Immune cell constitution in the tumor microenvironment predicts the outcome in diffuse large B-cell lymphoma

The transition between M1 and M2 macrophage phenotypes is associated with the disease status following CD19 CAR-T therapy for B cell lymphoma/leukemia

Although anti-CD19 chimeric antigen receptor (CAR-T) cells demonstrate high response rates in relapsed/refractory B-cell lymphomas, a considerable proportion of patients eventually encounter disease progression or relapse. The short-term and long-term outcomes of CAR-T treatment are intricately linked to the tumor microenvironment (TME), wherein macrophages with polarized characteristics can exhibit either anti-tumorigenic or pro-tumorigenic roles. Despite evidence implicating the crucial involvement of macrophages in CAR-T cell-treated lymphoma, their dynamic distribution and immune function related to lymphoma progression remain poorly understood. Immunocompetent mice were utilized to establish syngeneic A20 lymphoma/leukemia models. The distribution and polarization of macrophages were detected using immunohistochemistry (IHC) and flow cytometry techniques. We observed that CD19 CAR-T therapy exhibited significant efficacy in protecting mice against lymphoma, leading to increased infiltration of macrophages into the tumor tissue. Notably, during remission stages, M1-like macrophages (CD11b+F4/80+C206-CD80+) were predominant, whereas in relapsed mice, there was a shift towards M2-like phenotypes (CD11b+F4/80+C206+CD80+). The transition from remissive to relapsed status was accompanied by a reduction in the M1/M2 ratio and a decrease in pro-inflammatory cytokines. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) analysis confirmed differential expression levels of CD206 and CD163 between remissive and relapsed mice, while signaling pathways involving PI3K and STAT3 may contribute to the skewing towards M2 polarization. In summary, our findings highlight the dynamic transformation of macrophage polarization during different stages of lymphoma progression and underscore its potential implications for immunotherapeutic interventions.

Proteome alterations in peripheral immune cells of DLBCL patients and evidence of cancer extracellular vesicles involvement

Diffuse large B-cell lymphoma (DLBCL) is an aggressive disease and a frequent form of non-Hodgkin lymphoma. Given the primary localization of DLBCL and the effect of tumors on the systemic immune response, we investigated the proteome of DLBCL patients' and healthy donors (HDs') peripheral immune cells (PICs). Since the ubiquitin-proteasome system has a vital role in proteome regulation and immune cells' functions, this study also explores the potential impact of DLBCL secretome on the polyubiquitination level in PICs. PICs from DLBCL patients and HDs were isolated and analyzed by mass spectrometry-based proteomics. The analysis resulted in 135 down and 51 upregulated proteins (adjusted p-value <0.05). Unsupervised principal component analysis revealed distinct proteomic profiles between DLBCL and HDs. Functional enrichment analysis for comparison between DLBCL and HDs-PICs proteome identified immune-related pathways such as innate immune system, specifically neutrophil degranulation, Fcγ receptor-dependent phagocytosis, and JAK-STAT signaling after IL-12 stimulation as downregulated. Proteomics analysis of DLBCL-PICs also showed dysregulation of proteostasis factors. This prompted the investigation of the effect of tumor secretome on viability and polyubiquitination level in mononuclear immune cells. Therefore, human HD peripheral blood mononuclear cells (PBMCs) were cultured in the presence of DLBCL cell line-derived soluble factors, small-EVs, and large-EVs in vitro. Our results revealed that exposure of mainly small-EVs, and large-EVs to HD PBMCs increased the polyubiquitination in PBMCs and decreased PIC viability. These findings suggest impaired immune responses in DLBCL-PICs, with tumor secretome-inducing polyubiquitination and reduced PIC viability.

Prognostic significance of CD8 + tumor-infiltrating lymphocytes in operable breast cancer: a meta-analysis

BACKGROUND

As key mediators of antitumor immunity, CD8 + tumor-infiltrating lymphocytes present antigens and initiate robust immune responses against cancer cells. When stratified by location, CD8 + T lymphocytes were counted and classified as intratumoral, stromal, or total CD8 + tumor-infiltrating lymphocytes. Despite their crucial role, the impact, especially the specific type of CD8 + T lymphocytes on breast cancer prognosis remains controversial. This meta-analysis synthesized evidence to delineate the relationship between CD8 + tumor-infiltrating lymphocytes density of different counting methods and breast cancer patient outcomes.

METHODS

PubMed, Embase, and the Cochrane Library were systemically searched from inception through January 2024 for studies evaluating the prognostic significance of CD8 + tumor-infiltrating lymphocytes in breast cancer. The primary endpoint was disease-free survival (DFS), and the second endpoints were overall survival (OS), breast cancer-specific survival (BCSS), and recurrence-free survival (RFS).

RESULTS

Thirty-four studies encompassing 23,626 breast cancer patients were included. Pooled hazard ratios (HRs) indicated a significant association of high CD8 + TIL presence with improved DFS (HR = 0.63; 95% CI = 0.54-0.73), OS (HR = 0.72; 95% CI = 0.65-0.79), BCSS (HR = 0.67; 95% CI = 0.58-0.78), and RFS (HR = 0.53; 95% CI = 0.38-0.73). Stratification by TIL location (intratumoral [iCD8], stromal [sCD8], or total [tCD8]) did not significantly impact DFS or OS.

CONCLUSION

High CD8 + TIL density in breast cancer patients is correlated with a favorable prognosis, irrespective of the location of CD8 + tumor-infiltrating lymphocytes. These findings affirm the prognostic utility of CD8 + TIL assessment and may guide future immunotherapeutic strategies.

Liver-FDG-uptake augments early PET/CT prognostic value for CD19-targeted CAR-T cell therapy in diffuse large B cell lymphoma

BACKGROUND

Despite revolutionary efficacy of CD19-CAR-T cell therapy (CAR-T) in aggressive B cell lymphoma, many patients still relapse mostly early. In early failure, distinct drugs support CAR-T which makes reliable and early prediction of imminent relapse/refractoriness critical. A complete metabolic remission (CR) on Fluor-18-Deoxyglucose (FDG) Positron-Emission-Computed Tomography (PET) 30 days after CAR-T (PET30) strongly predicts progression-free survival (PFS), but still fails in a relevant proportion of patients. We aimed to identify additional routine parameters in PET evaluation to enhance CAR-T response prediction.

RESULTS

Thirty patients with aggressive B cell lymphoma treated with CAR-T were retrospectively analyzed. Pre-CAR-T, LDH was the strongest PFS-predictor also by multivariate analysis. Post-CAR-T, 10 out of 14 patients (71.4%) with PET30-CR remained in disease remission, while 12 out of 16 patients (75%) with incomplete metabolic remission (PET30-nCR) relapsed after CAR-T. 28.6% of patients with PET30-CR ultimately progressed. Change of liver FDG-uptake from baseline to day30 (Delta-Liver-SUVmean) was identified as an independent biomarker for response. PET30-nCR and a decrease of Delta-Liver-SUVmean were associated with a high risk of tumor progression (HR 4.79 and 3.99, respectively). The combination of PET30 and Delta-Liver-SUVmean identified patients at very low, at intermediate and at very high risk of relapse (PFS not reached, 7.5 months, 1.5 months, respectively).

CONCLUSION

Additionally to PET30 metabolic remission, longitudinal metabolic changes in Delta-Liver-SUVmean predicted CAR-T efficiency. Our results may guide early intervention studies aiming to enhance CAR-T particularly in the very high-risk patients.

Identification of intratumoral microbiome-driven immune modulation and therapeutic implications in diffuse large B-cell lymphoma

OBJECTIVE

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma, with significant clinical heterogeneity. Recent studies suggest that the intratumoral microbiome may influence the tumor microenvironment, affecting patient prognosis and therapeutic responses. This study aims to identify microbiome-related subtypes in DLBCL and assess their impact on prognosis, immune infiltration, and therapeutic sensitivity.

METHODS

Transcriptomic and microbiome data from 48 DLBCL patients were obtained from public databases. Consensus clustering was used to classify patients into distinct microbiome-related subtypes. Functional enrichment analysis, immune infiltration assessments, and single-cell RNA sequencing were performed to explore the biological characteristics of these subtypes. Drug sensitivity predictions were made using the OncoPredict tool. Hub genes' expression and biological function were validated and inferred in cell lines and independent cohorts of DLBCL.

RESULTS

Two distinct microbiome-related subtypes were identified. Patients in Cluster 1 exhibited significantly better overall survival (P < 0.05), with higher immune infiltration of regulatory T cells and M0 macrophages compared to Cluster 2, which was associated with poorer outcomes. Functional enrichment analysis revealed that genes in Cluster 1 were involved in immune regulatory pathways, including cytokine-cytokine receptor interactions and chemokine signaling, suggesting enhanced anti-tumor immune responses. In contrast, genes in Cluster 2 were enriched in immunosuppressive pathways, contributing to a less favorable prognosis. Single-cell RNA sequencing analysis revealed significant heterogeneity in immune cell populations within the tumor microenvironment. B cells exhibited the most notable heterogeneity, as indicated by stemness and differentiation potential scoring. Intercellular communication analysis demonstrated that B cells played a key role in immune cell interactions, with significant differences observed in MIF signaling between B-cell subgroups. Pseudo-time analysis further revealed distinct differentiation trajectories of B cells, highlighting their potential heterogeneity across different immune environments. Metabolic pathway analysis showed significant differences in the average expression levels of metabolic pathways among B-cell subgroups, suggesting functional specialization. Furthermore, interaction analysis between core genes involved in B-cell differentiation and microbiome-driven differentially expressed genes identified nine common genes (GSTM5, LURAP1, LINC02802, MAB21L3, C2CD4D, MMEL1, TSPAN2, and CITED4), which were found to play critical roles in B-cell differentiation and were influenced by the intratumoral microbiome. DLBCL cell lines and clinical cohorts validated that MMEL1 and CITED4 with important biologically function in DLBCL cell survival and subtype classification.

CONCLUSIONS

This study demonstrates the prognostic significance of the intratumoral microbiome in DLBCL, identifying distinct microbiome-related subtypes that impact immune infiltration, metabolic activity, and therapeutic responses. The findings provide insights into the immune heterogeneity within the tumor microenvironment, focusing on B cells and their differentiation dynamics. These results lay the foundation for microbiome-based prognostic biomarkers and personalized treatment approaches, ultimately aiming to enhance patient outcomes in DLBCL.

Phase 2 study of alemtuzumab and dose-adjusted EPOCH-R in relapsed or refractory aggressive B-cell lymphomas

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.

Immunotherapeutic strategies beyond the PD-1/PD-L1 pathway in head and neck squamous cell carcinoma - A scoping review on current developments in agents targeting TIM-3, TIGIT, LAG-3, and VISTA

Head and neck squamous cell carcinoma (HNSCC) poses a considerable challenge due to its high incidence and mortality rates. Immunotherapy targeting PD-(L)1 emerges as a promising approach for HNSCC, as it has the potential to trigger a broad and long-lasting anti-tumor response. Nevertheless, the effectiveness of immunotherapy encounters hurdles, and only a small proportion of patients benefit, with many eventually experiencing relapse. Consequently, there is a pursuit of strategies to enhance overall treatment outcomes. Understanding the mechanisms driving resistance to PD-(L)1 inhibition and devising strategies to overcome these challenges are vital for advancing more effective treatments. Furthermore, gaining insights into the mechanisms of action and safety profiles of novel combination therapies is critical for their successful adoption in clinical practice. As a result, current research is dedicated to investigating various immunotherapeutic agents beyond the PD-1/PD-L1 axis. This review offers a comprehensive overview of the existing immunotherapy strategies in HNSCC with a focus on TIM-3, TIGIT, LAG-3, and VISTA. The aim is to lay a strong foundation for the continual advancement of therapies for HNSCC.

Prognostic model based on M2 macrophage-related signatures for predicting outcomes, enhancing risk stratification, and providing therapeutic insights in diffuse large B-cell lymphoma

Purpose

The tumor microenvironment (TME) in lymphoma is influenced by M2 macrophages. This research proposes an novel predictive model that leverages M2 macrophage-associated genes to categorize risk, forecast outcomes, and evaluate the immune profile in patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL) undergoing R-CHOP therapy.

Methods

Gene expression data and clinical information from DLBCL patients were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Co-expressed genes linked to M2 macrophage in DLBCL were analyzed using CIBERSORT. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to explore associated signaling pathways. The M2 macrophage-related gene prognostic model was developed and validated using Cox and LASSO regression. Prognostic signature genes were verified by single-cell RNA-seq analysis.

Results

92 M2 macrophage-related genes were identified based on bulk-seq data. MS4A4A, CCL13, LTB, CCL23, CCL18, XKR4, IL22RA2, and FOLR2 were used to construct the risk model. AUC values for 1-, 3-, and 5-year survival were 0.74, 0.72, and 0.72, respectively. High-risk patients demonstrated elevated immune scores and poorer overall survival. The high-risk subgroup also exhibited greater sensitivity to both chemotherapeutic agents and immune checkpoint inhibitors.

Conclusion

This study presents an accurate and reliable M2 macrophage-related risk model, enhancing understanding of distinct prognostic subsets in DLBCL. It offers potential novel drug options for future treatments.

Lipid metabolism-related gene signature predicts prognosis and unveils novel anti-tumor drugs in specific type of diffuse large B cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma which possess highly aggressive and heterogeneous. Despite advances in understanding heterogeneity and development of novel targeted agents, the prognosis of DLBCL patients remains unsatisfied. Lipids are crucial components of biological membranes and signal transduction while accumulating evidence has supported the vital roles of abnormal lipid metabolism in tumorigenesis. Furthermore, some related pathways could serve as prognostic biomarkers and potential therapeutic targets. However, the clinical significance of abnormal lipid metabolism reprogramming in DLBCL has not been investigated. In the current study, we developed a prognostic risk model for DLBCL based on the abnormal expressed lipid metabolism genes and moreover based on our risk model we classified patients with DLBCL into novel subtypes and identified potential drugs for DLBCL patients with certain lipid metabolism profiles.

METHODS

We utilized univariate Cox regression analysis to identify the prognosis-related lipid metabolism genes, and then performed LASSO Cox regression to identify prognostic related lipid metabolism related genes. Multivariate cox regression was used to establish the prognostic model. Patients were divided in to high and low risk groups based on the median risk score. Immune cell infiltration and GSEA were used to identify the pathways between high and low risk groups. Oncopredict algorithm was utilized to identify potential drug for high-risk patients. In vitro cell apoptosis and viability analysis were employed to verify the specific tumor inhibition effects of AZD5153.

RESULTS

Nineteen survival related lipid metabolism genes TMEM176B, LAYN, RAB6B, MMP9, ATAD3B, SLC2A11, CD3E, SLIT2, SLC2A13, SLC43A3, CD6, SIRPG, NEK6, LCP2, CTTN, CXCL2, SNX22, BCL6 and FABP4 were identified and subjected to build the prognostic model which was further verified in four external microarray cohorts and one RNA seq cohorts. Tumor immune microenvironment analysis and GSEA results showed that the activation of MYC targets genes rather than immunosuppression contribute to the poor survival outcome of patients in the high-risk group. AZD5153, a novel bivalent BET bromodomain inhibitor which could inhibit the transcription of MYC and E2F exhibited specific antitumor function for cells with high-risk score.

CONCLUSIONS

Our results provide the first lipid metabolism-based gene signature for predicting the survival of patients with DLBCL. Furthermore, by determining novel subtypes with our lipid metabolism prognostic model we illustrated that drugs that compromising MYC target genes rather than immune checkpoint inhibitors may be beneficial to DLBCL patients with certain lipid metabolism profiles.

Identification of ferroptosis-related genes associated with diffuse large B-cell lymphoma via bioinformatics and machine learning approaches

Ferroptosis has emerged as a critical mechanism in the development and progression of various tumors, particularly diffuse large B-cell lymphoma (DLBCL). However, the thorough characterization of ferroptosis-related genes in DLBCL remains inadequately explored. We retrieved datasets associated with DLBCL and ferroptosis gene sets from the Gene Expression Omnibus (GEO) database and the Ferroptosis Database (FerrDb), resulting in the identification of 27 differentially expressed ferroptosis-related genes (DE-FRGs) linked to DLBCL. Utilizing the LASSO and Support Vector Machine Recursive Feature Elimination (SVW-RFE) algorithms, we identified 10 genes-MT1G, MTOR, BRD4, ACO1, SAT1, PEBP1, LPIN1, ATM, SRXN1, and PRDX1-as key biomarker candidates with significant diagnostic potential. Functional enrichment analyses revealed that these biomarker genes are likely involved in regulating several critical biological pathways implicated in DLBCL pathogenesis, including immune response, oxidative phosphorylation, and cell cycle regulation. Moreover, we identified 246 potential therapeutic agents targeting these 10 biomarker genes. Concurrently, competitive endogenous RNA (ceRNA) network analysis uncovered a complex regulatory network centered on the identified biomarker genes. Additionally, CIBERSORT analysis highlighted notable alterations in the immune microenvironment of DLBCL patients. We propose a diagnostic strategy that provides novel insights into the molecular mechanisms underlying DLBCL. Nevertheless, further validation of the practical value of this strategy for DLBCL diagnosis is necessary before its clinical application.

How lactate affects immune strategies in lymphoma

Tumor cells undergo metabolic reprogramming through shared pathways, resulting in a hypoxic, acidic, and highly permeable internal tumor microenvironment (TME). Lactate, once only regarded as a waste product of glycolysis, has an inseparable dual role with tumor immunity. It can not only provide a carbon source for immune cells to enhance immunity but also help the immune escape through a variety of ways. Lymphoma also depends on the proliferation signal of TME. This review focuses on the dynamic process of lactate metabolism and immune function changes in lymphoma and aims to comprehensively summarize and explore which genes, transcription factors, and pathways affect the biological changes and functions of immune cells. To deeply understand the complex and multifaceted role of lactate metabolism and immunity in lymphoma, the combination of lactate targeted therapy and classical immunotherapy will be a promising development direction in the future.

Integrated multi-omics profiling reveals the ZZZ3/CD70 axis is a super-enhancer-driven regulator of diffuse large B-cell lymphoma cell-natural killer cell interactions

Tumor immune microenvironment is crucial for diffuse large B-cell lymphoma (DLBCL) development. However, the mechanisms by which super-enhancers (SEs) regulate the interactions between DLBCL cells and tumor-infiltrating immune cells remains largely unknown. This study aimed to investigate the role of SE-controlled genes in regulating the interactions between DLBCL cells and tumor-infiltrating immune cells. Single-cell RNA-seq, bulk RNA-seq and H3K27ac ChIP-seq data were downloaded from the Heidelberg Open Research Data database and Gene Expression Omnibus database. HOMER algorithm and Seurat package in R were used for bioinformatics analysis. Cell proliferation and lactate dehydrogenase (LDH) release was detected by MTS and LDH release assays, respectively. Interaction between B cell cluster and CD8+ T cell and NK cell cluster was most obviously enhanced in DLBCL, with CD70-CD27, MIF-CD74/CXCR2 complex, MIF-CD74/CD44 complex and CCL3-CCR5 interactions were significantly increased. NK cell sub-cluster showed the strongest interaction with B cell cluster. ZZZ3 upregulated the transcription of CD70 by binding to its SE. Silencing CD70 in DOHH2 cells significantly promoted the proliferation of co-cultured NK92 cells and LDH release from DOHH2 cells, which was counteracted by ZZZ3 overexpression in DOHH2 cells. CD70 silencing combined with PD-L1 blockade promoted LDH release from DOHH2 cells co-cultured with NK92 cells. In conclusion, DLBCL cells inhibited the proliferation and killing of infiltrating NK cells by regulating ZZZ3/CD70 axis. Targeting ZZZ3/CD70 axis combined with PD-L1 blockade is expected to be a promising strategy for DLBCL treatment.

Prognostic relevance of tumor-infiltrating CD4+ cells and total metabolic tumor volume-based risk stratification in diffuse large B-cell lymphoma

In order to elucidate the relationship between pretreatment radiomic parameters and the proportions of various tumor-infiltrating (TI) cells, we retrospectively analyzed the association of total metabolic tumor volume (TMTV) and TI cells on biopsied tumor lesions in 171 patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL). The surface markers of TI cells were analyzed by multicolor flow cytometry using a dissected single-cell suspension. In examining the correlation between TI cells and positron-emission tomography-derived parameters (maximum standardized uptake value [SUVmax], total metabolic tumor volume [TMTV], and total lesion glycolysis), intratumoral cell types minimally influenced the results, except for a weak negative correlation between CD4+ cells and SUVmax (R=-0.16, P=0.045). Even for the lesion fluorodeoxyglucose uptake at the biopsied site, CD19+ cells (indicative of malignant burden) showed only a weak correlation with the highest SUV (R=0.21, P=0.009), whereas CD3+ (R=-0.25, P=0.002) and CD4+ cells (R=-0.29, P<0.001) demonstrated a similarly weak inverse correlation. High TMTV and low TI CD4+ cells were independently associated with poor prognosis and their combination identified the most adverse population (3-year progression-free survival: 32.3%, 95% confidence interval [CI]: 19.4-53.7; 3-year overall survival: 48.4%, 95% CI: 33.6-69.6). Moreover, radiomic parameters incorporating the international prognostic index significantly improved the 3-year survival prediction (area under the curve: 0.76, P<0.05) compared to their standalone use. This study underscores the prognostic impact of TI CD4+ cells on DLBCL and suggests that integration of TMTV and TI cell analysis enhances the accuracy of prognostic prediction.

The significance of CD8+ tumor-infiltrating lymphocytes exhaustion heterogeneity and its underlying mechanism in diffuse large B-cell lymphoma

CD8+ tumor-infiltrating lymphocytes (TILs) exhaustion is a major barrier to effective tumor control in diffuse large B-cell lymphoma (DLBCL) and may consist of heterogeneous populations with different functional states. We profiled the CD8+TILs exhaustion heterogeneity and explored its clinical significance as well as the underlying mechanism through single-cell RNA sequencing (n = 7), bulk RNA sequencing (n = 3300), immunohistochemistry (n = 116), and reverse transcription-quantitative polymerase chain reaction (n = 95), and somatic mutation data (n = 48). Our results demonstrated that exhausted CD8+TILs in DLBCL were composed of progenitor and terminal states characterized by CCL5 and TUBA1B, respectively. High terminally exhausted CD8+TILs indicated an immunosuppressive tumor microenvironment, activated B-cell-like subtype, inferior prognosis, and poor response to immune checkpoint blockade therapy in DLBCL. Our study further demonstrated that the CD39/A2AR-related signaling may be the potential pathway that promoted the transition of progenitor toward terminally exhausted CD8+TILs in DLBCL. Furthermore, the CD39/A2AR-related pathway in DLBCL may be regulated by BATF and STAT3 in exhausted CD8+TILs, and MYD88 mutation in tumor cells. Our study highlights CD8+TILs exhaustion heterogeneity and its possible regulatory mechanism provides a novel prognostic indicator and can facilitate the optimization of individualized immunotherapy.

Rupatadine-inhibited OTUD3 promotes DLBCL progression and immune evasion through deubiquitinating MYL12A and PD-L1

The obstacle to effectively treating Diffuse Large B-cell Lymphoma (DLBCL) lies in the resistance observed toward standard therapies. Identifying therapeutic targets that prove effective for relapsed or refractory patients poses a significant challenge. OTUD3, a deubiquitinase enzyme, is overexpressed in DLBCL tissues. However, its role in DLBCL has not been investigated. Our study has brought to light the multifaceted impact of OTUD3 in DLBCL. Not only does it enhance cell survival through the deubiquitination of MYL12A, but it also induces CD8+ T cell exhaustion within the local environment by deubiquitinating PD-L1. Our findings indicate that the OTUD3 inhibitor, Rupatadine, exerts its influence through competitive binding with OTUD3. This operation diminishes the deubiquitination of both MYL12A and PD-L1 by OTUD3. This research unveils the central and oncogenic role of OTUD3 in DLBCL and highlights the potential clinical application value of the OTUD3 inhibitor, Rupatadine. These findings contribute valuable insights into addressing the challenges of resistant DLBCL cases and offer a promising avenue for further clinical exploration.

Non-neoplastic cells as prognostic biomarkers in diffuse large B-cell lymphoma: A system review and meta-analysis

The microenvironment of diffuse large B-cell lymphoma (DLBCL) is composed of various components, including immune cells and immune checkpoints, some of which have been correlated with the prognosis of DLBCL, but their results remain controversial. Therefore, we conducted a systematic review and meta-analysis to investigate the association between the microenvironment and prognosis in DLBCL. We searched PubMed, Web of Science, and EMBASE for relevant articles between 2001 and 2022. Twenty-five studies involving 4495 patients with DLBCL were included in the analysis. This meta-analysis confirmed that high densities of Foxp3+Tregs and PD-1+T cells are good indicators for overall survival (OS) in DLBCL, while high densities of programmed cell death protein ligand1(PD-L1)-positive expression cells and T-cell immunoglobulin-and mucin domain-3-containing molecule 3 (TIM-3)-positive expression tumor-infiltrating cells (TILs) play a contrary role in OS. Additionally, higher numbers of T-cell intracytoplasmic antigen-1(TIA-1)-positive expression T cells imply better OS and progression-free survival (PFS), while high numbers of lymphocyte activation gene(LAG)-positive expression TILs predict bad OS and PFS. Various non-tumoral cells in the microenvironment play important roles in the prognosis of DLBCL.

KMT2D mutations promoted tumor progression in diffuse large B-cell lymphoma through altering tumor-induced regulatory T cell trafficking via FBXW7-NOTCH-MYC/TGF-β1 axis

Histone methyltransferase KMT2D is one of the most frequently mutated genes in diffuse large B-cell lymphoma (DLBCL) and has been identified as an important pathogenic factor and prognostic marker. However, the biological relevance of KMT2D mutations on tumor microenvironment remains to be determined. KMT2D mutations were assessed by whole-genome/exome sequencing (WGS/WES) in 334 patients and by targeted sequencing in 427 patients with newly diagnosed DLBCL. Among all 761 DLBCL patients, somatic mutations in KMT2D were observed in 143 (18.79%) patients and significantly associated with advanced Ann Arbor stage and MYC expression ≥ 40%, as well as inferior progression-free survival and overall survival. In B-lymphoma cells, the mutation or knockdown of KMT2D inhibited methylation of lysine 4 on histone H3 (H3K4), downregulated FBXW7 expression, activated NOTCH signaling pathway and downstream MYC/TGF-β1, resulting in alterations of tumor-induced regulatory T cell trafficking. In B-lymphoma murine models established with subcutaneous injection of SU-DHL-4 cells, xenografted tumors bearing KMT2D mutation presented lower H3K4 methylation, higher regulatory T cell recruitment, thereby provoking rapid tumor growth compared with wild-type KMT2D via FBXW7-NOTCH-MYC/TGF-β1 axis.

Tumor purity-related genes for predicting the prognosis and drug sensitivity of DLBCL patients

Background

Diffuse large B-cell lymphoma (DLBCL) is the predominant type of malignant B-cell lymphoma. Although various treatments have been developed, the limited efficacy calls for more and further exploration of its characteristics.

Methods

Datasets from the Gene Expression Omnibus (GEO) database were used for identifying the tumor purity of DLBCL. Survival analysis was employed for analyzing the prognosis of DLBCL patients. Immunohistochemistry was conducted to detect the important factors that influenced the prognosis. Drug-sensitive prediction was performed to evaluate the value of the model.

Results

VCAN, CD3G, and C1QB were identified as three key genes that impacted the outcome of DLBCL patients both in GEO datasets and samples from our center. Among them, VCAN and CD3G+ T cells were correlated with favorable prognosis, and C1QB was correlated with worse prognosis. The ratio of CD68 + macrophages and CD8 + T cells was associated with better prognosis. In addition, CD3G+T cells ratio was significantly correlated with CD68 + macrophages, CD4 + T cells, and CD8 +T cells ratio, indicating it could play an important role in the anti-tumor immunity in DLBCL. The riskScore model constructed based on the RNASeq data of VCAN, C1QB, and CD3G work well in predicting the prognosis and drug sensitivity.

Conclusions

VCAN, CD3G, and C1QB were three key genes that influenced the tumor purity of DLBCL, and could also exert certain impact on drug sensitivity and prognosis of DLBCL patients.

Funding

This work is supported by the Shenzhen High-level Hospital Construction Fund and CAMS Innovation Fund for Medical Sciences (CIFMS) (2022-I2M-C&T-B-062).

Inflammatory and subtype-dependent serum protein signatures predict survival beyond the ctDNA in aggressive B cell lymphomas

BACKGROUND

Biological heterogeneity of large B cell lymphomas (LBCLs) is poorly captured by current prognostic tools, hampering optimal treatment decisions.

METHODS

We dissected the levels of 1,463 serum proteins in a uniformly treated trial cohort of 109 patients with high-risk primary LBCL (ClinicalTrials.gov: NCT01325194) and correlated the profiles with molecular data from tumor tissue and circulating tumor DNA (ctDNA) together with clinical data.

FINDINGS

We discovered clinically and biologically relevant associations beyond established clinical estimates and ctDNA. We identified an inflamed serum protein profile, which reflected host response to lymphoma, associated with inflamed and exhausted tumor microenvironment features and high ctDNA burden, and translated to poor outcome. We composed an inflammation score based on the identified inflammatory proteins and used the score to predict survival in an independent LBCL trial cohort (ClinicalTrials.gov: NCT03293173). Furthermore, joint analyses with ctDNA uncovered multiple serum proteins that correlate with tumor burden. We found that SERPINA9, TACI, and TARC complement minimally invasive subtype profiling and that TACI and TARC can be used to evaluate treatment response in a subtype-dependent manner in the liquid biopsy.

CONCLUSIONS

Altogether, we discovered distinct serum protein landscapes that dissect the heterogeneity of LBCLs and provide agile, minimally invasive tools for precision oncology.

FUNDING

This research was funded by grants from the Research Council of Finland, Finnish Cancer Organizations, Sigrid Juselius Foundation, University of Helsinki, iCAN Digital Precision Cancer Medicine Flagship, Orion Research Foundation sr, and Helsinki University Hospital.

Cuproptosis-related lncRNA signature as a prognostic tool and therapeutic target in diffuse large B cell lymphoma

Cuproptosis is a newly defined form of programmed cell death that relies on mitochondria respiration. Long noncoding RNAs (lncRNAs) play crucial roles in tumorigenesis and metastasis. However, whether cuproptosis-related lncRNAs are involved in the pathogenesis of diffuse large B cell lymphoma (DLBCL) remains unclear. This study aimed to identify the prognostic signatures of cuproptosis-related lncRNAs in DLBCL and investigate their potential molecular functions. RNA-Seq data and clinical information for DLBCL were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Cuproptosis-related lncRNAs were screened out through Pearson correlation analysis. Utilizing univariate Cox, least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analysis, we identified seven cuproptosis-related lncRNAs and developed a risk prediction model to evaluate its prognostic value across multiple groups. GO and KEGG functional analyses, single-sample GSEA (ssGSEA), and the ESTIMATE algorithm were used to analyze the mechanisms and immune status between the different risk groups. Additionally, drug sensitivity analysis identified drugs with potential efficacy in DLBCL. Finally, the protein-protein interaction (PPI) network were constructed based on the weighted gene co-expression network analysis (WGCNA). We identified a set of seven cuproptosis-related lncRNAs including LINC00294, RNF139-AS1, LINC00654, WWC2-AS2, LINC00661, LINC01165 and LINC01398, based on which we constructed a risk model for DLBCL. The high-risk group was associated with shorter survival time than the low-risk group, and the signature-based risk score demonstrated superior prognostic ability for DLBCL patients compared to traditional clinical features. By analyzing the immune landscapes between two groups, we found that immunosuppressive cell types were significantly increased in high-risk DLBCL group. Moreover, functional enrichment analysis highlighted the association of differentially expressed genes with metabolic, inflammatory and immune-related pathways in DLBCL patients. We also found that the high-risk group showed more sensitivity to vinorelbine and pyrimethamine. A cuproptosis-related lncRNA signature was established to predict the prognosis and provide insights into potential therapeutic strategies for DLBCL patients.

Ethyl pyruvate attenuates cellular adhesion and proliferation of diffuse large B-cell lymphoma by targeting c-Jun

Diffuse large B-cell lymphoma (DLBCL) stands out as the most common type of malignant cancer, representing the majority of cases of non-Hodgkin's lymphoma. Ethyl pyruvate (EP) is a derivative of pyruvic acid and found to have potent anti-tumor properties. Despite its potential benefits, the impact of EP on DLBCL remains ambiguous. Our objective is to elucidate the role of EP in modulating the development of DLBCL. Analysis of cholecystokinin-8 (CCK-8) revealed that treatment with EP significantly diminished the viability of DLBCL cells. Furthermore, EP administration suppressed colony formation and hindered cell adhesion and invasion in DLBCL cells. Examination of cell cycle progression showed that EP treatment induced arrest at the G1 phase and subsequently reduced the S phase population in DLBCL cells. EP treatment consistently exhibited apoptosis-inducing properties in Annexin-V assays, and notably downregulated the expression of Bcl-2 while increasing levels of proapoptotic cleaved caspase 3 and BAX in DLBCL cells. Additionally, EP treatment decreased the overexpression of c-Jun in c-Jun-transfected DLBCL cells. Further, EP demonstrated DNA-damaging effects in TUNEL assays. In vivo, xenograft animal models revealed that EP treatment significantly mitigated DLBCL tumor growth and suppressed DLBCL cell adhesion to bone marrow stromal cells. In summary, these findings suggest that EP mitigates DLBCL progression by inducing apoptosis, inducing cell cycle arrest, and promoting DNA damage.

A novel anoikis-related signature predicts prognosis risk and treatment responsiveness in diffuse large B-cell lymphoma

BACKGROUND

Although anoikis plays a role in cancer metastasis and aggressiveness, it has rarely been reported in diffuse large B cell lymphoma (DLBCL).

METHODS

We obtained RNA sequencing data and matched clinical data from the GEO database. An anoikis-related genes (ARGs)-based risk signature was developed in GSE10846 training cohort and validated in three other cohorts. Additionally, we predicted half-maximal inhibitory concentration (IC50) of drugs based on bioinformatics method and obtained the actual IC50 to some chemotherapy drugs via cytotoxicity assay.

RESULTS

The high-risk group, as determined by our signature, was associated with worse prognosis and an immunosuppressive environment in DLBCL. Meanwhile, the nomogram based on eight variables had more accurate ability in forecasting the prognosis than the international prognostic index in DLBCL. The prediction of IC50 indicated that DLBCL patients in the high-risk group were more sensitive to doxorubicin, IPA-3, lenalidomide, gemcitabine, and CEP.701, while patients in the low-risk group were sensitive to cisplatin and dasatinib. Consistent with the prediction, cytotoxicity assay suggested the higher sensitivity to doxorubicin and gemcitabine and the lower sensitivity to dasatinib in the high-risk group in DLBCL.

CONCLUSION

The ARG-based signature may provide a promising direction for prognosis prediction and treatment optimization for DLBCL patients.

Radiomics signature for dynamic changes of tumor-infiltrating CD8+ T cells and macrophages in cervical cancer during chemoradiotherapy

BACKGROUND

Our previous study suggests that tumor CD8+ T cells and macrophages (defined as CD68+ cells) infiltration underwent dynamic and heterogeneous changes during concurrent chemoradiotherapy (CCRT) in cervical cancer patients, which correlated with their short-term tumor response. This study aims to develop a CT image-based radiomics signature for such dynamic changes.

METHODS

Thirty cervical squamous cell carcinoma patients, who were treated with CCRT followed by brachytherapy, were included in this study. Pre-therapeutic CT images were acquired. And tumor biopsies with immunohistochemistry at primary sites were performed at baseline (0 fraction (F)) and immediately after 10F. Radiomics features were extracted from the region of interest (ROI) of CT images using Matlab. The LASSO regression model with ten-fold cross-validation was utilized to select features and construct an immunomarker classifier and a radiomics signature. Their performance was evaluated by the area under the curve (AUC).

RESULTS

The changes of tumor-infiltrating CD8+T cells and macrophages after 10F radiotherapy as compared to those at baseline were used to generate the immunomarker classifier (AUC= 0.842, 95% CI:0.680-1.000). Additionally, a radiomics signature was developed using 4 key radiomics features to predict the immunomarker classifier (AUC=0.875, 95% CI:0.753-0.997). The patients stratified based on this signature exhibited significant differences in treatment response (p = 0.004).

CONCLUSION

The radiomics signature could be used as a potential predictor for the CCRT-induced dynamic alterations of CD8+ T cells and macrophages, which may provide a less invasive approach to appraise tumor immune status during CCRT in cervical cancer compared to tissue biopsy.

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.

Spatially-resolved transcriptomics reveal macrophage heterogeneity and prognostic significance in diffuse large B-cell lymphoma

Macrophages are abundant immune cells in the microenvironment of diffuse large B-cell lymphoma (DLBCL). Macrophage estimation by immunohistochemistry shows varying prognostic significance across studies in DLBCL, and does not provide a comprehensive analysis of macrophage subtypes. Here, using digital spatial profiling with whole transcriptome analysis of CD68+ cells, we characterize macrophages in distinct spatial niches of reactive lymphoid tissues (RLTs) and DLBCL. We reveal transcriptomic differences between macrophages within RLTs (light zone /dark zone, germinal center/ interfollicular), and between disease states (RLTs/ DLBCL), which we then use to generate six spatially-derived macrophage signatures (MacroSigs). We proceed to interrogate these MacroSigs in macrophage and DLBCL single-cell RNA-sequencing datasets, and in gene-expression data from multiple DLBCL cohorts. We show that specific MacroSigs are associated with cell-of-origin subtypes and overall survival in DLBCL. This study provides a spatially-resolved whole-transcriptome atlas of macrophages in reactive and malignant lymphoid tissues, showing biological and clinical significance.

Diffuse large B-cell lymphoma: the significance of CD8+ tumor-infiltrating lymphocytes exhaustion mediated by TIM3/Galectin-9 pathway

BACKGROUND

Overexpression of T-cell immunoglobulin and mucin domain-containing protein 3 (TIM3) is related to the exhaustion of CD8+ tumor-infiltrating lymphocytes (TILs) in diffuse large B-cell lymphoma (DLBCL). However, the mechanism of TIM3-mediated CD8+TILs exhaustion in DLBCL remains poorly understood. Therefore, we aimed to clarify the potential pathway involved in TIM3-mediated CD8+TILs exhaustion and its significance in DLBCL.

METHODS

The expression of TIM3 and its correlation with CD8+TILs exhaustion, the key ligand of TIM3, and the potential pathway of TIM3-mediated CD8+TILs exhaustion in DLBCL were analyzed using single-cell RNA sequencing and validated by RNA sequencing. The biological significance of TIM3-related pathway in DLBCL was investigated based on RNA sequencing, immunohistochemistry, and reverse transcription-quantitative polymerase chain reaction data. Finally, the possible regulatory mechanism of TIM3-related pathway in DLBCL was explored using single-cell RNA sequencing and RNA sequencing.

RESULTS

Our results demonstrated that CD8+TILs, especially the terminally exhausted state, were the major clusters that expressed TIM3 in DLBCL. Galectin-9, mainly expressed in M2 macrophages, is the key ligand of TIM3 and can induce the exhaustion of CD8+TILs through TIM3/Galectin-9 pathway. Meanwhile, high TIM3/Galectin-9 enrichment is related to immunosuppressive tumor microenvironment, severe clinical manifestations, inferior prognosis, and poor response to CHOP-based chemotherapy, and can predict the clinical efficacy of immune checkpoint blockade therapy in DLBCL. Furthermore, the TIM3/Galectin-9 enrichment in DLBCL may be regulated by the IFN-γ signaling pathway.

CONCLUSIONS

Our study highlights that TIM3/Galectin-9 pathway plays a crucial role in CD8+TILs exhaustion and the immune escape of DLBCL, which facilitates further functional studies and could provide a theoretical basis for the development of novel immunotherapy in DLBCL.

S100A8 is a prognostic signature and associated with immune response in diffuse large B-cell lymphoma

Background

S100A8, a calcium-binding protein belonging to the S100 family, is involved in immune responses and multiple tumor pathogens. Diffuse large B-cell lymphoma (DLBCL) is one of the most common types of B-cell lymphoma and remains incurable in 40% of patients. However, the role of S100A8 and its regulation of the immune response in DLBCL remain unclear.

Methods

The differential expression of S100A8 was identified via the GEO and TCGA databases. The prognostic role of S100A8 in DLBCL was calculated using the Kaplan-Meier curve. The function enrichment of differentially expressed genes (DEGs) was explored through GO, KEGG, GSEA, and PPI analysis. In our cohort, the expression of S100A8 was verified. Meanwhile, the biological function of S100A8 was applied after the inhibition of S100A8 in an in vitro experiment. The association between S100A8 and immune cell infiltration and treatment response in DLBCL was analyzed.

Results

S100A8 was significantly overexpressed and related to a poor prognosis in DLBCL patients. Function enrichment analysis revealed that DEGs were mainly enriched in the IL-17 signaling pathway. Our cohort also verified this point. In vitro experiments suggested that inhibition of S100A8 should promote cell apoptosis and suppress tumor growth. Single-cell RNA sequence analysis indicated that S100A8 might be associated with features of the tumor microenvironment (TME), and immune infiltration analyses discovered that S100A8 expression was involved in TME. In terms of drug screening, we predicted that many drugs were associated with preferable sensitivity.

Conclusion

Elevated S100A8 expression is associated with a poor prognosis and immune infiltration in DLBCL. Inhibition of S100A8 could promote cell apoptosis and suppress tumor growth. Meanwhile, S100A8 has the potential to be a promising immunotherapeutic target for patients with DLBCL.

Tumor microenvironment and CAR-T cell immunotherapy in B-cell lymphoma

Chimeric receptor antigen T cell (CAR-T cell) therapy has demonstrated effectiveness and therapeutic potential in the immunotherapy of hematological malignancies, representing a promising breakthrough in cancer treatment. Despite the efficacy of CAR-T cell therapy in B-cell lymphoma, response variability, resistance, and side effects remain persistent challenges. The tumor microenvironment (TME) plays an intricate role in CAR-T cell therapy of B-cell lymphoma. The TME is a complex and dynamic environment that includes various cell types, cytokines, and extracellular matrix components, all of which can influence CAR-T cell function and behavior. This review discusses the design principles of CAR-T cells, TME in B-cell lymphoma, and the mechanisms by which TME influences CAR-T cell function. We discuss emerging strategies aimed at modulating the TME, targeting immunosuppressive cells, overcoming inhibitory signaling, and improving CAR-T cell infiltration and persistence. Therefore, these processes enhance the efficacy of CAR-T cell therapy and improve patient outcomes in B-cell lymphoma. Further research will be needed to investigate the molecular and cellular events that occur post-infusion, including changes in TME composition, immune cell interactions, cytokine signaling, and potential resistance mechanisms. Understanding these processes will contribute to the development of more effective CAR-T cell therapies and strategies to mitigate treatment-related toxicities.

Flow cytometry quantification of tumor-infiltrating lymphocytes to predict the survival of patients with diffuse large B-cell lymphoma

Introduction

Our previous studies have demonstrated that tumor-infiltrating lymphocytes (TILs), including normal B cells, T cells, and natural killer (NK) cells, in diffuse large B-cell lymphoma (DLBCL) have a significantly favorable impact on the clinical outcomes of patients treated with standard chemoimmunotherapy. In this study, to gain a full overview of the tumor immune microenvironment (TIME), we assembled a flow cytometry cohort of 102 patients diagnosed with DLBCL at the Duke University Medical Center.

Methods

We collected diagnostic flow cytometry data, including the proportion of T cells, abnormal B cells, normal B cells, plasma cells, NK cells, monocytes, and granulocytes in fresh biopsy tissues at clinical presentation, and analyzed the correlations with patient survival and between different cell populations.

Results

We found that low T cell percentages in all viable cells and low ratios of T cells to abnormal B cells correlated with significantly poorer survival, whereas higher percentages of normal B cells among total B cells (or high ratios of normal B cells to abnormal B cells) and high percentages of NK cells among all viable cells correlated with significantly better survival in patients with DLBCL. After excluding a small number of patients with low T cell percentages, the normal B cell percentage among all B cells, but not T cell percentage among all cells, continued to show a remarkable prognostic effect. Data showed significant positive correlations between T cells and normal B cells, and between granulocytes and monocytes. Furthermore, we constructed a prognostic model based on clinical and flow cytometry factors, which divided the DLBCL cohort into two equal groups with remarkable differences in patient survival and treatment response.

Summary

TILs, including normal B cells, T cells, and NK cells, are associated with favorable clinical outcomes in DLBCL, and flow cytometry capable of quantifying the TIME may have additional clinical utility for prognostication.

Contribution of the TIME in BCP-ALL: the basis for novel approaches therapeutics

The bone marrow (BM) niche is a microenvironment where both immune and non-immune cells functionally interact with hematopoietic stem cells (HSC) and more differentiated progenitors, contributing to the regulation of hematopoiesis. It is regulated by various signaling molecules such as cytokines, chemokines, and adhesion molecules in its microenvironment. However, despite the strict regulation of BM signals to maintain their steady state, accumulating evidence in B-cell precursor acute lymphoblastic leukemia (BCP-ALL) indicates that leukemic cells can disrupt the physiological hematopoietic niche in the BM, creating a new leukemia-supportive microenvironment. This environment favors immunological evasion mechanisms and the interaction of these cells with the development and progression of BCP-ALL. With a growing understanding of the tumor immune microenvironment (TIME) in the development and progression of BCP-ALL, current strategies focused on "re-editing" TIME to promote antitumor immunity have been developed. In this review, we summarize how TIME cells are disrupted by the presence of leukemic cells, evading immunosurveillance mechanisms in the BCP-ALL model. We also explore the crosstalk between TIME and leukemic cells that leads to treatment resistance, along with the most promising immuno-therapy strategies. Understanding and further research into the role of the BM microenvironment in leukemia progression and relapse are crucial for developing more effective treatments and reducing patient mortality.

Gene expression profiles associated with early relapse during first remission induction in canine multicentric high-grade B-cell lymphoma

Although chemotherapy using CHOP-based protocol induces remission in most cases of canine multicentric high-grade B-cell lymphoma (mhBCL), some cases develop early relapse during the first induction protocol. In this study, we examined the gene expression profiles of canine mhBCL before chemotherapy and investigated their associations with early relapse during the first whole CHOP-based protocol. Twenty-five cases of mhBCL treated with CHOP-based protocol as first induction chemotherapy were included in this study. Sixteen cases completed the first whole CHOP-based protocol without relapse (S-group), and nine developed relapse during the chemotherapy (R-group). RNA-seq was performed on samples from neoplastic lymph nodes. Differentially expressed genes (DEGs) were extracted by the comparison of gene expression profiles between S- and R-groups, and the differences in the expression levels of these genes were validated by RT-qPCR. Extracted 179 DEGs included the genes related to chemokine CC motif ligand, T-cell receptor signaling pathway, and PD-L1 expression and PD-1 checkpoint pathway. We focused on chemokine CC motif ligand, and CCL4 was confirmed to be significantly downregulated in the R-group (P=0.039). We also focused on the genes related to T-cell signaling pathway, and CD3E (P=0.039), ITK (P=0.023), and LAT (P=0.023) genes were confirmed to be significantly upregulated in the R-group. The current results suggest that both changes in tumor cells and the interactions between tumor cells and immune cells are associated with the efficacy of the chemotherapy for first remission induction.

Efficient 3D imaging and pathological analysis of the human lymphoma tumor microenvironment using light-sheet immunofluorescence microscopy

Rationale: The composition and spatial structure of the lymphoma tumor microenvironment (TME) provide key pathological insights for tumor survival and growth, invasion and metastasis, and resistance to immunotherapy. However, the 3D lymphoma TME has not been well studied owing to the limitations of current imaging techniques. In this work, we take full advantage of a series of new techniques to enable the first 3D TME study in intact lymphoma tissue. Methods: Diverse cell subtypes in lymphoma tissues were tagged using a multiplex immunofluorescence labeling technique. To optically clarify the entire tissue, immunolabeling-enabled three-dimensional imaging of solvent-cleared organs (iDISCO+), clear, unobstructed brain imaging cocktails and computational analysis (CUBIC) and stabilization to harsh conditions via intramolecular epoxide linkages to prevent degradation (SHIELD) were comprehensively compared with the ultimate dimensional imaging of solvent-cleared organs (uDISCO) approach selected for clearing lymphoma tissues. A Bessel-beam light-sheet fluorescence microscope (B-LSFM) was developed to three-dimensionally image the clarified tissues at high speed and high resolution. A customized MATLAB program was used to quantify the number and colocalization of the cell subtypes based on the acquired multichannel 3D images. By combining these cutting-edge methods, we successfully carried out high-efficiency 3D visualization and high-content cellular analyses of the lymphoma TME. Results: Several antibodies, including CD3, CD8, CD20, CD68, CD163, CD14, CD15, FOXP3 and Ki67, were screened for labeling the TME in lymphoma tumors. The 3D imaging results of the TME from three types of lymphoma, reactive lymphocytic hyperplasia (RLN), diffuse large B-cell lymphoma (DLBCL), and angioimmunoblastic T-cell lymphoma (AITL), were quantitatively analyzed, and their cell number, localization, and spatial correlation were comprehensively revealed. Conclusion: We present an advanced imaging-based method for efficient 3D visualization and high-content cellular analysis of the lymphoma TME, rendering it a valuable tool for tumor pathological diagnosis and other clinical research.

The Eradication of Carcinogenic Viruses in Established Solid Cancers

Carcinogenic viruses (oncoviruses) can initiate cancer, but their impact on established cancer varies. Some of these viruses prolong survival while others shorten it. This study classifies oncoviruses into two categories: viruses which induce a strong CD8+T cell reaction in non-cancerous tissues, and viruses which induce a weak CD8+ T cell reaction in non-cancerous tissues. The classification proves useful in predicting the effect of oncoviruses on the prognosis of solid cancers. Therefore, while eliminating carcinogenic viruses in healthy individuals (for example by immunization) may be important for cancer prevention, this study suggests that only viruses which induce a weak CD8+ T cell reaction should be eradicated in established solid tumors. The model correctly predicts the effect of oncoviruses on survival for six out of seven known oncoviruses, indicating that immune modulation by oncoviruses has a prominent effect on prognosis. It seems that CD8+ T cell response to oncoviruses observed in infected benign tissues is retained in infected tumors. Clinical significance: the effect of oncoviruses on solid cancer prognosis can be predicted with confidence based on immunological responses when clinical data are unavailable.

Comprehensive analysis of the prognostic implication and immune infiltration of CISD2 in diffuse large B-cell lymphoma

Background

Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell lymphoma in adults. CDGSH iron sulfur domain 2 (CISD2) is an iron-sulfur protein and plays a critical role of cell proliferation. The aberrant expression of CISD2 is associated with the progression of multiple cancers. However, its role in DLBCL remains unclear.

Methods

The differential expression of CISD2 was identified via public databases, and quantitative real-time PCR (qRT-PCR) and western blot were used to identifed the expression of CISD2. We estimated the impact of CISD2 on clinical prognosis using the Kaplan-Meier plotter. Meanwhile, the drug sensitivity of CISD2 was assessed using CellMiner database. The 100 CISD2-related genes from STRING obtained and analyzed using the LASSO Cox regression. A CISD2 related signature for risk model (CISD2Risk) was established. The PPI network of CISD2Risk was performed, and functional enrichment was conducted through the DAVID database. The impacts of CISD2Risk on clinical features were analyzed. ESTIMATE, CIBERSORT, and MCP-counter algorithm were used to identify CISD2Risk associated with immune infiltration. Subsequently, Univariate and multivariate Cox regression analysis were applied, and a prognostic nomogram, accompanied by a calibration curve, was constructed to predict 1-, 3-, and 5-years survival probabilities.

Results

CISD2 was upregulated in DLBCL patients comparing with normal controls via public datasets, similarly, CISD2 was highly expressed in DLBCL cell lines. Overexpression of CISD2 was associated with poor prognosis in DLBCL patients based on the GSE31312, the GSE32918, and GSE93984 datasets (P<0.05). Nine drugs was considered as a potential therapeutic agents for CISD2. By using the LASSO cox regression, twenty seven genes were identified to construct CISD2Risk, and biological functions of these genes might be involved in apoptosis and P53 signaling pathway. The high CISD2Risk value had a worse prognosis and therapeutic effect (P<0.05). The higher stromal score, immune score, and ESTIMATE score were associated with lowe CISD2Risk value, CISD2Risk was negatively correlated with several immune infiltrating cells (macrophages M0 and M1, CD8 T cells, CD4 naïve T cells, NK cell, etc) that might be correlated with better prognosis. Additionally, The high CISD2Risk was identified as an independent prognostic factor for DLBCL patients using both univariate and multivariate Cox regression. The nomogram produced accurate predictions and the calibration curves were in good agreement.

Conclusion

Our study demonstrates that high expression of CISD2 in DLBCL patients is associated with poor prognosis. We have successfully constructed and validated a good prognostic prediction and efficacy monitoring for CISD2Risk that included 27 genes. Meanwhile, CISD2Risk may be a promising evaluator for immune infiltration and serve as a reference for clinical decision-making in DLBCL patients.

Breast cancer stem cells generate immune-suppressive T regulatory cells by secreting TGFβ to evade immune-elimination

Cancer stem cells (CSCs), being the primary contributors in tumor initiation, metastasis, and relapse, ought to have seminal roles in evasion of immune surveillance. Tumor-promoting CD4+CD25+FOXP3+ T-regulatory cells (Tregs) have been described to abolish host defense mechanisms by impeding the activities of other immune cells including effector T cells. However, whether CSCs can convert effector T cells to immune-suppressive Treg subset, and if yes, the mechanism underlying CSC-induced Treg generation, are limitedly studied. In this regard, we observed a positive correlation between breast CSC and Treg signature markers in both in-silico and immunohistochemical analyses. Mirroring the conditions during tumor initiation, low number of CSCs could successfully generate CD4+CD25+FOXP3+ Treg cells from infiltrating CD4+ T lymphocytes in a contact-independent manner. Suppressing the proliferation potential as well as IFNγ production capacity of effector T cells, these Treg cells might be inhibiting antitumor immunity, thereby hindering immune-elimination of CSCs during tumor initiation. Furthermore, unlike non-stem cancer cells (NSCCs), CSCs escaped doxorubicin-induced apoptosis, thus constituting major surviving population after three rounds of chemotherapy. These drug-survived CSCs were also able to generate CD4+CD25+FOXP3+ Treg cells. Our search for the underlying mechanism further unveiled the role of CSC-shed immune-suppressive cytokine TGFβ, which was further increased by chemotherapy, in generating tumor Treg cells. In conclusion, during initiation as well as after chemotherapy, when NSCCs are not present in the tumor microenvironment, CSCs, albeit present in low numbers, generate immunosuppressive CD4+CD25+FOXP3+ Treg cells in a contact-independent manner by shedding high levels of immune-suppressive Treg-polarizing cytokine TGFβ, thus escaping immune-elimination and initiating the tumor or causing tumor relapse.

A novel angiogenesis-related scoring model predicts prognosis risk and treatment responsiveness in diffuse large B-cell lymphoma

Diffuse large B cell lymphoma (DLBCL) is a highly heterogeneous disease with varying therapeutic responses and prognoses. Angiogenesis is a crucial factor in lymphoma growth and progression, but no scoring model based on angiogenesis-related genes (ARGs) has been developed for prognostic evaluation of DLBCL patients. In this study, we used univariate Cox regression to identify prognostic ARGs and found two distinct clusters of DLBCL patients in the GSE10846 dataset based on the expression of these prognostic ARGs. These two clusters had different prognoses and immune cell infiltration. Using LASSO regression analysis, we constructed a novel seven-ARG-based scoring model in GSE10846 dataset, and it was further validated in the GSE87371 dataset. The DLBCL patients were divided into high- and low-score groups based on the median risk score as a cut-off. The high-score group had a worse prognosis and showed higher expression of immune checkpoints, M2 macrophages, myeloid-derived suppressor cells, and regulatory T cells, indicating a stronger immunosuppressive environment. DLBCL patients in high-score group were resistant to doxorubicin and cisplatin, which are components of frequently used chemotherapy regimens, but more sensitive to gemcitabine and temozolomide. Using RT-qPCR, we found that two candidate risk genes, RAPGEF2 and PTGER2, were over-expressed in DLBCL tissues compared with control tissues. Taken together, the ARG-based scoring model provides a promising direction for the prognosis and immune status of DLBCL patients, and benefits the development of personalized treatment for DLBCL patients.

Characterization and clinical impact of the tumor microenvironment in post-transplant aggressive B-cell lymphomas

Post-transplant lymphoproliferative disorders (PTLD) are iatrogenic immune deficiency-associated lymphoid/plasmacytic proliferations developing due to immunosuppression in solid organ or hematopoietic stem cell allograft patients. PTLD are characterized by abnormal proliferation of lymphoid cells and have a heterogeneous clinical behavior. We profiled expression of >700 tumor microenvironment (TME)-related genes in 75 post-transplant aggressive B-cell lymphomas (PTABCL). Epstein-Barr virus (EBV)-positive PT-ABCL clustered together and were enriched for type I interferon pathway and antiviral-response genes. Additionally, a cytotoxicity gene signature associated with EBV-positivity and favorable overall survival (OS) (hazard ratio =0.61; P=0.019). In silico immunophenotyping revealed two subgroups with distinct immune cell compositions. The inflamed subgroup with higher proportions of immune cells had better outcome compared to noninflamed subgroup (median OS >200.0 vs. 15.2 months; P=0.006). In multivariable analysis with EBV status, International Prognostic Index, and rituximab-containing treatment, inflamed TME remained as an independent predictor for favorable outcome. We also compared TME between post-transplant and immunocompetent host diffuse large B-cell lymphomas (n=75) and discovered that the proportions of T cells were lower in PT-diffuse large B-cell lymphomas. In conclusion, we provide a comprehensive phenotypic characterization of PT-ABCL, highlighting the importance of immune cell composition of TME in determining the clinical behavior and prognosis of PT-ABCL.

Dynamic single-cell mapping unveils Epstein‒Barr virus-imprinted T-cell exhaustion and on-treatment response

Epstein‒Barr virus (EBV)-associated gastric cancer (GC) manifests an intriguing immunotherapy response. However, the cellular basis for EBV-imprinted tumour immunity and on-treatment response remains undefined. This study aimed to finely characterize the dynamic tumour immune contexture of human EBV (+) GC treated with immunochemotherapy by longitudinal scRNA-seq and paired scTCR/BCR-seq. EBV (+) GC exhibits an inflamed-immune phenotype with increased T-cell and B-cell infiltration. Immunochemotherapy triggers clonal revival and reinvigoration of effector T cells which step to determine treatment response. Typically, an antigen-specific ISG-15+CD8+ T-cell population is highly enriched in EBV (+) GC patients, which represents a transitory exhaustion state. Importantly, baseline intratumoural ISG-15+CD8+ T cells predict immunotherapy responsiveness among GC patients. Re-emerged clonotypes of pre-existing ISG-15+CD8+ T cells could be found after treatment, which gives rise to a CXCL13-expressing effector population in responsive EBV (+) tumours. However, LAG-3 retention may render the ISG-15+CD8+ T cells into a terminal exhaustion state in non-responsive EBV (+) tumours. In accordance, anti-LAG-3 therapy could effectively reduce tumour burden in refractory EBV (+) GC patients. Our results delineate a distinct implication of EBV-imprinted on-treatment T-cell immunity in GC, which could be leveraged to optimize the rational design of precision immunotherapy.

Prognostic Impact of the Immunoscore Based on Whole-Slide Image Analysis of CD3+ Tumor-Infiltrating Lymphocytes in Diffuse Large B-Cell Lymphoma

An Immunoscore based on tumor-infiltrating T-cell density was validated as a prognostic factor in patients with solid tumors. However, the potential utility of the Immunoscore in predicting the prognosis of patients with diffuse large B-cell lymphoma (DLBCL) is unclear. Here, the prognostic value of an Immunoscore based on tumor-infiltrating CD3+ T-cell density was evaluated in 104 patients with DLBCL who underwent R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone) therapy. Digitally scanned whole-slide images were analyzed using Aperio ImageScope software. CD3+ cell densities in the whole tumor area were quantitated using 3 different methods, including number of CD3+ cells/area (mm2), ratio of CD3+ cells to total cells, and ratio of CD3+ cells to CD20+ cells. There was a high concordance among the 3 methods. Patients with low CD3+ cell density had an elevated serum lactate dehydrogenase level and a high Ki-67 proliferation index (all, P < .05). Patients with low CD3+ cell density, according to all 3 methods, had worse overall survival (OS) and worse progression-free survival (P < .05, all). They also had poor OS, independent of MYC/BCL2 double expression (DE) status, Eastern Cooperative Oncology Group performance status, or Ann Arbor stage (all, P < .05). These results were validated using 2 publicly available data sets. In both validation cohorts, patients with low CD3E mRNA expression had an elevated serum lactate dehydrogenase level, extranodal site involvement, and DE status (P < .05). They also had worse progression-free survival (P = .067 and P = .002, respectively) and OS (both P < .05). A low CD3E mRNA level was predictive of poor OS, independent of DE status. An Immunoscore based on whole-slide image analysis of CD3+ T-cell infiltration was sufficient to predict survival in patients with DLBCL. Low CD3+ cell density was a poor prognostic factor, independent of other prognostic parameters and DE status.

Prognostic and immunological characterization of diffuse large B-cell lymphoma evaluated by co-stimulatory molecular-related features

Background

Co-stimulatory molecules have been shown to enhance antitumor immune responses, but their role in Diffuse Large B-cell Lymphoma (DLBCL) remains unexplored.

Methods

This study aimed to explore the molecular typing of DLBCL with co-stimulatory molecule genes and to construct a prognostic profile to improve treatment decisions and clinical outcomes.

Results

We conducted the first comprehensive analysis of co-stimulatory molecules in DLBCL patients and identified five co-stimulatory molecule genes with prognostic and diagnostic values. Consensus cluster analysis based on these five co-stimulatory molecule genes revealed that the two identified clusters had different distribution patterns and prognostic differences. Co-stimulatory molecular correlation signatures were then constructed based on these five co-stimulatory molecular genes and validated in an external dataset, showing good performance in predicting patient prognosis. The signature is an independent risk factor for DLBCL patients and significantly correlates with clinical factors in patients and can be used as a complement to clinical factors. Furthermore, the signature was associated with the tumor immune microenvironment. Patients identified as being at high risk according to our signature exhibit high levels of immune cell infiltration microenvironment.

Conclusions

In conclusion, our signature can provide clinicians with prognostic predictions and help guide the treatment of patients with DLBCL.

Baseline tumor gene expression signatures correlate with chemoimmunotherapy treatment responsiveness in canine B cell lymphoma

Pet dogs develop spontaneous diffuse large B cell lymphoma (DLBCL), and veterinary clinical trials have been employed to treat canine DLBCL and to inform clinical trials for their human companions. A challenge that remains is selection of treatment to improve outcomes. The dogs in this study were part of a larger clinical trial evaluating the use of combinations of doxorubicin chemotherapy, anti-CD20 monoclonal antibody, and one of three small molecule inhibitors: KPT-9274, TAK-981, or RV1001. We hypothesized that significant differential expression of genes (DEGs) in the tumors at baseline could help predict which dogs would respond better to each treatment based on the molecular pathways targeted by each drug. To this end, we evaluated gene expression in lymph node aspirates from 18 trial dogs using the NanoString nCounter Canine Immuno-oncology (IO) Panel. We defined good responders as those who relapsed after 90 days, and poor responders as those who relapsed prior to 90 days. We analyzed all dogs at baseline and compared poor responders to good responders, and found increased CCND3 correlated with poor prognosis and increased CD36 correlated with good prognosis, as is observed in humans. There was minimal DEG overlap between treatment arms, prompting separate analyses for each treatment cohort. Increased CREBBP and CDKN1A for KPT-9274, increased TLR3 for TAK-981, and increased PI3Kδ, AKT3, and PTEN, and decreased NRAS for RV1001 were associated with better prognoses. Trends for selected candidate biomarker genes were confirmed via qPCR. Our findings emphasize the heterogeneity in DLBCL, similarities and differences between canine and human DLBCL, and ultimately identify biomarkers that may help guide the choice of chemoimmunotherapy treatment in dogs.

Diffuse large B-cell lymphomas have spatially defined, tumor immune microenvironments revealed by high-parameter imaging

Diffuse large B-cell lymphoma (DLBCL) not otherwise specified is the most common aggressive non-Hodgkin lymphoma and a biologically heterogeneous disease. Despite the development of effective immunotherapies, the organization of the DLBCL tumor-immune microenvironment (TIME) remains poorly understood.We interrogated the intact TIME of 51 de novo DLBCLs with triplicate sampling to characterize 337 995 tumor and immune cells using a 27-plex antibody panel that captured cell lineage, architectural, and functional markers. We spatially assigned individual cells, identified local cell neighborhoods, and established their topographical organization in situ. We found that the organization of local tumor and immune cells can be modeled by 6 composite cell neighborhood types (CNTs). Differential CNT representation divided cases into 3 aggregate TIME categories: immune-deficient, dendritic cell-enriched (DC-enriched), and macrophage-enriched (Mac-enriched). Cases with immune-deficient TIMEs have tumor cell-rich CNTs, in which the few infiltrating immune cells are enriched near CD31+ vessels, in keeping with limited immune activity. Cases with DC-enriched TIMEs selectively include tumor cell-poor/immune cell-rich CNTs with high numbers of CD11c+ DCs and antigen-experienced T cells also enriched near CD31+ vessels, in keeping with increased immune activity. Cases with Mac-enriched TIMEs selectively include tumor cell-poor/immune cell-rich CNTs with high numbers of CD163+ macrophages and CD8 T cells throughout the microenvironment, accompanied by increased IDO-1 and LAG-3 and decreased HLA-DR expression and genetic signatures in keeping with immune evasion. Our findings reveal that the heterogenous cellular components of DLBCL are not randomly distributed but organized into CNTs that define aggregate TIMEs with distinct cellular, spatial, and functional features.

The genetic polymorphisms of immune-related genes contribute to the susceptibility and survival of lymphoma

BACKGROUND

Though immunological abnormalities have been proven involved in the pathogenesis of lymphoma, the underlying mechanism remains unclear.

METHODS

We investigated 25 single nucleotide polymorphisms (SNPs) of 21 immune-related genes and explored their roles in lymphoma. The genotyping assay of the selected SNPs was used by the Massarray platform. Logistic regression and Cox proportional hazards models were used to analyze the associations of SNPs and the susceptibility of lymphoma or clinical characteristics of lymphoma patients. In addition, Least Absolute Shrinkage and Selection Operator regression was used to further analyze the relationships with the survival of lymphoma patients and candidate SNPs, and the significant difference between genotypes was verified by the expression of RNA.

RESULTS

By comparing 245 lymphoma patients with 213 healthy controls, we found eight important SNPs related to the susceptibility of lymphoma, which were involved in JAK-STAT, NF-κB and other functional pathways. We further analyzed the relationships between SNPs and clinical characteristics. Our results showed that both IL6R (rs2228145) and STAT5B (rs6503691) significantly contributed to the Ann Arbor stages of lymphoma. And the STAT3 (rs744166), IL2 (rs2069762), IL10 (rs1800871), and PARP1 (rs907187) manifested a significant relationship with the peripheral blood counts in lymphoma patients. More importantly, the IFNG (rs2069718) and IL12A (rs6887695) were associated with the overall survival (OS) of lymphoma patients remarkably, and the adverse effects of GC genotypes could not be offset by Bonferroni correction for multiple comparison in rs6887695 especially. Moreover, we determined that the mRNA expression levels of IFNG and IL12A were significantly decreased in patients with shorter-OS genotypes.

CONCLUSIONS

We used multiple methods of analysis to predict the correlations between lymphoma susceptibility, clinical characteristics or OS with SNPs. Our findings reveal that immune-related genetic polymorphisms contribute to the prognosis and treatment of lymphoma, which may serve as promising predictive targets.

Efficacy of Immune Checkpoint Blockade and Biomarkers of Response in Lymphoma: A Narrative Review

Immune checkpoint blockade (ICB) has revolutionized the prognosis of several advanced-stage solid tumors. However, its success has been far more limited in hematological malignancies and is mostly restricted to classical Hodgkin lymphoma (cHL) and primary mediastinal B cell lymphoma (PMBCL). In patients with non-Hodgkin lymphoma (NHL), response to PD-1/PD-L1 ICB monotherapy has been relatively limited, although some subtypes are more sensitive than others. Numerous predictive biomarkers have been investigated in solid malignancies, such as PD-L1 expression, tumor mutational burden (TMB) and microsatellite instability (MSI), among others. This review aims to appraise the current knowledge on PD-1/PD-L1 ICB efficacy in lymphoma when used either as monotherapy or combined with other agents, and describes potential biomarkers of response in this specific setting.

Novel insights into Hodgkin lymphoma biology by single-cell analysis

The emergence and rapid development of single-cell technologies mark a paradigm shift in cancer research. Various technology implementations represent powerful tools to understand cellular heterogeneity, identify minor cell populations that were previously hard to detect and define, and make inferences about cell-to-cell interactions at single-cell resolution. Applied to lymphoma, recent advances in single-cell RNA sequencing have broadened opportunities to delineate previously underappreciated heterogeneity of malignant cell differentiation states and presumed cell of origin, and to describe the composition and cellular subsets in the ecosystem of the tumor microenvironment (TME). Clinical deployment of an expanding armamentarium of immunotherapy options that rely on targets and immune cell interactions in the TME emphasizes the requirement for a deeper understanding of immune biology in lymphoma. In particular, classic Hodgkin lymphoma (CHL) can serve as a study paradigm because of its unique TME, featuring infrequent tumor cells among numerous nonmalignant immune cells with significant interpatient and intrapatient variability. Synergistic to advances in single-cell sequencing, multiplexed imaging techniques have added a new dimension to describing cellular cross talk in various lymphoma entities. Here, we comprehensively review recent progress using novel single-cell technologies with an emphasis on the TME biology of CHL as an application field. The described technologies, which are applicable to peripheral blood, fresh tissues, and formalin-fixed samples, hold the promise to accelerate biomarker discovery for novel immunotherapeutic approaches and to serve as future assay platforms for biomarker-informed treatment selection, including immunotherapies.

Longitudinal expression profiling identifies a poor risk subset of patients with ABC-type diffuse large B-cell lymphoma

Despite the effectiveness of immuno-chemotherapy, 40% of patients with diffuse large B-cell lymphoma (DLBCL) experience relapse or refractory disease. Longitudinal studies have previously focused on the mutational landscape of relapse but fell short of providing a consistent relapse-specific genetic signature. In our study, we have focused attention on the changes in GEP accompanying DLBCL relapse using archival paired diagnostic/relapse specimens from 38 de novo patients with DLBCL. COO remained stable from diagnosis to relapse in 80% of patients, with only a single patient showing COO switching from activated B-cell-like (ABC) to germinal center B-cell-like (GCB). Analysis of the transcriptomic changes that occur following relapse suggest ABC and GCB relapses are mediated via different mechanisms. We developed a 30-gene discriminator for ABC-DLBCLs derived from relapse-associated genes that defined clinically distinct high- and low-risk subgroups in ABC-DLBCLs at diagnosis in datasets comprising both population-based and clinical trial cohorts. This signature also identified a population of <60-year-old patients with superior PFS and OS treated with ibrutinib-R-CHOP as part of the PHOENIX trial. Altogether this new signature adds to the existing toolkit of putative genetic predictors now available in DLBCL that can be readily assessed as part of prospective clinical trials.

Immune priming with avelumab and rituximab prior to R-CHOP in diffuse large B-cell lymphoma: the phase II AvR-CHOP study

Immune evasion, due to abnormal expression of programmed-death ligands 1 and 2 (PD-L1/PD-L2), predicts poor outcomes with chemoimmunotherapy in diffuse large B-cell lymphoma (DLBCL). Immune checkpoint inhibition (ICI) has limited efficacy at relapse but may sensitise relapsed lymphoma to subsequent chemotherapy. ICI delivery to immunologically intact patients may thus be the optimal use of this therapy. In the phase II AvR-CHOP study, 28 patients with treatment-naive stage II-IV DLBCL received sequential avelumab and rituximab priming ("AvRp;" avelumab 10 mg/kg and rituximab 375 mg/m2 2-weekly for 2 cycles), R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisolone for 6 cycles) and avelumab consolidation (10 mg/kg 2-weekly for 6 cycles). Grade 3/4 immune-related adverse events occurred in 11%, meeting the primary endpoint of a grade ≥3 irAE rate of <30%. R-CHOP delivery was not compromised but one patient ceased avelumab. Overall response rates (ORR) after AvRp and R-CHOP were 57% (18% CR) and 89% (all CR). High ORR to AvRp was observed in primary mediastinal B-cell lymphoma (67%; 4/6) and molecularly-defined EBV-positive DLBCL (100%; 3/3). Progression during AvRp was associated with chemorefractory disease. Two-year failure-free and overall survival were 82% and 89%. An immune priming strategy with AvRp, R-CHOP and avelumab consolidation shows acceptable toxicity with encouraging efficacy.

A prognostic 15-gene model based on differentially expressed genes among metabolic subtypes in diffuse large B-cell lymphoma

The outcomes of patients with diffuse large B-cell lymphoma (DLBCL) vary widely, and about 40% of them could not be cured by the standard first-line treatment, R-CHOP, which could be due to the high heterogeneity of DLBCL. Here, we aim to construct a prognostic model based on the genetic signature of metabolic heterogeneity of DLBCL to explore therapeutic strategies for DLBCL patients. Clinical and transcriptomic data of one training and four validation cohorts of DLBCL were obtained from the GEO database. Metabolic subtypes were identified by PAM clustering of 1,916 metabolic genes in the 7 major metabolic pathways in the training cohort. DEGs among the metabolic clusters were then analyzed. In total, 108 prognosis-related DEGs were identified. Through univariable Cox and LASSO regression analyses, 15 DEGs were used to construct a risk score model. The overall survival (OS) and progression-free survival (PFS) of patients with high risk were significantly worse than those with low risk (OS: HR 2.86, 95%CI 2.04-4.01, p < 0.001; PFS: HR 2.42, 95% CI 1.77-3.31, p < 0.001). This model was also associated with OS in the four independent validation datasets (GSE10846: HR 1.65, p = 0.002; GSE53786: HR 2.05, p = 0.02; GSE87371: HR 1.85, p = 0.027; GSE23051: HR 6.16, p = 0.007) and PFS in the two validation datasets (GSE87371: HR 1.67, p = 0.033; GSE23051: HR 2.74, p = 0.049). Multivariable Cox analysis showed that in all datasets, the risk model could predict OS independent of clinical prognosis factors (p < 0.05). Compared with the high-risk group, patients in the low-risk group predictively respond to R-CHOP (p = 0.0042), PI3K inhibitor (p < 0.05), and proteasome inhibitor (p < 0.05). Therefore, in this study, we developed a signature model of 15 DEGs among 3 metabolic subtypes, which could predict survival and drug sensitivity in DLBCL patients.

High expression of AP2M1 correlates with worse prognosis by regulating immune microenvironment and drug resistance to R-CHOP in diffuse large B cell lymphoma

BACKGROUND

First-line treatment with R-CHOP has cured 50%-60% patients of diffuse large B cell lymphoma (DLBCL), and more than one-third patients will eventually progressed to relapsed/refractory disease with dismal outcomes. Adaptor Related Protein Complex 2 Subunit Mu 1 (AP2M1) is required for the activity of a vacuolar ATPase and may also play an important role in regulating the intracellular trafficking and function of CTLA-4 protein. Herein, using both public databases and our own tumor samples, we aimed to demonstrate the prognostic role of AP2M1 and the potential tumor-promoting mechanisms in DLBCL.

METHOD

Using public datasets of DLBCL from both GEO and TCGA databases, we analyzed the role of AP2M1 in mediating chemoresistance to R-CHOP and its correlation with various clinical parameters and prognosis. By using various R packages, we evaluated the role of AP2M1 on regulating tumor immune microenvironment. Moreover, tumor samples of DLBCL from Beijing TongRen Hospital were used to validate our findings by immunohistochemistry staining.

RESULT

Expression of AP2M1 was significantly increased in DLBCL, which was correlated with poor prognosis and a variety of clinical indicators. On the basis of enrichment analysis, it was found that AP2M1 may be related to intracellular receptor signaling pathway. Through immune analysis and drug prediction, we found that the expression of AP2M1 affected the immune environment and drug response of DLBCL, which further revealed the important role of AP2M1 in DLBCL. By analyzing 61 patients treated uniformly with R-CHOP regimen in our center, we validated the above findings that high expression of AP2M1 correlated with inferior survival outcomes and affected sensitivity to R-CHOP treatment.

CONCLUSION

Expression of AP2M1 may affect the prognosis of DLBCL patients probably by affecting the immune environment and the responses to many drugs in treating DLBCL, indicating AP2M1 as a potential therapy target in DLBCL.

Treg-selective IL-2 starvation synergizes with CD40 activation to sustain durable responses in lymphoma models

BACKGROUND

Roughly half of all diffuse large B-cell lymphomas (DLBCLs) are infiltrated by large numbers of regulatory T-cells (Tregs). Although the presence of 'effector' Tregs in particular is associated with an inferior prognosis in patients on standard rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) immunochemotherapy, the role of this cell type during lymphoma initiation and progression is poorly understood.

METHODS

Here, we use tissue microarrays containing prospectively collected DLBCL patient specimens, as well as data from publicly available cohorts to explore the mutational landscape of Treg-infiltrated DLBCL. We further take advantage of a model of MYC-driven lymphoma to mechanistically dissect the contribution of Tregs to lymphoma pathogenesis and to develop a strategy of Treg-selective interleukin-2 (IL-2) starvation to improve immune control of MYC-driven lymphoma.

RESULTS

We find that all genetic DLBCL subtypes, except for one characterized by co-occurring MYD88/CD79 mutations, are heavily infiltrated by Tregs. Spectral flow cytometry and scRNA-sequencing reveal the robust expression of functional and immunosuppressive markers on Tregs infiltrating MYC-driven lymphomas; notably, we find that intratumoral Tregs arise due to local conversion from naïve CD4+ precursors on tumor contact. Treg ablation in Foxp3iDTR mice, or by antibody-mediated Treg-selective blockade of IL-2 signaling, strongly reduces the lymphoma burden. We identify lymphoma B-cells as a major source of IL-2, and show that the effects of Treg depletion are reversed by the simultaneous depletion of Foxp3-negative CD4+ T-cells, but not CD8+ T-cells or natural killer (NK) cells. The inhibition of ATP hydrolyzation and adenosine production by Tregs at least partly phenocopies the effects of Treg depletion. Treg depletion further synergizes with pro-apoptotic CD40 activation to sustain durable responses.

CONCLUSION

The combined data implicate Tregs as a potential therapeutic target in DLBCL, especially in combination with other immunotherapies.