Immune checkpoint inhibitors and cellular treatment for lymphoma immunotherapy

Immunomodulatory Precision: A Narrative Review Exploring the Critical Role of Immune Checkpoint Inhibitors in Cancer Treatment

An immune checkpoint is a signaling pathway that regulates the recognition of antigens by T-cell receptors (TCRs) during an immune response. These checkpoints play a pivotal role in suppressing excessive immune responses and maintaining immune homeostasis against viral or microbial infections. There are several FDA-approved immune checkpoint inhibitors (ICIs), including ipilimumab, pembrolizumab, and avelumab. These ICIs target cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed cell death protein 1 (PD-1), and programmed death ligand 1 (PD-L1). Furthermore, ongoing efforts are focused on developing new ICIs with emerging potential. In comparison to conventional treatments, ICIs offer the advantages of reduced side effects and durable responses. There is growing interest in the potential of combining different ICIs with chemotherapy, radiation therapy, or targeted therapies. This article comprehensively reviews the classification, mechanism of action, application, and combination strategies of ICIs in various cancers and discusses their current limitations. Our objective is to contribute to the future development of more effective anticancer drugs targeting immune checkpoints.

Comprehensive analysis of the interaction of antigen presentation during anti-tumour immunity and establishment of AIDPS systems in ovarian cancer

There are hundreds of prognostic models for ovarian cancer. These genes are based on different gene classes, and there are many ways to construct the models. Therefore, this paper aims to build the most stable prognostic evaluation system known to date through 101 machine learning strategies. We combined 101 algorithm combinations with 10 machine learning algorithms to create antigen presentation-associated genetic markers (AIDPS) with outstanding precision and steady performance. The inclusive set of algorithms comprises the elastic network (Enet), Ridge, stepwise Cox, Lasso, generalized enhanced regression model (GBM), random survival forest (RSF), supervised principal component (SuperPC), Cox partial least squares regression (plsRcox), survival support vector machine (Survival-SVM). Then, in the train cohort, the prediction model was fitted using a leave-one cross-validation (LOOCV) technique, which involved 101 different possible combinations of prognostic genes. Seven validation data sets (GSE26193, GSE26712, GSE30161, GSE63885, GSE9891, GSE140082 and ICGC_OV_AU) were compared and analysed, and the C-index was calculated. Finally, we collected 32 published ovarian cancer prognostic models (including mRNA and lncRNA). All data sets and prognostic models were subjected to a univariate Cox regression analysis, and the C-index was calculated to demonstrate that the antigen presentation process should be the core criterion for evaluating ovarian cancer prognosis. In a univariate Cox regression analysis, 22 prognostic genes were identified based on the expression profiles of 283 genes involved in antigen presentation and the intersection of genes (p < 0.05). AIDPS were developed by our machine learning-based integration method, which was applied to these 22 genes. One hundred and one prediction models are fitted using the LOOCV framework, and the C-index is calculated for each model across all validation sets. Interestingly, RSF + Lasso was the best model overall since it had the greatest average C-index and the highest C-index of any combination of models tested on the validated data sets. In comparing external cohorts, we found that the C-index correlated AIDPS method using the RSF + Lasso method in 101 prediction models was in contrast to other features. Notably, AIDPS outperformed the vast majority of models across all data sets. Antigen-presenting anti-tumour immune pathways can be used as a representative gene set of ovarian cancer to track the prognosis of patients with cancer. The antigen-presenting model obtained by the RSF + Lasso method has the best C-INDEX, which plays a key role in developing antigen-presenting targeted drugs in ovarian cancer and improving the treatment outcome of patients.

CAR-NK cells in combination therapy against cancer: A potential paradigm

Various preclinical and a limited number of clinical studies of CAR-NK cells have shown promising results: efficient elimination of target cells without side effects similar to CAR-T therapy. However, the homing and infiltration abilities of CAR-NK cells are poor due to the inhibitory tumor microenvironment. From the perspective of clinical treatment strategies, combined with the biological and tumor microenvironment characteristics of NK cells, CAR-NK combination therapy strategies with anti-PD-1/PD-L1, radiotherapy and chemotherapy, kinase inhibitors, proteasome inhibitors, STING agonist, oncolytic virus, photothermal therapy, can greatly promote the proliferation, migration and cytotoxicity of the NK cells. In this review, we will summarize the targets selection, structure constructions and combinational therapies of CAR-NK cells for tumors to provide feasible combination strategies for overcoming the inhibitory tumor microenvironment and improving the efficacy of CAR-NK cells.

Brief research report: in-depth immunophenotyping reveals stability of CD19 CAR T-cells over time

Variability or stability might have an impact on treatment success and toxicity of CD19 CAR T-cells. We conducted a prospective observational study of 12 patients treated with Tisagenlecleucel for CD19+ B-cell malignancies. Using a 31-color spectral flow cytometry panel, we analyzed differentiation stages and exhaustion markers of CAR T-cell subsets prior to CAR T-cell infusion and longitudinally during 6 months of follow-up. The majority of activation markers on CAR T-cells showed stable expression patterns over time and were not associated with response to therapy or toxicity. Unsupervised cluster analysis revealed an immune signature of CAR T-cell products associated with the development of immune cell-associated neurotoxicity syndrome. Warranting validation in an independent patient cohort, in-depth phenotyping of CAR T-cell products as well as longitudinal monitoring post cell transfer might become a valuable tool to increase efficacy and safety of CAR T-cell therapy.

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.

A glycolysis-related gene signatures in diffuse large B-Cell lymphoma predicts prognosis and tumor immune microenvironment

Background: Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma which that highly aggressive and heterogeneous. Glycolysis has been implicated in the regulation of tumor microenvironment (TME) and development. In this study, we aimed to establish a glycolysis-related prognostic model for the risk stratification, prognosis prediction, and immune landscape evaluation in patients with DLBCL. Methods: Three independent datasets GSE181063, GSE10846, and GSE53786 containing gene expression profiles and clinical data were downloaded from the Gene Expression Omnibus (GEO) database. The glycolysis-related prognostic model was developed with Cox and Least Absolute Shrinkage and Selector Operation (LASSO) regression and validated. A nomogram integrating clinical factors and glycolytic risk scores was constructed. The composition of the TME was analyzed with the ESTIMATE algorithm and single-sample gene set enrichment analysis (ssGSEA). Results: A glycolytic risk model containing eight genes was developed. The area under the receiver operating characteristic (ROC) curve (AUC) for the 1-, 3-, and 5-year was 0.718, 0.695, and 0.688, respectively. Patients in the high-risk group had significantly lower immune scores, elevated tumor purity, and poorer survival compared with those in the low-risk group. The nomogram constructed based on glycolytic risk score, age, Eastern Cooperative Oncology Group performance status (ECOG-PS), use of rituximab, and cell of origin (COO) displayed better prediction performance compared with the International Prognostic Index (IPI) in DLBCL. The glycolytic risk score was negatively correlated with the infiltration level of activated CD8 T cells, activated dendritic cells, natural killer cells, and macrophages and immune checkpoint molecules including PD-L2, CTLA4, TIM-3, TIGIT, and B7-H3. Conclusion: These results suggested that the glycolytic risk model could accurately and stably predict the prognosis of patients with DLBCL and might unearth the possible explanation for the glycolysis-related poor prognosis.

Current Status and Future Directions of Bacteria-Based Immunotherapy

With the in-depth understanding of the anti-cancer immunity, immunotherapy has become a promising cancer treatment after surgery, radiotherapy, and chemotherapy. As natural immunogenicity substances, some bacteria can preferentially colonize and proliferate inside tumor tissues to interact with the host and exert anti-tumor effect. However, further research is hampered by the infection-associated toxicity and their unpredictable behaviors in vivo. Due to modern advances in genetic engineering, synthetic biology, and material science, modifying bacteria to minimize the toxicity and constructing a bacteria-based immunotherapy platform has become a hotspot in recent research. This review will cover the inherent advantages of unedited bacteria, highlight how bacteria can be engineered to provide greater tumor-targeting properties, enhanced immune-modulation effect, and improved safety. Successful applications of engineered bacteria in cancer immunotherapy or as part of the combination therapy are discussed as well as the bacteria based immunotherapy in different cancer types. In the end, we highlight the future directions and potential opportunities of this emerging field.

Heterogeneity of the tumor immune microenvironment and its clinical relevance

During the course of tumorigenesis and subsequent metastasis, malignant cells gradually diversify and become more heterogeneous. Consequently, the tumor mass might be infiltrated by diverse immune-related components, including the cytokine/chemokine environment, cytotoxic activity, or immunosuppressive elements. This immunological heterogeneity is universally presented spatially or varies temporally along with tumor evolution or therapeutic intervention across almost all solid tumors. The heterogeneity of anti-tumor immunity shows a profound association with the progression of disease and responsiveness to treatment, particularly in the realm of immunotherapy. Therefore, an accurate understanding of tumor immunological heterogeneity is essential for the development of effective therapies. Facilitated by multi-regional and -omics sequencing, single cell sequencing, and longitudinal liquid biopsy approaches, recent studies have demonstrated the potential to investigate the complexity of immunological heterogeneity of the tumors and its clinical relevance in immunotherapy. Here, we aimed to review the mechanism underlying the heterogeneity of the immune microenvironment. We also explored how clinical assessments of tumor heterogeneity might facilitate the development of more effective personalized therapies.

LAG-3 is a promising inhibitory immune checkpoint for antitumor immunotherapy

INTRODUCTION

Lymphocyte activation gene-3 (LAG-3) is a member of the immunoglobulin superfamily. Engagement of LAG-3 by its ligands to trigger downstream signaling can inhibit immune responses and regulate the pathogenesis of many diseases, including cancer and inflammatory diseases.

AREAS COVERED

We used keywords to search for relevant publications in PubMed and information on websites. After systematic analysis, we discuss the biological characteristics of LAG-3 and its ligands, LAG-3 related signaling, its roles in the pathogenesis of tumors, and its blockages for the treatment of cancers, as well as current challenges and future directions of research.

EXPERT OPINION

Although the mechanisms underlying the action of LAG-3/ligand-related signaling in tumor development are not fully understood, advances in scientific research and LAG-3-based immunotherapies are promising. Further studies to explore its biological roles and molecular mechanisms may aid in developing new LAG-3- and ligand-based therapeutic drugs to benefit patients with different types of cancers.

Roles of Podoplanin in Malignant Progression of Tumor

Podoplanin (PDPN) is a cell-surface mucin-like glycoprotein that plays a critical role in tumor development and normal development of the lung, kidney, and lymphatic vascular systems. PDPN is overexpressed in several tumors and is involved in their malignancy. PDPN induces platelet aggregation through binding to platelet receptor C-type lectin-like receptor 2. Furthermore, PDPN modulates signal transductions that regulate cell proliferation, differentiation, migration, invasion, epithelial-to-mesenchymal transition, and stemness, all of which are crucial for the malignant progression of tumor. In the tumor microenvironment (TME), PDPN expression is upregulated in the tumor stroma, including cancer-associated fibroblasts (CAFs) and immune cells. CAFs play significant roles in the extracellular matrix remodeling and the development of immunosuppressive TME. Additionally, PDPN functions as a co-inhibitory molecule on T cells, indicating its involvement with immune evasion. In this review, we describe the mechanistic basis and diverse roles of PDPN in the malignant progression of tumors and discuss the possibility of the clinical application of PDPN-targeted cancer therapy, including cancer-specific monoclonal antibodies, and chimeric antigen receptor T technologies.

'Le Roi est mort, vive le Roi': New Roles of Radiotherapy in the Treatment of Lymphomas in Combination With Immunotherapy

BACKGROUND

immunotherapy (IT), including checkpoint inhibitors (CIs) and Chimeric Antigen Receptor T cell therapy (CAR-T) revolutionized the treatment of relapsing or refractory (r/r) lymphoma. Several preliminary experiences evaluated concomitant administration of radiotherapy and IT.

METHODS

we performed a systematic review of current literature as of March 30, 2020. A total of 1090 records was retrieved, 42 articles were selected on the basis of title and abstract and, after the removal of analyses with no original data or insufficient clinical information, 28 papers were included in the review.

RESULTS

previous studies were mostly represented by case reports/series or small cohorts. Nonetheless, combination of radiotherapy and CIs or CAR-T led to promising outcomes, resulting in extremely high rates of complete response and improving progression free and overall survival compared with data from recent clinical trials. Combination of RT and CIs had a fair toxicity profile with no reports of severe side effects. Within the limits of the small cohorts retrieved, RT seems a superior option compared with systemic treatment as a 'bridge' to CAR-T and could as well reduce severe complications rates. Radiotherapy could elicit immune response against lymphoma, as demonstrated by multiple cases of abscopal effect and its inclusion in anti-neoplastic vaccines protocols.

CONCLUSION

The results of this review warrant the evaluation of combination of RT and immunotherapy in larger and preferably prospective and randomized cohorts to confirm these preliminary impressive outcomes. The optimal dose, fractionation and timing of RT still have to be clarified.