The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma

Metabolic pathway-based subtyping reveals distinct microenvironmental states associated with diffuse large B-cell lymphoma outcomes

Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogeneous disease that requires personalized clinical treatment. Assigning patients to different risk categories and cytogenetic abnormality and genetic mutation groups has been widely applied for prognostic stratification of DLBCL. Increasing evidence has demonstrated that dysregulated metabolic processes contribute to the initiation and progression of DLBCL. Metabolic competition within the tumor microenvironment is also known to influence immune cell metabolism. However, metabolism- and immune-related stratification has not been established. Here, 1660 genes involved in 84 metabolic pathways were selected and tested to establish metabolic clusters (MECs) of DLBCL. MECs established based on independent lymphoma datasets distinguished different survival outcomes. The CIBERSORT algorithm and EcoTyper were applied to quantify the relative abundance of immune cell types and identify variation in cell states for 13 lineages comprising the tumor micro environment among different MECs, respectively. Functional characterization showed that MECs were an indicator of the immune microenvironment and correlated with distinctive mutational characteristics and oncogenic signaling pathways. The novel immune-related MECs exhibited promising clinical prognostic value and potential for informing DLBCL treatment decisions.

Comprehensive analysis of ATP6V1s family member, ATP6V1C2, with prognostic and drug development values in colorectal cancer

Member of the V-type ATPase family have attracted vast attention in tumor progression. Nevertheless, the specific member of V-ATPase, ATP6V1C2, its regulatory function in colorectal cancer (CRC) progression was poorly understood. In this study, comprehensive analyses demonstrated the role of ATP6V1C2 in CRC progression and drug screening based on ATP6V1C2 was carried out. As a result, among the ATPV1s family, ATP6V1C2 was significantly highly expressed in CRC. Immuno-infiltration analysis suggests that, the interaction between CRC cells and immune cells resulting in reduced immune and estimate scores. GSEA analysis found that, ATP6V1C2 negatively correlates with immune cells，especially CD8T cells. Next, Ecotyper database queries indicated that ATP6V1C2 was negatively correlates with characteristic gene expression in CD8T cells. Then, COX regression analysis and survival curves made it clear that ATP6V1C2 is positively correlates with clinicopathological progression leading to poor CRC prognosis. CellMiner explore told us LOR-253 and Sonidegib may be effective in CRC cancer treatment. Molecular Docking between ATP6V1C2 and 9 first-line and 9 natural drugs showed that ATP6V1C2 was recognized by the best geometrical and energetic matching pattern of 2 First-line and 4 natural drugs. RT-PCR and immunoblotting confirmed that ATP6V1C2 was significantly overexpressed in CRC. Four natural drugs screened by molecular docking were effective in cell proliferation inhibition by CCK8 test. In summary, ATP6V1C2 may be a new therapeutic target for CRC. The illustration is shown in Figure 9.

HIV and prior exposure to antiretroviral therapy alter tumour composition and tumour: T-cell associations in diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of lymphoma worldwide, accounting for up to 40% of new non-Hodgkin Lymphoma (NHL) globally. People living with HIV are up to 17 times more likely to develop NHL, and as such, DLBCL is the leading cause of cancer death in this high-risk population. While histologically indistinguishable, HIV-associated (HIV+) and HIV-negative (HIV-) DLBCL are molecularly distinct, and biological differences may have implications for the development of future therapeutic interventions. Further, the impact of immunologic differences in people with HIV, including preceding ART, remains largely unknown. Here, we investigate the impact of HIV infection and ART exposure on the clinical features of DLBCL and T-cell immune response by performing imaging mass cytometry on our unique patient cohort in Malawi. In this cohort, HIV infection is positively prognostic, and HIV+/ART-naïve patients have the best outcomes. No established biomarkers other than Ki67 are associated with HIV or ART status, and the only tumour-intrinsic biomarkers that remain prognostic are MYC and MYC/BCL2 protein co-expression. Finally, TCR clonality is associated with distinct tumour-T cell interactions by HIV/ART status, indicating differential anti-tumour immune responses. We demonstrate previously undescribed HIV and ART-related differences in the DLBCL tumour microenvironment.

From immune equilibrium to tumor ecodynamics

Objectives

There is no theory to quantitatively describe the complex tumor ecosystem. At the same time, cancer immunotherapy is considered a revolution in oncology, but the methods used to describe tumors and the criteria used to evaluate efficacy are not keeping pace. The purpose of this study is to establish a new theory for quantitatively describing the tumor ecosystem, innovating the methods of tumor characterization, and establishing new efficacy evaluation criteria for cancer immunotherapy.

Methods

Based on the mathematization of immune equilibrium theory and the establishment of immunodynamics in a previous study, the method of reverse immunodynamics was used, namely, the immune braking force was regarded as the tumor ecological force and the immune force was regarded as the tumor ecological braking force, and the concept of momentum in physics was applied to the tumor ecosystem to establish a series of tumor ecodynamic equations. These equations were used to solve the fundamental and applied problems of the complex tumor ecosystem.

Results

A series of tumor ecodynamic equations were established. The tumor ecological momentum equations and their component factors could be used to distinguish disease progression, pseudoprogression, and hyperprogression in cancer immunotherapy. On this basis, the adjusted tumor momentum equations were established to achieve the equivalence of tumor activity (including immunosuppressive activity and metabolic activity) and tumor volume, which could be used to calculate individual disease remission rate and establish new efficacy evaluation criteria (ieRECIST) for immunotherapy of solid tumor based on tumor ecodynamics. At the same time, the concept of moving cube-to-force square ratio and its expression were proposed to calculate the area under the curve of tumor ecological braking force of blood required to achieve an individual disease remission rate when the adjusted tumor ecological momentum was known.

Conclusions

A new theory termed tumor ecodynamics emphasizing both tumor activity and tumor volume is established to solve a series of basic and applied problems in the complex tumor ecosystem. It can be predicted that the future will be the era of cancer immune ecotherapy that targets the entire tumor ecosystem.

High-multiplex single-cell imaging analysis reveals tumor immune contexture associated with clinical outcomes after CAR T cell therapy

Chimeric antigen receptor (CAR) T cell therapy has made great progress in treating lymphoma, yet patient outcomes still vary greatly. The lymphoma microenvironment may be an important factor in the efficacy of CAR T therapy. In this study, we designed a highly multiplexed imaging mass cytometry (IMC) panel to simultaneously quantify 31 biomarkers from 13 patients with relapsed/refractory diffuse large B cell lymphoma (DLBCL) who received CAR19/22 T cell therapy. A total of 20 sections were sampled before CAR T cell infusion or after infusion when relapse occurred. A total of 35 cell clusters were identified, annotated, and subsequently redefined into 10 metaclusters. The CD4+ T cell fraction was positively associated with remission duration. Significantly higher Ki67, CD57, and TIM3 levels and lower CD69 levels in T cells, especially the CD8+/CD4+ Tem and Te cell subsets, were seen in patients with poor outcomes. Cellular neighborhood containing more immune cells was associated with longer remission. Fibroblasts and vascular endothelial cells resided much closer to tumor cells in patients with poor response and short remission after CAR T therapy. Our work comprehensively and systematically dissects the relationship between cell composition, state, and spatial arrangement in the DLBCL microenvironment and the outcomes of CAR T cell therapy, which is beneficial to predict CAR T therapy efficacy.

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.

Genetic mechanisms underlying tumor microenvironment composition and function in diffuse large B-cell lymphoma

ABSTRACT

Cells in the tumor microenvironment (TME) of diffuse large B-cell lymphoma (DLBCL) show enormous diversity and plasticity, with functions that can range from tumor inhibitory to tumor supportive. The patient's age, immune status, and DLBCL treatments are factors that contribute to the shaping of this TME, but evidence suggests that genetic factors, arising principally in lymphoma cells themselves, are among the most important. Here, we review the current understanding of the role of these genetic drivers of DLBCL in establishing and modulating the lymphoma microenvironment. A better comprehension of the relationship between lymphoma genetic factors and TME biology should lead to better therapeutic interventions, especially immunotherapies.

Spatially Resolved Tumor Microenvironment Predicts Treatment Outcomes in Relapsed/Refractory Hodgkin Lymphoma

PURPOSE

About a third of patients with relapsed or refractory classic Hodgkin lymphoma (r/r CHL) succumb to their disease after high-dose chemotherapy followed by autologous stem-cell transplantation (HDC/ASCT). Here, we aimed to describe spatially resolved tumor microenvironment (TME) ecosystems to establish novel biomarkers associated with treatment failure in r/r CHL.

PATIENTS AND METHODS

We performed imaging mass cytometry (IMC) on 71 paired primary diagnostic and relapse biopsies using a marker panel specific to CHL biology. For each cell type in the TME, we calculated a spatial score measuring the distance of nearest neighbor cells to the malignant Hodgkin Reed Sternberg cells within the close interaction range. Spatial scores were used as features in prognostic model development for post-ASCT outcomes.

RESULTS

Highly multiplexed IMC data revealed shared TME patterns in paired diagnostic and early r/r CHL samples, whereas TME patterns were more divergent in pairs of diagnostic and late relapse samples. Integrated analysis of IMC and single-cell RNA sequencing data identified unique architecture defined by CXCR5+ Hodgkin and Reed Sternberg (HRS) cells and their strong spatial relationship with CXCL13+ macrophages in the TME. We developed a prognostic assay (RHL4S) using four spatially resolved parameters, CXCR5+ HRS cells, PD1+CD4+ T cells, CD68+ tumor-associated macrophages, and CXCR5+ B cells, which effectively separated patients into high-risk versus low-risk groups with significantly different post-ASCT outcomes. The RHL4S assay was validated in an independent r/r CHL cohort using a multicolor immunofluorescence assay.

CONCLUSION

We identified the interaction of CXCR5+ HRS cells with ligand-expressing CXCL13+ macrophages as a prominent crosstalk axis in relapsed CHL. Harnessing this TME biology, we developed a novel prognostic model applicable to r/r CHL biopsies, RHL4S, opening new avenues for spatial biomarker development.

Dual CAR-T Cells Targeting CD19 and CD37 Are Effective in Target Antigen Loss B-cell Tumor Models

Chimeric antigen receptor T (CAR-T) cells targeting multiple antigens (Ag), may reduce the risk of immune escape following the loss of the target Ag and further increase the efficacy of treatment. We developed dual-targeting CAR-T cells that target CD19 and CD37 Ags and evaluated their antitumor effects. CD19/CD37 dual CAR-T cells were generated using cotransduction and simultaneous gene transfer of two types of lentiviral vectors transferring CD19CAR or CD37CAR genes, including the intracellular domains of CD28 and CD3ζ signaling domains. These dual CAR-T cells contained three fractions: CD19/CD37 bispecific CAR-T cells, single CD19CAR-T cells, and single CD37CAR-T cells. In the functional evaluation of CAR-T cells in vitro, CD19/CD37 dual CAR-T cells showed adequate proliferation and cytokine production in response to CD19 and CD37 antigen stimulation alone or in combination. Evaluation of intracellular signaling revealed that dual CAR-T cell-mediated signals were comparable with single CAR-T cells in response to CD19- and CD37-positive B-cell tumors. Although the cytotoxicity of CD19/CD37 dual CAR-T cells in both CD19- and CD37-positive B-cell tumors was similar to that of single CD19 and CD37CAR-T cells, against CD19 and CD37 Ag-heterogeneous tumor, dual CAR-T cells demonstrated significantly superior tumor lysis compared with single CAR-T cells. Furthermore, CD19/CD37 dual CAR-T cells effectively suppressed Ag-heterogeneous Raji cells in a xenograft mouse model. Collectively, these results suggest that CD19/CD37 dual CAR-T cells may be effective target-Ag-loss B-cell tumor models in vitro and in vivo, which represents a promising treatment for patients with relapsed/refractory B-cell malignancies.

NCAPD3 promotes diffuse large B-cell lymphoma progression through modulating SIRT1 expression in an H3K9 monomethylation-dependent manner

INTRODUCTION

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 but remains unexplored in lymphoma.

OBJECTIVES

The study aims to unravel the molecular function and mechanism of NCAPD3 in diffuse large B-cell lymphoma (DLBCL).

METHODS

The expression and clinical significance of NCAPD3 were assessed in public database and clinical specimens. Chromosome spreads, co-immunoprecipitation (co-IP), mass spectrometry (MS), and chromatin immunoprecipitation (ChIP) assays were conducted to untangle the role and mechanism of NCAPD3 in DLBCL.

RESULTS

NCAPD3 was highly expressed in DLBCL, correlated with poor prognosis. NCAPD3 deficiency impeded cell proliferation, induced apoptosis and increased the chemosensitivity. Instead, NCAPD3 overexpression facilitated cell proliferation. In vivo experiments further indicated targeting NCAPD3 suppressed tumor growth. Noteworthily, NCAPD3 deficiency disturbed the mitosis, triggering the formation of aneuploids. To reveal the function of NCAPD3 in DLBCL, chromosome spreads were conducted, presenting that chromosomes became compact upon NCAPD3 overexpression, instead, loose, twisted and lacking axial rigidity upon NCAPD3 absence. Meanwhile, the classical transcription-activated marker, H3K4 trimethylation, was found globally upregulated after NCAPD3 knockout, suggesting that NCAPD3 might participate in chromatin remodeling and transcription regulation. MS revealed NCAPD3 could interact with transcription factor, TFII I. Further co-IP and ChIP assays verified NCAPD3 could be anchored at the promoter of SIRT1 by TFII I and then supported the transcription of SIRT1 via recognizing H3K9 monomethylation (H3K9me1) on SIRT1 promoter. Function reversion assay verified the oncogenic role of NCAPD3 in DLBCL was partially mediated by SIRT1.

CONCLUSION

This study demonstrated that dysregulation of NCAPD3 could disturb chromosome compaction and segregation and regulate the transcription activity of SIRT1 in an H3K9me1-dependent manner, which provided novel insights into targeted strategy for DLBCL.

Challenges and perspectives in computational deconvolution of genomics data

Deciphering cell-type heterogeneity is crucial for systematically understanding tissue homeostasis and its dysregulation in diseases. Computational deconvolution is an efficient approach for estimating cell-type abundances from a variety of omics data. Despite substantial methodological progress in computational deconvolution in recent years, challenges are still outstanding. Here we enlist four important challenges related to computational deconvolution: the quality of the reference data, generation of ground truth data, limitations of computational methodologies, and benchmarking design and implementation. Finally, we make recommendations on reference data generation, new directions of computational methodologies, and strategies to promote rigorous benchmarking.

Genetic and transcriptomic analyses of diffuse large B-cell lymphoma patients with poor outcomes within two years of diagnosis

Despite the improvements in clinical outcomes for DLBCL, a significant proportion of patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R-CHOP treatment. To further elucidate the underlying mechanism of R/R disease and to develop methods for identifying patients at risk of early disease progression, we integrated clinical, genetic and transcriptomic data derived from 2805 R-CHOP-treated patients from seven independent cohorts. Among these, 887 patients exhibited R/R disease within two years (poor outcome), and 1918 patients remained in remission at two years (good outcome). Our analysis identified four preferentially mutated genes (TP53, MYD88, SPEN, MYC) in the untreated (diagnostic) tumor samples from patients with poor outcomes. Furthermore, transcriptomic analysis revealed a distinct gene expression pattern linked to poor outcomes, affecting pathways involved in cell adhesion/migration, T-cell activation/regulation, PI3K, and NF-κB signaling. Moreover, we developed and validated a 24-gene expression score as an independent prognostic predictor for treatment outcomes. This score also demonstrated efficacy in further stratifying high-risk patients when integrated with existing genetic or cell-of-origin subtypes, including the unclassified cases in these models. Finally, based on these findings, we developed an online analysis tool ( https://lymphprog.serve.scilifelab.se/app/lymphprog ) that can be used for prognostic prediction for DLBCL patients.

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.

Impact of tumor microenvironment on efficacy of anti-CD19 CAR T cell therapy or chemotherapy and transplant in large B cell lymphoma

The phase 3 ZUMA-7 trial in second-line large B cell lymphoma demonstrated superiority of anti-CD19 CAR T cell therapy (axicabtagene ciloleucel (axi-cel)) over standard of care (SOC; salvage chemotherapy followed by hematopoietic transplantation) ( NCT03391466 ). Here, we present a prespecified exploratory analysis examining the association between pretreatment tumor characteristics and the efficacy of axi-cel versus SOC. B cell gene expression signature (GES) and CD19 expression associated significantly with improved event-free survival for axi-cel (P = 0.0002 for B cell GES; P = 0.0165 for CD19 expression) but not SOC (P = 0.9374 for B cell GES; P = 0.5526 for CD19 expression). Axi-cel showed superior event-free survival over SOC irrespective of B cell GES and CD19 expression (P = 8.56 × 10-9 for B cell GES high; P = 0.0019 for B cell GES low; P = 3.85 × 10-9 for CD19 gene high; P = 0.0017 for CD19 gene low). Low CD19 expression in malignant cells correlated with a tumor GES consisting of immune-suppressive stromal and myeloid genes, highlighting the inter-relation between malignant cell features and immune contexture substantially impacting axi-cel outcomes. Tumor burden, lactate dehydrogenase and cell-of-origin impacted SOC more than axi-cel outcomes. T cell activation and B cell GES, which are associated with improved axi-cel outcome, decreased with increasing lines of therapy. These data highlight differences in resistance mechanisms to axi-cel and SOC and support earlier intervention with axi-cel.

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.

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.

The Oncogenic Lipid Sphingosine-1-Phosphate Impedes the Phagocytosis of Tumor Cells by M1 Macrophages in Diffuse Large B Cell Lymphoma

BACKGROUND

A total of 30-40% of diffuse large B cell lymphoma (DLBCL) patients will either not respond to the standard therapy or their disease will recur. The first-line treatment for DLBCL is rituximab and combination chemotherapy. This treatment involves the chemotherapy-induced recruitment of tumor-associated macrophages that recognize and kill rituximab-opsonized DLBCL cells. However, we lack insights into the factors responsible for the recruitment and functionality of macrophages in DLBCL tumors.

METHODS

We have studied the effects of the immunomodulatory lipid sphingosine-1-phosphate (S1P) on macrophage activity in DLBCL, both in vitro and in animal models.

RESULTS

We show that tumor-derived S1P mediates the chemoattraction of both monocytes and macrophages in vitro and in animal models, an effect that is dependent upon the S1P receptor S1PR1. However, S1P inhibited M1 macrophage-mediated phagocytosis of DLBCL tumor cells opsonized with the CD20 monoclonal antibodies rituximab and ofatumumab, an effect that could be reversed by an S1PR1 inhibitor.

CONCLUSIONS

Our data show that S1P signaling can modulate macrophage recruitment and tumor cell killing by anti-CD20 monoclonal antibodies in DLBCL. The administration of S1PR1 inhibitors could enhance the phagocytosis of tumor cells and improve outcomes for patients.

In-depth analysis of immune cell landscapes reveals differences between lung adenocarcinoma and lung squamous cell carcinoma

Background

Lung cancer is the leading cause of cancer deaths globally, with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) being major subtypes. Immunotherapy has emerged as a promising approach for the treatment of lung cancer, but understanding the underlying mechanisms of immune dysregulation is crucial for the development of effective therapies. This study aimed to investigate the distinctive cellular features of LUAD and LUSC and identify potential biomarkers associated with the pathogenesis and clinical outcomes of each subtype.

Methods

We used digital cytometry techniques to analyze the RNA-Seq data of 1128 lung cancer patients from The Cancer Genome Atlas (TCGA) database. The abundance of cell subtypes and ecotypes in LUAD and LUSC patients was quantified. Univariate survival analysis was used to investigate their associations with patient overall survival (OS). Differential gene expression analysis and gene co-expression network construction were carried out to explore the gene expression patterns of LUSC patients with distinct survival outcomes. Scratch wound-healing assay, colony formation assay, and transwell assay were used to validate the candidate drugs for LUSC treatment.

Results

We found differential expression of cell subtypes between LUAD and LUSC, with certain cell subtypes being prognostic for survival in both subtypes. We also identified differential gene expression and gene co-expression modules associated with macrophages.3/PCs.2 ratio in LUSC patients with distinct survival outcomes. Furthermore, ecotype ratios were found to be prognostic in both subtypes and machine learning models showed that certain cell subtypes, such as epithelial.cells.1, epithelial.cells.5, and endothelial.cells.2 are important for predicting LUSC. Ginkgolide B and triamterene can inhibit the proliferation, invasion, and migration of LUSC cell lines.

Conclusion

We provide insight into the distinctive cellular features of LUAD and LUSC, and identify potential biomarkers associated with the pathogenesis and clinical outcomes of each subtype. Ginkgolide B and triamterene could be promising drugs for LUSC treatment.

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.

Integrative analyses reveal outcome-associated and targetable molecular partnerships between TP53, BRD4, TNFRSF10B, and CDKN1A in diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a common, genomically heterogenous disease that presents a clinical challenge despite the success of frontline regimens and second-line chimeric antigen receptor T-cell (CAR-T) therapy. Recently, genomic alterations and tumor microenvironment features associated with poor CAR-T response have been identified, namely those to the TP53 tumor suppressor gene. This retrospective analysis aimed to integrate various data to identify genomic partnerships capable of providing further clarity and actionable treatment targets within this population. Publicly available data were analyzed for differential expression based on TP53 and 24-month event-free survival (EFS24) status, revealing enrichments of the BRD4 bromodomain oncogene (p < 0.0001, p = 0.001). High-BRD4 and TP53 alterations were significantly associated with lower CDKN1A (p21) and TNFRSF10B (TRAIL-R2), a key tumor suppressor and CAR-T modulator, respectively. Significant loss of CD8 T-cell presence within low-TNFRSF0B (p = 0.0042) and altered-TP53 (p = 0.0424) patients showcased relevant outcome-associated tumor microenvironment features. Furthermore, reduced expression of CDKN1A was associated with low TNFRSF10B (FDR < 0.0001) and increased BRD4 interactant genes (FDR < 0.0001). Promisingly, in vitro MDM2 inhibition with Idasnutlin and TP53 reactivation via Eprenetapopt was able to renew TNFRSF10B protein expression. Additionally, applying the BRD4-degrading PROTAC ARV-825 and the CDK4/6 inhibitor Abemaciclib as single-agents and in synergistic combination significantly reduced TP53-altered DLBCL cell line viability. Our analysis presents key associations within a genomic network of actionable targets capable of providing clarity within the evolving precision CAR-T treatment landscape.

Role of the tumor microenvironment in CLL pathogenesis

Chronic lymphocytic leukemia (CLL) cells extensively interact with and depend on their surrounding tumor microenvironment (TME). The TME encompasses a heterogeneous array of cell types, soluble signals, and extracellular vesicles, which contribute significantly to CLL pathogenesis. CLL cells and the TME cooperatively generate a chronic inflammatory milieu, which reciprocally reprograms the TME and activates a signaling network within CLL cells, promoting their survival and proliferation. Additionally, the inflammatory milieu exerts chemotactic effects, attracting CLL cells and other immune cells to the lymphoid tissues. The intricate CLL-TME interactions also facilitate immune evasion and compromise leukemic cell surveillance. We also review recent advances that have shed light on additional aspects that are substantially influenced by the CLL-TME interplay.

Diversity of intratumoral regulatory T cells in B-cell non-Hodgkin lymphoma

Tumor-infiltrating regulatory T cells (Tregs) contribute to an immunosuppressive tumor microenvironment. Despite extensive studies, the prognostic impact of tumor-infiltrating Tregs in B-cell non-Hodgkin lymphomas (B-NHLs) remains unclear. Emerging studies suggest substantial heterogeneity in the phenotypes and suppressive capacities of Tregs, emphasizing the importance of understanding Treg diversity and the need for additional markers to identify highly suppressive Tregs. Here, we applied single-cell RNA sequencing and T-cell receptor sequencing combined with high-dimensional cytometry to decipher the heterogeneity of intratumoral Tregs in diffuse large B-cell lymphoma and follicular lymphoma (FL), compared with that in nonmalignant tonsillar tissue. We identified 3 distinct transcriptional states of Tregs: resting, activated, and unconventional LAG3+FOXP3- Tregs. Activated Tregs were enriched in B-NHL tumors, coexpressed several checkpoint receptors, and had stronger immunosuppressive activity compared with resting Tregs. In FL, activated Tregs were found in closer proximity to CD4+ and CD8+ T cells than other cell types. Furthermore, we used a computational approach to develop unique gene signature matrices, which were used to enumerate each Treg subset in cohorts with bulk gene expression data. In 2 independent FL cohorts, activated Tregs was the major subset, and high abundance was associated with adverse outcome. This study demonstrates that Tregs infiltrating B-NHL tumors are transcriptionally and functionally diverse. Highly immunosuppressive activated Tregs were enriched in tumor tissue but absent in the peripheral blood. Our data suggest that a deeper understanding of Treg heterogeneity in B-NHL could open new paths for rational drug design, facilitating selective targeting to improve antitumor immunity.

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

Background

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.

Methods

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.

Results

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.

Conclusions

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.

Tumor-Infiltrating Normal B Cells Revealed by Immunoglobulin Repertoire Clonotype Analysis Are Highly Prognostic and Crucial for Antitumor Immune Responses in DLBCL

PURPOSE

Tumor-infiltrating B lymphocytes (TIL-B) have demonstrated prognostic and predictive significance in solid cancers. In this study, we aimed to distinguish TIL-Bs from malignant B-cells in diffuse large B-cell lymphoma (DLBCL) and determine the clinical and biological significance.

EXPERIMENTAL DESIGN

A total of 269 patients with de novo DLBCL from the International DLBCL R-CHOP Consortium Program were studied. Ultra-deep sequencing of the immunoglobulin genes was performed to determine B-cell clonotypes. The frequencies and numbers of TIL-B clonotypes in individual repertoires were correlated with patient survival, gene expression profiling (GEP) data, and frequencies of DLBCL-infiltrating immune cells quantified by fluorescent multiplex IHC at single-cell resolution.

RESULTS

TIL-B abundance, evaluated by frequencies of normal B-cell clonotypes in the immunoglobulin repertoires, remarkably showed positive associations with significantly better survival of patients in our sequenced cohorts. DLBCLs with high versus low TIL-B abundance displayed distinct GEP signatures, increased pre-memory B-cell state and naïve CD4 T-cell state fractions, and higher CD4+ T-cell infiltration. TIL-B frequency, as a new biomarker in DLBCL, outperformed the germinal center (GC) B-cell-like/activated B-cell-like classification and TIL-T frequency. The identified TIL-B-high GEP signature, including genes upregulated during T-dependent B-cell activation and those highly expressed in normal GC B cells and T cells, showed significant favorable prognostic effects in several external validation cohorts.

CONCLUSIONS

TIL-B frequency is a significant prognostic factor in DLBCL and plays a crucial role in antitumor immune responses. This study provides novel insights into the prognostic determinants in DLBCL and TIL-B functions with important therapeutic implications.

Biological heterogeneity in diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is heterogeneous both in clinical outcomes and the underlying disease biology. Over the last 2 decades, several different approaches for dissecting biological heterogeneity have emerged. Gene expression profiling (GEP) stratifies DLBCL into 3 broad groups (ABC, GCB, and DZsig/MHG), each with parallels to different normal mature B cell developmental states and prognostic implications. More recently, several different genomic approaches have been developed to categorize DLBCL based on the co-occurrence of tumor somatic mutations, identifying more granular biologically unified subgroups that complement GEP-based approaches. We review the molecular approaches and clinical evidence supporting the stratification of DLBCL patients based on tumor biology. By offering a platform for subtype-guided therapy, these divisions remain a promising avenue for improving patient outcomes, especially in subgroups with inferior outcomes with current standard-of-care therapy.

Scientific techniques in adolescent and young adult classic Hodgkin lymphoma

Understanding the tumor microenvironment and genomic landscape is crucial for better prediction of treatment outcomes and developing novel therapies in Hodgkin lymphoma (HL). Recent advancements in genomics have enabled researchers to gain deeper insights into the genomic characteristics of HL at both single-cell resolution and the whole genome level. The use of noninvasive methods such as liquid biopsies and formalin-fixed paraffin-embedded-based imaging techniques has expanded the possibilities of applying cutting-edge analyses to routine clinically available samples. Collaborative efforts between adult and pediatric group are imperative to translate novel findings into routine patient care.

CAR-T Cell Therapy in Large B Cell Lymphoma

Large B-cell lymphomas (LBCLs) are among the most frequent (about 30%) non-Hodgkin's lymphoma. Despite the aggressive behavior of these lymphomas, more than 60% of patients can be cured with first-line chemoimmunotherapy using the R-CHOP regimen. Patients with refractory or relapsing disease show a poor outcome even when treated with second-line therapies. CD19-targeted chimeric antigen receptor (CAR) T-cells are emerging as an efficacious second-line treatment strategy for patients with LBCL. Three CD19-CAR-T-cell products received FDA and EMA approval. CAR-T cell therapy has also been explored for treating high-risk LBCL patients in the first-line setting and for patients with central nervous system involvement. Although CD19-CAR-T therapy has transformed the care of refractory/relapsed LBCL, about 60% of these patients will ultimately progress or relapse following CD19-CAR-T; therefore, it is fundamental to identify predictive criteria of response to CAR-T therapy and to develop salvage therapies for patients relapsing after CD19-CAR-T therapies. Moreover, ongoing clinical trials evaluate bispecific CAR-T cells targeting both CD19 and CD20 or CD19 and CD22 as a tool to improve the therapeutic efficacy and reduce the number of refractory/relapsing patients.

Phenotypic maps for precision medicine: a promising systems biology tool for assessing therapy response and resistance at a personalized level

In this perspective we discuss how tumor heterogeneity and therapy resistance necessitate a focus on more personalized approaches, prompting a shift toward precision medicine. At the heart of the shift towards personalized medicine, omics-driven systems biology becomes a driving force as it leverages high-throughput technologies and novel bioinformatics tools. These enable the creation of systems-based maps, providing a comprehensive view of individual tumor's functional plasticity. We highlight the innovative PHENOSTAMP program, which leverages high-dimensional data to construct a visually intuitive and user-friendly map. This map was created to encapsulate complex transitional states in cancer cells, such as Epithelial-Mesenchymal Transition (EMT) and Mesenchymal-Epithelial Transition (MET), offering a visually intuitive way to understand disease progression and therapeutic responses at single-cell resolution in relation to EMT-related single-cell phenotypes. Most importantly, PHENOSTAMP functions as a reference map, which allows researchers and clinicians to assess one clinical specimen at a time in relation to their phenotypic heterogeneity, setting the foundation on constructing phenotypic maps for personalized medicine. This perspective argues that such dynamic predictive maps could also catalyze the development of personalized cancer treatment. They hold the potential to transform our understanding of cancer biology, providing a foundation for a future where therapy is tailored to each patient's unique molecular and cellular tumor profile. As our knowledge of cancer expands, these maps can be continually refined, ensuring they remain a valuable tool in precision oncology.

Location, location, location: mapping the lymphoma tumor microenvironment using spatial transcriptomics

Lymphomas are a heterogenous group of lymphoid neoplasms with a wide variety of clinical presentations. Response to treatment and prognosis differs both between and within lymphoma subtypes. Improved molecular and genetic profiling has increased our understanding of the factors which drive these clinical dynamics. Immune and non-immune cells within the lymphoma tumor microenvironment (TME) can both play a key role in antitumor immune responses and conversely also support lymphoma growth and survival. A deeper understanding of the lymphoma TME would identify key lymphoma and immune cell interactions which could be disrupted for therapeutic benefit. Single cell RNA sequencing studies have provided a more comprehensive description of the TME, however these studies are limited in that they lack spatial context. Spatial transcriptomics provides a comprehensive analysis of gene expression within tissue and is an attractive technique in lymphoma to both disentangle the complex interactions between lymphoma and TME cells and improve understanding of how lymphoma cells evade the host immune response. This article summarizes current spatial transcriptomic technologies and their use in lymphoma research to date. The resulting data has already enriched our knowledge of the mechanisms and clinical impact of an immunosuppressive TME in lymphoma and the accrual of further studies will provide a fundamental step in the march towards personalized medicine.

Follicular lymphoma microenvironment: insights provided by single-cell analysis

Follicular lymphoma (FL) is the most frequent indolent lymphoma and is characterized by the abundant infiltration of tumor microenvironment (TME) cells. The activity of TME cells reportedly plays an important role in the biology of FL. TME cells that reside within neoplastic follicles, such as T-follicular helper cells and follicular dendritic cells, have been shown to aid in FL development and progression through interactions with malignant B cells, whereas regulatory T cells have unexpectedly shown an apparently favorable prognostic impact in FL. Unfortunately, the understanding of the FL TME, particularly regarding minor cell subsets, has been hampered by unknown cell heterogeneity. As with other solid and hematologic cancers, novel single-cell analysis technologies have recently been applied to FL research and have uncovered previously unrecognized heterogeneities, not only in malignant B cells but also in TME cells. These reports have greatly increased the resolution of our understanding of the FL TME and, at the same time, raised questions about newly identified TME cells. This review provides an overview of the unique aspects of FL TME cells with a clinical viewpoint and highlights recent discoveries from single-cell analysis, while also suggesting potential future directions.

FCRL1 immunoregulation in B cell development and malignancy

Immunotherapeutic targeting of surface regulatory proteins and pharmacologic inhibition of critical signaling pathways has dramatically shifted our approach to the care of individuals with B cell malignancies. This evolution in therapy reflects the central role of the B cell receptor (BCR) signaling complex and its co-receptors in the pathogenesis of B lineage leukemias and lymphomas. Members of the Fc receptor-like gene family (FCRL1-6) encode cell surface receptors with complex tyrosine-based regulation that are preferentially expressed by B cells. Among them, FCRL1 expression peaks on naïve and memory B cells and is unique in terms of its intracellular co-activation potential. Recent studies in human and mouse models indicate that FCRL1 contributes to the formation of the BCR signalosome, modulates B cell signaling, and promotes humoral responses. Progress in understanding its regulatory properties, along with evidence for its over-expression by mature B cell leukemias and lymphomas, collectively imply important yet unmet opportunities for FCRL1 in B cell development and transformation. Here we review recent advances in FCRL1 biology and highlight its emerging significance as a promising biomarker and therapeutic target in B cell lymphoproliferative disorders.

Dissecting the tumor ecosystem of liver cancers in the single-cell era

Primary liver cancers (PLCs) are a broad class of malignancies that include HCC, intrahepatic cholangiocarcinoma, and combined hepatocellular and intrahepatic cholangiocarcinoma. PLCs are often associated with a poor prognosis due to their high relapse and low therapeutic response rates. Importantly, PLCs exist within a dynamic and complex tumor ecosystem, which includes malignant, immune, and stromal cells. It is critical to dissect the PLC tumor ecosystem to uncover the underlying mechanisms associated with tumorigenesis, relapse, and treatment resistance to facilitate the discovery of novel therapeutic targets. Single-cell and spatial multi-omics sequencing techniques offer an unprecedented opportunity to elucidate spatiotemporal interactions among heterogeneous cell types within the complex tumor ecosystem. In this review, we describe the latest advances in single-cell and spatial technologies and review their applications with respect to dissecting liver cancer tumor ecosystems.

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.

Advances in single-cell RNA sequencing and its applications in cancer research

Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.

SOHO State of the Art Updates and Next Questions | New Pathways and New Targets in PTCL: Staying on Target

While the peripheral T-cell lymphomas (PTCL) remain a therapeutic challenge, and increasingly account for a disproportionate number of lymphoma-related deaths, improved understanding of disease pathogenesis and classification, and the development of novel therapeutic agents over the past decade, all provide reasons for a more optimistic outlook in the next. Despite their genetic and molecular heterogeneity, many PTCL are dependent upon signaling input provided by antigen, costimulatory, and cytokine receptors. While gain-of-function alterations effecting these pathways are recurrently observed in many PTCL, more often than not, signaling remains ligand-and tumor microenvironment (TME)-dependent. Consequently, the TME and its constituents are increasingly recognized as "on target". Utilizing a "3 signal" model, we will review new-and old-therapeutic targets that are relevant for the more common nodal PTCL subtypes.

Integrative Prognostic Machine Learning Models in Mantle Cell Lymphoma

Patients with mantle cell lymphoma (MCL), an incurable B-cell malignancy, benefit from accurate pretreatment disease stratification. We curated an extensive database of 862 patients diagnosed between 2014 and 2022. A machine learning (ML) gradient-boosted model incorporated baseline features from clinicopathologic, cytogenetic, and genomic data with high predictive power discriminating between patients with indolent or responsive MCL and those with aggressive disease (AUC ROC = 0.83). In addition, we utilized the gradient-boosted framework as a robust feature selection method for multivariate logistic and survival modeling. The best ML models incorporated features from clinical and genomic data types highlighting the need for correlative molecular studies in precision oncology. As proof of concept, we launched our most accurate and practical models using an application interface, which has potential for clinical implementation. We designated the 20-feature ML model-based index the "integrative MIPI" or iMIPI and a similar 10-feature ML index the "integrative simplified MIPI" or iMIPI-s. The top 10 baseline prognostic features represented in the iMIPI-s are: lactase dehydrogenase (LDH), Ki-67%, platelet count, bone marrow involvement percentage, hemoglobin levels, the total number of observed somatic mutations, TP53 mutational status, Eastern Cooperative Oncology Group performance level, beta-2 microglobulin, and morphology. Our findings emphasize that prognostic applications and indices should include molecular features, especially TP53 mutational status. This work demonstrates the clinical utility of complex ML models and provides further evidence for existing prognostic markers in MCL.

Significance

Our model is the first to integrate a dynamic algorithm with multiple clinical and molecular features, allowing for accurate predictions of MCL disease outcomes in a large patient cohort.

Deep immunophenotyping reveals clinically distinct cellular states and ecosystems in large-scale colorectal cancer

Determining the diverse cell types in the tumor microenvironment (TME) and their organization into cellular communities, is critical for understanding the biological heterogeneity and therapy of cancer. Here, we deeply immunophenotype the colorectal cancer (CRC) by integrative analysis of large-scale bulk and single cell transcriptome of 2350 patients and 53,137 cells. A rich landscape of 42 cellular states and 7 ecosystems in TMEs is uncovered and extend the previous immune classifications of CRC. Functional pathways and potential transcriptional regulators analysis of cellular states and ecosystems reveal cancer hallmark-related pathways and several critical transcription factors in CRC. High-resolution characterization of the TMEs, we discover the potential utility of cellular states (i.e., Monocytes/Macrophages and CD8 T cell) and ecosystems for prognosis and clinical therapy selection of CRC. Together, our results expand our understanding of cellular organization in TMEs of CRC, with potential implications for the development of biomarkers and precision therapies.

Discovering the fibroblastic reticular cell in the immune tumor microenvironment in lymphoma

The study of the cellular and molecular microenvironment in B cell lymphoma, especially diffuse large B cell lymphoma (DLBCL), has led to prognostic and therapeutic algorithms that may improve patient outcomes. Emerging gene signature panels provide a granular understanding of DLBCL based on the immune tumor microenvironment (iTME). In addition, some gene signatures identify lymphomas that are more responsive to immune-based treatment, indicating that the iTME has a biological signature that could affect outcomes when targeted. In this issue of the JCI, Apollonio et al. report on fibroblastic reticular cells (FRCs) as potential targets in aggressive lymphoma. FRCs interacted with lymphoma cells and induced a state of chronic inflammation that suppressed immune function by impeding optimal T cell migration and inhibiting CD8+ T cell lytic function. These findings suggest that manipulating the iTME by directly targeting FRCs may enhance responses to immunotherapy in DLBCL.

Tumor-activated lymph node fibroblasts suppress T cell function in diffuse large B cell lymphoma

Recent transcriptomic-based analysis of diffuse large B cell lymphoma (DLBCL) has highlighted the clinical relevance of LN fibroblast and tumor-infiltrating lymphocyte (TIL) signatures within the tumor microenvironment (TME). However, the immunomodulatory role of fibroblasts in lymphoma remains unclear. Here, by studying human and mouse DLBCL-LNs, we identified the presence of an aberrantly remodeled fibroblastic reticular cell (FRC) network expressing elevated fibroblast-activated protein (FAP). RNA-Seq analyses revealed that exposure to DLBCL reprogrammed key immunoregulatory pathways in FRCs, including a switch from homeostatic to inflammatory chemokine expression and elevated antigen-presentation molecules. Functional assays showed that DLBCL-activated FRCs (DLBCL-FRCs) hindered optimal TIL and chimeric antigen receptor (CAR) T cell migration. Moreover, DLBCL-FRCs inhibited CD8+ TIL cytotoxicity in an antigen-specific manner. Notably, the interrogation of patient LNs with imaging mass cytometry identified distinct environments differing in their CD8+ TIL-FRC composition and spatial organization that associated with survival outcomes. We further demonstrated the potential to target inhibitory FRCs to rejuvenate interacting TILs. Cotreating organotypic cultures with FAP-targeted immunostimulatory drugs and a bispecific antibody (glofitamab) augmented antilymphoma TIL cytotoxicity. Our study reveals an immunosuppressive role of FRCs in DLBCL, with implications for immune evasion, disease pathogenesis, and optimizing immunotherapy for patients.

Cell-free DNA in large B-cell lymphoma: MRD and beyond

Large B-cell lymphomas (LBCLs) are a strikingly diverse set of diseases, including clinical, biological, and molecular heterogeneity. Despite a wealth of information resolving this heterogeneity in the research setting, applying molecular features routinely in the clinic remains challenging. The advent of circulating tumor DNA (ctDNA) liquid biopsies promises to unlock additional molecular information in the clinic, including mutational genotyping, molecular classification, and minimal residual disease detection. Here, we examine the technologies, applications, and studies exploring the utility of ctDNA in LBCLs.

Single-cell landscape of primary central nervous system diffuse large B-cell lymphoma

Understanding tumor heterogeneity and immune infiltrates within the tumor-immune microenvironment (TIME) is essential for the innovation of immunotherapies. Here, combining single-cell transcriptomics and chromatin accessibility sequencing, we profile the intratumor heterogeneity of malignant cells and immune properties of the TIME in primary central nervous system diffuse large B-cell lymphoma (PCNS DLBCL) patients. We demonstrate diverse malignant programs related to tumor-promoting pathways, cell cycle and B-cell immune response. By integrating data from independent systemic DLBCL and follicular lymphoma cohorts, we reveal a prosurvival program with aberrantly elevated RNA splicing activity that is uniquely associated with PCNS DLBCL. Moreover, a plasmablast-like program that recurs across PCNS/activated B-cell DLBCL predicts a worse prognosis. In addition, clonally expanded CD8 T cells in PCNS DLBCL undergo a transition from a pre-exhaustion-like state to exhaustion, and exhibit higher exhaustion signature scores than systemic DLBCL. Thus, our study sheds light on potential reasons for the poor prognosis of PCNS DLBCL patients, which will facilitate the development of targeted therapy.

Multiomic Analysis Identifies a High-Risk Metabolic and TME Depleted Signature that Predicts Early Clinical Failure in DLBCL

PURPOSE

60-70% of newly diagnosed diffuse large B-cell lymphoma (DLBCL) patients avoid events within 24 months of diagnosis (EFS24) and the remainder have poor outcomes. Recent genetic and molecular classification of DLBCL has advanced our knowledge of disease biology, yet were not designed to predict early events and guide anticipatory selection of novel therapies. To address this unmet need, we used an integrative multiomic approach to identify a signature at diagnosis that will identify DLBCL at high risk of early clinical failure.

PATIENTS AND METHODS

Tumor biopsies from 444 newly diagnosed DLBCL were analyzed by WES and RNAseq. A combination of weighted gene correlation network analysis and differential gene expression analysis followed by integration with clinical and genomic data was used to identify a multiomic signature associated with high risk of early clinical failure.

RESULTS

Current DLBCL classifiers are unable to discriminate cases who fail EFS24. We identified a high risk RNA signature that had a hazard ratio (HR, 18.46 [95% CI 6.51-52.31] P < .001) in a univariate model, which did not attenuate after adjustment for age, IPI and COO (HR, 20.8 [95% CI, 7.14-61.09] P < .001). Further analysis revealed the signature was associated with metabolic reprogramming and a depleted immune microenvironment. Finally, WES data was integrated into the signature and we found that inclusion of ARID1A mutations resulted in identification of 45% of cases with an early clinical failure which was validated in external DLBCL cohorts.

CONCLUSION

This novel and integrative approach is the first to identify a signature at diagnosis that will identify DLBCL at high risk for early clinical failure and may have significant implications for design of therapeutic options.

Locus specific human endogenous retroviruses reveal new lymphoma subtypes

The heterogeneity of cancers are driven by diverse mechanisms underlying oncogenesis such as differential 'cell-of-origin' (COO) progenitors, mutagenesis, and viral infections. Classification of B-cell lymphomas have been defined by considering these characteristics. However, the expression and contribution of transposable elements (TEs) to B cell lymphoma oncogenesis or classification have been overlooked. We hypothesized that incorporating TE signatures would increase the resolution of B-cell identity during healthy and malignant conditions. Here, we present the first comprehensive, locus-specific characterization of TE expression in benign germinal center (GC) B-cells, diffuse large B-cell lymphoma (DLBCL), Epstein-Barr virus (EBV)-positive and EBV-negative Burkitt lymphoma (BL), and follicular lymphoma (FL). Our findings demonstrate unique human endogenous retrovirus (HERV) signatures in the GC and lymphoma subtypes whose activity can be used in combination with gene expression to define B-cell lineage in lymphoid malignancies, highlighting the potential of retrotranscriptomic analyses as a tool in lymphoma classification, diagnosis, and the identification of novel treatment groups.

Applications of single-cell RNA sequencing in drug discovery and development

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved disease understanding through cell subtyping, and highly multiplexed functional genomics screens incorporating scRNA-seq are enhancing target credentialling and prioritization. ScRNA-seq is also aiding the selection of relevant preclinical disease models and providing new insights into drug mechanisms of action. In clinical development, scRNA-seq can inform decision-making via improved biomarker identification for patient stratification and more precise monitoring of drug response and disease progression. Here, we illustrate how scRNA-seq methods are being applied in key steps in drug discovery and development, and discuss ongoing challenges for their implementation in the pharmaceutical industry.

Elsholtzia bodinieri Vaniot ameliorated acute lung injury in mice by regulating pyroptosis, inflammation, oxidative stress and macrophage polarization

ETHNOPHARMACOLOGICAL RELEVANCE

Elsholtzia bodinieri Vaniot, perennial herbs, a traditional Yunnan Chinese herbal medicine. Its whole herb can be used as commonly used herbs to cure fever, headache, inflammation, indigestion etc., and its tender tip can also be used as tea in Yunnan of China. However, the protective mechanism of Elsholtzia bodinieri Vaniot on acute lung injury (ALI) still needs to be explored.

AIM OF STUDY

ALI is characterized by acute respiratory inflammation, which remains a significant source of morbidity and mortality. The current study with the aim of determining the therapeutic the efficacy of E. bodinieri Vaniot on lipopolysaccharide-induced ALI, moreover uncovered the underlying gene-regulated framework, so E. bodinieri Vaniot might serve as functional food for adjuvant therapy or therapeutic agent.

MATERIALS AND METHODS

These potential pharmacological targets of E. bodinieri Vaniot against ALI were analyzed by multiple bioinformatics databases. E. bodinieri Vaniot methanol extract (EBE) was obtained by ultrasonic-assisted extraction method, and detected by UHPLC-ESI-HRMS/MS. These pyroptosis, inflammation and oxidative stress associated factors were measured using ELISA assay, western blotting, and histopathological examination to assess the effects of EBE. EcoTyper and immunofluorescence staining were employed to estimate macrophage polarization states in ALI lungs tissue.

RESULTS

In ALI lung tissues, EBE treatment could increase B cell leukemia/lymphoma 2 (BCL2) to inhibit pyroptosis, downregulate prostaglandin-endoperoxide synthase 2 (PTGS2) to attenuate inflammation, upregulating NAD(P)H dehydrogenase, quinone 1 (NQO1) to alleviate oxidative stress and induce macrophage polarization toward the M2 phenotype.

CONCLUSION

E. bodinieri Vaniot ameliorated ALI thought regulating pyroptosis, inflammation, oxidative stress and macrophage polarization, as well as could be a promising source for therapeutic agent.

OX40 shapes an inflamed tumor immune microenvironment and predicts response to immunochemotherapy in diffuse large B-cell lymphoma

OX40 enhances the T-cell activation via costimulatory signaling. However, its molecular characteristics and value in predicting response to immunochemotherapy in DLBCL remain largely unexplored. Here, we performed an integrative analysis of sequencing and multiplex immunofluorescence staining, and discovered abnormally higher expression of OX40 in DLBCL patients. Elevated OX40 could activate T cells leading to a higher immune score for tumor immune microenvironment (TiME). OX40 upregulation simultaneously happened with immune-related genes including PD-1, CTLA4 and TIGIT et,al. Patients with high OX40 expression exhibited a lower Ann Arbor stage and IPI score and more easily achieved a complete response/partial response. The analysis of infiltrated T-cell subset revealed that patients with a greater number of CD4+/OX40+ or CD8+/OX40+ T cells had a longer OS. Our findings indicated that OX40 shapes an inflamed tumor immune microenvironment and predicts response to immunochemotherapy, providing insights for the application of OX40 agonist in DLBCL patients.