, with focus on ferroptosis-related genes (FRGs). To examine the connection between ferroptosis-related genes (FRGs) and clinical outcomes in DLBCL patients based on public datasets. An expression profile dataset for DLBCL was downloaded from GSE32918 (https://www.ncbi.nlm.nih.gov/geo/ query/acc.cgi?acc=gse32918), and a ferroptosis-related gene cluster was obtained from the FerrDb database (http://www. zhounan.org/ferrdb/). A prognostic signature was developed from this gene cluster by applying a least absolute shrinkage and selection operator (LASSO) Cox regression analysis to GSE32918, followed by external validation. Its effectiveness as a biomarker and the prognostic value was determined by a receiver operator characteristic curve mono factor analysis. Finally, functional enrichment was evaluated by the package Cluster Profiler of R. Five ferroptosis-related genes (FRGs) (GOP1, GPX2, SLC7A5, ATF4, and CXCL2) associated with DLBCL were obtained by a multivariate analysis. The prognostic power of these five FRGs was verified by TCGA (https://xenabrowser.net/datapages/?dataset=TCGA.DLBC.sampleMap%2FHiSeqV2_PANCAN&host=https%3A%2F%2Ftcga.xenahubs.net&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A44) and GEO (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse 32918) datasets, with ROC analyses. KEGG and GO analyses revealed that upregulated genes in the high-risk group based on the gene signature were enriched in receptor interactions and other cancer-related pathways, including pathways related to abnormal metabolism and cell differentiation. The newly developed signature involving GOP1, GPX2, SLC7A5, ATF4, and CXCL2 has the potential to serve as a prognostic biomarker. Furthermore, our results provide additional support for the contribution of ferroptosis to DLBCL.