Increased frequencies of circulating and tumor-resident Vδ1+ T cells in patients with diffuse large B-cell lymphoma

Landscape of unconventional γδ T cell subsets in cancer

T cells are broadly categorized into two groups, namely conventional and unconventional T cells. Conventional T cells are the most prevalent and well-studied subset of T cells. On the other hand, unconventional T cells exhibit diverse functions shared between innate and adaptive immune cells. During recent decades, γδ T cells have received attention for their roles in cancer immunity. These cells can detect various molecules, such as lipids and metabolites. Also, they are known for their distinctive ability to recognize and target cancer cells in the tumor microenvironment (TME). This feature of γδ T cells could provide a unique therapeutic tool to fight against cancer. Understanding the role of γδ T cells in TME is essential to prepare the groundwork to use γδ T cells for clinical purposes. Here, we provide recent knowledge regarding the role γδ T cell subsets in different cancer types.

Prediction significance of autophagy-related genes in survival probability and drug resistance in diffuse large B-cell lymphoma

BACKGROUND/AIMS

Diffuse large B-cell lymphoma (DLBCL), the most common subtype of non-Hodgkin lymphoma, has significant prognostic heterogeneity. This study aimed to generate a prognostic prediction model based on autophagy-related genes for DLBCL patients.

METHODS

Utilizing bioinformatics techniques, we analyzed the clinical information and transcriptome data of DLBCL patients from the Gene Expression Omnibus (GEO) database. Through unsupervised clustering, we identified new autophagy-related molecular subtypes and pinpointed differentially expressed genes (DEGs) between these subtypes. Based on these DEGs, a prognostic model was constructed using Cox and Lasso regression. The effectiveness, accuracy, and clinical utility of this prognostic model were assessed using numerous independent validation cohorts, survival analyses, receiver operating characteristic (ROC) curves, multivariate Cox regression analysis, nomograms, and calibration curves. Moreover, functional analysis, immune cell infiltration, and drug sensitivity analysis were performed.

RESULTS

DLBCL patients with different clinical characterizations (age, molecular subtypes, ECOG scores, and stages) showed different expression features of autophagy-related genes. The prediction model was constructed based on the eight autophagy-related genes (ADD3, IGFBP3, TPM1, LYZ, AFDN, DNAJC10, GLIS3, and CCDC102A). The prognostic nomogram for overall survival of DLBCL patients incorporated risk level, stage, ECOG scores, and molecular subtypes, showing excellent agreement between observed and predicted outcomes. Differences were noted in the proportions of immune cells (native B cells, Treg cells, CD8+ T cell, CD4+ memory activated T cells, gamma delta T cells, macrophages M1, and resting mast cells) between high-risk and low-risk groups. LYZ and ADD3 exhibited correlations with drug resistance to most chemotherapeutic drugs.

CONCLUSIONS

This study established a novel prognostic assessment model based on the expression profile of autophagy-related genes and clinical characteristics of DLBCL patients, explored immune infiltration and predicted drug resistance, which may guide precise and individualized immunochemotherapy regimens.

CD8 T-cell subsets: heterogeneity, functions, and therapeutic potential

CD8 T cells play crucial roles in immune surveillance and defense against infections and cancer. After encountering antigenic stimulation, naïve CD8 T cells differentiate and acquire effector functions, enabling them to eliminate infected or malignant cells. Traditionally, cytotoxic T cells, characterized by their ability to produce effector cytokines and release cytotoxic granules to directly kill target cells, have been recognized as the constituents of the predominant effector T-cell subset. However, emerging evidence suggests distinct subsets of effector CD8 T cells that each exhibit unique effector functions and therapeutic potential. This review highlights recent advancements in our understanding of CD8 T-cell subsets and the contributions of these cells to various disease pathologies. Understanding the diverse roles and functions of effector CD8 T-cell subsets is crucial to discern the complex dynamics of immune responses in different disease settings. Furthermore, the development of immunotherapeutic approaches that specifically target and regulate the function of distinct CD8 T-cell subsets holds great promise for precision medicine.

γδ T cells in immunotherapies for B-cell malignancies

Despite the advancements in therapy for B cell malignancies and the increase in long-term survival of patients, almost half of them lead to relapse. Combinations of chemotherapy and monoclonal antibodies such as anti-CD20 leads to mixed outcomes. Recent developments in immune cell-based therapies are showing many encouraging results. γδ T cells, with their potential of functional plasticity and their anti-tumoral properties, emerged as good candidates for cancer immunotherapies. The representation and the diversity of γδ T cells in tissues and in the blood, in physiological conditions or in B-cell malignancies such as B cell lymphoma, chronic lymphoblastic leukemia or multiple myeloma, provides the possibility to manipulate them with immunotherapeutic approaches for these patients. In this review, we summarized several strategies based on the activation and tumor-targeting of γδ T cells, optimization of expansion protocols, and development of gene-modified γδ T cells, using combinations of antibodies and therapeutic drugs and adoptive cell therapy with autologous or allogenic γδ T cells following potential genetic modifications.

Dysfunctions of innate and adaptive immune tumor microenvironment in Waldenström macroglobulinemia

Waldenström macroglobulinemia (WM) is a rare subtype of non-Hodgkin lymphoma characterized by malignant lymphoplasmacytic cells in the bone marrow (BM). To dissect the pathophysiology of WM, we evaluated clonal cells by mapping of B cell lymphomagenesis with adaptive and innate immune tumor microenvironment (TME) in the BM of WM patients using mass cytometry (CyTOF). In-depth immunophenotypic profiling of WM cells exhibited profound expansion of clonal cells in both unswitched and switched memory B cells and also plasma cells with aberrant expression variations. WM B lymphomagenesis was associated with reduction of most B cell precursors assessed with the same clonally restricted light chain and phenotypic changes. The immune TME was infiltrated by mature monocytes, neutrophils and adaptive T cells, preferentially subsets of effector T helper, effector CTL and effector memory CTL cells that were associated with superior overall survival (OS), in contrast to progenitors of T cells and myeloid/monocytic lineage subsets that were suppressed in WM cohort. Moreover, decrease in immature B and NKT cells was related to worse OS in WM patients. Innate and adaptive immune subsets of WM TME were modulated by immune checkpoints, including PD-1/PD-L1&PD-L2, TIGIT/PVR, CD137/CD137-L, CTLA-4, BTLA and KIR expression. The response of ibrutinib treatment to the reduction of clonal memory B cell was associated with high levels of immature B cells and effector memory CTL cells. Our study demonstrates that CyTOF technology is a powerful approach for characterizing the pathophysiology of WM at various stages, predicting patient risk and monitoring the effectiveness of treatment strategies.

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

BACKGROUND

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

METHOD

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

RESULT

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

CONCLUSION

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

Immune scoring model based on immune cell infiltration to predict prognosis in diffuse large B-cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is genetically heterogeneous in both pathogenesis and clinical symptoms. Most studies on tumor prognosis have not fully considered the role of tumor-infiltrating immune cells. This study focused on the role of tumor-infiltrating immune cells in the prognosis of DLBCL.

METHODS

The GSE10846 data set from the National Center for Biotechnology Information's Gene Expression Omnibus was used as the training set, and the GSE53786 data set was used as the validation set. The proportion of immune cells in each sample was calculated with the CIBERSORT algorithm using R software. After 10 immune cells were screened out (activated memory CD4 positive T cells, follicular helper T cells, regulatory T cells, gamma-delta T cells, activated natural killer cells, M0 macrophages, M2 macrophages, resting dendritic cells, and eosinophils) by univariate Cox analysis, Lasso regression and random forest sampling analyses were performed, the intersecting immune cells were selected for multifactor Cox analysis, and a predictive model was constructed combined with clinical information. Predictive performance was assessed using survival analysis and time-dependent receiver operating characteristic curve analysis.

RESULTS

In total, 539 samples were included in this study, and samples with p < .05 were retained using CIBERSORT. Univariate Cox analysis yielded 10 cell types that were associated with overall survival. Two kinds of immune cells were obtained by Lasso regression combined with the random forest method and were used to construct a prognostic model combined with clinical information. The reliability of the model was validated in two data sets.

CONCLUSIONS

The immune cell-based prediction model constructed by the authors can effectively predict the prognostic outcome of patients with DLBCL, whereas nomogram plots can help clinicians assess the probability of long-term survival.

Identification and Validation of a DNA Damage Repair-Related Signature for Diffuse Large B-Cell Lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin's lymphoma in adults, whose prognostic scoring system remains to be improved. Dysfunction of DNA repair genes is closely associated with the development and prognosis of diffuse large B-cell lymphoma. The aim of this study was to establish and validate a DNA repair-related gene signature associated with the prognosis of DLBCL and to investigate the clinical predictive value of this signature.

METHODS

DLBCL cases were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. One hundred ninety-nine DNA repair-related gene sets were retrieved from the GeneCards database. The LASSO Cox regression was used to generate the DNA repair-related gene signature. Subsequently, the level of immune cell infiltration and the correlation between the gene signature and immune cells were analyzed using the CIBERSORT algorithm. Based on the Genomics of Drug Sensitivity in Cancer (GDSC) database, the relationship between the signature and drug sensitivity was analyzed, and together with the nomogram and gene set variation analysis (GSVA), the value of the signature for clinical application was evaluated.

RESULTS

A total of 14 DNA repair genes were screened out and included in the final risk model. Subgroup analysis of the training and validation cohorts showed that the risk model accurately predicted overall survival of DLBCL patients, with patients in the high-risk group having a worse prognosis than patients in the low-risk group. Subsequently, the risk score was confirmed as an independent prognostic factor by multivariate analysis. Furthermore, by CIBERSORT analysis, we discovered that immune cells, such as regulatory T cells (Tregs), activated memory CD4+ T cells, and gamma delta T cells showed significant differences between the high- and low-risk groups. In addition, we found some interesting associations of our signature with immune checkpoint genes (CD96, TGFBR1, and TIGIT). By analyzing drug sensitivity data in the GDSC database, we were able to identify potential therapeutics for DLBCL patients stratified according to our signature.

CONCLUSIONS

Our study identified and validated a 14-DNA repair-related gene signature for stratification and prognostic prediction of DLBCL patients, which might guide clinical personalization of treatment.

Identification of the function of γδ1 T cells in the lung cancer microenvironments

PURPOSE

To investigate whether γδ1 T cells derived from lung cancer tissues have immunosuppressive function and to verify the mechanism of immunosuppressive effect.

METHODS

Fresh lung cancer tissue samples were collected, some of them were prepared tissue sections, the others were isolated and amplified into TILs cells, γδ1 T cells were isolated from TILs cells by immunomagnetic beads kits, and then cloned and amplified. The immunomodulatory effects of γδ1 T cells on naive and effector CD4⁺ T cells were detected by immunohistochemistry, flow cytometry, CCK8, ELISA and transwell culture.

RESULTS

A high proportion of γδ1 T cells was found in lung cancer tissues. The cultural supernatants of γδ1 T cells could inhibit the proliferation of naive CD4⁺ T cells and decrease the secretion level of IL-2 by effector CD4⁺ T cells. Further studies showed that the expression levels of IL-8, MIP-1α, MIP-1β and RANTES were higher than that of IFN-γ, GM-CSF and TNF-α, TNF-β, however, their neutralizing antibodies could not block the immunosuppressive activity of the supernatant.

CONCLUSION

γδ1 T cells play an negative immunoregulation function in lung cancer microenvironments, and have obvious immunosuppressive effects on proliferation and cytokine release of naive CD4⁺ T cells and effector CD4⁺ T cells. Preliminary evidence from this study suggests that the mechanism of immunosuppressive effects is mediated by the soluble factors in γδ1 T cell culture supernatants, but its exact molecular mechanism needs to be further explored.

Harnessing Unconventional T Cells and Innate Lymphoid Cells to Prevent and Treat Hematological Malignancies: Prospects for New Immunotherapy

Unconventional T cells and innate lymphoid cells (ILCs) make up a heterogeneous set of cells that characteristically show prompt responses toward specific antigens. Unconventional T cells recognize non-peptide antigens, which are bound and presented by diverse non-polymorphic antigen-presenting molecules and comprise γδ T cells, MR1-restricted mucosal-associated invariant T cells (MAITs), and natural killer T cells (NKTs). On the other hand, ILCs lack antigen-specific receptors and act as the innate counterpart to the T lymphocytes found in the adaptive immune response. The alteration of unconventional T cells and ILCs in frequency and functionality is correlated with the onset of several autoimmune diseases, allergy, inflammation, and tumor. However, depending on the physio-pathological framework, unconventional T cells may exhibit either protective or pathogenic activity in a range of neoplastic diseases. Nonetheless, experimental models and clinical studies have displayed that some unconventional T cells are potential therapeutic targets, as well as prognostic and diagnostic markers. In fact, cell-mediated immune response in tumors has become the focus in immunotherapy against neoplastic disease. This review concentrates on the present knowledge concerning the function of unconventional T cell sets in the antitumor immune response in hematological malignancies, such as acute and chronic leukemia, multiple myeloma, and lymphoproliferative disorders. Moreover, we discuss the possibility that modulating the activity of unconventional T cells could be useful in the treatment of hematological neoplasms, in the prevention of specific conditions (such as graft versus host disease), and in the formulation of an effective anticancer vaccine therapy. The exact knowledge of the role of these cells could represent the prerequisite for the creation of a new form of immunotherapy for hematological neoplasms.

Immune microenvironment-related gene mapping predicts immunochemotherapy response and prognosis in diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin's lymphoma (NHL). The R-CHOP immunochemotherapy regimen is the first-line treatment option for DLBCL patients and has greatly improved the prognosis of DLBCL, making it a curable disease. However, drug resistance or relapse is the main challenge for current DLBCL treatment. Studies have shown that the tumor microenvironment plays an important role in the onset, development, and responsiveness to drugs in DLBCL. Here, we used the CIBERSORT algorithm to resolve the composition of the immune microenvironment of 471 DLBCL patients from the GEO database. We found that activated memory CD4+ T cells and γδ T cells were significantly associated with immunochemotherapy response. Weighted gene co-expression networks (WGCNA) were constructed using differentially expressed genes from immunochemotherapy responders and non-responders. The module most associated with these two types of T cells was defined as hub module. Enrichment analysis of the hub module showed that baseline immune status was significantly stronger in responders than in non-responders. A protein-protein interaction (PPI) network was constructed for hub module to identify hub genes. After survival analysis, five prognosis-related genes (CD3G, CD3D, GNB4, FCHO2, GPR183) were identified and all these genes were significantly negatively associated with PD1. Using our own patient cohort, we validated the efficacy of CD3G and CD3D in predicting immunochemotherapy response. Our study showed that CD3G, CD3D, GNB4, FCHO2, and GPR183 are involved in the regulation of the immune microenvironment of DLBCL. They can be used as biomarkers for predicting immunochemotherapy response and potential therapeutic targets in DLBCL.

A prognostic immune risk score for diffuse large B-cell lymphoma

We constructed a prognostic score for persons with diffuse large B-cell lymphoma (DLBCL) based on infiltrating immune cells. Data of 956 consecutive subjects were retrieved from the Gene Expression Omnibus database and assigned to training (GSE10846, n = 305) or validation (GSE87371 n = 206 and GSE117556 n = 445 combined) cohorts. Proportions of non-lymphoma cells in the sample were inferred using the ESTIMATE algorithm. An immune risk score was constructed comprised of eight types of non-lymphoma immune cells calculated using the CIBERSORT algorithm. Five-year survival of subjects with an immune risk score ≤ 0·45 in the training cohort was better than that of subjects with a score > 0·45 (hazard ratio [HR] = 3·99; 95% confidence interval [CI] = 2·74, 5·82; P < 0·001). HR in the validation cohort was HR = 2·17 (1·47, 3·21; P < 0·001). Enrichment analyses indicated correlations with genes controlling immune-related biological processes and pathways. A nomogram comprised of the immune risk score and most covariates including age, lactate dehydrogenase concentration (LDH), lymphoma-type (germinal centre B cell [GCB] versus non-GCB), Eastern Cooperative Oncology Group performance status (ECOG-PS) and rituximab therapy had a C-statistic of 0·76 compared with C-statistics of 0·69 and 0·69 for the International Prognostic Index (IPI) and Revised International Prognostic Index (R-IPI). These data indicate the immune risk score is an accurate, independent survival predictor in persons with DLBCL.

The Dual Roles of Human γδ T Cells: Anti-Tumor or Tumor-Promoting

γδ T cells are the unique T cell subgroup with their T cell receptors composed of γ chain and δ chain. Unlike αβ T cells, γδ T cells are non-MHC-restricted in recognizing tumor antigens, and therefore defined as innate immune cells. Activated γδ T cells can promote the anti-tumor function of adaptive immune cells. They are considered as a bridge between adaptive immunity and innate immunity. However, several other studies have shown that γδ T cells can also promote tumor progression by inhibiting anti-tumor response. Therefore, γδ T cells may have both anti-tumor and tumor-promoting effects. In order to clarify this contradiction, in this review, we summarized the functions of the main subsets of human γδ T cells in how they exhibit their respective anti-tumor or pro-tumor effects in cancer. Then, we reviewed recent γδ T cell-based anti-tumor immunotherapy. Finally, we summarized the existing problems and prospect of this immunotherapy.

Off-the-Shelf Allogeneic T Cell Therapies for Cancer: Opportunities and Challenges Using Naturally Occurring "Universal" Donor T Cells

Chimeric antigen receptor (CAR) engineered T cell therapies individually prepared for each patient with autologous T cells have recently changed clinical practice in the management of B cell malignancies. Even though CARs used to redirect polyclonal T cells to the tumor are not HLA restricted, CAR T cells are also characterized by their endogenous T cell receptor (TCR) repertoire. Tumor-antigen targeted TCR-based T cell therapies in clinical trials are thus far using “conventional” αβ-TCRs that recognize antigens presented as peptides in the context of the major histocompatibility complex. Thus, both CAR- and TCR-based adoptive T cell therapies (ACTs) are dictated by compatibility of the highly polymorphic HLA molecules between donors and recipients in order to avoid graft-versus-host disease and rejection. The development of third-party healthy donor derived well-characterized off-the-shelf cell therapy products that are readily available and broadly applicable is an intensive area of research. While genome engineering provides the tools to generate “universal” donor cells that can be redirected to cancers, we will focus our attention on third-party off-the-shelf strategies with T cells that are characterized by unique natural features and do not require genome editing for safe administration. Specifically, we will discuss the use of virus-specific T cells, lipid-restricted (CD1) T cells, MR1-restricted T cells, and γδ-TCR T cells. CD1- and MR1-restricted T cells are not HLA-restricted and have the potential to serve as a unique source of universal TCR sequences to be broadly applicable in TCR-based ACT as their targets are presented by the monomorphic CD1 or MR1 molecules on a wide variety of tumor types. For each cell type, we will summarize the stage of preclinical and clinical development and discuss opportunities and challenges to deliver off-the-shelf targeted cellular therapies against cancer.

Memory T cells: strategies for optimizing tumor immunotherapy

Several studies have demonstrated that memory T cells including stem cell memory (Tscm) T cells and central memory (Tcm) T cells show superior persistence and antitumor immunity compared with effector memory T (Tem) cells and effector T (Teff) cells. Furthermore, the Tcm/Teff ratio has been reported to be a predictive biomarker of immune responses against some tumors. Thus, a system-level understanding of the mechanisms underlying the differentiation of effector and memory T cells is of increasing importance for developing immunological strategies against various tumors. This review focuses on recent advances in efficacy against tumors, the origin, formation mechanisms of memory T cells, and the role of the gut microbiota in memory T cell formation. Furthermore, we summarize strategies to generate memory T cells in (ex) vivo that, might be applicable in clinical practice.