A T Cell-B Cell Tumor-Suppressive Axis in the Germinal Center

Pan-cancer analysis of immune checkpoint receptors and ligands in various cells in the tumor immune microenvironment

Drugs that target immune checkpoint have become the most popular weapon in cancer immunotherapy, yet only have practical benefits for a small percentage of patients. Tumor cells constantly interact with their microenvironment, which is made up of a variety of immune cells as well as endothelial cells and fibroblasts. Immune checkpoint expression and blocked signaling of immune cells in the tumor microenvironment (TME) are key to tumor progression. In this study, we perform deliberation convolution on the TCGA database for human lung, breast, and colorectal cancer to infer crosstalk between immune checkpoint receptors (ICRs) and ligands (ICLs) in TME of pan-carcinogenic solid tumor types, validated by flow cytometry. Analysis of immune checkpoints showed that there was little variation between different tumor types. It showed that CD160, LAG3, TIGIT were found to be highly expressed in CD8+ T cells instead of CD4+ T cells, PD-L1, PD-L2, CD86, LGALS9, TNFRSF14, LILRB4 and other ligands were highly expressed on macrophages, FVR, NECTIN2, FGL1 were highly expressed on Epithelial cells, CD200 was highly expressed in Endothelial cells, and CD80 was highly expressed in CD8 High expression on T cells. Overall, our study provides a new resource for the expression of immune checkpoints in TME on various types of cells. Significance: This study provides immune checkpoint expression of immune cells of multiple cancer types to infer immune mechanisms in the tumor microenvironment and provide ideas for the development of new immune checkpoint-blocking drugs.

Adenosine signaling: Optimal target for gastric cancer immunotherapy

Gastric cancer (GC) is one of the most common malignancy and leading cause of cancer-related deaths worldwide. Due to asymptomatic or only nonspecific early symptoms, GC patients are usually in the advanced stage at first diagnosis and miss the best opportunity of treatment. Immunotherapies, especially immune checkpoint inhibitors (ICIs), have dramatically changed the landscape of available treatment options for advanced-stage cancer patients. However, with regards to existing ICIs, the clinical benefit of monotherapy for advanced gastric cancer (AGC) is quite limited. Therefore, it is urgent to explore an optimal target for the treatment of GC. In this review, we summarize the expression profiles and prognostic value of 20 common immune checkpoint-related genes in GC from Gene Expression Profiling Interactive Analysis (GEPIA) database, and then find that the adenosinergic pathway plays an indispensable role in the occurrence and development of GC. Moreover, we discuss the pathophysiological function of adenosinergic pathway in cancers. The accumulation of extracellular adenosine inhibits the normal function of immune effector cells and facilitate the effect of immunosuppressive cells to foster GC cells proliferation and migration. Finally, we provide insights into potential clinical application of adenosinergic-targeting therapies for GC patients.

Epigenetic, Metabolic, and Immune Crosstalk in Germinal-Center-Derived B-Cell Lymphomas: Unveiling New Vulnerabilities for Rational Combination Therapies

B-cell non-Hodgkin lymphomas (B-NHLs) are highly heterogenous by genetic, phenotypic, and clinical appearance. Next-generation sequencing technologies and multi-dimensional data analyses have further refined the way these diseases can be more precisely classified by specific genomic, epigenomic, and transcriptomic characteristics. The molecular and genetic heterogeneity of B-NHLs may contribute to the poor outcome of some of these diseases, suggesting that more personalized precision-medicine approaches are needed for improved therapeutic efficacy. The germinal center (GC) B-cell like diffuse large B-cell lymphomas (GCB-DLBCLs) and follicular lymphomas (FLs) share specific epigenetic programs. These diseases often remain difficult to treat and surprisingly do not respond advanced immunotherapies, despite arising in secondary lymphoid organs at sites of antigen recognition. Epigenetic dysregulation is a hallmark of GCB-DLBCLs and FLs, with gain-of-function (GOF) mutations in the histone methyltransferase EZH2, loss-of-function (LOF) mutations in histone acetyl transferases CREBBP and EP300, and the histone methyltransferase KMT2D representing the most prevalent genetic lesions driving these diseases. These mutations have the common effect to disrupt the interactions between lymphoma cells and the immune microenvironment, via decreased antigen presentation and responsiveness to IFN-γ and CD40 signaling pathways. This indicates that immune evasion is a key step in GC B-cell lymphomagenesis. EZH2 inhibitors are now approved for the treatment of FL and selective HDAC3 inhibitors counteracting the effects of CREBBP LOF mutations are under development. These treatments can help restore the immune control of GCB lymphomas, and may represent optimal candidate agents for more effective combination with immunotherapies. Here, we review recent progress in understanding the impact of mutant chromatin modifiers on immune evasion in GCB lymphomas. We provide new insights on how the epigenetic program of these diseases may be regulated at the level of metabolism, discussing the role of metabolic intermediates as cofactors of epigenetic enzymes. In addition, lymphoma metabolic adaptation can negatively influence the immune microenvironment, further contributing to the development of immune cold tumors, poorly infiltrated by effector immune cells. Based on these findings, we discuss relevant candidate epigenetic/metabolic/immune targets for rational combination therapies to investigate as more effective precision-medicine approaches for GCB lymphomas.

Construction and Validation of a Newly Prognostic Signature for CRISPR-Cas9-Based Cancer Dependency Map Genes in Breast Cancer

Cancer Dependency Map (CDM) genes comprise an extensive series of genome-scale RNAi-based loss-of-function tests; hence, it served as a method based on the CRISPR-Cas9 technique that could assist scientists in investigating potential gene functions. These CDM genes have a role in tumor cell survival and proliferation, suggesting that they may be used as new therapeutic targets for some malignant tumors. So far, there have been less research on the involvement of CDM genes in breast cancer, and only a tiny percentage of CDM genes have been studied. In this study, information of patients with breast cancer was extracted from The Cancer Genome Atlas (TCGA), from which differentially expressed CDM genes in breast cancer were determined. A variety of bioinformatics techniques were used to assess the functions and prognostic relevance of these confirmed CDM genes. In all, 290 CDM genes were found differentially expressed. Six CDM genes (SRF, RAD51, PMF1, EXOSC3, EXOC1, and TSEN54) were found to be associated with the prognosis of breast cancer samples. Based on the expression of the identified CDM genes and their coefficients, a prognosis model was constructed for prediction, according to which patients with breast cancer were separated into two risk groups. Those with high risk had substantially poorer overall survival (OS) than patients in the other risk group in the TCGA training set, TCGA testing set, and an external cohort from Gene Expression Omnibus (GEO) database. The area under the receiver operating characteristic (ROC) curve for this prognostic signature was, respectively, 0.717 and 0.635 for TCGA training and testing sets, demonstrating its reliability in predicting the prognosis of patients with breast cancer. We next created a nomogram using the six CDM genes discovered to create a therapeutically useful model. The Human Protein Atlas database was used to acquire all immunohistochemistry staining images of the discovered CDM genes. The proportions of tumor-infiltrating immune cells, as well as the expression levels of checkpoint genes, varied substantially between the two risk groups, according to the analyses of immune response. In conclusion, the findings of this research may aid in the understanding of the prognostic value and biological roles of CDM genes in breast cancer.

Unraveling the Role of Immune Checkpoints in Leishmaniasis

Leishmaniasis are Neglected Tropical Diseases affecting millions of people every year in at least 98 countries and is one of the major unsolved world health issues. Leishmania is a parasitic protozoa which are transmitted by infected sandflies and in the host they mainly infect macrophages. Immunity elicited against those parasites is complex and immune checkpoints play a key role regulating its function. T cell receptors and their respective ligands, such as PD-1, CTLA-4, CD200, CD40, OX40, HVEM, LIGHT, 2B4 and TIM-3 have been characterized for their role in regulating adaptive immunity against different pathogens. However, the exact role those receptors perform during Leishmania infections remains to be better determined. This article addresses the key role immune checkpoints play during Leishmania infections, the limiting factors and translational implications.

Identification of an Immune Gene-Associated Prognostic Signature and Its Association With a Poor Prognosis in Gastric Cancer Patients

The immune response plays a critical role in gastric cancer (GC) development, metastasis, and treatment. A better understanding of the tumor-immune system interactions in gastric cancer may provide promising diagnostic, prognostic, and therapeutic biomarkers for patients with this disease. In the present study, we aimed to identify a prognostic signature of GC through a comprehensive bioinformatics analysis on the tumor-immune interactions as well as the molecular characteristics. We firstly identified two immunophenotypes and immunological characteristics by employing multiple algorithms, such as the single sample Gene Sets Enrichment Analysis and Cell type Identification By Estimating Relative Subsets of RNA Transcripts. Next, we developed a six-immune-gene signature as a promising independent prognostic biomarker for GC using Lasso Cox regression and verified it via the external validation set and systematically correlated the immune signature with GC clinicopathologic features and genomic characteristics. Finally, a nomogram was successfully constructed based on the immune signature and clinical characteristics and showed a high potential for GC prognosis prediction. This study may shed light on the treatment strategies for GC patients from the perspective of immunology.