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Outcomes for patients with refractory diffuse large B cell lymphoma (DLBCL) are poor. In the multicenter ZUMA-1 phase 1 study, we evaluated KTE-C19, an autologous CD3ζ/CD28-based chimeric antigen receptor (CAR) T cell therapy, in patients with refractory DLBCL. Patients received low-dose conditioning chemotherapy with concurrent cyclophosphamide (500 mg/m2) and fludarabine (30 mg/m2) for 3 days followed by KTE-C19 at a target dose of 2 × 106 CAR T cells/kg. The incidence of dose-limiting toxicity (DLT) was the primary endpoint. Seven patients were treated with KTE-C19 and one patient experienced a DLT of grade 4 cytokine release syndrome (CRS) and neurotoxicity. Grade ≥3 CRS and neurotoxicity were observed in 14% (n = 1/7) and 57% (n = 4/7) of patients, respectively. All other KTE-C19-related grade ≥3 events resolved within 1 month. The overall response rate was 71% (n = 5/7) and complete response (CR) rate was 57% (n = 4/7). Three patients have ongoing CR (all at 12+ months). CAR T cells demonstrated peak expansion within 2 weeks and continued to be detectable at 12+ months in patients with ongoing CR. This regimen of KTE-C19 was safe for further study in phase 2 and induced durable remissions in patients with refractory DLBCL. In a multicenter phase 1 study, Locke, Neelapu, et al. report tolerability and safety of KTE-C19, a CD19 chimeric antigen receptor technology, in patients with chemorefractory DLBCL. More importantly, KTE-C19 could provide durable clinical benefit in this difficult-to-treat patient population, demonstrating broad clinical applicability of KTE-C19.

B-cell receptor (BCR) is a B cell hallmark surface complex regulating multiple cellular processes in normal as well as malignant B cells. Igα (CD79a)/Igβ (CD79b) are essential components of BCR that are indispensable for its functionality, signal initiation, and signal transduction. CD79a/CD79b-mediated BCR signaling is required for the survival of normal as well as malignant B cells via a wide signaling network. Recent studies identified the great complexity of this signaling network and revealed the emerging role of CD79a/CD79b in signal integration. In this review, we have focused on functional features of CD79a/CD79b, summarized signaling consequences of CD79a/CD79b post-translational modifications, and highlighted specifics of CD79a/CD79b interactions within BCR and related signaling cascades. We have reviewed the complex role of CD79a/CD79b in multiple aspects of normal B cell biology and how is the normal BCR signaling affected by lymphoid neoplasms associated CD79A/CD79B mutations. We have also summarized important unresolved questions and highlighted issues that remain to be explored for better understanding of CD79a/CD79b-mediated signal transduction and the eventual identification of additional therapeutically targetable BCR signaling vulnerabilities.

Development of chimeric antigen receptor T‐cell therapy has revolutionized the treatment of B‐cell malignancies, although challenges such as antigen escape and tumor heterogeneity often decrease treatment success. Modular CARs targeting multiple antigens have been proposed as an interesting solution to address these challenges by reducing the likelihood of tumor cells evading treatment through the loss of a single antigen. In this study, we present a new modular CAR platform, termed CARtein, which takes advantage of intein interactions to jointly target CD19 and CD20 antigens. We demonstrate that the CARtein system, which features a universal CAR signaling backbone that covalently binds to specific scFv‐intein recognition partners, generates fully active CARs. Functionality was validated using Raji cells and K562 cells expressing CD19 and/or CD20, observing significant T cell activation through NFAT and NFκB promoter activity and CD69 upregulation. Overall, our study lays the foundation for the establishment of a new way to target multiple antigens through a universal and inert CAR backbone with highly specific activation.

Peripheral T-cell lymphoma (PTCL) is a rare and heterogeneous group of hematological malignancies. Compared to our knowledge of B-cell tumors, our understanding of T-cell leukemia and lymphoma remains less advanced, and a significant number of patients are diagnosed with advanced stages of the disease. Unfortunately, the development of drug resistance in tumors leads to relapsed or refractory peripheral T-Cell Lymphomas (r/r PTCL), resulting in highly unsatisfactory treatment outcomes for these patients. This review provides an overview of potential mechanisms contributing to PTCL treatment resistance, encompassing aspects such as tumor heterogeneity, tumor microenvironment, and abnormal signaling pathways in PTCL development. The existing drugs aimed at overcoming PTCL resistance and their potential resistance mechanisms are also discussed. Furthermore, a summary of ongoing clinical trials related to PTCL is presented, with the aim of aiding clinicians in making informed treatment decisions.

Non-Hodgkin Lymphoma (NHL) is an increasingly prevalent hematological malignancy in Egypt, highlighting the need for a better understanding of its genetic risk factors. The TP53 and MDM4 genes play critical roles in cellular homeostasis and cancer development. This study aimed to assess the frequency of the TP53 (SNP rs1042522) Arg72Pro and MDM4 (SNP rs4245739) A > C polymorphisms as potential risk factors for NHL in adult Egyptian patients. A case-control study was conducted involving 80 adult NHL patients and 100 control age- and sex-matched healthy controls. Genotyping for the TP53 (rs1042522) Arg72Pro and MDM4 (rs4245739) A > C polymorphisms was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. A significant association was found between the homozygous TP53 Pro/Pro genotype and increased susceptibility to NHL (47.5% in patients vs 4.0% in controls;  < .001), as well as a higher frequency of the mutant C allele among NHL cases (63.8% vs 28.0%;  < .001). In contrast, no significant association was observed between MDM4 polymorphisms and NHL risk. In addition, analysis of treatment outcomes revealed no statistically significant differences in overall survival or progression-free survival based on TP53 or MDM4 genotypes. These findings suggest that the TP53 Arg72Pro polymorphism is a significant genetic marker for NHL susceptibility in the Egyptian population, while MDM4 polymorphisms do not appear to contribute to disease risk. Further studies are warranted to elucidate the genetic mechanisms underlying NHL and to explore their implications for risk stratification and therapeutic strategies.

AMD3100 (plerixafor, Mozobil®) was first identified as an anti-HIV agent specifically active against the T4-lymphotropic HIV strains, as it selectively blocked the CXCR4 receptor. Through interference with the interaction of CXCR4 with its natural ligand, SDF-1 (also named CXCL12), it also mobilized the CD34+stem cells from the bone marrow into the peripheral blood stream. In December 2008, AMD3100 was formally approved by the US FDA for autologous transplantation in patients with Non-Hodgkin’s Lymphoma or multiple myeloma. It may be beneficially used in various other malignant diseases as well as hereditary immunological disorders such as WHIM syndrome, and physiopathological processes such as hepatopulmonary syndrome.

Background This study was to examine the link between astrocyte elevated gene-1 (AEG-1) and hypoxia induced-chemoresistance in T-cell non-Hodgkin’s lymphoma (T-NHL), as well as the underlying molecular mechanisms. Methods Expression of AEG-1, LC3-II, and Beclin-1 were initially examined in human T-NHL tissues ( n  = 30) and normal lymph node tissues ( n  = 16) using western blot, real-time PCR and immunohistochemistry. Western blot was also performed to analyze the expression of AEG-1, LC3-II, and Beclin-1 in T-NHL cells (Hut-78 and Jurkat cells) under normoxia and hypoxia. Additionally, the proliferation and apoptosis of Hut-78 cells exposed to different concentration of Adriamycin (ADM) in normoxia and hypoxia were evaluated by MTT and Annexin-V FITC/PI staining assay. Finally, the effects of AEG-1 on Hut-78 cells exposed to ADM in hypoxia were assessed by MTT and Annexin-V FITC/PI staining assay, and 3-MA (autophagy inhibitor) was further used to determine the underlying mechanism. Results AEG-1, LC3-II and Beclin-1 expression were significantly increased in T-NHL tissues compared with normal tissues. Incubation of Hut-78 and Jurkat cells in hypoxia obviously increased AEG-1, LC3-II and Beclin-1 expression. Hypoxia induced proliferation and reduced apoptosis of Hut-78 cells exposed to ADM. AEG-1 overexpression further increased proliferation and decreased apoptosis of Hut-78 cells exposed to ADM in hypoxia. Moreover, overexpression of AEG-1 significantly inversed 3-MA induced-changes in cell proliferation and apoptosis of Hut-78 cells exposed to ADM in hypoxia. Conclusions This study suggested that AEG-1 is associated with hypoxia-induced T-NHL chemoresistance via regulating autophagy, uncovering a novel target against hypoxia-induced T-NHL chemoresistance.

Backgrounds and Aims Our previous study (CCCG‐BNHL‐2015) reported the treatment strategies and outcomes of pediatric B‐cell non‐Hodgkin's lymphoma (B‐NHL) in China which showed that children in low‐risk groups already have a dramatically favorable prognosis. However, for high‐risk groups, the prognosis still needs to be improved. In this study, we aimed to identify the factors influencing prognosis in high‐risk groups (stage III and stage IV). Results Our results revealed that gender, lactate dehydrogenase (LDH) level, stage at the time of diagnosis, and early complete remission (CR) achievement were significant factors influencing prognosis (p < 0.05). The 3‐year EFS rate for R4 group patients without rituximab treatment was only 25.0% ± 20.4%. Among all patients in stage IV, the 5‐year EFS rates for those with involvement of only bone marrow (BM) or central nervous system (CNS) were 83.0% ± 4.5%, 81.8% ± 8.2%, but the 5‐year EFS rates for those with both BM and CNS involved were only 37.5% ± 15.3% (p = 0.002). For stage III patients with LDH ≥ 4N, the 5‐year EFS rates for those achieving CR and those not achieving CR after 2 treatment cycle were 88.9% ± 5.2% and 67.9% ± 7.3%(p = 0.036). Conclusions Therefore, R4 group patients benefited from rituximab treatment. However, children at stage III, LDH ≥ 4N not achieving CR after the 2nd treatment cycle, and those with both BM and CNS involved are still at a very high risk of treatment failure. This study serves as a crucial reference for optimizing risk stratification, refining treatment categorizations, and optimizing treatment protocols.

Background: The opportunity to quantitatively predict next-season injury risk in the National Hockey League (NHL) has become a reality with the advent of advanced computational processors and machine learning (ML) architecture. Unlike static regression analyses that provide a momentary prediction, ML algorithms are dynamic in that they are readily capable of imbibing historical data to build a framework that improves with additive data. Purpose: To (1) characterize the epidemiology of publicly reported NHL injuries from 2007 to 2017, (2) determine the validity of a machine learning model in predicting next-season injury risk for both goalies and position players, and (3) compare the performance of modern ML algorithms versus logistic regression (LR) analyses. Study Design: Descriptive epidemiology study. Methods: Professional NHL player data were compiled for the years 2007 to 2017 from 2 publicly reported databases in the absence of an official NHL-approved database. Attributes acquired from each NHL player from each professional year included age, 85 performance metrics, and injury history. A total of 5 ML algorithms were created for both position player and goalie data: random forest, K Nearest Neighbors, Naïve Bayes, XGBoost, and Top 3 Ensemble. LR was also performed for both position player and goalie data. Area under the receiver operating characteristic curve (AUC) primarily determined validation. Results: Player data were generated from 2109 position players and 213 goalies. For models predicting next-season injury risk for position players, XGBoost performed the best with an AUC of 0.948, compared with an AUC of 0.937 for LR (P < .0001). For models predicting next-season injury risk for goalies, XGBoost had the highest AUC with 0.956, compared with an AUC of 0.947 for LR (P < .0001). Conclusion: Advanced ML models such as XGBoost outperformed LR and demonstrated good to excellent capability of predicting whether a publicly reportable injury is likely to occur the next season.