While biomarker-guided treatments and NGS-based approaches are refining precision medicine, they are not universally applicable. The gap between the genomic characterization of tumors and their functional behavior is becoming increasingly evident. There is an escalating demand for functional assays that can customize cancer treatments for individual patients and bridge this gap. We have developed OncoFlow, an integrated microfluidic platform that automates viability assays. This platform customizes treatment options by assessing the functional responses of a patient's tumor cells to a specific drug panel. This study specifically addressed non-small cell lung adenocarcinoma (NSCLC) in patients presenting pleural effusion. We used the NCI-H2228 adenocarcinoma cell line, which harbors the EML4-ALK fusion oncogene, to develop and fine-tune the viability assay. Cells cultivated in microfluidic chambers were treated with various concentrations of the tyrosine kinase inhibitors alectinib and crizotinib, and the cytotoxic effects were measured. The results were consistent with those from conventional cell culture methods, thereby validating the assay's reliability. Next, pleural effusion samples from six NSCLC patients, four of them harboring the EML4-ALK rearrangement were tested with alectinib and crizotinib using the OncoFlow system. Monitoring and analysis of cell viability showed varied sensitivities to crizotinib, while all samples exhibited resistance to alectinib. These findings underscore OncoFlow's potential to enhance physician decision-making and customize treatment plans, ultimately improving patient outcomes.

Immune cells within the lymphoma tumor microenvironment promote immune evasion and are rational therapeutic targets. Alemtuzumab targets CD52 expressed on malignant B-cells and infiltrating nonmalignant T-cells. We evaluated the safety and efficacy of alemtuzumab with DA-EPOCH-R in 48 patients with relapsed/refractory aggressive B-cell lymphoma. Febrile neutropenia occurred in 18% of cycles and serious infections in 21% of patients. Responses were observed in 30 (62%) patients, including 12 (80%) patients with classical HL and 3 (75%) patients with T-cell/histiocyte-rich large B-cell lymphoma (THRLCL). Seventeen (35%) patients achieved complete responses, and 12 (25%) were bridged to consolidation. The 2-year progression-free survival (PFS) and overall survival were 22.1% (95% CI, 11.5-34.7%) and 45.2% (95% CI, 34.3-58.9%), respectively. The 2-year PFS for HL and THRLCL patients was 35% and 50%, respectively. Alemtuzumab can be safely combined with DA-EPOCH-R in relapsed/refractory aggressive B-cell lymphomas and can induce durable responses in patients with T-cell-rich microenvironments.

Older adults (OA) with DLBCL are a heterogenous population with suboptimal outcomes. In this review, we identify and address the unique challenges encountered in the care of OA with DLBCL. We elaborate on the role and limitations of current geriatric assessment (GA) tools and ways to incorporate fitness in therapeutic decision making. We suggest best practices to implement GA in routine practice and clinical trials. The most widely used tool is simplified GA (sGA) which categorizes patients into fit, unfit and frail groups. Patients who are fit benefit from full dose/curative approach, whereas consideration should be made to reduce the intensity of chemotherapy for unfit patients. Frail patients with DLBCL are a major unmet need without any satisfactory treatment options. Ongoing investigations combining novel therapies into chemotherapy-free regimens are underway with promising early results. In the relapsed/refractory (R/R) setting, anti-CD19 CAR-T cell therapy (CART) is now the standard of care for primary refractory disease or relapse within 12 months of completing therapy. Autologous stem cell transplant is still a consideration for fit OA with relapse >12 months after completing therapy. The recent approval of bispecific antibodies is a welcome advance that will greatly benefit OA not eligible for CART. Other regimens available for patients ineligible for CART or for those who experience progression post-CART include polatuzumab-rituximab±bendamustine, tafasitamab-lenalidomide, loncastuximab or chemotherapy-based approaches such as rituximab-gemcitabine-oxaliplatin. We discuss the changing paradigm in R/R DLBCL and spotlight emerging data from recent congresses that can improve outcomes in this vulnerable population.

Current subtyping methods of diffuse large B-cell lymphoma (DLBCL) could not satisfy the clinical demands for risk assessment and prognostic prediction. We aimed to investigate the prognostic effect of autophagy-related genes (ARGs) in DLBCL. Transcriptomic data of 1,409 DLBCL patients, 531 healthy controls (HCs), and single-cell sequencing data of 4 DLBCL were included. Validation involved spatial transcriptomics from 10 DLBCL patients and 110 DLBCL proteomic data from a local cohort. We identified 153 differentially expressed ARGs between DLBCL patients (n=48) and HCs (n=531), classifying 414 DLBCL patients into two subtypes based on autophagy heterogeneity. Subtype I, characterized by upregulated T regulatory (Treg) cells (P<0.0001) and T follicular helper (Tfh) cells (P=0.0012), showed a superior prognosis (P=0.035). Eight prognostic ARGs were selected to construct an autophagy-related model, dividing patients into low- and high-risk groups. Kaplan-Meier survival analysis revealed significantly better outcomes for the low-risk group in both the discovery (P<0.0001) and validation cohorts (P=0.0041). High-risk patients exhibited elevated IDO1 (P=0.042) and LAG3 (P<0.001) levels. Among the eight signature proteins, higher FAS was further verified to indicate a better prognosis in the local cohort (n=110) using antibody array (P=0.0083). FAS was primarily expressed in T cells such as Treg and Tfh cells and was elevated in non-progressive disease patients. FAS-positive T cells showed increased interferon-gamma (normalized enrichment score (NES)=2.196, FDR<0.0001) and alpha (NES=1.836, FDR<0.01) response activities. We constructed an autophagy-related model and identified FAS as a prognostic biomarker. FAS+ Treg and Tfh cell-enriched TME indicated a favorable prognosis.

Diffuse large B-cell lymphoma (DLBCL) is clinically heterogeneous, and gene expression profiling has identified at least two biologically distinct DLBCL subtypes defined by their cell of origin (COO): germinal center B cell (GCB) and activate B cell (ABC) or non-GCB. We evaluated a variety of putative DLBCL risk factors for etiologic heterogeneity by the COO in a clinic-based study of newly diagnosed DLBCL cases (N = 638) and frequency-matched controls (N = 2,253).

The COO was determined on formalin-fixed, paraffin-embedded tumor tissue, with DLBCL classified as GCB (N = 283), non-GCB (N = 188), or undetermined/missing (N = 167; mainly because of lack of tissue). Multivariable logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI).

We identified heterogeneity by the COO for low socioeconomic status (SES), which was only associated with non-GCB DLBCL (OR = 1.88 for low vs. average SES; 95% CI, 1.08-3.27); alcohol use, which was only associated with GCB DLBCL (OR = 0.48 for former drinkers; 95% CI, 0.29-0.80 and OR = 0.47 for current drinkers; 95% CI, 0.32-0.71); and borderline heterogeneity for the regular use of regular/extra-strength aspirin, which was only associated with non-GCB DLBCL (OR = 0.36; 95% CI, 0.16-0.85). In contrast, there was no significant heterogeneity by the COO for family history, medical history, or other lifestyle factors.

Although requiring confirmation, most risk factors for DLBCL did not show etiologic heterogeneity by the COO, with some notable exceptions including alcohol use, SES, and perhaps regular use of regular/extra-strength aspirin showing associations.

Mechanistically, these findings suggest that most of the DLBCL risk factors evaluated here influence lymphomagenesis prior to differentiation into COO subtypes, with selected factors acting later.

Over 60% of relapsed/refractory large B-cell lymphoma (R/R LBCL) patients treated with chimeric antigen receptor (CAR) T-cells experience progressive disease. The impact of site-specific extranodal involvement on CAR-T outcomes has not been fully elucidated. This multicenter study included 516 R/R LBCL patients infused with CD19-targeted CAR T-cells; 177 (34%) had only-nodal (N), 66 (13%) only-extranodal (E) and 273 (53%) nodal and extranodal (NE) disease at time of CAR T-cells. The NE cohort included more patients with a poor performance status and high tumor burden. In the multivariable analysis, the NE group had a shorter progression-free survival (PFS) (HR 1.27 [95%CI 0.98-1.64], p = 0.07) and overall survival (HR 1.41 [95%CI 1.05-1.88], p = 0.02) compared to N. Conversely, we did not identify efficacy differences between N and E patients. A higher number of extranodal sites and specific organ involvement (liver, adrenal glands, pancreas), were associated with shorter PFS. Finally, extranodal involvement increased at time of relapse, displaying heterogeneous individual site clearance rates. In conclusion, patients with concomitant nodal and extranodal involvement at time of CAR-T had worse outcomes, but this cohort harbored high-risk baseline characteristics. An increasing number of extranodal sites and certain disease locations were associated with lower CAR-T efficacy.

Primary testicular lymphoma (PTL) is a rare extranodal lymphoma. The majority of cases are of diffuse large B cell lymphoma (DLBCL) histology (PT-DLBCL) with an activated B-cell-like (ABC) gene expression profile. These are characterised clinically by a high risk of contralateral testis and central nervous system (CNS) relapse, representing an ongoing area of unmet clinical need. Here, we review the epidemiology, clinical presentation and diagnostic evaluation of PT-DLBCL along with the advances in molecular biology that have occurred in the last decade, concerning the now-recognised molecular subtypes of DLBCL and their role of immune escape and sustained signalling in disease pathophysiology. We also appraise the retrospective and prospective clinical trials underpinning modern treatment recommendations, including the updated guidance on the role of radiotherapy and the latest evidence regarding strategies for preventing CNS relapse.

Diffuse large B-cell lymphoma (DLBCL) with TP53 mutations has specific clinicopathological features and is usually associated with a poor prognosis. TP53 gene mutations typically lead to aberrant expression patterns of the p53 protein. We studied 123 DLBCL patients at Henan Cancer Hospital, 35.8% (44/123) had TP53 mutations. Analysis of mutation sites in 44 cases of DLBCL patients revealed that the mutations primarily occur in the DNA-binding domain (DBD region) of the encoded p53 protein; among all mutation types, there were 8 truncation or frameshift mutations, and 36 missense mutations. Further, immunohistochemistry (IHC) detected expression levels of p53 protein in 123 DLBCL samples. The mutation results were used as a reference, and receiver operating characteristic (ROC) curve analysis was employed. Ultimately, the expression ratio of 65% and the moderate-strong expression intensity were regarded as the cut-off value, namely high p53 expression or p53 negative (<1%) indicated mutant-type p53 protein. the complete remission (CR) rate of the mutant-type p53 protein group after receiving R-CHOP regimen was 50% (14/28), and the objective response rate (ORR) was 75%, which differed significantly (P<0.01) compared with wild-type p53 protein group [CR rate of 75.86% (66/87) and ORR rate of 89.66%]. Common gene mutations in the mutant-type p53 protein group primarily involve alterations in pathways related to epigenetics, B cell antigen receptor signaling, cell cycle, among others. IHC analysis of the p53 protein is a simple and low-cost approach that can be employed to predict TP53 mutation status and therapy response.

Diffuse large B-cell lymphoma (DLBCL) has variable prognosis, with only 50 to 60% of patients cured by standard first line treatment. Identifying patients unlikely to benefit from standard first line therapy is therefore crucial. Schmitz's study identified four molecular subtypes of DLBCL with differing prognoses: MCD, BN2, Nl, and EZB, with BN2 and EZB showing more favorable outcomes. This study aimed to evaluate the effectiveness of the Archer FusionPlex Lymphoma Assay in identifying the newly defined genetic subtypes of DLBCL, while also exploring the association between immunohistochemical (IHC) and next-generation sequencing (NGS) methods for classifying the cell of origin (COO) and assessing their predictive value for patient survival.

We classified 131 DLBCL patients using Hans algorithm into GCB (germinal center B-cell-like) and ABC (activated B-cell-like) subtypes, and with NGS applying Archer FusionPlex lymphoma assay into ABC, GCB, unclassified, and into Schmitz's novel genetic subtypes. A mutational analysis of just 7 genes (MYD88L265P, CD79B, EZH2, NOTCH1, NOTCH2, BCL2, and BCL6) was used for genetic classification. Various statistical models were applied to assess survival differences between subtypes. Finally, STRATOS analysis was conducted to validate our preliminary statistical findings.

35.9% of patients were successfully classified into new genetic subtypes, with acceptable consistency between IHC and NGS method for COO determination. However, the new genetic subtype classification by NGS did not correlate with overall survival, nor did the COO classifications by IHC or NGS. The inclusion of these classifications also did not improve the predictive value of models compared to the basic model based on the International Prognostic Index (IPI) only.

The Archer FusionPlex Lymphoma assay showed a somewhat lower detection rate of novel genetic subtypes compared to reports based on exome sequencing, yet identified novel genetic subtypes in over one-third of patients. However, an in-depth STRATOS statistical analysis did not confirm its predictive value for DLBCL prognosis, likely due to factors like patient selection and sample size limitations.

CD5 positive diffuse large B-cell lymphoma (DLBCL) has unique clinical and pathological characteristics.

We analyzed 25 cases of CD5-positive DLBCL, focusing on their clinical, morphological, immunohistochemical and genetic features.

Among the 13 females and 12 males, 14 were over 60 years (14/25, 56%). A majority of them presented in stage IV (15/21, 71.43%), primarily with extranodal lesions (14/25, 56%). The positive expression rates of CD20, CD10, BCL6, MUM1, MYC, and BCL2 were 100% (25/25), 40% (10/25), 84% (21/25), 100% (25/25), 87.5% (21/24) and 100% (25/25), respectively. Twenty-one cases (87.5%, 21/24) were MYC/BCL2 double-expressing. More than half of the cases were non-germinal center origin (15/25, 60%). The accuracy of p53 in predicting TP53 mutation was 95.65% (22/23). Genetic subtypes were MCD (13/25, 52%), TP53Mut (7/25, 28%), EZB (1/25, 4%) and Other subtype (4/25, 16%). Among CD5 strong positive cases, 7 of the p53 wild-pattern cases were MCD subtype (7/8, 87.5%) and 6 of the p53 mutant-pattern cases were classified as TP53Mut subtype (6/7, 85.71%). In the CD5 weak-moderate positive group, one p53 mutant-pattern case was TP53Mut subtype (1/2, 50%), 4 of the wild-pattern cases were Other subtype (4/6, 66.67%).

For CD5 strong positive cases, a wild pattern of p53 likely indicates MCD subtype, while a mutant p53 pattern may suggest TP53Mut subtype. CD5 and p53 may potentially offer initial molecular subtyping for CD5-positive DLBCLs. We suggest incorporating these two markers into the routine pathological diagnosis of DLBCL to assist in guiding preliminary classification and influencing treatment decisions.

Background: Chimeric antigen receptor T-cell (CAR-T) therapies have been approved by the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) for the treatment of diffuse large B-cell lymphoma (DLBCL), primarily based on single-arm trials or indirect comparisons with stem cell transplantation. However, no direct head-to-head comparisons of CAR-T therapies have been conducted, largely due to their high cost. To assess their true value, indirect treatment comparisons (ITCs) are essential. These comparisons, however, are prone to confounding biases, which necessitate careful adjustments through the identification and measurement of relevant variables. Materials and Methods: This study aims to identify the variables used for adjustment in ITCs of CAR-T therapies for DLBCL and examine the methodologies employed to select them. A rapid literature review was conducted in PubMed in September 2023, focusing on ITCs involving CAR-T therapies for DLBCL. The search was based on keywords categorized into three groups: techniques (ITCs and related terms), drugs (CAR-T therapies), and indication (DLBCL). Results: The rapid literature review identified 21 articles, of which 11 were selected for analysis. Exclusions were made for articles that did not identify confounders, were letters to editors, or addressed conditions other than DLBCL. Among the 11 selected publications, 10 did not clearly specify the methodology used to identify adjustment variables. A total of 25 potential confounders were identified across the studies, with substantial variability in the set of variables used, reflecting a lack of standardization in confounder selection. Commonly identified confounders included the number of prior treatment lines and Eastern Cooperative Oncology Group Performance Status (ECOG PS), although their inclusion as adjustment variables in ITCs was inconsistent, often due to missing data. Conclusions: While the identified confounders are clinically relevant, the methodologies for selecting them remain unclear, resulting in significant variability across studies. Additionally, key variables commonly considered in health technology assessments (HTAs), such as age, sex, and disease severity, were inconsistently incorporated into ITCs. To improve the reliability and consistency of ITC outcomes, there is a pressing need for standardized methodologies for identifying and adjusting for confounders.

Primary thyroid lymphoma (PTL) is a rare and aggressive malignancy with a need for more precise prognostication tools due to the limitations of existing staging systems. This study aims to develop a nomogram to predict overall survival (OS) rates in PTL patients, addressing the gap in personalized treatment protocols.

We analyzed 1469 PTL cases. Cox regression analyses were used to identify key prognostic factors and construct a survival prognostic nomogram. The nomogram's performance was evaluated using receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, a web-based dynamic nomogram was developed to estimate mortality risk for PTL patients.

The nomogram exhibited high clinical utility and precision as determined by decision curve analysis and ROC curves. Furthermore, a novel risk stratification system was introduced. Kaplan-Meier survival curves illustrated significant differences among various risk groups, reinforcing the nomogram's substantial clinical value in predicting OS for PTL patients (P < 0.0001). SHAP value analysis clarified each variable's specific impact on the outcome.

The nomogram provides a valuable instrument for clinicians to individualize OS predictions for PTL patients, addressing the unmet need for personalized prognostication in this rare malignancy.

Double expressor lymphoma (DEL) refers to diffuse large B-cell lymphoma (DLBCL) cases characterized by the overexpression of both MYC and BCL2 proteins, as determined by immunohistochemistry (IHC), without requiring underlying genetic rearrangements. DEL is associated with more aggressive disease behavior and poorer prognosis. This study aimed to assess the impact of DEL on progression-free survival (PFS) and overall survival (OS) compared to non-DEL patients. We conducted a retrospective study at the Hospital, analyzing 177 patients diagnosed with DLBCL between March 2014 and March 2021. Patients were classified as DEL or non-DEL based on immunohistochemical analysis. Survival rates, clinical characteristics, and treatment responses were compared using Kaplan-Meier survival analysis, and multivariable Cox regression was performed to identify independent prognostic factors. Among 177 patients, 113 (63.8%) were DEL and 64 (36.2%) non-DEL. DEL patients had significantly worse outcomes, with a median follow-up of 39.4 months. The 3-year PFS (44.2% vs. 68.8%) and OS (54.9% vs. 81.3%) were significantly lower in DEL (PFS: p < 0.001; OS: p = 0.001). Median PFS in DEL was 19 months. Multivariable analysis confirmed DEL as an independent predictor of worse PFS (HR: 1.488, 95% CI: 1.091-2.03, p = 0.012) and OS (HR: 1.376, 95% CI: 1.011-1.873, p = 0.043). DEL status is strongly linked to poor survival in DLBCL, highlighting the need for targeted therapies beyond R-CHOP. Future research should explore personalized treatment strategies to improve outcomes in this high-risk group.

Lymphomas have diverse etiologies, treatment approaches, and prognoses. Accurate survival estimation is challenging for lymphoma patients due to their heightened susceptibility to non-lymphoma-related mortality. To overcome this challenge, we propose a novel lymphoma classification system that utilizes latent class analysis (LCA) and incorporates demographic and clinicopathological factors as indicators. We conducted LCA using data from 221,812 primary lymphoma patients in the Surveillance, Epidemiology, and End Results (SEER) database and identified four distinct LCA-derived classes. The LCA-derived classification efficiently stratified patients, thereby adjusting the bias induced by competing risk events such as non-lymphoma-related death. This remains effective even in cases of limited availability of cause-of-death information, leading to an enhancement in the accuracy of lymphoma prognosis assessment. Additionally, we validated the LCA-derived classification model in an external cohort and observed its improved prognostic stratification of molecular subtypes. We further explored the molecular characteristics of the LCA subgroups and identified potential driver genes specific to each subgroup. In conclusion, our study introduces a novel LCA-based lymphoma classification system that provides improved prognostic prediction by accounting for competing risk events. The proposed classification system enhances the clinical relevance of molecular subtypes and offers insights into potential therapeutic targets.

Lymphoma, a malignant tumor derived from lymphocytes and lymphoid tissues, presents with complex and heterogeneous clinical manifestations, requiring accurate patient classification for appropriate treatment. While invasive pathological examination of lymph nodes or lymphoid tissue remains the gold standard for lymphoma diagnosis, its utility is limited in cases of deep-seated tumors such as intraperitoneal and central nervous system lymphomas. In addition, biopsy procedures carry an inherent risk of complications. Computed tomography (CT) and positron emission tomography/computed tomography (PET/CT) imaging are essential for treatment assessment and monitoring, but lack the ability to detect early clonal evolution and minimal residual disease (MRD). Liquid biopsy-based analysis of circulating tumor DNA (ctDNA) offers a non-invasive alternative that allows for repeated sampling and overcomes the limitations of spatial heterogeneity and invasive biopsies. ctDNA provides genetic and epigenetic insights into lymphoma and serves as a dynamic, quantifiable biomarker for diagnosis, risk stratification, and treatment response. This review comprehensively summarizes common genetic variations in lymphoma and systematically evaluates ctDNA detection technologies, including PCR-based assays and next-generation sequencing (NGS). Applications of ctDNA detection in noninvasive genotyping, risk stratification, therapeutic response monitoring, and MRD detection are discussed across various lymphoma subtypes, including diffuse large B-cell lymphoma, Hodgkin lymphoma, follicular lymphoma, and T-cell lymphoma. By integrating recent research findings, the review highlights the role of ctDNA profiling in advancing precision medicine, enabling personalized therapeutic strategies, and improving clinical outcomes in lymphoma.

Diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) are the most common histological types of B-cell lymphoma, but have significantly different pathological and biological characteristics. In recent years, understanding of the genetic abnormalities and microenvironmental structures of these lymphomas has progressed, and various molecular targeted drugs and immunotherapies have been introduced into clinical practice. Therefore, accurate understanding of etiology and its clinical relevance is required for the appropriate management of these lymphomas.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoid tumor, and accounts for approximately 30-40% of non-Hodgkin lymphomas. Although the prognosis has significantly improved with the advent of rituximab combination chemotherapy in the early 2000s, recurrence still occurs in about 40% of cases. Even though chemotherapy with increased dose-intensity is used in recurrent cases, the prognosis of such patients remains poor. Thus, the development of personalized medicine, including molecular-targeted drugs, is required to improve the prognosis of DLBCL patients, and further understanding of the molecular pathogenesis of DLBCL is essential for this purpose. With recent advances in genetic analysis technology, unknown genetic abnormalities and gene expression patterns have been discovered, and based on these discoveries, progress is being made in elucidating and subdividing molecular pathologies. This article summarizes recent findings regarding molecular pathogenesis in DLBCL using transcriptome and genomics technologies, and outlines the path to personalized medicine.

Regularization methods such as LASSO, adaptive LASSO, Elastic-Net, and SCAD are widely employed for variable selection in statistical modeling. However, these methods primarily focus on variables with strong effects while often overlooking weaker signals, potentially leading to biased parameter estimates. To address this limitation, Gao, Ahmed, and Feng (2017) introduced a corrected shrinkage estimator that incorporates both weak and strong signals, though their results were confined to linear models. The applicability of such approaches to survival data remains unclear, despite the prevalence of survival regression involving both strong and weak effects in biomedical research. To bridge this gap, we propose a novel class of post-selection shrinkage estimators tailored to the Cox model framework. We establish the asymptotic properties of the proposed estimators and demonstrate their potential to enhance estimation and prediction accuracy through simulations that explicitly incorporate weak signals. Finally, we validate the practical utility of our approach by applying it to two real-world datasets, showcasing its advantages over existing methods.

Diffuse large B-cell lymphoma (DLBCL) is an aggressive subtype of non-Hodgkin's lymphoma that arises from the germinal center. It represents a heterogeneous disease characterized by different pathological, clinical, and molecular entities. Gene expression profiling based on the alleged cell of origin differentiates transcriptional subtypes such as germinal center and activated B cell-like. DLBCL accounts for around 40% of all non-Hodgkin's lymphomas worldwide. Its incidence generally increases with age. The international prognostic index remains the most important tool for disease stratification.The diagnosis of DLBCL is best made through an excisional biopsy of a suspicious lymph node. Nowadays, advanced techniques are employed to accurately diagnose and determine the clinical outcomes of patients. Immunohistochemistry, next-generation sequencing, and array-based comparative hybridization facilitate the global identification of diverse and numerous genetic alterations. However, further validation should be necessary to apply advanced techniques in clinical practice. In this review, we summarize the current literature and discuss the pathophysiology, epidemiology, and diagnostic advancements of DLBCL.

Primary sinonasal diffuse large B-cell lymphoma (PSDLBCL) is a rare aggressive lymphoma. Recently, genetic classification using Next Generation Sequencing (NGS) demonstrated that PSDLBCL largely consists of the MCD genotype, which has a poor prognosis mainly driven by MYD88 L265P and CD79B gene abnormalities. This study investigated the prevalence and clinicopathological significance of MYD88 L265P and CD79B Y196 mutations using droplet digital PCR in 55 patients with PSDLBCL, as well as the translocation of BCL2 / BCL6 / c-Myc with FISH. We found mutations in MYD88 L265P (29/55, 52.7%) and CD79B Y196 (20/55, 36.4%). The MCD-like subtype, defined by the mutation of MYD88 and/or CD79B , was found in 32 out of 55 cases (58.2%). This subtype largely consists of non-GCB type (31/32, 96.9%; P <0.01) and double-expressor cases (20/32, 62.5%; P =0.01) compared with the MYD88 / CD79B co-wild type, with BCL6 translocation in a small subset (2/32, 6.3%) and no translocations of BCL2 (0/32) or c-Myc (0/32). The MCD-like subtype tended to relapse in specific sites such as the central nervous system, testis, and/or skin compared with the co-wild type ( P =0.03), showing poorer outcomes in overall survival ( P =0.02) and progression-free survival ( P =0.01). In conclusion, our study highlights a high prevalence of MYD88 and CD79B mutations in PSDLBCL, identifying an aggressive MCD-like subtype with a distinct relapse pattern. This molecular subclassification can be helpful for both prognostic prediction and therapeutic strategy in patients with PSDLBCL.

Previous researches mainly focused on whether cancer stem cells exist in diffuse large B-cell lymphoma (DLBCL). However, subgroups with dismal prognosis and stem cell-like characteristics have been overlooked.

Using large scale data (n = 2133), we conducted machine learning algorithms to identify a high risk DLBCL subgroup with stem cell-like features, and then investigated the potential mechanisms in shaping this subgroup using transcriptome, genome and single-cell RNA-seq data, and in vitro experiments.

We identified a high-risk subgroup (25.6 % of DLBCL) with stem cell-like characteristics and dismal prognosis. This high-risk group (HRG) was featured by upregulation of key enzyme (ODC1) in polyamine metabolism and cold tumor microenvironment (TME), and had a poor prognosis with lower 3-year overall survival (OS) (54.3 % vs. 83.6 %, P < 0.0001) and progression-free survival (PFS) (42.8 % vs. 74.7 %, P < 0.0001) rates compared to the low-risk group. HRG also exhibited malignant proliferative phenotypes similar to Burkitt lymphoma. Patients with MYC rearrangement, double-hit, double-expressors, or complete remission might have either favorable or poor prognosis, which could be further distinguished by our risk stratification model. Genomic analysis revealed widespread copy number losses in the chemokine and interferon coding regions 8p23.1 and 9p21.3 in HRG. We identified ODC1 as a therapeutic vulnerability for HRG-DLBCL. Single-cell analysis and in vitro experiments demonstrated that ODC1 overexpression enhanced DLBCL cell proliferation and drove macrophage polarization towards the M2 phenotype. Conversely, ODC1 inhibition reduced DLBCL cell proliferation, induced cell cycle arrest and apoptosis, and promoted macrophage polarization towards the M1 phenotype. Finally, we developed a comprehensive database of DLBCL for clinical application.

Our study effectively advances the precise risk stratification of DLBCL and reveals that ODC1 and immune-deserted microenvironment jointly shape a group of DLBCL patients with stem cell-like features. Targeting ODC1 regulates immunotherapies in DLBCL, offering new insights for DLBCL treatment.

Primary central nervous system diffused large B-cell lymphoma (PCNS-DLBCL) is a rare type of non-Hodgkin lymphoma restricted to the central nervous system (CNS). To explore its specific pathogenesis and therapeutic targets, we performed multi-omics sequencing on tumor samples from patients diagnosed with PCNS-DLBCL, secondary CNS-DLBCL or extracranial (ec) DLBCL.By single-cell RNA sequencing, highly proliferated and dark zone (DZ)-related B cell subclusters, MKI67_B1, PTTG1_B2 and BTG1_B3, were predominant significantly in PCNS-DLBCL. Compared to SCNS-DLBCL and ecDLBCL, an immune-suppressive tumor microenvironment was observed in PCNS-DLBCL by analysis of immune-stimulating/inhibitory ligand‒receptor (L-R) pairs. By performing whole-exome sequencing in 93 patients, mutations enriched in BCR-NFkB and TLR pathways and the cooperation of these two pathways were found to be predominant in PCNS-DLBCL comparing to nonGCB-ecDLBCL. In summary, our study provides comprehensive insights into the transcriptomic and genetic characteristics of PCNS-DLBCL in contrast to ecDLBCL and will help dissect the oncogenic mechanism of this disease.

CD47 interacts with signal regulatory protein alpha (SIRPα) on macrophages to deliver an anti-phagocytic signal, enabling tumor cells to evade immune destruction. This study explores the relationship between CD47 and SIRPα expression and key clinical prognostic factors, microvascular density (MVD), and tumor-infiltrating lymphocytes (TIL) in Diffuse Large B Cell Lymphoma (DLBCL) cases. We analyzed tissue samples from 122 DLBCL cases using tissue microarray (TMA) blocks and immunohistochemical staining for CD47, SIRPα, CD31, and CD3. CD47 expression was scored using the Allred scoring system, and SIRPα expression was quantified based on the percentage of positive membranous and cytoplasmic expression. Clinical data, including IPI scores, relapse rates, and gene expression profiles, were correlated with the immunohistochemical findings.CD47 expression score ≥ 6 was significantly associated with the DLBCL-ABC phenotype (p = 0.029), higher IPI scores (p = 0.020), and increased relapse rates (p = 0.021). High SIRPα expression (≥25 % staining) was also linked to the ABC phenotype (p = 0.022) and frequent relapses (p = 0.021). Notably, cases with high microvascular density exhibited lower SIRPα expression (p = 0.013). There was no significant relationship between MVD and CD47 or other clinical prognostic factors. Additionally, higher CD3-positive TIL percentages were inversely correlated with IPI scores (p = 0.005), although no significant association was found between CD3 and CD47-SIRPα. The study reveals that increased CD47-SIRPα expression is partially linked to adverse prognostic indicators and reduced MVD in DLBCL cases. These findings suggest that targeting the CD47-SIRPα axis could offer a novel therapeutic approach in DLBCL, particularly for patients with poor prognostic features.

Cancer immunotherapy-including immune checkpoint inhibition (ICI) and adoptive cell therapy (ACT)-has become a standard, potentially curative treatment for a subset of advanced solid and liquid tumors. However, most patients with cancer do not benefit from the rapidly evolving improvements in the understanding of principal mechanisms determining cancer immune responsiveness (CIR); including patient-specific genetically determined and acquired factors, as well as intrinsic cancer cell biology. Though CIR is multifactorial, fundamental concepts are emerging that should be considered for the design of novel therapeutic strategies and related clinical studies. Recent advancements as well as novel approaches to address the limitations of current treatments are discussed here, with a specific focus on ICI and ACT.

Immunoglobulin (IG) gene remodeling by V(D)J recombination plays a central role in the generation of normal B cells, and somatic hypermutation and class switching of IG genes are key processes during antigen-driven B cell differentiation in the germinal center reaction. However, errors of these processes are involved in the development of B cell lymphomas. IG locus-associated translocations of proto-oncogenes are a hallmark of many B cell malignancies. Additional transforming events include inactivating mutations in various tumor suppressor genes and also latent infection of B cells with viruses, such as Epstein-Barr virus. Most B cell lymphomas require B cell antigen receptor expression, and in several instances chronic antigenic stimulation plays a role in lymphoma development and/or sustaining tumor growth. Often, survival and proliferation signals provided by other cells in the microenvironment are a further critical factor in lymphoma development and pathophysiology. Most B cell malignancies derive from germinal center B cells, most likely due to the high proliferative activity of these B cells and aberrant mutations caused by their naturally active mutagenic processes.

Diffuse large B-cell lymphoma (DLBCL) patients that fail to achieve a complete metabolic response with frontline immunochemotherapy have a poor prognosis. Genomic profiling has led to a broader understanding of the molecular drivers in DLBCL, but it is unknown how well current classifiers identify patients that will experience primary treatment resistance (PTR). Using whole exome and RNA sequencing data from newly diagnosed DLBCL patients, we evaluated the genomic landscape of PTR and compared it to that of non-PTR DLBCL. We found a significant increase in the frequency of TP53 (34% vs. 15%, p = 0.005) and ARID1A mutations (21% vs. 7%, p = 0.007) in PTR cases, with pathway analysis further demonstrating a downregulation of TP53 and an increase in chromatin modifying pathways. These results suggest that TP53 and ARID1A may be key mediators of PTR and important pathways contributing to the poor outcomes. We found that the current molecular classifiers were unable to identify PTR cases at diagnosis. However, our newly identified high-risk signature identified 46% of PTR cases at diagnosis. Overall, these results contribute to our understanding of the genomic landscape of patients with primary treatment resistance.

This review aims to provide an overview of the latest developments in the classification and molecular understanding of aggressive B-cell lymphomas, specifically focusing on diffuse large B-cell lymphoma (DLBCL) and high-grade B-cell lymphoma (HGBL). Advances in molecular techniques have led to novel ways to classify these lymphomas based on clinical, histological, transcriptional, and genetic properties. While these methods have predominantly focused on the malignant compartment, recent studies emphasize the value of profiling the tumour microenvironment for a more comprehensive disease classification. Additionally, the integration of liquid biopsies represents a promising advancement, offering less invasive and dynamic insights into tumour characteristics and treatment response. Although molecular profiles are not yet routinely used to guide therapy, emerging data highlight their potential to predict responses to novel treatments. It is our belief that integrating molecular profiling and liquid biopsies into clinical practice and research now will pave the way for more personalized and effective therapies in the future.

Diffuse large B-cell lymphoma (DLBCL) encompasses a diverse spectrum of aggressive B-cell lymphomas with remarkable genetic heterogeneity and myriad clinical presentations. Multiplatform genomic analyses of DLBCL have identified oncogenic drivers within genetic subtypes that allow for pathologic subclassification of tumors into discrete entities with shared immunophenotypic, genetic, and clinical features. Robust classification of lymphoid tumors establishes a foundation for precision medicine and enables the identification of novel therapeutic vulnerabilities within biologically homogeneous entities. Most cases of DLBCL involving the central nervous system (CNS), vitreous, and testis exhibit immunophenotypic features suggesting an activated B-cell (ABC) origin. Shared molecular features include frequent comutations of MYD88 (L265P) and CD79B and frequent genetic alterations promoting immune evasion, which are hallmarks of the MCD/C5/MYD88 genetic subtype of DLBCL. Clinically, these lymphomas primarily arise within anatomic sanctuary sites and have a predilection for remaining confined to extranodal sites and strong CNS tropism. Given the shared clinical and molecular features, the umbrella term primary large B-cell lymphoma of immune-privileged sites (IP-LBCL) was proposed. Other extranodal DLBCL involving the breast, adrenal glands, and skin are often ABC DLBCL but are more heterogeneous in their genomic profile and involve anatomic sites that are not considered immune privileged. In this review, we describe the overlapping clinical, pathologic, and molecular features of IP-LBCL and highlight important considerations for diagnosis, staging, and treatment. We also discuss potential therapeutic vulnerabilities of IP-LBCL including sensitivity to inhibitors of Bruton tyrosine kinase, immunomodulatory agents, and immunotherapy.

Diffuse large B-cell lymphoma (DLBCL), not otherwise specified, is the most common subtype of large B-cell lymphoma, with differences in prognosis reflecting heterogeneity in the pathological, molecular, and clinical features. Current treatment standard is based on multiagent chemotherapy, including anthracycline and monoclonal anti-CD20 antibody, which leads to cure in 60% of patients. Recent years have brought new insights into lymphoma biology and have helped refine the risk groups. The results of these studies inspired the design of new clinical trials with targeted therapies and response-adapted strategies and allowed to identify groups of patients potentially benefiting from new agents. This review summarizes recent progress in identifying high-risk patients with DLBCL using clinical and biological prognostic factors assessed at diagnosis and during treatment in the front-line setting, as well as new treatment strategies with the application of targeted agents and immunotherapy, including response-adapted strategies.

Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive lymphoma, accounting for ~40% of all cases in adults. Whilst approximately two-thirds of DLBCL patients can be cured by first-line therapy, one-third of patients are primary refractory or relapse after an initial response (r/r DLBCL). Recent advances in the treatment of DLBCL have been achieved by a plethora of novel drugs, such as monoclonal antibodies, antibody-drug conjugates (ADC), bi-specific T-cell engagers (BITEs), and CD-19 directed chimeric antigen receptor (CAR)-T-cell therapies. The increasing number of therapeutic options significantly improved the outcome of patients; however, the therapeutic algorithm has become increasingly complex. In this review, we provide an overview of novel therapies for DLBCL patients and potential treatment sequencing from first to second, third, and later lines.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma (NHL) in adults, constituting a significant portion of global incidence rates. DLBCL can be further classified via genetic expression profiling into molecular subsets consisting of not-otherwise specified (NOS) subset being the most prevalent, germinal center B-cell-like (GCB) subset, and activated B-cell-like (ABC) subset. The ABC subset, marked by abnormal NF-κB signaling, is associated with poorer outcomes. This report presents an unusual case of a 30-year-old male with no past medical history who was found to have advanced-stage ABC-type DLBCL-NOS, featuring rare symptoms such as hypothermia, autonomic dysfunction, and atrial fibrillation, illustrating the unpredictable clinical manifestations of this aggressive lymphoma and the importance of molecular subtyping in treatment and prognosis.

Mitogen-activated protein kinase 12 (MAPK12), also known as p38γ, is a member of the p38 MAPK family and plays a crucial role in tumor occurrence and invasion. However, there is still uncertainty regarding MAPK12 involvement in diffuse large B-cell lymphoma (DLBCL).

Our study investigated the expression of MAPK12 mRNA in various types of cancer using bioinformatic analysis. Furthermore, we performed immunohistochemistry (IHC) to detect the expression of MAPK12 in patients with DLBCL and compared clinical indicators and survival rates.

We found that the high expression rate of MAPK12 was 43.1% in DLBCL patients. Several clinical indicators, including IPI scores, Hans classifications, LDH levels, and Ki-67 expression were closely associated with MAPK12 expression. Survival analysis revealed that higher expression of MAPK12 was significantly correlated with shorter progression-free survival (PFS) and overall survival (OS) in DLBCL patients. In addition, both univariate and multivariate analyses revealed IPI score, MAPK12 expression, and rituximab use as the independent OS risk factors (P < 0.05). To explore the functional role of MAPK12 in DLBCL, weighted gene co-expression network analysis (WGCNA) and gene ontology (GO) were used to confirm the involvement of MAPK12 in the regulation of type II interferon production, positive regulation of lymphocyte proliferation, and other related biological processes.

DLBCL patients have poor prognoses when MAPK12 levels are high, which is expected to be a therapeutic target and prognostic factor.

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of lymphoma, accounting for 30% of non-Hodgkin lymphomas. Although comprehensive analysis of genetic abnormalities has led to the classification of lymphomas, the exact mechanism of lymphomagenesis remains elusive. The Ets family transcription factor, PU.1, encoded by Spi1, is essential for the development of myeloid and lymphoid cells. Our previous research illustrated the tumor suppressor function of PU.1 in classical Hodgkin lymphoma and myeloma cells. In the current study, we found that patients with DLBCL exhibited notably reduced PU.1 expression in their lymphoma cells, particularly in the non-germinal center B-cell-like (GCB) subtype. This observation suggests that downregulation of PU.1 may be implicated in DLBCL tumor growth. To further assess PU.1's role in mature B cells in vivo, we generated conditional Spi1 knockout mice using Cγ1-Cre mice. Remarkably, 13 of the 23 knockout mice (56%) showed splenomegaly, lymphadenopathy, or masses, with some having histologically confirmed B-cell lymphomas. In contrast, no wild-type mice developed B-cell lymphoma. In addition, RNA-seq analysis of lymphoma cells from Cγ1-Cre Spi1F/F mice showed high frequency of each monoclonal CDR3 sequence, indicating that these lymphoma cells were monoclonal tumor cells. When these B lymphoma cells were transplanted into immunodeficient recipient mice, all mice died within 3 weeks. Lentiviral-transduced Spi1 rescued 60% of the recipient mice, suggesting that PU.1 has a tumor suppressor function in vivo. Collectively, PU.1 is a tumor suppressor in mature B cells, and decreased PU.1 results in mature B-cell lymphoma development.

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma (NHL) and is characterized by high heterogeneity. Assessment of its prognosis and genetic subtyping hold significant clinical implications. However, existing DLBCL prognostic models are mainly based on transcriptomic profiles, while genetic variation detection is more commonly used in clinical practice. In addition, current clustering-based subtyping methods mostly focus on genes with high mutation frequencies, providing insufficient explanations for the heterogeneity of DLBCL. Here, we proposed VNNSurv (https://bio-web1.nscc-gz.cn/app/VNNSurv), a survival model for DLBCL patients based on a biologically informed visible neural network (VNN). VNNSurv achieved an average C-index of 0.72 on the cross-validation set (HMRN cohort, n = 928), outperforming the baseline methods. The remarkable interpretability of VNNSurv facilitated the identification of the most impactful genes and the underlying pathways through which they act on patient outcomes. When only the 30 highest-impact genes were used as genetic input, the overall performance of VNNSurv improved, and a C-index of 0.70 was achieved on the external TCGA cohort (n = 48). Leveraging these high-impact genes, including 16 genes with low (<5 %) alteration frequencies, we devised a genetic-based prognostic index (GPI) for risk stratification and a subtype identification method. We stratified the patient group according to the International Prognostic Index (IPI) into three risk grades with significant prognostic differences. Furthermore, the defined subtypes exhibited greater prognostic consistency than clustering-based methods. Broadly, VNNSurv is a valuable DLBCL survival model. Its high interpretability has significant value for precision medicine, and its framework is scalable to other diseases.

Biocompatible rod-shaped nanoparticles of controlled length can be produced through the heat-induced "living" seeded crystallization-driven self-assembly (CDSA) of poly(2-isopropyl-2-oxazoline)-containing block copolymers. With a hydrophilic poly(2-methyl-2-oxazine) or poly(2-methyl-2-oxazoline) corona, these nanorods have proven non-cytotoxic, non-hemolytic, and ideal for use as a polymer-based drug delivery system. This study demonstrates a facile, one-pot method for the synthesis of mycophenolic acid (MPA)-conjugated block copolymer "unimers" for use in seeded CDSA. Through altering block order during sequential monomer addition cationic ring-opening polymerization (CROP), MPA is conjugated to either the chain end of the core-forming or corona-forming block. This allows bioactive polymer nanorods to be prepared with MPA positioned at either the periphery of the corona, or at the core-corona interface of the nanorod formed during seeded CDSA. In vitro, these nanorods arrest growth in human T and B lymphocytes, with reduced effect in "off-target" monocytes when compared with unconjugated MPA. Furthermore, the conjugation of MPA to the core-corona interface of the nanorods leads to a slower release and reduced cytostatic effect. This study offers a robust investigation into the effect of steric hindrance and corona chemistry on the therapeutic potential of drug-conjugated CDSA nanorods and demonstrates the potential of poly(2-oxazoline)/poly(2-oxazine)-based CDSA nanomaterials as effective drug delivery platforms.

Bulk RNA expression data are widely accessible, whereas single-cell data are relatively scarce in comparison. However, single-cell data offer profound insights into the cellular composition of tissues and cell type-specific gene regulation, both of which remain hidden in bulk expression analysis.

Here, we present tissueResolver, an algorithm designed to extract single-cell information from bulk data, enabling us to attribute expression changes to individual cell types. When validated on simulated data tissueResolver outperforms competing methods. Additionally, our study demonstrates that tissueResolver reveals cell type-specific regulatory distinctions between the activated B-cell-like (ABC) and germinal center B-cell-like (GCB) subtypes of diffuse large B-cell lymphomas (DLBCL).

R package available at https://github.com/spang-lab/tissueResolver (archived as 10.5281/zenodo.14160846).Code for reproducing the results of this article is available at https://github.com/spang-lab/tissueResolver-docs archived as swh:1:dir:faea2d4f0ded30de774b28e028299ddbdd0c4f89).