Understanding the Immune-Stroma Microenvironment in B Cell Malignancies for Effective Immunotherapy

Malnutrition in cancer patients: Causes, consequences and treatment options

Cancer patients are at a high risk of malnutrition and disease-associated catabolic derangements. It is important to differentiate between 'simple' - voluntary or involuntary - caloric restriction with protein-sparing ketogenic metabolic adaptation and cachexia, characterized by the combination of weight loss and dysmetabolism, most prominently systemic inflammation. While both conditions result in the sacrifice of fat and protein stores and thus impact on treatment tolerance, complication rates and survival, the presence of metabolic derangements is especially dangerous by straining multiple organ functions. To avoid underdiagnosing and undertreating malnutrition, all cancer patients should be routinely screened for nutritional risk. At-risk patients require comprehensive assessment for contributing and treatable causes and, if available, multi-professional efforts to improve food intake, support anabolism, alleviate distress and antagonize pro-inflammatory processes. In curative settings, anabolic support should accompany or even precede anticancer treatments. Prehabilitation before major surgery, has been studied extensively, including muscle training as well as nutritional and/or psychological support. Recent meta-analyses report a consistent benefit on functional capacity and possible improvement in postoperative complications and length of hospital stay. In palliative settings, prevailing catabolic derangements require careful assessment of the individual constellation of disturbed functions and an empathic evaluation of benefits and risks of nutritional interventions. This is of special relevance in patients with an expected survival of less than a few months. Due to the complex interactions of mechanical, metabolic and psychological factors, multi-professional teams should be involved.

Cancer-on-chip models for metastasis: importance of the tumor microenvironment

Cancer-on-chip (CoC) models, based on microfluidic chips harboring chambers for 3D tumor-cell culture, enable us to create a controlled tumor microenvironment (TME). CoC models are therefore increasingly used to systematically study effects of the TME on the various steps in cancer metastasis. Moreover, CoC models have great potential for developing novel cancer therapies and for predicting patient-specific response to cancer treatments. We review recent developments in CoC models, focusing on three main TME components: (i) the anisotropic extracellular matrix (ECM) architectures, (ii) the vasculature, and (iii) the immune system. We aim to provide guidance to biologists to choose the best CoC approach for addressing questions about the role of the TME in metastasis, and to inspire engineers to develop novel CoC technologies.

Immune and stromal transcriptional patterns that influence the outcome of classic Hodgkin lymphoma

Classic Hodgkin lymphoma (cHL) is characterized by a rich immune microenvironment as the main tumor component. It involves a broad range of cell populations, which are largely unexplored, even though they are known to be essential for growth and survival of Hodgkin and Reed-Sternberg cells. We profiled the gene expression of 25 FFPE cHL samples using NanoString technology and resolved their microenvironment compositions using cell-deconvolution tools, thereby generating patient-specific signatures. The results confirm individual immune fingerprints and recognize multiple clusters enriched in refractory patients, highlighting the relevance of: (1) the composition of immune cells and their functional status, including myeloid cell populations (M1-like, M2-like, plasmacytoid dendritic cells, myeloid-derived suppressor cells, etc.), CD4-positive T cells (exhausted, regulatory, Th17, etc.), cytotoxic CD8 T and natural killer cells; (2) the balance between inflammatory signatures (such as IL6, TNF, IFN-γ/TGF-β) and MHC-I/MHC-II molecules; and (3) several cells, pathways and genes related to the stroma and extracellular matrix remodeling. A validation model combining relevant immune and stromal signatures identifies patients with unfavorable outcomes, producing the same results in an independent cHL series. Our results reveal the heterogeneity of immune responses among patients, confirm previous findings, and identify new functional phenotypes of prognostic and predictive utility.

CAR-T Cell Therapy for Classical Hodgkin Lymphoma

Classical Hodgkin lymphoma (cHL) is a malignancy characterized by the presence of Hodgkin and Reed-Sternberg (HRS) cells within a complex tumor microenvironment (TME). Despite advances in conventional therapies, a subset of cHL patients experience relapse or refractory disease, necessitating the exploration of novel treatment strategies. Chimeric antigen receptor T cell (CAR-T cell) therapy has emerged as a promising approach for the management of cHL, harnessing the power of genetically modified T cells to recognize and eliminate tumor cells. In this article, we provide an overview of the pathogenesis of cHL, highlighting the key molecular and cellular mechanisms involved. Additionally, we discuss the rationale for the development of CAR-T cell therapy in cHL, focusing on the identification of suitable targets on HRS cells (such as CD30, CD123, LMP1, and LMP2A), clonotypic lymphoma initiating B cells (CD19, CD20), and cells within the TME (CD123, CD19, CD20) for CAR-T cell design. Furthermore, we explore various strategies employed to enhance the efficacy and safety of CAR-T cell therapies in the treatment of cHL. Finally, we present an overview of the results obtained from clinical trials evaluating the efficacy of CAR-T cell therapies in cHL, highlighting their potential as a promising therapeutic option. Collectively, this article provides a comprehensive review of the current understanding of cHL pathogenesis and the rationale for CAR-T cell therapy development, offering insights into the future directions of this rapidly evolving field.

Tumor Regression upon Intratumoral and Subcutaneous Dosing of the STING Agonist ALG-031048 in Mouse Efficacy Models

Stimulator of interferon genes (STING) agonists have shown potent anti-tumor efficacy in various mouse tumor models and have the potential to overcome resistance to immune checkpoint inhibitors (ICI) by linking the innate and acquired immune systems. First-generation STING agonists are administered intratumorally; however, a systemic delivery route would greatly expand the clinical use of STING agonists. Biochemical and cell-based experiments, as well as syngeneic mouse efficacy models, were used to demonstrate the anti-tumoral activity of ALG-031048, a novel STING agonist. In vitro, ALG-031048 is highly stable in plasma and liver microsomes and is resistant to degradation via phosphodiesterases. The high stability in biological matrices translated to good cellular potency in a HEK 293 STING R232 reporter assay, efficient activation and maturation of primary human dendritic cells and monocytes, as well as long-lasting, antigen-specific anti-tumor activity in up to 90% of animals in the CT26 mouse colon carcinoma model. Significant reductions in tumor growth were observed in two syngeneic mouse tumor models following subcutaneous administration. Combinations of ALG-031048 and ICIs further enhanced the in vivo anti-tumor activity. This initial demonstration of anti-tumor activity after systemic administration of ALG-031048 warrants further investigation, while the combination of systemically administered ALG-031048 with ICIs offers an attractive approach to overcome key limitations of ICIs in the clinic.

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.

Recent revelations and future directions using single-cell technologies in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a clinically and biologically heterogeneous disease with varying outcomes. In the last decade, the application of next-generation sequencing technologies has allowed extensive mapping of disease-specific genomic, epigenomic, immunogenetic, and transcriptomic signatures linked to CLL pathogenesis. These technologies have improved our understanding of the impact of tumor heterogeneity and evolution on disease outcome, although they have mostly been performed on bulk preparations of nucleic acids. As a further development, new technologies have emerged in recent years that allow high-resolution mapping at the single-cell level. These include single-cell RNA sequencing for assessment of the transcriptome, both of leukemic and non-malignant cells in the tumor microenvironment; immunogenetic profiling of B and T cell receptor rearrangements; single-cell sequencing methods for investigation of methylation and chromatin accessibility across the genome; and targeted single-cell DNA sequencing for analysis of copy-number alterations and single nucleotide variants. In addition, concomitant profiling of cellular subpopulations, based on protein expression, can also be obtained by various antibody-based approaches. In this review, we discuss different single-cell sequencing technologies and how they have been applied so far to study CLL onset and progression, also in response to treatment. This latter aspect is particularly relevant considering that we are moving away from chemoimmunotherapy to targeted therapies, with a potentially distinct impact on clonal dynamics. We also discuss new possibilities, such as integrative multi-omics analysis, as well as inherent limitations of the different single-cell technologies, from sample preparation to data interpretation using available bioinformatic pipelines. Finally, we discuss future directions in this rapidly evolving field.

T-cell immunoglobulin mucin molecule-3, transformation growth factor β, and chemokine-12 and the prognostic status of diffuse large B-cell lymphoma

BACKGROUND

The effects of T-cell immunoglobulin mucin molecule-3 (Tim-3), transforming growth factor β (TGF-β), and chemokine-12 (CXCL12) expression on the prognosis of patients with diffuse large B-cell lymphoma (DLBCL) have not been elucidated.

AIM

To examine the correlation between Tim-3, TGF-β and CXCL12 expression and DLBCL prognosis.

METHODS

Lymph node tissues of 97 patients with DLBCL and 93 normal-response hyperplastic lymph node tissues treated from January 2017 to May 2019 were selected as the DLBCL and control groups, respectively. The expression of Tim-3, TGF-β, and CXCL12 was detected immunohistochemically. Patients were followed up for 3 years, and progression-free survival was recorded. Cox multifactorial analysis was performed to analyze the risk factors for poor prognosis.

RESULTS

The positive expression rates of Tim-3, TGF-β, and CXCL12 were higher in DLBCL tissues than in non-cancerous (control) tissues (P < 0.05). One-year post-surgery, the positive expression rates of Tim-3, TGF-β, and CXCL12 were higher in patients with effective treatment than in those with ineffective treatment (P < 0.05). The 3-year progression-free survival of 97 patients with DLBCL was 67.01% (65/97). Univariate analysis revealed that clinical stage, bone marrow infiltration, International Prognostic Index (IPI) score, Tim-3 positivity, TGF-β positivity, and CXCL12 positivity were associated with poor prognosis (P < 0.05). Multivariate Cox regression analysis demonstrated that clinical stage III–IV, bone marrow infiltration, mediate-to-high-risk IPI scores, Tim-3 positivity, TGF-β positivity, and CXCL12 positivity were independent risk factors affecting prognosis (P < 0.05).

CONCLUSION

DLBCL tissues exhibit high positive expression of Tim-3, TGF-β, and CXCL12, and a high expression of all three indicates a poor prognosis.

A Naive Bayes model on lung adenocarcinoma projection based on tumor microenvironment and weighted gene co-expression network analysis

Based on the lung adenocarcinoma (LUAD) gene expression data from the cancer genome atlas (TCGA) database, the Stromal score, Immune score and Estimate score in tumor microenvironment (TME) were computed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm. And gene modules significantly related to the three scores were identified by weighted gene co-expression network analysis (WGCNA). Based on the correlation coefficients and P values, 899 key genes affecting tumor microenvironment were obtained by selecting the two most correlated modules. It was suggested through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis that these key genes were significantly involved in immune-related or cancer-related terms. Through univariate cox regression and elastic network analysis, genes associated with prognosis of the LUAD patients were screened out and their prognostic values were further verified by the survival analysis and the University of ALabama at Birmingham CANcer (UALCAN) database. The results indicated that eight genes were significantly related to the overall survival of LUAD. Among them, six genes were found differentially expressed between tumor and control samples. And immune infiltration analysis further verified that all the six genes were significantly related to tumor purity and immune cells. Therefore, these genes were used eventually for constructing a Naive Bayes projection model of LUAD. The model was verified by the receiver operating characteristic (ROC) curve where the area under curve (AUC) reached 92.03%, which suggested that the model could discriminate the tumor samples from the normal accurately. Our study provided an effective model for LUAD projection which improved the clinical diagnosis and cure of LUAD. The result also confirmed that the six genes in the model construction could be the potential prognostic biomarkers of LUAD.

CCL8 as a promising prognostic factor in diffuse large B-cell lymphoma via M2 macrophage interactions: A bioinformatic analysis of the tumor microenvironment

Backgrounds

Prior investigations of the tumor microenvironment (TME) of diffuse large B-cell lymphoma (DLBCL) have shown that immune and stromal cells are key contributing factors to patients’ outcome. However, challenges remain in finding reliable prognostic biomarkers based on cell infiltration. In this study, we attempted to shed some light on chemokine C–C motif chemokine ligand 8 (CCL8) in DLBCL via interaction with M2 macrophages.

Methods

The Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm was applied to evaluate immune and stromal scores from transcriptomic profiles of 443 DLBCL samples from The Cancer Genome Atlas (TCGA) and GSE10846 datasets. Immune cell infiltration (ICI) clusters were obtained based on different immune cell infiltrations of each sample, and gene clusters were derived through differentially expressed genes (DEGs) between the distinct ICI clusters. Five immune-related hub genes related to overall survival (OS) and clinical stages were obtained by COX regression analysis and protein–protein interaction (PPI) network construction then verified by quantitative real-time PCR (qPCR) and immunofluorescence staining in the FFPE tissues. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and TIMER websites were employed to explore the biological functions of CCL8-related DEGs. Uni- and multivariable Cox regression analyses were performed to analyze CCL8 as an independent prognostic risk factor in GSE10846 and were verified in other independent GEO cohorts.

Results

A higher stromal score was associated with favorable prognosis in DLBCL. Patients in the ICI B cluster and gene B clusters had a better follow-up status with a higher programmed death ligand 1 (PD-L1) and cytotoxic T-lymphocyte antigen 4 (CTLA4) expression. Most of ICI-related DEGs were enriched for immune-related signaling pathways. Five hub genes with a distinct prognosis association were identified, including CD163, which is a biomarker of M2 macrophages, and CCL8. Abundant M2 macrophages were discovered in the high-CCL8 expression group. The functional analysis indicated that CCL8 is a key component of immune-related processes and secretory granule groups. Cox regression analysis and data from other GSE datasets yielded additional evidence of the prognostic value of CCL8 in DLBCL.

Conclusions

CCL8 has been implicated in macrophage recruitment in several solid tumors, and only a few reports have been published on the role of CCL8 in the pathogenesis of hematological malignancies. This article attempted to find out TME-related genes that associated with the survival in DLBCL patients. CCL8 was identified to be involved in immune activities. Importantly, a series of bioinformatics analysis indicated that CCL8 might become an effective target for DLBCL, which interacts with M2 macrophage and immune checkpoint. The potential related mechanisms need to be further elucidated.

Formation of Lymphoma Hybrid Spheroids and Drug Testing in Real Time with the Use of Fluorescence Optical Tweezers

Interactions between stromal and lymphoma cells in the bone marrow are closely related to drug resistance and therapy failure. Physiologically relevant pre-clinical three-dimensional (3D) models recapitulating lymphoma microenvironmental complexity do not currently exist. In this study, we proposed a scheme for optically controlled hybrid lymphoma spheroid formation with the use of optical tweezers (OT). Following the preparation of stromal spheroids using agarose hydrogel, two aggressive non-Hodgkin lymphoma B-cell lines, Ri-1 (DLBCL) and Raji (Burkitt lymphoma), were used to conduct multi-cellular spheroid formation driven by in-house-developed fluorescence optical tweezers. Importantly, the newly formed hybrid spheroid preserved the 3D architecture for the next 24 h. Our model was successfully used for the evaluation of the influence of the anticancer agents doxorubicin (DOX), ibrutinib (IBR), and AMD3100 (plerixafor) on the adhesive properties of lymphoma cells. Importantly, our study revealed that a co-treatment of DOX and IBR with AMD3100 affects the adhesion of B-NHL lymphoma cells.

Age-Associated B Cell Features of the Murine High-Grade B Cell Lymphoma Bc.DLFL1 and Its Extranodal Expansion in Abdominal Adipose Tissues

Diffuse large B cell lymphoma comprises a heterogeneous group of B cell-derived tumors, with different degrees of aggressiveness, as defined by their cellular origin and tissue microenvironment. Using the spontaneous Bc.DLFL1 lymphoma originating from a BALB/c mouse as a diffuse large B cell lymphoma model, in this study we demonstrate that the lymphoma cells display surface phenotype, IgH V-region somatic mutations, transcription factor characteristics and in vivo location to splenic extrafollicular regions of age-associated B cells (ABCs), corresponding to T-bet⁺ and Blimp-1⁺/CD138^- plasmablasts derivation. The expansion of lymphoma cells within lymphoid tissues took place in a close arrangement with CD11c⁺ dendritic cells, whereas the extranodal infiltration occurred selectively in the mesentery and omentum containing resident gp38/podoplanin⁺ fibroblastic reticular cells. Antagonizing BAFF-R activity by mBR3-Fc soluble receptor fusion protein led to a significant delay of disease progression. The extranodal expansion of Bc.DLFL1 lymphoma within the omental and mesenteric adipose tissues was coupled with a significant change of the tissue cytokine landscape, including both shared alterations and tissue-specific variations. Our findings indicate that while Bc.DLFL1 cells of ABC origin retain the positioning pattern within lymphoid tissues of their physiological counterpart, they also expand in non-lymphoid tissues in a BAFF-dependent manner, where they may alter the adipose tissue microenvironment to support their extranodal growth.

Specific TCR V-J gene segment recombinations leading to the identification pan-V-J CDR3s associated with survival distinctions: diffuse large B-cell lymphoma

In the diffuse large B-cell lymphoma (DLBCL) setting, we examined lymph node biopsy, T-cell receptor features, and the DLBLC patient human leukocyte antigen (HLA) alleles, to provide a basis for assessing survival distinctions represented by the National Cancer Institute Center for Cancer Research (NCICCR) dataset. While previous analyses of other cancer datasets have indicated that specific T-cell receptor (TCR) V or J gene segments, independently, can be associated with a survival distinction, we have here identified V-J recombinations, representing specific V and J gene segments associated with survival distinctions. As specific V-J recombinations represent relatively conserved complementarity determining region-3 (CDR3) amino acid sequences, we assessed the entire DLBCL NCICCR dataset for such conserved CDR3 features. Overall, this approach indicated the opportunity of identifying DLBCL patient subpopulations with TCR CDR3 features, and HLA alleles, with significant survival distinctions, possibly identifying cohorts more likely to benefit from a given immunotherapy.