Diffuse Large B-cell Lymphoma Tissues Research Articles

SENP1 knockdown potentiates the apoptosis, cell cycle arrest, and reduces cisplatin resistance of diffuse large B cell lymphoma cells via inducing ferroptosis.

Ferroptosis has been regarded as a critical event in the process of diffuse large B cell lymphoma (DLBCL). Sentrin-specific protease 1 (SENP1) has emerged as an oncogene in multiple human malignancies. The present work was to investigate the effects of SENP1 on the progression of DLBCL and the possible regulatory mechanism involving ferroptosis. SENP1 expression in DLBCL tissues, parental and cisplatin-resistant DLBCL cells were, respectively, tested by GEPIA database, RT-qPCR, and Western blot. Cell viability was estimated via CCK-8 assay. Flow cytometry analysis estimated cell apoptosis and cycle. Western blot examined the expression of apoptosis-, cell cycle-, and ferroptosis-associated proteins. TBARS assay and BODIPY 581/591 C11 probe measured lipid peroxidation. Related assay kit assessed total iron levels. CCK-8 and flow cytometry evaluated cisplatin resistance. SENP1 expression was raised in DLBCL tissues and cells. SENP1 knockdown reduced cell viability, boosted cell apoptosis, cell cycle arrest, and elevated cisplatin sensitivity in DLBCL. SENP1 depletion drove the ferroptosis of both parental and cisplatin-resistant DLBCL cells and ferroptosis inhibitor Fer-1 reversed the influences of SENP1 inhibition on cell viability, apoptosis, cell cycle, and cisplatin resistance in DLBCL. Anyway, SENP1 absence might facilitate ferroptosis to obstruct the development of DLBCL and cisplatin resistance.

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

ABSTRACT 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.

Recombinant hirudin suppresses angiogenesis of diffuselarge B-cell lymphoma through regulation of the PAR-1-VEGF.

Hirudin is one of the specific inhibitors of thrombin, which has been confirmed to have strong bioactivities, including inhibiting tumors. However, the function and mechanism of hirudin and protease-activated receptor 1 (PAR-1) in diffuse large B-cell lymphoma (DLBCL) have not been clear. Detecting the expression PAR-1 in DLBCL tissues and cells by RT-qPCR and IHC. Transfected sh-NC, sh-PAR-1, or pcDNA3.1-PAR-1 in DLBCL cells or processed DLBCL cells through added thrombin, Vorapaxar, Recombinant hirudin (RH), or Na2S2O4 and co-culture with EA.hy926. And built DLBCL mice observed tumor growth. Detecting the expression of related genes by RT-qPCR, Western blot, IHC, and immunofluorescence, measured the cellular hypoxia with Hypoxyprobe-1 Kit, and estimated the cell inflammatory factors, proliferation, migration, invasion, and apoptosis by ELISA, CCK-8, flow cytometry, wound-healing and Transwell. Co-immunoprecipitation and pull-down measurement were used to verify the relationship. PAR-1 was highly expressed in DLBCL tissues and cells, especially in SUDHL2. Na2S2O4 induced SUDHL2 hypoxia, and PAR-1 did not influence thrombin-activated hypoxia. PAR-1 could promote SUDHL2 proliferation, migration, and invasion, and it was unrelated to cellular hypoxia. PAR-1 promoted proliferation, migration, and angiogenesis of EA.hy926 or SUDHL2 through up-regulation vascular endothelial growth factor (VEGF). RH inhibited tumor growth, cell proliferation, and migration, promoted apoptosis of DLBCL, and inhibited angiogenesis by down-regulating PAR-1-VEGF. RH inhibits proliferation, migration, and angiogenesis of DLBCL cells by down-regulating PAR-1-VEGF.

LncRNA CHROMR/miR-27b-3p/MET axis promotes the proliferation, invasion, and contributes to rituximab resistance in diffuse large B-cell lymphoma

Long non-coding RNAs (LncRNAs) could regulate chemoresistance through sponging microRNAs (miRNAs) and sequestering RNA binding proteins. However, the mechanism of lncRNAs in rituximab resistance in diffuse large B-cell lymphoma (DLBCL) is largely unknown. Here, we investigated the functions and molecular mechanisms of lncRNA CHROMR in DLBCL tumorigenesis and chemoresistance. LncRNA CHROMR is highly expressed in DLBCL tissues and cells. We examined the oncogenic functions of lncRNA CHROMR in DLBCL by a panel of gain-or-loss-of-function assays and in vitro experiments. LncRNA CHROMR suppression promotes CD20 transcription in DLBCL cells and inhibits rituximab resistance. RNA immunoprecipitation, RNA pull-down and dual luciferase reporter assay reveal that lncRNA CHROMR sponges with miR-27b-3p to regulate mesenchymal-epithelial transition factor (MET) levels and Akt signaling in DLBCL cells. Targeting the lncRNA CHROMR/miR-27b-3p/MET axis reduces DLBCL tumorigenesis. Altogether, these findings provide a new regulatory model, lncRNA CHROMR/miR-27b-3p/MET, which can serve as a potential therapeutic target for DLBCL.

Targeting HDACs for diffuse large B-cell lymphoma therapy

Histone deacetylases (HDACs) are involved in tumorigenesis and progression, however, their role in diffuse large B-cell lymphoma (DLBCL) is not well understood. In this study, we examined the expression levels, mutations, and clinical significance of HDACs in DLBCL. Additionally, we investigated the therapeutic potential of Chidamide, a novel HDAC inhibitor, to provide scientific evidence for targeting HDACs in DLBCL patients. We extracted transcriptome data of DLBCLs––including 47 lymph node samples and 337 whole-blood-cell controls––from The Cancer Genome Atlas. Bioinformatic analyses of HDAC expression, mutation, and correlation with the clinical significance of DLBCL patients were performed with the Gene Expression Profiling Interactive Analysis, GENEMANIA, and web-based software including cBioPortal and WebGestalt. To examine the therapeutic effect of Chidamide, DLBCL cell lines (WSU-DLCL-2 and DB cells) were employed. Cell proliferation and apoptosis were analyzed with Cell Counting Kit-8 and flow cytometry assays. The impact of Chidamide treatment was also analyzed by RNA sequencing of treated DB cells. Western blot was used to explore the molecular mechanism of the cytotoxicity of Chidamide on DLBCL cell lines. The expression of some HDACs (HDAC1, 2, 3, 4, 6, 7, 8, and 9) were significantly higher in the lymph node samples of DLBCL than that in whole-blood-cell controls. Moreover, we found that the mutation rate of HDACs was also higher in DLBCL tissues, although the overall survival of DLBCL patients was not associated with HDAC expression. Chidamide was found to have a cytotoxic effect on DLBCL cells in a dose-dependent manner, while transcriptome analysis and western blot revealed that using it for treatment impacted several biological processes, including PI3K/AKT signaling, mTOR signaling, the cell cycle, and apoptosis pathways. Alterations of HDAC genes, including enhanced expression and mutations, are positively related to DLBCL. Targeting HDACs with specific inhibitors such as Chidamide may represent a potential therapeutic approach for DLBCL patients.

Analysis and Investigation of Bioinformatics and Epigenetics Reveal the Underlying Mechanisms by which FLOT2 Modulates the Progression of Diffuse Large B-cell Lymphoma.

Diffuse large B-cell lymphoma (DLBCL) poses a significant threat to the quality of life for people worldwide. Regrettably, effective treatment strategies for this disease remain elusive in clinical practice due to the unclear understanding of its molecular mechanisms. Therefore, this study was devised to address these issues and identify novel diagnostic, therapeutic, and prognostic biomarkers for DLBCL. Gene expression and clinical data for DLBCL patients were retrieved from The Cancer Genome Atlas (TCGA) database, and relevant clinical data, tumor mutational burden (TMB), and gene expression levels were extracted. Bioinformatics analysis was conducted to screen for differentially expressed genes (DEGs). The prognostic significance of flotillin-2 (FLOT2) was assessed using Kaplan-Meier survival analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot analyses were employed to evaluate mRNA and protein levels of the genes. Cell proliferation, apoptosis, and invasion were assessed using cell counting kit-8 (CCK-8) assay, flow cytometry analysis, and Transwell assay, respectively. Our bioinformatics analysis revealed that FLOT2 was significantly overexpressed in DLBCL tissues compared to normal tissues, a finding corroborated by subsequent immunohistochemistry staining, qRT-PCR, and Western blot analyses. To elucidate its biological functions, shRNAs targeting FLOT2 were transfected into DLBCL cell lines (LY-3 and U2932), resulting in suppressed cell proliferation and invasion, while promoting apoptosis. Furthermore, a positive correlation between TMB and FLOT2 expression in DLBCL was observed. Subsequently, quanTIseq was utilized to calculate the immune score and assess FLOT2 gene expression. In DLBCL, FLOT2 gene expression was found to be associated with T cell CD4+ (non-regulatory) (p < 0.01), monocytes (p < 0.05), and uncharacterized cells (p < 0.05). Regarding immune checkpoint markers, including the cluster of differentiation 274 (CD274), cytotoxic T lymphocyte-associated antigen-4 (CTLA4), hepatitis A virus cellular receptor 2 (HAVCR2), lymphocyte activation gene-3 (LAG3), programmed cell death protein 1 (PDCD1), programmed cell death 1 ligand 2 (PDCD1LG2), Siglec-15 (SIGLEC15), and T cell immunoreceptor with Ig and ITIM domains (TIGIT), our analysis indicated that in DLBCL, FLOT2 exhibited a relationship only with TIGIT (p < 0.05). In summary, FLOT2 functions as an oncogene and is linked to DLBCL prognosis and the tumor microenvironment. Targeting FLOT2 deletion emerges as a novel strategy to impede DLBCL aggressiveness by inhibiting cell proliferation and invasion, ultimately inducing apoptotic cell death.

Identifying CD1c as a potential biomarker by the comprehensive exploration of tumor mutational burden and immune infiltration in diffuse large B cell lymphoma.

Tumor mutational burden (TMB) is a valuable prognostic biomarker. This study explored the predictive value of TMB and the potential association between TMB and immune infiltration in diffuse large B-cell lymphoma (DLBCL). We downloaded the gene expression profile, somatic mutation, and clinical data of DLBCL patients from The Cancer Genome Atlas (TCGA) database. We classified the samples into high-and low-TMB groups to identify differentially expressed genes (DEGs). Functional enrichment analyses were performed to determine the biological functions of the DEGs. We utilized the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm to estimate the abundance of 22 immune cells, and the significant difference was determined by the Wilcoxon rank-sum test between the high- and low-TMB group. Hub gene had been screened as the prognostic TMB-related immune biomarker by the combination of the Immunology Database and Analysis Portal (ImmPort) database and the univariate Cox analysis from the Gene Expression Omnibus (GEO) database including six DLBCL datasets. Various database applications such as Tumor Immune Estimation Resource (TIMER), CellMiner, konckTF, and Genotype-Tissue Expression (GTEx) verified the functions of the target gene. Wet assay confirmed the target gene expression at RNA and protein levels in DLBCL tissue and cell samples. Single nucleotide polymorphism (SNP) occurred more frequently than insertion and deletion, and C > T was the most common single nucleotide variant (SNV) in DLBCL. Survival analysis showed that the high-TMB group conferred poor survival outcomes. A total of 62 DEGs were obtained, and 13 TMB-related immune genes were identified. Univariate Cox analysis results illustrated that CD1c mutation was associated with lower TMB and manifested a satisfactory clinical prognosis by analysis of large samples from the GEO database. In addition, infiltration levels of immune cells in the high-TMB group were lower. Using the TIMER database, we systematically analyzed that the expression of CD1c was positively correlated with B cells, neutrophils, and dendritic cells and negatively correlated with CD8+ T cells, CD4+ T cells, and macrophages. Drug sensitivity showed a significant positive correlation between CD1c expression level and clinical drug sensitivity from the CellMiner database. CREB1, AHR, and TOX were used to comprehensively explore the regulation of CD1c-related transcription factors and signaling pathways by the KnockTF database. We searched the GETx database to compare the mRNA expression levels of CD1c between DLBCL and normal tissues, and the results suggested a significant difference between them. Moreover, wet experiments were conducted to verify the high expression of CD1c in DLBCL at the RNA and protein levels. Higher TMB correlated with poor survival outcomes and inhibited the immune infiltrates in DLBCL. Our results suggest that CD1c is a TMB-related prognostic biomarker.

Unraveling the enigma of B cells in diffuse large B-cell lymphoma: unveiling cancer stem cell-like B cell subpopulation at single-cell resolution.

Diffuse large B-cell lymphoma (DLBCL) represents the most prevalent form of aggressive non-Hodgkin lymphoma. Despite receiving standard treatment, a subset of patients undergoes refractory or recurrent cases, wherein the involvement of cancer stem cells (CSCs) could be significant. We comprehensively characterized B cell subpopulations using single-cell RNA sequencing data from three DLBCL samples and one normal lymph tissue. The CopyKat R package was employed to assess the malignancy of B cell subpopulations based on chromosomal copy number variations. CIBERSORTx software was utilized to estimate the proportions of B cell subpopulations in 230 DLBCL tissues. Furthermore, we employed the pySCENIC to identify key transcription factors that regulate the functionality of B cell subpopulations. By employing CellphoneDB, we elucidated the interplay among tumor microenvironment components within the B cell subpopulations. Finally, we validated our findings through immunofluorescence experiments. Our analysis revealed a specific cancer stem cell-like B cell subpopulation exhibiting self-renewal and multilineage differentiation capabilities based on the exploration of B cell subpopulations in DLBCL and normal lymph tissues at the single-cell level. Notably, a high infiltration of cancer stem cell-like B cells correlated with a poor prognosis, potentially due to immune evasion mediated by low expression of major histocompatibility complex molecules. Furthermore, we identified key transcription factor regulatory networks regulated by HMGB3, SAP30, and E2F8, which likely played crucial roles in the functional characterization of the cancer stem cell-like B cell subpopulation. The existence of cancer stem cell-like B cells in DLBCL was validated through immunofluorescent staining. Finally, cell communication between B cells and tumor-infiltrating T cell subgroups provided further insights into the functional characterization of the cancer stem cell-like B cell subpopulation. Our research provides a systematic description of a specific cancer stem cell-like B cell subpopulation associated with a poor prognosis in DLBCL. This study enhances our understanding of CSCs and identifies potential therapeutic targets for refractory or recurrent DLBCL patients.

The Characterization and Prognostic Value of Tumor Immune Microenvironment in Diffuse Large B-Cell Lymphoma

Introduction: Diffuse large B-cell lymphoma (DLBCL) is featured by high heterogeneity, especially in clinical outcome. Tumor microenvironment (TME) represents a complex ecosystem around tumor cells, which has been found to be associated with the prognosis of DLBCL patients. However, the overall profile of TME immune components, perception of its correlation with tumor development and molecular mechanism are still insufficient in DLBCL. Here, we aimed to investigate novel prognostic scoring system and biomarkers based on TME immune components, and explore their underlying molecular mechanism in the development of DLBCL. Methods: Microarray transcriptomic data and corresponding clinical information of DLBCL patients (n=946) from GSE23501, GSE53786, GSE10846, GSE136971, GSE57611 and GSE32918 in GEO database were analyzed. The immune composition was calculated by CIBERSORT. Immunohistochemistry (IHC) was used to assess the expression level of CD2 in DLBCL tissues. Seurat in R was employed for conducting single-cell analysis. The study was performed with the approval of the Medical Ethical Committee of Shandong Provincial Hospital, and all samples were collected with informed consents. Results: To assess the immune cell composition of TME in DLBCL patients, we conducted a comprehensive analysis of the relative proportions of 22 distinct immune cell types within DLBCL TME. Subsequently, the prognostic role of TME immune components in DLBCL patients was probed, and a novel TME immune score based on the proportion of 22 immune cells was established. Furthermore, to evaluate the association between TME immune score and clinical prognosis in DLBCL patients, we performed K-M analysis and 3,5,10-year ROC analysis, which revealed the high prognostic efficacy of TME immune score. Higher TME immune scores were demonstrated to be significantly associated with worse prognosis, which was subsequently validated in an external cohort containing 230 DLBCL patients. Survival data of quartile subgroups also unveiled the prognostic value of TME immune score in DLBCL patients ( Fig. 1A). We further explored the correlation between TME immune score and clinical pathological features in DLBCL patients. Higher TME immune scores were observed to be correlated with more advanced Ann Arbor stage, non-germinal center B-cell-like subtype, lower expression levels of immune checkpoint molecules (CTLA-4, PD-1, PD-L2), decreased ESTIMATE stromal and immune scores, as well as higher tumor purity, indicating that the TME immune score may enable the prediction of treatment response to immune checkpoint inhibitors. The potential molecular mechanism of TME modulation in DLBCL development was further explored. Results of GO and KEGG enrichment illuminated that differential expression genes (DEGs) in two groups were significantly enriched in the anti-tumor immunity related processes and pathways, especially T-cell receptor activation. Subsequently, 6 hub genes (CCL5, CD2, CD3E, MMP9, CCR5, GATA3) in protein-protein interaction network constructed by DEGs were identified, whose expression levels were found to be associated with prognosis in DLBCL patients. Moreover, IHC was used to investigate the relevance of CD2 protein expression with prognosis in DLBCL patients. The expression of CD2 protein was found to be associated with poor prognosis in DLBCL patients ( Fig. 1A). To further investigate the regulatory function of CD2 in the immune microenvironment of DLBCL, we conducted single-cell analysis based on three DLBCL patients, and revealed that CD2 was prominently expressed in T cell subpopulation and was correlated with different differentiation trajectory of T cells in DLBCL. Subsequent differential gene analysis revealed that DEGs between state 1 and state 2, 3 were significantly enriched in KEGG pathways including antigen presentation and Th cell differentiation ( Fig. 1B), suggesting the role of CD2 in T cell activation and differentiation. Conclusions: Taken together, we established a novel TME immune score which could serve as a prognostic indicator in DLBCL patients. More importantly, we identified CD2 as a prognostic biomarker in DLBCL patients and unveiled its association with different T-cell activation states. Our study might provide a novel prognostic stratification strategy and promising biomarkers, which could facilitate the individualized management in DLBCL patients.

NCAPD3 Prompts Diffuse Large B-Cell Lymphoma Progression through Modulating SIRT1 Expression in H3K9 Monomethylation-Dependent Manner

Chromosomal instability, including number and structure abnormality, is the critical molecular basis in lymphoid oncogenesis. Condensin, a family of structural maintenance of chromosome complexes, has been shown to regulate chromosome compaction and segregation during mitosis. NCAPD3, a HEAT-repeat subunit of condensin II, plays a dominant role in condensin-mediated chromosome dynamics, whose abnormalities are related to tumorigenesis and developmental disorders but remain unexplored in lymphoma. This study aims to unravel the expression, molecular function and mechanism of NCAPD3 in diffuse large B-cell lymphoma (DLBCL). We first elucidated the expression of NCAPD3 in DLBCL. Lymph node tissues from 70 DLBCL patients and 35 reactive hyperplasia cases were collected with informed consent approved by the Medical Ethical Committee of Shandong Provincial Hospital. Higher NCAPD3 expression was identified in DLBCL tissues and correlated with advanced Ann Arbor stage and higher IPI score. The survival analysis presented patients with higher NCAPD3 suffered shorter survival (P=0.045). Meanwhile, upregulation of NCAPD3 was validated in DLBCL cells compared with normal CD19+ B-cell. We further explored the biological functions of NCAPD3 in DLBCL and constructed NCAPD3-knockdown, knockout and overexpression models. Deficiency of NCAPD3 impeded cell proliferation, induced apoptosis and increased the sensitivity to doxorubicin and ibrutinib. Instead, NCAPD3 overexpression facilitated cell proliferation and therapeutic resistance. In vivo experiments further indicated that xenograft DLBCL mice with deficient NCAPD3 presented delayed tumor growth. These suggested NCAPD3 promoted DLBCL progression. Strikingly, we found knocking down NCAPD3 disturbed the mitosis, triggering the formation of aneuploidy, due to its function in chromatin structure and dynamics. Hence, we further portrayed the transformation of chromosome architecture under different NCAPD3 expression. Chromosome spreads exhibited chromosomes became slim and elongated upon NCAPD3 overexpression, instead, NCAPD3 knockout triggered short and highly-curled transformation with the global upregulation of H3K4me3, an indication of transcriptional activation and chromatin decompaction (Figure 1). This suggested NCAPD3 could modulate transcriptional activity. Therewith, we investigated how NCAPD3 regulated gene transcription. We examined the interacting proteins of NCAPD3 by mass spectrometry and Clusters of Orthologous Groups analysis revealed they were mainly enriched in RNA processing and modification, chromatin dynamics and cell cycle control. Of them, transcription factor, GTF2I, may be responsible for NCAPD3-mediated transcription regulation. Coimmunoprecipitation (co-IP) verified their interaction and chromatin immunoprecipitation (ChIP) presented they were both located on the promoter of target gene, SIRT1. We further examined SIRT1 expression after regulating NCAPD3 expression, showing a significantly positive correlation. This suggested NCAPD3 could support SIRT1 transcription via being anchored by GTF2I on the promoter of SIRT1. We further elucidated the potential mechanism how NCAPD3 regulated SIRT1 expression. Previous study found that NCAPD3 could interact with histone methylation markers in mammalian genome, thus, we explored whether NCAPD3 could modulate the SIRT1 expression via recognizing the histone methylation marker on SIRT1 promoter. Co-IP assay identified the interaction between NCAPD3 and monomethylation of lysine residue K9 of histone H3 (H3K9me1), an active promoter tag, in DLBCL and ChIP assay verified the location of H3k9me1 on SIRT1 promoter. When NCAPD3 downregulated, H3K9me1 on SIRT promoter diminished, ruining the transcription of SIRT. To clarify whether the oncogenic effects of NCAPD3 was mediated by SIRT1, we conducted functional reversion assays, showing regulating SIRT1 partially reversed the effects of NCAPD3. The above suggested NCAPD3 prompted DLBCL progression through modulating SIRT expression in H3k9me1-mediated manner. In conclusion, this study unraveled that dysregulation of NCAPD3 could disturb chromosome compaction and segregation, induce genome instability and alter the transcription of SIRT1 via modulating H3k9 monomethylation, which provided novel insights into NCAPD3-based targeting strategy for DLBCL.

Long non-coding RNA SNHG17 may function as a competitive endogenous RNA in diffuse large B-cell lymphoma progression by sponging miR-34a-5p.

We investigated the functional mechanism of long non-coding small nucleolar host gene 17 (SNHG17) in diffuse large B-cell lymphoma (DLBCL). lncRNAs related to the prognosis of patients with DLBCL were screened to analyze long non-coding small nucleolar host gene 17 (SNHG17) expression in DLBCL and normal tissues, and a nomogram established for predicting DLBCL prognosis. SNHG17 expression in B-cell lymphoma cells was detected using qPCR. The effects of SNHG17 with/without doxorubicin on the proliferation and apoptosis of DoHH2 and Daudi were detected. The effects of combined SNHG17 and doxorubicin were analyzed. The regulatory function of SNHG17 in DLBCL was investigated using a mouse tumor xenotransplantation model. RNA sequencing was used to analyze the signaling pathways involved in SNHG17 knockdown in B-cell lymphoma cell lines. The target relationships among SNHG17, microRNA, and downstream mRNA biomolecules were detected. A higher SNHG17 level predicted a lower survival rate. SNHG17 was highly expressed in DLBCL patient tissues and cell lines. We established a prognostic model containing SNHG17 expression, which could effectively predict the overall survival rate of DLBCL patients. SNHG17 knockdown inhibited the proliferation and induced the apoptosis of B-cell lymphoma cells, and the combination of SNHG17 and doxorubicin had a synergistic effect. SNHG17, miR-34a-5p, and ZESTE gene enhancer homolog 2 (EZH2) had common hypothetical binding sites, and the luciferase reporter assay verified that miR-34a-5p was the direct target of SNHG17, and EZH2 was the direct target of miR-34a-5p. The carcinogenic function of SNHG17 in the proliferation and apoptosis of DLBCL cells was partially reversed by a miR-34a-5p inhibitor. SNHG17 increases EZH2 levels by inhibiting miR-34a-5p. Our findings indicate SNHG17 as critical for promoting DLBCL progression by regulating the EZH2 signaling pathway and sponging miR-34a-5p. These findings provide a new prognostic marker and therapeutic target for the prognosis and treatment of DLBCL.

Blockade of PD-1 and LAG-3 expression on CD8+ T cells promotes the tumoricidal effects of CD8+ T cells.

The diffuse large B-cell lymphoma (DLBCL) has the highest incidence of all lymphomas worldwide. To investigate the functions of lymphocyte activation gene 3 (LAG-3) and programmed cell death 1 (PD-1) in tissues and peripheral blood of patients with DLBCL, the expression of LAG-3 and PD-1 genes in DLBCL-TCGA were analyzed. LAG-3 and PD-1 mRNA levels in DLBCL were analyzed using data from The Cancer Genome Atlas (TCGA) database. Utilize the Genotype-Tissue Expression (GTEx) database for assessing the variance in the expression of LAG-3, PD-1, and other associated factors between the tissues of DLBCL patients and healthy individuals. Immunohistochemistry was applied to detect the expression of LAG-3 and PD-1 levels in 137 cases of DLBCL tissues and 20 cases of reactive lymphoid hyperplasia. The prognostic value of LAG-3 and PD-1 were assessed using the Kaplan-Meier curve. The Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) and ssGSEA algorithm were used to explore the immune microenvironment of DLBCL. Additionally, the expression and co-expression of LAG-3 and PD-1 were detected on CD4 and CD8 T cells in peripheral blood samples from 100 cases of DLBCL tissues and 30 cases of healthy individuals using flow cytometry. According to TCGA database, LAG-3 and PD-1 gene expression levels were significantly up-regulated in DLBCL tissues. LAG-3 and PD-1 levels were also strongly positively correlated with those of most infiltrating immune cells. Overall survival of patients with high LAG-3 and PD-1 co-expression was significantly shorter than that of patients with low co-expression. In DLBCL patients, LAG-3 and PD-1 were highly expressed in peripheral blood CD8+ T cells. In addition, LAG-3 was highly expressed in CD4+ T cells, while the expression of PD-1 in CD4+ T cells of DLBCL patients showed no significant difference compared to healthy individuals. Additionally, CD8+ T cells and SU-DHL6/OCI-LY3 from patients with DLBCL were co-cultured in vitro; after addition of LAG-3 and/or PD-1 inhibitors alone, an increased perforin and granzyme B secretion levels by CD8+ T cells were detected, as well as an increase in the overall proportion of tumor cells undergoing apoptosis. High LAG-3 and PD-1 levels significantly inhibit CD8+ T cell function, resulting in weakened ability to kill tumor cells. Combined LAG-3 and PD-1 blockade can restore CD8+ T cell function and provides a potential avenue for development of personalized cellular immunotherapy for DLBCL.

PAQR3 facilitates the ferroptosis of diffuse large B-cell lymphoma via the regulation of LDLR-mediated PI3K/AKT pathway.

Progesterone and adiponectin receptor 3 (PAQR3) has been found to regulate tumor progression by mediating cell ferroptosis. However, whether PAQR3 mediates ferroptosis in diffuse large B-cell lymphoma (DLBCL) needs further investigation. The mRNA and protein levels of PAQR3 and low-density lipoprotein receptor (LDLR) were assessed by qRT-PCR and WB assays. Cell proliferation was detected by MTT assay and EdU assay. Shrunken mitochondria was counted under transmission electron microscope. Cell ferroptosis was evaluated by measuring the levels of malondialdehyde, reactive oxygen species, glutathione, Fe2+ , and the protein expression of ferroptosis-related markers. PAQR3 and LDLR interaction was confirmed by RIP assay and pull-down assay. Our study showed that PAQR3 was underexpressed, while LDLR was overexpressed in DLBCL tissues and cells. Functionally, PAQR3 overexpression or LDLR knockdown restrained DLBCL cell proliferation and enhanced ferroptosis. Mechanistically, PAQR3 reduced LDLR expression by inhibiting its mRNA stability. Meanwhile, LDLR overexpression reversed PAQR3-mediated the promoting on DLBCL cell ferroptosis, and LY294002 (PI3K/AKT inhibitor) eliminated the inhibiting effects of LDLR overexpression on DLBCL cell ferroptosis. Additionally, excessive PAQR3 reduced DLBCL tumor growth by enhancing tumor cell ferroptosis through LDLR-mediated PI3K/AKT pathway. In conclusion, our data suggested that PAQR3 restrained DLBCL progression by aggravating ferroptosis, which was achieved by inhibiting LDLR expression to repress PI3K/AKT pathway.

E3 ubiquitin ligase neural precursor cell-expressed developmentally downregulated gene 4 motivates FOXA1 ubiquitination and restrains proliferation of diffuse large B-cell lymphoma cells via the Wnt/β-Catenin pathway.

Neural precursor cell-expressed developmentally downregulated gene 4 (NEDD4) is an E3 ubiquitin ligase that recognizes substrates via protein-protein interactions and takes part in tumor development. This study aims to clarify NEDD4's functions in diffuse large B-cell lymphoma (DLBCL) and its downstream mechanisms. Collection of 53 DLBCL tissues and adjacent normal lymphoid tissues, and detection of NEDD4 and Forkhead box protein A1 (FOXA1) in the tissues were conducted. The selection of DLBCL cells was for FARAGE, and test of cells' advancement was after transfection. Analysis of NEDD4 and FOXA1's link, and test of Wnt/β-catenin pathway were implemented. In vivo tumor xenograft experiments were put into effect. Detection of the pathological conditions of tumor tissues and the positive Ki67 in the family was implemented. It came out NEDD4 was reduced in DLBCL tissues and cell lines, and FOXA1 was elevated; Enhancing NEDD4 or repressing FOXA1 refrained DLBCL cells' advancement; NEDD4 could combine with FOXA1 and trigger its ubiquitination and degradation; NEDD4 inactivates the Wnt/β-catenin pathway by motivating FOXA1 ubiquitination; NEDD4 enhancement refrained DLBCL growth in vivo. In conclusion, the E3 ubiquitin ligase NEDD4 accelerates FOXA1 ubiquitination but refrains DLBCL cell proliferation via the Wnt/β-Catenin pathway.

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.

SPATIALLY‐RESOLVED TRANSCRIPTOMICS DEFINE CLINICALLY RELEVANT SUBSETS OF MACROPHAGES IN DIFFUSE LARGE B‐CELL LYMPHOMA

Introduction: Tumor-associated macrophages (TAMs) are abundant immune cells in the microenvironment of diffuse large B-cell lymphoma (DLBCL) and are implicated in tumor progression and therapy resistance. Conventional immunohistochemistry-based studies have relied on the oversimplified M1/M2 classification of TAMs which does not fully capture the functional diversity of macrophage biology, thus potentially contributing to their inconsistent prognostic significance in DLBCL. Spatial whole-transcriptomic analysis allows in-depth investigation of specific cell types in different spatial regions within normal and malignant lymphoid tissues, enabling detailed macrophage phenotyping. Here, we employed spatial whole-transcriptomic analysis in the characterization of CD68+ cells of DLBCL and reactive lymphoid tissues (RLTs) to identify novel macrophage subsets with biological and clinical significance. Methods: Digital spatial profiling with whole-transcriptomic analysis of CD68+ cells was performed in 47 DLBCL and 17 RLTs, to define macrophage signatures (termed “MacroSigs”) of distinct lymphoid spatial niches and clinical scenarios. Eight independent DLBCL datasets (4594 patients) with complete transcriptomic and survival information were used for validation of these spatial-derived MacroSigs. Results: Digital spatial profiling revealed previously unrecognized transcriptomic differences between macrophages populating distinct spatial compartments in RLTs (light zone (LZ)/dark zone (DZ), germinal center (GC)/interfollicular (IF) regions), and in between disease states (RLTs and DLBCL with or without relapsed disease). This transcriptomic diversity of macrophages was categorized into eight MacroSigs. Spatial-derived MacroSigs associate with specific cell-of-origin (COO) subtypes of DLBCL, of particular interest being the IF-MacroSig enriched in the unclassified COO (p < 0.005, 6/8 datasets). MacroSigs of relapsed-DLBCL and DZ were prognostic for shorter overall survival in multiple datasets (p < 0.05 in 5/8 datasets; p < 0.05 in 8/8 datasets, respectively). Projection onto a macrophage single-cell RNA-sequencing atlas reveals the Non-relapse-DLBCL MacroSig to depict HES1/FOLR2-like macrophages, while relapse-DLBCL-MacroSig represents IL1B-like monocytes, with unique therapeutic vulnerabilities for each. The research was funded by: Work in ADJ’s laboratory is funded by a core grant from the Cancer Science Institute of Singapore, National University of Singapore through the National Research Foundation Singapore and the Singapore Ministry of Education under its Research Centres of Excellence initiative. CT was supported by the Italian Foundation for Cancer Research (AIRC) Investigator Grant IG ID.22145; 5 × 1000 Grant ID.22759. Keywords: aggressive B-cell non-Hodgkin lymphoma, diagnostic and prognostic biomarkers No conflicts of interests pertinent to the abstract.

NAT10 REGULATES THE AMPK SIGNALING PATHWAY TO PROMOTE DLBCL PROGRESSION VIA AC4C ACETYLATION OF SLC30A9 MRNA

Introduction: N-acetyltransferase 10 (NAT10) is the only confirmed regulator to mediate the N4-acetylcytidine (ac4C) modification of mRNA and is crucial for mRNA stability and translation efficiency. However, its role in diffuse large B-cell lymphoma (DLBCL) development and prognosis has not yet been explored. Herein, we explored the functional significance and regulatory mechanism of NAT10 mediated mRNA ac4C modification in DLBCL, which is expected to propose novel therapeutic strategy. Methods: The expression levels of NAT10 were evaluated in DLBCL cell lines and lymph node biopsies tissues, and its prognostic value in patients was further analyzed. Stable NAT10 knockout DLBCL cell lines were constructed using CRISPR/Cas9 mediated genomic deletion. The biological functions of NAT10 in DLBCL cells were analyzed in vitro by cell proliferation and cell cycle assays. Xenograft models were used to analyze the effect of NAT10 on the tumorigenesis of DLBCL cells in vivo. RNA sequencing, acetylated RNA immunoprecipitation sequencing (acRIP-seq), LC-MS/MS, RIP and RNA stability analyses were performed to explore the mechanism by which NAT10 functions in DLBCL progression. Results: NAT10 was upregulated in DLBCL cell lines and tissues. NAT10 high expression was associated with poor patient prognosis. Knockout of NAT10 impaired cellular phase progression and proliferation of DLBCL. Further analysis revealed that NAT10-mediated ac4C acetylation of SLC30A9 transcript and subsequently stabilized SLC30A9 mRNA, leading to activation of AMPK signaling and thereby facilitating DLBCL progression (Figure 1). Keywords: aggressive B-cell non-Hodgkin lymphoma, diagnostic and prognostic biomarkers, genomics, epigenomics, and other -omics No conflicts of interests pertinent to the abstract.

Expressions and Clinical Significance of Notch1 and Hes1 in Diffuse Large B-Cell Lymphoma

To investigate the expressions of Notch1 and Hes1 in diffuse large B-cell lymphoma (DLBCL), and their correlations with clinical features. Immunohistochemistry (IHC) was performed on DLBCL samples (54 cases) and lymphadenitis tissues (20 cases) to evaluate the expressions of Notch1 and Hes1, and analyze their correlations with clinical characteristics of patients. Based on Oncomine database, the expressions of Notch1 and Hes1 mRNA and DNA were also explored. IHC result showed that the positive expression rates of Notch1 and Hes1 in DLBCL patients were significantly higher than those in the control group (P <0.05). In DLBCL patients, the expression of Notch1 was closely associated with B symptoms, Ann Arbor stage, lymphocyte count and the level of lactate dehydrogenase (P <0.05), while the expression level of Hes1 was significantly higher in patients with B symptoms (P <0.05). Notch+/Hes1+ expression was found in 21 DLBCL tissues (38.9%), and there was a correlation between Notch1 and Hes1 expression (r =0.296, P <0.05). Bioinformatics analysis (Oncomine database) showed that the mRNA expressions of Notch1 and Hes1 in the Brune dataset were significantly higher than those in the control tissues (P <0.05). The expressions of Notch1 and Hes1 in DLBCL are significantly higher than those in lymphadenitis, and correlated with B symptoms and Ann Arbor stage, suggesting that Notch1 and Hes1 play important roles in the occurrence and development of DLBCL.

Diffuse large B-cell lymphoma microenvironment displays a predominant macrophage infiltrate marked by a strong inflammatory signature.

Inflammasomes are cytosolic signaling hubs that promote the inflammatory response (i.e. an immune reaction to counteract threats in physiological conditions). Their potential role in lymphomagenesis remains to be elucidated. Depending on the context, innate immune cells, such as macrophages, may induce inflammation that contributes to the anti-tumor function; however, if uncontrolled, inflammation can promote cancer development. Here, we exploited bioinformatic tools, TCGA data, and tumor tissue samples from patients with diffuse large B-cell lymphoma (DLBCL), one of the most frequent non-Hodgkin lymphomas of B-cell origin, to investigate the distribution of the different immune cell subpopulations in DLBCL samples in order to characterize the immune landscape of their microenvironment. We found a clear prominence of macrophages in the DLBCL microenvironment. Particularly, the proportions of resting M0 and pro-inflammatory M1 macrophages were higher in DLBCL than spleen samples (controls). As each inflammasome has unique sensor activation and platform assembly mechanisms, we examined the expression of a large panel of inflammasome actors. We found that inflammasome components, cytokines and Toll-like receptors were upregulated in DLBCL samples, particularly in M0 and M1 macrophages, compared with controls. Moreover, their expression level was positively correlated with that of CD68 (a pan-macrophage marker). We confirmed the positive correlation between CD68 and IRF8 expression at the protein level in DLBCL tissue samples, where we observed increased infiltration of CD68- and IRF8-positive cells compared with normal lymph nodes. Altogether, our results highlight the inflammatory status of the DLBCL microenvironment orchestrated by macrophages. More work is needed to understand the complexity and potential therapeutic implications of inflammasomes in DLBCL.

ALL-tRNAseq enables robust tRNA profiling in tissue samples.

Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. However, it remains unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research.