Dissecting intratumour heterogeneity of nodal B-cell lymphomas at the transcriptional, genetic and drug-response levels

Single-Cell Transcriptomic Analysis of Normal and Malignant B Cells

In the past decade, single-cell (sc) transcriptomics has overcome the limitations of bulk analysis by measuring gene expression in individual cells, not just a population average. This can identify diverse cell types and states within a sample with high resolution, even without prior purification. Various technologies exist, each with its own capture, barcoding, and library preparation methods. This chapter focuses on the analysis of normal and malignant mature B cells using the 10× Genomics 5' sc-gene expression in parallel with B cell immune repertoire profiling. By integrating the gene expression data from similar cells, the complete transcriptome for each population can be reconstructed, while the identification of the expressed immunoglobulin genes allows investigating clonotype evolution and the detection of tumor clones that share the same clonally rearranged B cell receptor sequence. Researchers are guided through both the experimental protocols and data analysis with a comprehensive, step-by-step walkthrough of how to use some of the more popular single-cell software tools.

CaClust: linking genotype to transcriptional heterogeneity of follicular lymphoma using BCR and exomic variants

Tumours exhibit high genotypic and transcriptional heterogeneity. Both affect cancer progression and treatment, but have been predominantly studied separately in follicular lymphoma. To comprehensively investigate the evolution and genotype-to-phenotype maps in follicular lymphoma, we introduce CaClust, a probabilistic graphical model integrating deep whole exome, single-cell RNA and B-cell receptor sequencing data to infer clone genotypes, cell-to-clone mapping, and single-cell genotyping. CaClust outperforms a state-of-the-art model on simulated and patient data. In-depth analyses of single cells from four samples showcase effects of driver mutations, follicular lymphoma evolution, possible therapeutic targets, and single-cell genotyping that agrees with an independent targeted resequencing experiment.

Follicular lymphoma research: an open dialogue for a collaborative roadmap

Follicular lymphoma (FL) is the second most common type of lymphoma (20% of all non-Hodgkin lymphomas), derived from germinal centre (GC) B cells, and is characterised by its significant clinical, prognostic and biological heterogeneity, leading to complexity in management. Despite significant biological investigation and indisputable clinical progress since the advent of the immunotherapy era more than 20 years ago, much remains to be done to understand and cure this lymphoma. Today, FL is metaphorically a giant puzzle on the table with patches of sky, landscape and foliage clearly appearing. However, many of the remaining pieces are held by various stakeholders (e.g. clinicians, pathologists, researchers, drug developers) without global agreement on what the gaps are, or any clear blueprint on how to solve the puzzle of understanding the heterogeneity of this disease and create curative and tailored therapies. With the advent of new investigation and drug technologies, together with recent advances in our capacity to manage big data, the time seems ripe for a change of scale. More than ever, this will require collaboration between and within all stakeholders to overcome the current bottlenecks in the field. As for every investigator, we acknowledge that this first draft is necessarily biased, incomplete and some FL expert readers might recognise some remaining gaps not addressed. We hope they will reply to make this effort a collaborative one to assemble all the pieces in the most ideal fashion. As such, this review intends to be a first step and an interactive platform to a collaborative roadmap towards better understanding and care of FL.

Single-cell transcriptomics of pediatric Burkitt lymphoma reveals intra-tumor heterogeneity and markers of therapy resistance

Burkitt lymphoma (BL) is the most frequent B-cell lymphoma in pediatric patients. While most patients are cured, a fraction of them are resistant to therapy. To investigate BL heterogeneity and the features distinguishing therapy responders (R) from non-responders (NR), we analyzed by single-cell (sc)-transcriptomics diagnostic EBV-negative BL specimens. Analysis of the non-tumor component revealed a predominance of immune cells and a small representation of fibroblasts, enriched in NR. Tumors displayed patient-specific features, as well as shared subpopulations that expressed transcripts related to cell cycle, signaling pathways and cell-of-origin signatures. Several transcripts were differentially expressed in R versus NR. The top candidate, Tropomyosin 2 (TPM2), a member of the tropomyosin actin filament binding protein family, was confirmed to be significantly higher in NR both at the transcript and protein level. Stratification of patients based on TPM2 expression at diagnosis significantly correlated with prognosis, independently of TP53 mutations. These results indicate that BL displays transcriptional heterogeneity and identify candidate biomarkers of therapy resistance.

Clinical Meaningfulness of an Algorithm-Based Service for Analyzing Treatment Response in Patients with Metastatic Cancer Using FDG PET/CT

Background/Objectives: Determining how a patient with metastatic cancer is responding to therapy can be difficult for medical oncologists, especially with text-only radiology reports. In this investigation, we assess the clinical usefulness of a new algorithm-based analysis that provides spatial location and quantification for each detected lesion region of interest (ROI) and compare it to information included in radiology reports in the United States. Methods: Treatment response radiology reports for FDG PET/CT scans were retrospectively gathered from 228 patients with metastatic cancers. Each radiology report was assessed for the presence of both qualitative and quantitative information. A subset of patients (N = 103) was further analyzed using an algorithm-based service that provides the clinician with comprehensive quantitative information, including change over time, of all detected ROI with visualization of anatomical location. For each patient, three medical oncologists from different practices independently rated the usefulness of the additional analysis overall and in four subcategories. Results: In the 228 radiology reports, quantitative information of size and uptake was provided for at least one lesion at one time point in 78% (size) and 95% (uptake) of patients. This information was reported for both analyzed time points (current scan and previous comparator) in 52% (size) and 66% (uptake) of patients. Only 7% of reports quantified the total number of lesions, and none of the reports quantified changes in all lesions for patients with more than a few lesions. In the assessment of the augmentative algorithm-based analysis, the majority of oncologists rated it as overall useful for 98% of patients (101/103). Within specific categories of use, the majority of oncologists voted to use it for making decisions regarding systemic therapy in 97% of patients, for targeted therapy decisions in 72% of patients, for spatial location information in 96% of patients, and for patient education purposes in 93% of patients. Conclusions: For patients with metastatic cancer, the algorithm-based analysis of all ROI would allow oncologists to better understand treatment response and support their work to more precisely optimize the patient's therapy.

Quantitative evaluation of lesion response heterogeneity for superior prognostication of clinical outcome

PURPOSE

Standardized reporting of treatment response in oncology patients has traditionally relied on methods like RECIST, PERCIST and Deauville score. These endpoints assess only a few lesions, potentially overlooking the response heterogeneity of all disease. This study hypothesizes that comprehensive spatial-temporal evaluation of all individual lesions is necessary for superior prognostication of clinical outcome.

METHODS

[18F]FDG PET/CT scans from 241 patients (127 diffuse large B-cell lymphoma (DLBCL) and 114 non-small cell lung cancer (NSCLC)) were retrospectively obtained at baseline and either during chemotherapy or post-chemoradiotherapy. An automated TRAQinform IQ software (AIQ Solutions) analyzed the images, performing quantification of change in regions of interest suspicious of cancer (lesion-ROI). Multivariable Cox proportional hazards (CoxPH) models were trained to predict overall survival (OS) with varied sets of quantitative features and lesion-ROI, compared by bootstrapping with C-index and t-tests. The best-fit model was compared to automated versions of previously established methods like RECIST, PERCIST and Deauville score.

RESULTS

Multivariable CoxPH models demonstrated superior prognostic power when trained with features quantifying response heterogeneity in all individual lesion-ROI in DLBCL (C-index = 0.84, p < 0.001) and NSCLC (C-index = 0.71, p < 0.001). Prognostic power significantly deteriorated (p < 0.001) when using subsets of lesion-ROI (C-index = 0.78 and 0.67 for DLBCL and NSCLC, respectively) or excluding response heterogeneity (C-index = 0.67 and 0.70). RECIST, PERCIST, and Deauville score could not significantly associate with OS (C-index < 0.65 and p > 0.1), performing significantly worse than the multivariable models (p < 0.001).

CONCLUSIONS

Quantitative evaluation of response heterogeneity of all individual lesions is necessary for the superior prognostication of clinical outcome.

Enhancing cell death in B-cell malignancies through targeted inhibition of Bcl-3

The t(14;19)(q32;q13) is a rare recurring translocation found in B-cell lymphoproliferative malignancies, involving the Bcl-3 gene. This chromosomal translocation is often found in patients under the age of 50 and causes a more progressive disease. The Bcl-3 gene encodes a protein belonging to the IκB family of proteins, which tightly regulates NFκB signaling by acting as an activator or repressor of transcription. Previously, we developed a second-generation Bcl-3 inhibitor that could directly interfere with Bcl-3 signaling pathway, resulting in reduced melanoma cell proliferation, invasion, and migration. The present study aimed to investigate the effect of a Bcl-3 inhibitor on B-cell lymphoma and leukemia cells. It was found that treatment of cells with this inhibitor caused a decrease in cell proliferation and cell survival. Furthermore, Bcl-3 inhibition in B-cell malignant cells resulted in the loss of mitochondrial membrane potential and functionality, as well as the increased expression of cleaved caspase 3, indicating that cell death occurs through the intrinsic apoptotic pathway. This observation is further supported by reduced expression of cIAP1 protein 1 (cIAP1) upon treatment of cancer cells. Given the current lack of clinical advancements targeting Bcl-3 in oncology, this opens a novel avenue for the development and investigation of highly specific therapeutic interventions against B-cell malignancies.

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

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

Impact of positive CD4 cells on event-free survival in follicular lymphoma patients

OBJECTIVE

Previous results about prognostic value of CD4+ T cells in follicular lymphoma (FL) remain controversial.

METHODS

Immunohistochemistry was used to examine expression of positive CD4 cells in 103 patients with FL 1-3A. Early failure was described as failing to achieve event-free survival (EFS) at 12 or 24 months.

RESULTS

There were 49 (47.6%) male and 54 (52.4%) females, with a median age of 54 years. Compared to patients with <20% of positive CD4 cells, patients with ≥20% of positive CD4 cells exhibited a significant lower risk of early failure (2-year EFS rate: 56.7% vs 73.5%, p = 0.047). When patients were stratified based on positive CD4 cell combined with FLIPI, the median EFS (p = 0.002) and median OS (p = 0.007) were significantly different.

CONCLUSIONS

This study demonstrated that higher expression of positive CD4 cells predicts lower risk of early failure in follicular lymphoma, and combination analysis of CD4 and FLIPI could better predict disease relapse and survival outcome.

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

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

Zanubrutinib is effective in non-germinal-center B-cell-like diffuse large B-cell lymphoma with mutated CD79B, high TCL1A expression, or over- expressed MYC/BCL-2

To evaluate the effects of gene mutations on Bruton tyrosine kinase inhibitor, zanubrutinib's effectiveness in patients with diffuse large B-cell lymphoma (DLBCL), we examined pooled data from four single-arm studies (BGB-3111-AU-003 [NCT02343120], BGB-3111-207 [NCT03145064], BGB-3111_GA101_Study_001 [NCT02569476], BGB-3111-213 [NCT03520920]; n = 121). Objective response rate (ORR) was higher, though not statistically significant, in patients with activated B-cell-like (ABC)- and unclassified DLBCL (42.9% [21/49]) versus those with germinal-center B-cell-like DLBCL (14.3% [1/7]; p = 0.15). Patients with CD79B mutations had better ORR (60%) versus patients with wild-type alleles (25.9%, p < 0.01). Higher TCL1A expression correlated with better zanubrutinib response (p = 0.03), longer progression-free survival (p = 0.01), and longer overall survival (p = 0.12). TCL1A expression was higher in ABC-DLBCL (p < 0.001) and MYD88/CD79B-mutated subtypes (p < 0.0001). Eighteen patients with high MYC/BCL-2 expression responded better to zanubrutinib (ORR = 61 vs. 29%, p = 0.02). Our results support assessing CD79B mutations, co-expressor DLBCL, and TCL1A expression status to identify patients with DLBCL who will benefit from zanubrutinib.

Integrated single cell analysis reveals co-evolution of malignant B cells and tumor micro-environment in transformed follicular lymphoma

Histological transformation of follicular lymphoma (FL) to aggressive forms is associated with poor outcome. Phenotypic consequences of this evolution and its impact on the tumor microenvironment (TME) remain unknown. We perform single-cell whole genome sequencing (scWGS) and transcriptome sequencing (scWTS) of 11 paired pre/post-transformation patient samples and scWTS of additional samples from patients without transformation. Our analysis reveals evolutionary dynamics of transformation at single-cell resolution, highlighting a shifting TME landscape, with an emerging immune-cell exhaustion signature, co-evolving with the shifting malignant B phenotype in a regulatory ecosystem. Integration of scWGS and scWTS identifies malignant cell pathways upregulated during clonal tumor evolution. Using multi-color immunofluorescence, we transfer these findings to a TME-based transformation biomarker, subsequently validated in two independent pretreatment cohorts. Taken together, our results provide a comprehensive view of the combined genomic and phenotypic evolution of malignant cells during transformation and shifting crosstalk between malignant cells and the TME.

Defining an Optimized Workflow for Enriching and Analyzing Residual Tumor Populations Using Intracellular Markers

Tumor relapse is well recognized to arise from treatment-resistant residual populations. Strategies enriching such populations for in-depth downstream analyses focus on tumor-specific surface markers; however, enrichment using intracellular biomarkers remains challenging. Using B-cell lymphoma as an exemplar, we demonstrate feasibility to enrich B-cell lymphoma 2 (BCL2)high populations, a surrogate marker for t(14;18)+ lymphomas, for use in downstream applications. Different fixation protocols were assessed for impact on antibody expression and RNA integrity; glyoxal fixation demonstrated superior results regarding minimal effects on surface and intracellular expression, and RNA quality, compared with alternative fixatives evaluated. Furthermore, t(14;18)+ B cells were effectively detected using intracellular BCL2 overexpression to facilitate tumor cell enrichment. Tumor cell populations were enriched using the cellenONE F1.4 single-cell sorting platform, which detected and dispensed BCL2high-expressing cells directly into library preparation reagents for transcriptome analyses. Sorted glyoxal-fixed cells generated good quality sequencing libraries, with high concordance between live and fixed single-cell transcriptomic profiles, discriminating cell populations predominantly on B-cell biology. Overall, we successfully developed a proof-of-concept workflow employing a robust cell preparation protocol for intracellular markers combined with cell enrichment using the cellenONE platform, providing an alternative to droplet-based technologies when cellular input is low or requires prior enrichment to detect rare populations. This workflow has wider prognostic and therapeutic potential to study residual cells in a pan-cancer setting.

Integrative single-cell analysis of LUAD: elucidating immune cell dynamics and prognostic modeling based on exhausted CD8+ T cells

Background

The tumor microenvironment (TME) plays a pivotal role in the progression and metastasis of lung adenocarcinoma (LUAD). However, the detailed characteristics of LUAD and its associated microenvironment are yet to be extensively explored. This study aims to delineate a comprehensive profile of the immune cells within the LUAD microenvironment, including CD8+ T cells, CD4+ T cells, and myeloid cells. Subsequently, based on marker genes of exhausted CD8+ T cells, we aim to establish a prognostic model for LUAD.

Method

Utilizing the Seurat and Scanpy packages, we successfully constructed an immune microenvironment atlas for LUAD. The Monocle3 and PAGA algorithms were employed for pseudotime analysis, pySCENIC for transcription factor analysis, and CellChat for analyzing intercellular communication. Following this, a prognostic model for LUAD was developed, based on the marker genes of exhausted CD8+ T cells, enabling effective risk stratification in LUAD patients. Our study included a thorough analysis to identify differences in TME, mutation landscape, and enrichment across varying risk groups. Moreover, by integrating risk scores with clinical features, we developed a new nomogram. The expression of model genes was validated via RT-PCR, and a series of cellular experiments were conducted, elucidating the potential oncogenic mechanisms of GALNT2.

Results

Our study developed a single-cell atlas for LUAD from scRNA-seq data of 19 patients, examining crucial immune cells in LUAD's microenvironment. We underscored pDCs' role in antigen processing and established a Cox regression model based on CD8_Tex-LAYN genes for risk assessment. Additionally, we contrasted prognosis and tumor environments across risk groups, constructed a new nomogram integrating clinical features, validated the expression of model genes via RT-PCR, and confirmed GALNT2's function in LUAD through cellular experiments, thereby enhancing our understanding and approach to LUAD treatment.

Conclusion

The creation of a LUAD single-cell atlas in our study offered new insights into its tumor microenvironment and immune cell interactions, highlighting the importance of key genes associated with exhausted CD8+ T cells. These discoveries have enabled the development of an effective prognostic model for LUAD and identified GALNT2 as a potential therapeutic target, significantly contributing to the improvement of LUAD diagnosis and treatment strategies.

Cell cross talk within the lymphoma tumor microenvironment: follicular lymphoma as a paradigm

ABSTRACT

Follicular lymphoma (FL) is an indolent yet incurable germinal center B-cell lymphoma retaining a characteristic follicular architecture. FL tumor B cells are highly dependent on direct and indirect interactions with a specific and complex tumor microenvironment (TME). Recently, great progress has been made in describing the heterogeneity and dynamics of the FL TME and in depicting how tumor clonal and functional heterogeneity rely on the integration of TME-related signals. Specifically, the FL TME is enriched for exhausted cytotoxic T cells, immunosuppressive regulatory T cells of various origins, and follicular helper T cells overexpressing B-cell and TME reprogramming factors. FL stromal cells have also emerged as crucial determinants of tumor growth and remodeling, with a key role in the deregulation of chemokines and extracellular matrix composition. Finally, tumor-associated macrophages play a dual function, contributing to FL cell phagocytosis and FL cell survival through long-lasting B-cell receptor activation. The resulting tumor-permissive niches show additional layers of site-to-site and kinetic heterogeneity, which raise questions about the niche of FL-committed precursor cells supporting early lymphomagenesis, clonal evolution, relapse, and transformation. In turn, FL B-cell genetic and nongenetic determinants drive the reprogramming of FL immune and stromal TME. Therefore, offering a functional picture of the dynamic cross talk between FL cells and TME holds the promise of identifying the mechanisms of therapy resistance, stratifying patients, and developing new therapeutic approaches capable of eradicating FL disease in its different ecosystems.

The follicular lymphoma tumor microenvironment at single-cell and spatial resolution

ABSTRACT

Follicular lymphoma (FL) is a generally incurable malignancy that originates from developmentally blocked germinal center B cells residing, primarily, within lymph nodes (LNs). During the long natural history of FL, malignant B cells often disseminate to multiple LNs and can affect virtually any organ. Nonmalignant LNs are highly organized structures distributed throughout the body, in which they perform functions critical for host defense. In FL, the malignant B cells "re-educate" the lymphoid environment by altering the phenotype, distribution, and abundance of other cells such as T cells, macrophages, and subsets of stromal cells. Consequently, dramatic anatomical changes occur and include alterations in the number, shape, and size of neoplastic follicles with an accompanying attenuation of the T-cell zone. Ongoing and dynamic interactions between FL B cells and the tumor microenvironment (TME) result in significant clinical heterogeneity observed both within and across patients. Over time, FL evolves into pathological variants associated with distinct outcomes, ranging from an indolent disease to more aggressive clinical courses with early death. Given the importance of both cell-intrinsic and -extrinsic factors in shaping disease progression and patient survival, comprehensive examination of FL tumors is critical. Here, we describe the cellular composition and architecture of normal and malignant human LNs and provide a broad overview of emerging technologies for deconstructing the FL TME at single-cell and spatial resolution. We additionally discuss the importance of capturing samples at landmark time points as well as longitudinally for clinical decision-making.

Follicular lymphoma B cells exhibit heterogeneous transcriptional states with associated somatic alterations and tumor microenvironments

Follicular lymphoma (FL) is an indolent non-Hodgkin lymphoma of germinal center origin, which presents with significant biologic and clinical heterogeneity. Using RNA-seq on B cells sorted from 87 FL biopsies, combined with machine-learning approaches, we identify 3 transcriptional states that divide the biological ontology of FL B cells into inflamed, proliferative, and chromatin-modifying states, with relationship to prior GC B cell phenotypes. When integrated with whole-exome sequencing and immune profiling, we find that each state was associated with a combination of mutations in chromatin modifiers, copy-number alterations to TNFAIP3, and T follicular helper cells (Tfh) cell interactions, or primarily by a microenvironment rich in activated T cells. Altogether, these data define FL B cell transcriptional states across a large cohort of patients, contribute to our understanding of FL heterogeneity at the tumor cell level, and provide a foundation for guiding therapeutic intervention.

Single-cell transcriptome sequencing provides insight into multiple chemotherapy resistance in a patient with refractory DLBCL: a case report

Relapsed and refractory diffuse large B-cell lymphoma (DLBCL) is associated with poor prognosis. As such, a comprehensive analysis of intratumoral components, intratumoral heterogeneity, and the immune microenvironment is essential to elucidate the mechanisms driving the progression of DLBCL and to develop new therapeutics. Here, we used single-cell transcriptome sequencing and conventional bulk next-generation sequencing (NGS) to understand the composite tumor landscape of a single patient who had experienced multiple tumor recurrences following several chemotherapy treatments. NGS revealed several key somatic mutations that are known to contribute to drug resistance. Based on gene expression profiles at the single-cell level, we identified four clusters of malignant B cells with distinct transcriptional signatures, showing high intra-tumoral heterogeneity. Among them, heterogeneity was reflected in activating several key pathways, human leukocyte antigen (HLA)-related molecules' expression, and key oncogenes, which may lead to multi-drug resistance. In addition, FOXP3+ regulatory CD4+ T cells and exhausted cytotoxic CD8+ T cells were identified, accounted for a significant proportion, and showed highly immunosuppressive properties. Finally, cell communication analysis indicated complex interactions between malignant B cells and T cells. In conclusion, this case report demonstrates the value of single-cell RNA sequencing for visualizing the tumor microenvironment and identifying potential therapeutic targets in a patient with treatment-refractory DLBCL. The combination of NGS and single-cell RNA sequencing may facilitate clinical decision-making and drug selection in challenging DLBCL cases.

Toolkit for mapping the clonal landscape of tumor-infiltrating B cells

Our current understanding of whether B cell involvement in the tumor microenvironment benefits the patient or the tumor - in distinct cancers, subcohorts and individual patients - is quite limited. Both statements are probably true in most cases: certain clonal B cell populations contribute to the antitumor response, while others steer the immune response away from the desired mechanics. To step up to a new level of understanding and managing B cell behaviors in the tumor microenvironment, we need to rationally discern these roles, which are cumulatively defined by B cell clonal functional programs, specificities of their B cell receptors, specificities and isotypes of the antibodies they produce, and their spatial interactions within the tumor environment. Comprehensive analysis of these characteristics of clonal B cell populations is now becoming feasible with the development of a whole arsenal of advanced technical approaches, which include (1) methods of single-cell and spatial transcriptomics, genomics, and proteomics; (2) methods of massive identification of B cell specificities; (3) methods of deep error-free profiling of B cell receptor repertoires. Here we overview existing techniques, summarize their current application for B cells studies and propose promising future directions in advancing B cells exploration.

Multimodal and spatially resolved profiling identifies distinct patterns of T cell infiltration in nodal B cell lymphoma entities

The redirection of T cells has emerged as an attractive therapeutic principle in B cell non-Hodgkin lymphoma (B-NHL). However, a detailed characterization of lymphoma-infiltrating T cells across B-NHL entities is missing. Here we present an in-depth T cell reference map of nodal B-NHL, based on cellular indexing of transcriptomes and epitopes, T cell receptor sequencing, flow cytometry and multiplexed immunofluorescence applied to 101 lymph nodes from patients with diffuse large B cell, mantle cell, follicular or marginal zone lymphoma, and from healthy controls. This multimodal resource revealed quantitative and spatial aberrations of the T cell microenvironment across and within B-NHL entities. Quantitative differences in PD1+ TCF7- cytotoxic T cells, T follicular helper cells or IKZF3+ regulatory T cells were linked to their clonal expansion. The abundance of PD1+ TCF7- cytotoxic T cells was associated with poor survival. Our study portrays lymphoma-infiltrating T cells with unprecedented comprehensiveness and provides a unique resource for the investigation of lymphoma biology and prognosis.

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.

Simple but powerful interactive data analysis in R with R/LinekdCharts

In research involving data-rich assays, exploratory data analysis is a crucial step. Typically, this involves jumping back and forth between visualizations that provide overview of the whole data and others that dive into details. For example, it might be helpful to have one chart showing a summary statistic for all samples, while a second chart provides details for points selected in the first chart. We present R/LinkedCharts, a framework that renders this task radically simple, requiring very few lines of code to obtain complex and general visualization, which later can be polished to provide interactive data access of publication quality.

Single-cell analysis of MYD88L265P and MYD88WT Waldenström macroglobulinemia patients

Waldenström macroglobulinemia (WM) is characterized by the expansion of clonal lymphoplasmacytic cells; the MYD88L265P somatic mutation is found in >90% of patients, but malignant B cells may still display intra-clonal heterogeneity. To assess clonal heterogeneity in WM, we generated and performed single-cell RNA sequencing of CD19+ sorted cells from five patients with MYD88 L265P and two patients with MYD88 WT genotype as well as two healthy donors. We identified distinct transcriptional patterns in the clonal subpopulations not only between the two genetically distinct WM subgroups but also among MYD88 L265P patients, which affected the B cell composition in the different subgroups. Comparison of clonal and normal/polyclonal B cells within each patient sample enabled the identification of patient-specific transcriptional changes. We identified gene signatures active in a subset of MYD88L265P patients, while other signatures were active in MYD88 WT patients. Finally, gene expression analysis showed common transcriptional features between patients compared to the healthy control but also differentially expressed genes between MYD88 L265P and MYD88 WT patients involved in distinct pathways, including NFκΒ, BCL2, and BTK. Overall, our data highlight the intra-tumor clonal heterogeneity in WM with potential prognostic and therapeutic implications.

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.

Historical perspective and future directions: computational science in immuno-oncology

Immuno-oncology holds promise for transforming patient care having achieved durable clinical response rates across a variety of advanced and metastatic cancers. Despite these achievements, only a minority of patients respond to immunotherapy, underscoring the importance of elucidating molecular mechanisms responsible for response and resistance to inform the development and selection of treatments. Breakthroughs in molecular sequencing technologies have led to the generation of an immense amount of genomic and transcriptomic sequencing data that can be mined to uncover complex tumor-immune interactions using computational tools. In this review, we discuss existing and emerging computational methods that contextualize the composition and functional state of the tumor microenvironment, infer the reactivity and clonal dynamics from reconstructed immune cell receptor repertoires, and predict the antigenic landscape for immune cell recognition. We further describe the advantage of multi-omics analyses for capturing multidimensional relationships and artificial intelligence techniques for integrating omics data with histopathological and radiological images to encapsulate patterns of treatment response and tumor-immune biology. Finally, we discuss key challenges impeding their widespread use and clinical application and conclude with future perspectives. We are hopeful that this review will both serve as a guide for prospective researchers seeking to use existing tools for scientific discoveries and inspire the optimization or development of novel tools to enhance precision, ultimately expediting advancements in immunotherapy that improve patient survival and quality of life.

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.

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.

Long-Term Survivors after Failure of Chimeric Antigen Receptor T Cell Therapy for Large B Cell Lymphoma: A Role for Allogeneic Hematopoietic Cell Transplantation? A German Lymphoma Alliance and German Registry for Stem Cell Transplantation Analysis

The outcome of patients with large B cell lymphoma (LBCL) who relapse or progress after CD19-directed chimeric antigen receptor T cell therapy (CAR-T) administered as salvage therapy beyond the second treatment line is poor. However, a minority of patients become long-term survivors despite CAR-T failure. The German Lymphoma Alliance (GLA) has proposed a hierarchical management algorithm for CAR-T failure in LBCL, aimed at allogeneic hematopoietic cell transplantation (alloHCT) as definite therapy in eligible patients. The purpose of this study was to investigate characteristics, relapse patterns, and management strategies in long-term survivors after CAR-T failure, with a particular focus on the feasibility and outcome of alloHCT. This was a retrospective analysis of all evaluable patients with a relapse/progression event (REL) observed in a previously reported GLA sample between November 2018 and May 2021. REL occurred in 214 of 356 patients (60%) who underwent CAR-T for LBCL in the previous GLA study. An evaluable dataset was available for 143 of these 214 patients (67%). Twenty-six of 143 patients (18%) survived 12 months or longer from REL, 109 (76%) died within the first year after REL, and 8 (6%) were alive but had not reached the 12-month landmark. Long-term survivors had more favorable pre-CAR-T features, had a longer interval between CAR-T and REL, and had more often received a tumor biopsy after CAR-T failure, whereas the choice of the first salvage regimen had no impact. AlloHCT was feasible in 40 of 53 patients (75%) intended and resulted in a 12-month post-transplantation overall survival of 36% in those patients who underwent transplantation with sensitive or untreated REL. AlloHCT after CAR-T failure in LBCL is feasible and may be an important contributor to long-term survival, although selection bias must be taken into account. Thus, alloHCT should be considered as a reasonable treatment option for eligible patients in this setting. However, because the overall outlook after CAR-T failure remains poor, novel effective therapeutic approaches are needed, either to allow long-term disease control per se or to improve the preconditions for successful alloHCT.

GPCR signaling contributes to immune characteristics of microenvironment and process of EBV-induced lymphomagenesis

Epstein-Barr virus (EBV) is the oncogenic driver of multiple cancers. However, the underlying mechanism of virus-cancer immunological interaction during disease pathogenesis remains largely elusive. Here we reported the first comprehensive proteogenomic characterization of natural killer/T-cell lymphoma (NKTCL), a representative disease model to study EBV-induced lymphomagenesis, incorporating genomic, transcriptomic, and in-depth proteomic data. Our multi-omics analysis of NKTCL revealed that EBV gene pattern correlated with immune-related oncogenic signaling. Single-cell transcriptome further delineated the tumor microenvironment as immune-inflamed, -deficient, and -desert phenotypes, in association with different setpoints of cancer-immunity cycle. EBV interacted with transcriptional factors to provoke GPCR interactome (GPCRome) reprogramming. Enhanced expression of chemokine receptor-1 (CCR1) on malignant and immunosuppressive cells modulated virus-cancer interaction on microenvironment. Therapeutic targeting CCR1 showed promising efficacy with EBV eradication, T-cell activation, and lymphoma cell killing in NKTCL organoid. Collectively, our study identified a previously unknown GPCR-mediated malignant progression and translated sensors of viral molecules into EBV-specific anti-cancer therapeutics.

Interactions of Indoleamine 2,3-dioxygenase-expressing LAMP3+ dendritic cells with CD4+ regulatory T cells and CD8+ exhausted T cells: synergistically remodeling of the immunosuppressive microenvironment in cervical cancer and therapeutic implications

BACKGROUND

Cervical cancer (CC) is the fourth most common cancer in women worldwide. Although immunotherapy has been applied in clinical practice, its therapeutic efficacy remains far from satisfactory, necessitating further investigation of the mechanism of CC immune remodeling and exploration of novel treatment targets. This study aimed to investigate the mechanism of CC immune remodeling and explore potential therapeutic targets.

METHODS

We conducted single-cell RNA sequencing on a total of 17 clinical specimens, including normal cervical tissues, high-grade squamous intraepithelial lesions, and CC tissues. To validate our findings, we conducted multicolor immunohistochemical staining of CC tissues and constructed a subcutaneous tumorigenesis model in C57BL/6 mice using murine CC cell lines (TC1) to evaluate the effectiveness of combination therapy involving indoleamine 2,3-dioxygenase 1 (IDO1) inhibition and immune checkpoint blockade (ICB). We used the unpaired two-tailed Student's t-test, Mann-Whitney test, or Kruskal-Wallis test to compare continuous data between two groups and one-way ANOVA with Tukey's post hoc test to compare data between multiple groups.

RESULTS

Malignant cervical epithelial cells did not manifest noticeable signs of tumor escape, whereas lysosomal-associated membrane protein 3-positive (LAMP3+ ) dendritic cells (DCs) in a mature state with immunoregulatory roles were found to express IDO1 and affect tryptophan metabolism. These cells interacted with both tumor-reactive exhausted CD8+ T cells and CD4+ regulatory T cells, synergistically forming a vicious immunosuppressive cycle and mediating CC immune escape. Further validation through multicolor immunohistochemical staining showed co-localization of neoantigen-reactive T cells (CD3+ , CD4+ /CD8+ , and PD-1+ ) and LAMP3+ DCs (CD80+ and PD-L1+ ). Additionally, a combination of the IDO1 inhibitor with an ICB agent significantly reduced tumor volume in the mouse model of CC compared with an ICB agent alone.

CONCLUSIONS

Our study suggested that a combination treatment consisting of targeting IDO1 and ICB agent could improve the therapeutic efficacy of current CC immunotherapies. Additionally, our results provided crucial insights for designing drugs and conducting future clinical trials for CC.

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.

Comparing the value of mono- vs coculture for high-throughput compound screening in hematological malignancies

Large-scale compound screens are a powerful model system for understanding variability of treatment response and discovering druggable tumor vulnerabilities of hematological malignancies. However, as mostly performed in a monoculture of tumor cells, these assays disregard modulatory effects of the in vivo microenvironment. It is an open question whether and to what extent coculture with bone marrow stromal cells could improve the biological relevance of drug testing assays over monoculture. Here, we established a high-throughput platform to measure ex vivo sensitivity of 108 primary blood cancer samples to 50 drugs in monoculture and coculture with bone marrow stromal cells. Stromal coculture conferred resistance to 52% of compounds in chronic lymphocytic leukemia (CLL) and 36% of compounds in acute myeloid leukemia (AML), including chemotherapeutics, B-cell receptor inhibitors, proteasome inhibitors, and Bromodomain and extraterminal domain inhibitors. Only the JAK inhibitors ruxolitinib and tofacitinib exhibited increased efficacy in AML and CLL stromal coculture. We further confirmed the importance of JAK-STAT signaling for stroma-mediated resistance by showing that stromal cells induce phosphorylation of STAT3 in CLL cells. We genetically characterized the 108 cancer samples and found that drug-gene associations strongly correlated between monoculture and coculture. However, effect sizes were lower in coculture, with more drug-gene associations detected in monoculture than in coculture. Our results justify a 2-step strategy for drug perturbation testing, with large-scale screening performed in monoculture, followed by focused evaluation of potential stroma-mediated resistances in coculture.

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.

Quantitative PET-based biomarkers in lymphoma: getting ready for primetime

The use of functional quantitative biomarkers extracted from routine PET-CT scans to characterize clinical responses in patients with lymphoma is gaining increased attention, and these biomarkers can outperform established clinical risk factors. Total metabolic tumour volume enables individualized estimation of survival outcomes in patients with lymphoma and has shown the potential to predict response to therapy suitable for  risk-adapted treatment approaches in clinical trials. The deployment of machine learning tools in molecular imaging research can assist in recognizing complex patterns and, with image classification, in tumour identification and segmentation of data from PET-CT scans. Initial studies using fully automated approaches to calculate metabolic tumour volume and other PET-based biomarkers have demonstrated appropriate correlation with calculations from experts, warranting further testing in large-scale studies. The extraction of computer-based quantitative tumour characterization through radiomics can provide a comprehensive view of phenotypic heterogeneity that better captures the molecular and functional features of the disease. Additionally, radiomics can be integrated with genomic data to provide more accurate prognostic information. Further improvements in PET-based biomarkers are imminent, although their incorporation into clinical decision-making currently has methodological shortcomings that need to be addressed with confirmatory prospective validation in selected patient populations. In this Review, we discuss the current knowledge, challenges and opportunities in the integration of quantitative PET-based biomarkers in clinical trials and the routine management of patients with lymphoma.

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.

LRBmat: A novel gut microbial interaction and individual heterogeneity inference method for colorectal cancer

The gut microbial community has been shown to play a significant role in various diseases, including colorectal cancer (CRC), which is a major public health concern worldwide. The accurate diagnosis and etiological analysis of CRC are crucial issues. Numerous methods have utilized gut microbiota to address these challenges; however, few have considered the complex interactions and individual heterogeneity of the gut microbiota, which are important issues in genetics and intestinal microbiology, particularly in high-dimensional cases. This paper presents a novel method called Binary matrix based on Logistic Regression (LRBmat) to address these concerns. The binary matrix in LRBmat can directly mitigate or eliminate the influence of heterogeneity, while also capturing information on gut microbial interactions with any order. LRBmat is highly adaptable and can be combined with any machine learning method to enhance its capabilities. The proposed method was evaluated using real CRC data and demonstrated superior classification performance compared to state-of-the-art methods. Furthermore, the association rules extracted from the binary matrix of the real data align well with biological properties and existing literature, thereby aiding in the etiological analysis of CRC.

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.

Patterns of Oncogene Coexpression at Single-Cell Resolution Influence Survival in Lymphoma

Cancers often overexpress multiple clinically relevant oncogenes, but it is not known if combinations of oncogenes in cellular subpopulations within a cancer influence clinical outcomes. Using quantitative multispectral imaging of the prognostically relevant oncogenes MYC, BCL2, and BCL6 in diffuse large B-cell lymphoma (DLBCL), we show that the percentage of cells with a unique combination MYC+BCL2+BCL6- (M+2+6-) consistently predicts survival across four independent cohorts (n = 449), an effect not observed with other combinations including M+2+6+. We show that the M+2+6- percentage can be mathematically derived from quantitative measurements of the individual oncogenes and correlates with survival in IHC (n = 316) and gene expression (n = 2,521) datasets. Comparative bulk/single-cell transcriptomic analyses of DLBCL samples and MYC/BCL2/BCL6-transformed primary B cells identify molecular features, including cyclin D2 and PI3K/AKT as candidate regulators of M+2+6- unfavorable biology. Similar analyses evaluating oncogenic combinations at single-cell resolution in other cancers may facilitate an understanding of cancer evolution and therapy resistance.

SIGNIFICANCE

Using single-cell-resolved multiplexed imaging, we show that selected subpopulations of cells expressing specific combinations of oncogenes influence clinical outcomes in lymphoma. We describe a probabilistic metric for the estimation of cellular oncogenic coexpression from IHC or bulk transcriptomes, with possible implications for prognostication and therapeutic target discovery in cancer. This article is highlighted in the In This Issue feature, p. 1027.

Novel insights into Hodgkin lymphoma biology by single-cell analysis

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

Synergistic disruption of BTK and BCL-2 causes apoptosis while inducing ferroptosis in double-hit lymphoma

Double-hit lymphoma (DHL) is an aggressive subset of Diffuse Large B-cell Lymphoma (DLBCL) with poor outcomes and without satisfying treatment options. BTK inhibitor monotherapy is ineffective to suppress aggressive lymphoma. Hence, combination with other potential agents is warranted. Here, we demonstrated the second generation of BTK inhibitor, zanubrutinib, and a BCL-2 inhibitor, navitoclax, worked in synergistic manner to suppress DHL. Comprehensive in silico approach by interrogating single-cell to bulk-level profiling was employed along with in vitro and in vivo validation in DHL cell lines. Ablation of BTK enhanced sensitivity to navitoclax and suppressed proliferation of DHL cells. Combination of second generation of BTK inhibitor with navitoclax synergistically suppressed DLBCL cells with higher synergy score in DHL subset. The drug combination triggered apoptosis and ferroptosis, with the latter being characterized by reactive oxygen species (ROS) accumulation, extensive lipid peroxidation, and depletion of reduced glutathione. Moreover, ablation of BTK sensitized DHL cells to ferroptosis. Mechanistically, disruption of BTK and BCL-2 triggered ferroptosis by downregulating NRF2 and HMOX1, while deactivating GPX4. Combination of zanubrutinib and navitoclax effectively suppressed tumor growth in vivo. Our data suggest that zanubrutinib and navitoclax synergistically suppressed DHL by inducing apoptosis and ferroptosis.

The Immunology of DLBCL

Diffuse large B-cell lymphoma (DLBCL) is an aggressive malignancy and is the most common type of malignant lymphoid neoplasm. While some DLBCLs exhibit strong cell-autonomous survival and proliferation activity, others depend on interactions with non-malignant cells for their survival and proliferation. Recent next-generation sequencing studies have linked these interactions with the molecular classification of DLBCL. For example, germinal center B-cell-like DLBCL tends to show strong associations with follicular T cells and epigenetic regulation of immune recognition molecules, whereas activated B-cell-like DLBCL shows frequent genetic aberrations affecting the class I major histocompatibility complex. Single-cell technologies have also provided detailed information about cell-cell interactions and the cell composition of the microenvironment of DLBCL. Aging-related immunological deterioration, i.e., immunosenescence, also plays an important role in DLBCL pathogenesis, especially in Epstein-Barr virus-positive DLBCL. Moreover, DLBCL in "immune-privileged sites"-where multiple immune-modulating mechanisms exist-shows unique biological features, including frequent down-regulation of immune recognition molecules and an immune-tolerogenic tumor microenvironment. These advances in understanding the immunology of DLBCL may contribute to the development of novel therapies targeting immune systems.

Phenotypic plasticity of malignant T cells in blood and skin of a Sézary syndrome patient revealed by single cell transcriptomics

Background

Sézary Syndrome (SS) is an aggressive leukemic variant of cutaneous T-cell lymphomas (CTCL). In SS patients, malignant T cells are circulating through the blood and cause erythroderma.

Objective

To compare the transcriptome of single cells in blood and skin samples from a patient with advanced SS.

Methods

We utilized combined single cell RNA and T-cell receptor (TCR) sequencing (scRNA-seq).

Results

We scrutinized the malignant T cells in blood and skin in an unbiased manner without pre-sorting of cells. We observed different phenotypes of the same monoclonal malignant T-cell population, confirmed by TCR sequencing and inferred copy number variation analysis. Malignant T cells present in the circulating blood expressed genes resembling central memory T cells such as CCR7, IL7R and CD27. In the skin, we detected two major malignant T-cell populations: One subpopulation was closely related to the malignant T cells from the blood, while the other subpopulation expressed genes reminiscent of skin resident effector memory T cells including GZMB and NKG7. Pseudotime analysis indicated crucial transcriptomic changes in the transition of malignant T cells between blood and skin. These changes included the differential regulation of TXNIP, a putative tumor suppressor in CTCL, and the adaptation to the hypoxic conditions in the skin. Tumor cell proliferation in the skin was supported by stimulating interactions between myeloid cells and malignant T cells.

Conclusions

Using scRNA-seq we detected a high degree of functional heterogeneity within the malignant T-cell population in SS and highlighted crucial differences between SS cells in blood and skin.

Quantification of spatial pharmacogene expression heterogeneity in breast tumors

BACKGROUND

Chemotherapeutic drug concentrations vary across different regions of tumors and this is thought to be involved in development of chemotherapy resistance. Insufficient drug delivery to some regions of the tumor may be due to spatial differences in expression of genes involved in the disposition, transport, and detoxification of drugs (pharmacogenes). Therefore, in this study, we analyzed the spatial expression of 286 pharmacogenes in six breast cancer tissues using the recently developed Visium spatial transcriptomics platform to (1) determine if these pharmacogenes are expressed heterogeneously across tumor tissue and (2) to determine which pharmacogenes have the most spatial expression heterogeneity.

METHODS AND RESULTS

The spatial transcriptomics technology sequences the transcriptome of 55 um diameter barcoded sections (spots) across a tissue sample. We analyzed spatial gene expression profiles of four biobank-sourced breast tumor samples in addition to two breast tumor sample datasets from 10× Genomics. We define heterogeneity as the interquartile range of read counts. Collectively, we identified 8887 spots in tumor regions, 3814 in stroma, 44 in lymphocytes, and 116 in normal regions based on pathologist annotation of the tissues. We showed statistically significant differences in expression of pharmacogenes in tumor regions compared to surrounding non-tumor regions. We also observed that the most heterogeneously expressed genes within tumor regions were involved in reactive oxygen species (ROS) handling and detoxification mechanisms. GPX4, GSTP1, MGST3, SOD1, CYP4Z1, CYB5R3, GSTK1, and NAT1 showed the most heterogeneous expression within tumor regions.

CONCLUSIONS

The heterogeneous expression of these pharmacogenes may have important implications for cancer therapy due to their ability to impact drug distribution and efficacy throughout the tumor. Our results suggest that chemoresistance caused by expression of GPX4, GSTP1, MGST3, and SOD1 may be intrinsic, not acquired, since the heterogeneity is not specific to chemotherapy-treated samples or cell type. Additionally, we identified candidate chemoresistance pharmacogenes that can be further tested through focused follow-up studies.

Functional analysis of structural variants in single cells using Strand-seq

Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their functional consequences. We present a computational method, scNOVA, which uses Strand-seq to perform haplotype-aware integration of SV discovery and molecular phenotyping in single cells by using nucleosome occupancy to infer gene expression as a readout. Application to leukemias and cell lines identifies local effects of copy-balanced rearrangements on gene deregulation, and consequences of SVs on aberrant signaling pathways in subclones. We discovered distinct SV subclones with dysregulated Wnt signaling in a chronic lymphocytic leukemia patient. We further uncovered the consequences of subclonal chromothripsis in T cell acute lymphoblastic leukemia, which revealed c-Myb activation, enrichment of a primitive cell state and informed successful targeting of the subclone in cell culture, using a Notch inhibitor. By directly linking SVs to their functional effects, scNOVA enables systematic single-cell multiomic studies of structural variation in heterogeneous cell populations.

Impact of interaction networks of B cells with other cells on tumorigenesis, progression and response to immunotherapy of renal cell carcinoma: A review

Ample evidence indicates that the development and progression of renal cell carcinoma (RCC) are complex pathological processes involving interactions between tumor cells, immune cells and stromal components. Tumor infiltrated immune cells determine whether tumor advancement is promoted or inhibited. Among them, infiltrated B lymphocytes are present in all stages of RCC, playing a major role in determining tumor formation and advancement, as an essential part in the tumor microenvironment (TME). Although the advent of targeted and immune therapies has remarkably improved the survival of patients with advanced RCC, few cases can achieve complete response due to drug resistance. In this review article, we intend to summary the recent studies that outline the interaction networks of B cells with other cells, discuss the role of B cells in RCC development and progression, and assess their impact on RCC immunotherapy.

TCR-Independent Metabolic Reprogramming Precedes Lymphoma-Driven Changes in T-cell Fate

Chronic T-cell receptor (TCR) signaling in the tumor microenvironment is known to promote T-cell dysfunction. However, we reasoned that poorly immunogenic tumors may also compromise T cells by impairing their metabolism. To address this, we assessed temporal changes in T-cell metabolism, fate, and function in models of B-cell lymphoma driven by Myc, a promoter of energetics and repressor of immunogenicity. Increases in lymphoma burden most significantly impaired CD4+ T-cell function and promoted regulatory T cell (Treg) and Th1-cell differentiation. Metabolomic analyses revealed early reprogramming of CD4+ T-cell metabolism, reduced glucose uptake, and impaired mitochondrial function, which preceded changes in T-cell fate. In contrast, B-cell lymphoma metabolism remained robust during tumor progression. Finally, mitochondrial functions were impaired in CD4+ and CD8+ T cells in lymphoma-transplanted OT-II and OT-I transgenic mice, respectively. These findings support a model, whereby early, TCR-independent, metabolic interactions with developing lymphomas limits T cell-mediated immune surveillance.

Intratumor heterogeneity and T cell exhaustion in primary CNS lymphoma

BACKGROUND

Primary central nervous system lymphoma (PCNSL) is a rare lymphoma of the central nervous system, usually of diffuse large B cell phenotype. Stereotactic biopsy followed by histopathology is the diagnostic standard. However, limited material is available from CNS biopsies, thus impeding an in-depth characterization of PCNSL.

METHODS

We performed flow cytometry, single-cell RNA sequencing, and B cell receptor sequencing of PCNSL cells released from biopsy material, blood, and cerebrospinal fluid (CSF), and spatial transcriptomics of biopsy samples.

RESULTS

PCNSL-released cells were predominantly activated CD19+CD20+CD38+CD27+ B cells. In single-cell RNA sequencing, PCNSL cells were transcriptionally heterogeneous, forming multiple malignant B cell clusters. Hyperexpanded B cell clones were shared between biopsy- and CSF- but not blood-derived cells. T cells in the tumor microenvironment upregulated immune checkpoint molecules, thereby recognizing immune evasion signals from PCNSL cells. Spatial transcriptomics revealed heterogeneous spatial organization of malignant B cell clusters, mirroring their transcriptional heterogeneity across patients, and pronounced expression of T cell exhaustion markers, co-localizing with a highly malignant B cell cluster.

CONCLUSIONS

Malignant B cells in PCNSL show transcriptional and spatial intratumor heterogeneity. T cell exhaustion is frequent in the PCNSL microenvironment, co-localizes with malignant cells, and highlights the potential of personalized treatments.

Follicular Lymphoma Microenvironment Characteristics Associated with Tumor Cell Mutations and MHC Class II Expression

Follicular lymphoma (FL) is a B-cell malignancy with a complex tumor microenvironment that is rich in nonmalignant immune cells. We applied single-cell RNA sequencing to characterize the diverse tumor and immune cell populations of FL and identified major phenotypic subsets of FL T cells, including a cytotoxic CD4 T-cell population. We characterized four major FL subtypes with differential representation or relative depletion of distinct T-cell subsets. By integrating exome sequencing, we observed that somatic mutations are associated with, but not definitive for, reduced MHC expression on FL cells. In turn, expression of MHCII genes by FL cells was associated with significant differences in the proportions and targetable immunophenotypic characteristics of T cells. This provides a classification framework of the FL microenvironment in association with FL genotypes and MHC expression, and informs different potential immunotherapeutic strategies based upon tumor cell MHCII expression.

SIGNIFICANCE

We have characterized the FL-infiltrating T cells, identified cytotoxic CD4 T cells as an important component that is associated with tumor cell-intrinsic characteristics, and identified sets of targetable immune checkpoints on T cells that differed from FLs with normal versus low MHC expression. See related commentary by Melnick, p. 374. This article is highlighted in the In This Issue feature, p. 369.

Lkb1 aggravates diffuse large B-cell lymphoma by promoting the function of Treg cells and immune escape

Background

Regulatory T cells (Tregs) induce immune responses and may contribute to immune escape in tumors. Accumulation of Tregs in tumors represents a critical barrier to anti-tumor immunity and immunotherapy. However, conflicting results describing the role of Tregs in lymphoma warrant further investigation. The precise features and mechanisms underlying the alteration in Tregs in diffuse large B-cell lymphoma (DLBCL) are not well understood yet. In this study, we analyzed the mechanism underlying the observed alterations in Tregs in DLBCL and examined the effect of Lkb1 expression on the immunosuppressive function of human Tregs.

Methods

Flow cytometry and immunofluorescence were used to analyze the proportion of Tregs and effector Tregs in the peripheral blood and lymph nodes of patients with DLBCL and control group. In vitro culture assays were used to analyze the immunosuppressive function of Tregs in the two groups. Transcriptome sequencing was performed to analyze the differentially expressed genes in the two groups, and the transcription level and protein expression of Lkb1 in the two groups were detected using RT-PCR and WES microprotein technology. Lentiviral vectors were constructed to explore the functional changes of Tregs with stable upregulation and downregulation of Lkb1. Finally, a humanized murine lymphoma model was established to study the function of Lkb1 in Tregs in the pathogenesis of DLBCL.

Results

The number of Tregs was found to be dramatically increased in peripheral blood and tumor tissue in DLBCL patients compared with that in healthy controls, and decreased after treatment. Tregs from DLBCL patients exhibited multiple enhanced functions, including increased inhibition of CD8⁺cytotoxic T cells (CTL) against tumor cells, enhanced suppression of CD8⁺CTL secretion of granular enzyme, and suppression of CD8⁺CTL degranulation. Lkb1 was found to be upregulated in Tregs of DLBCL patients. Furthermore, Lkb1 contributes to Treg immunosuppressive function in DLBCL by regulating the mevalonate pathway. Finally, deletion of Lkb1 in Tregs suppressed tumor growth and promoted anti-tumor immunity in a DLBCL murine model.

Conclusions

These findings confirmed that Lkb1-regulated Tregs are critical for immune escape in DLBCL, which emphasizes that Lkb1 is a potential target for the immunotherapy of DLBCL.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03588-0.