Comparative proteomic analysis of cat eye syndrome critical region protein 1- function in tumor-associated macrophages and immune response regulation of glial tumors

Knockdown of liver cancer cell-secreted exosomal PSMA5 controls macrophage polarization to restrain cancer progression by blocking JAK2/STAT3 signaling

INTRODUCTION

Tumor-associated macrophages, a major component of the tumor microenvironment, undergo polarization into M2 macrophages (M2), and thereby exert an immunosuppressive effect to induce cancer metastasis. This study strives to uncover a molecular mechanism underlying this event in hepatocellular carcinoma (HCC).

METHODS

Proteasome subunit alpha 5 (PSMA5) expression in liver hepatocellular carcinoma (LIHC) tissues and its association with LIHC patients were predicted using StarBase. PSMA5 level in human HCC cells was manipulated via transfection. Exosomes were isolated from HCC cells, and internalized into macrophages which were cocultured with HCC cells. Exosome internalization was observed after fluorescence labeling. HCC cell migration and invasion were evaluated by wound healing and Transwell assays. Xenograft assay was performed to investigate the role of PSMA5 in in vitro tumorigenesis. M2 polarization was assessed by enzyme-linked immunosorbent assay, quantitative reverse transcription polymerase chain reaction, and immunohistochemistry. PSMA5 expression in exosomes and Janus Kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3) activation in macrophages and tumors were detected by Western blot analysis.

RESULTS

High PSMA5 expression was observed in LIHC tissues and associated with compromised survival of LIHC patients. PSMA5 knockdown inhibited HCC cell migration and invasion. PSMA5 knockdown in HCC cells downregulated PSMA5 level in exosomes from these HCC cells. HCC cell-isolated exosomes were successfully internalized into macrophages, and facilitated M2 polarization and JAK2/STAT3 pathway activation. HCC cell-secreted exosomal PSMA5 knockdown inhibited the exosome-induced effect on macrophages, and attenuated the promotion induced by exosome-treated macrophages on HCC cell migration/invasion and tumorigenesis along with in vivo M2 polarization and JAK2/STAT3 pathway activation.

CONCLUSION

HCC cell-secreted exosomal PSMA5 knockdown hinders M2 polarization to suppress cancer progression by restraining JAK2/STAT3 signaling.

Insight into Tetrabromobisphenol A-Associated Liver Transcriptional Landscape via Single Cell RNA Sequencing

In recent years, there has been growing concern over the rising incidence of liver diseases, with increasing exposure to environmental toxins as a significant contributing factor. However, the mechanisms of liver injury induced by environmental pollutants are largely unclear. Here, using tetrabromobisphenol A (TBBPA), a widely used brominated flame retardant, as an example, environmental toxin-induced liver toxicity in mice is characterized via single-cell sequencing technology. Heterogeneous gene expression profiles after exposure to TBBPA in major cell types of the liver are demonstrated. In hepatocytes, pathway analysis of differentially expressed genes reveals the enhanced interferon response and diminished metabolic processes. The disrupted endothelial functions in TBBPA-treated cells are then shown. Moreover, the activation of M2-polarization in Kupffer cells, as well as activated effector T and B cells are unveiled in TBBPA-treated cells. Finally, ligand-receptor pair analysis shows that TBBPA disrupts cell-cell communication and induces an inflammatory microenvironment. Overall, the results reveal that TBBPA-induced dysfunction of hepatocytes and endothelial cells may then activate and recruit other immune cells such as Kuffer cells, and T/NK cells into the liver, further increasing inflammatory response and liver injury. Thus, the results provide novel insight into undesiring environmental pollutant-induced liver injury.

Immunosuppressive cells in oncolytic virotherapy for glioma: challenges and solutions

Glioblastoma is a highly aggressive form of brain cancer characterized by the abundance of myeloid lineage cells in the tumor microenvironment. Tumor-associated macrophages and microglia (TAM) and myeloid-derived suppressor cells (MDSCs), play a pivotal role in promoting immune suppression and tumor progression. Oncolytic viruses (OVs) are self-amplifying cytotoxic agents that can stimulate local anti-tumor immune responses and have the potential to suppress immunosuppressive myeloid cells and recruit tumor-infiltrating T lymphocytes (TILs) to the tumor site, leading to an adaptive immune response against tumors. However, the impact of OV therapy on the tumor-resident myeloid population and the subsequent immune responses are not yet fully understood. This review provides an overview of how TAM and MDSC respond to different types of OVs, and combination therapeutics that target the myeloid population to promote anti-tumor immune responses in the glioma microenvironment.

Adipose Tissue-Derived Extracellular Vesicles Contribute to Phenotypic Plasticity of Prostate Cancer Cells

Metastatic prostate cancer is one of the leading causes of male cancer deaths in the western world. Obesity significantly increases the risk of metastatic disease and is associated with a higher mortality rate. Systemic chronic inflammation can result from a variety of conditions, including obesity, where adipose tissue inflammation is a major contributor. Adipose tissue endothelial cells (EC) exposed to inflammation become dysfunctional and produce a secretome, including extracellular vesicles (EV), that can impact function of cells in distant tissues, including malignant cells. The aim of this study was to explore the potential role of EVs produced by obese adipose tissue and the ECs exposed to pro-inflammatory cytokines on prostate cancer phenotypic plasticity in vitro. We demonstrate that PC3ML metastatic prostate cancer cells exposed to EVs from adipose tissue ECs and to EVs from human adipose tissue total explants display reduced invasion and increased proliferation. The latter functional changes could be attributed to the EV miRNA cargo. We also show that the functional shift is TWIST1-dependent and is consistent with mesenchymal-to-epithelial transition, which is key to establishment of secondary tumor growth. Understanding the complex effects of EVs on prostate cancer cells of different phenotypes is key before their intended use as therapeutics.

Preclinical and Clinical Applications of Metabolomics and Proteomics in Glioblastoma Research

Glioblastoma (GB) is a primary malignancy of the central nervous system that is classified by the WHO as a grade IV astrocytoma. Despite decades of research, several aspects about the biology of GB are still unclear. Its pathogenesis and resistance mechanisms are poorly understood, and methods to optimize patient diagnosis and prognosis remain a bottle neck owing to the heterogeneity of the malignancy. The field of omics has recently gained traction, as it can aid in understanding the dynamic spatiotemporal regulatory network of enzymes and metabolites that allows cancer cells to adjust to their surroundings to promote tumor development. In combination with other omics techniques, proteomic and metabolomic investigations, which are a potent means for examining a variety of metabolic enzymes as well as intermediate metabolites, might offer crucial information in this area. Therefore, this review intends to stress the major contribution these tools have made in GB clinical and preclinical research and highlights the crucial impacts made by the integrative "omics" approach in reducing some of the therapeutic challenges associated with GB research and treatment. Thus, our study can purvey the use of these powerful tools in research by serving as a hub that particularly summarizes studies employing metabolomics and proteomics in the realm of GB diagnosis, treatment, and prognosis.

Putting Proteomics Into Immunotherapy for Glioblastoma

In glioblastoma, the most aggressive brain cancer, a complex microenvironment of heterogeneity and immunosuppression, are considerable hurdles to classify the subtypes and promote treatment progression. Treatments for glioblastoma are similar to standard therapies for many other cancers and do not effectively prolong the survival of patients, due to the unique location and heterogeneous characteristics of glioblastoma. Immunotherapy has shown a promising effect for many other tumors, but its application for glioma still has some challenges. The recent breakthrough of high-throughput liquid chromatography-mass spectrometry (LC-MS/MS) systems has allowed researchers to update their strategy for identifying and quantifying thousands of proteins in a much shorter time with lesser effort. The protein maps can contribute to generating a complete map of regulatory systems to elucidate tumor mechanisms. In particular, newly developed unicellular proteomics could be used to determine the microenvironment and heterogeneity. In addition, a large scale of differentiated proteins provides more ways to precisely classify tumor subtypes and construct a larger library for biomarkers and biotargets, especially for immunotherapy. A series of advanced proteomic studies have been devoted to the different aspects of immunotherapy for glioma, including monoclonal antibodies, oncolytic viruses, dendritic cell (DC) vaccines, and chimeric antigen receptor (CAR) T cells. Thus, the application of proteomics in immunotherapy may accelerate research on the treatment of glioblastoma. In this review, we evaluate the frontline applications of proteomics strategies for immunotherapy in glioblastoma research.

Adenosine Signaling in the Tumor Microenvironment

Adenosine, deriving from ATP released by dying cancer cells and then degradated in the tumor environment by CD39/CD73 enzyme axis, is linked to the generation of an immunosuppressed niche favoring the onset of neoplasia. Signals delivered by extracellular adenosine are detected and transduced by G-protein-coupled cell surface receptors, classified into four subtypes: A₁, A_2A, A_2B, and A₃. A critical role of this nucleoside is emerging in the modulation of several immune and nonimmune cells defining the tumor microenvironment, providing novel insights about the development of novel therapeutic strategies aimed at undermining the immune-privileged sites where cancer cells grow and proliferate.

Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Lower-Grade Glioma

Objective

Despite several clinicopathological factors being integrated as prognostic biomarkers, the individual variants and risk stratification have not been fully elucidated in lower grade glioma (LGG). With the prevalence of gene expression profiling in LGG, and based on the critical role of the immune microenvironment, the aim of our study was to develop an immune-related signature for risk stratification and prognosis prediction in LGG.

Methods

RNA-sequencing data from The Cancer Genome Atlas (TCGA), Genome Tissue Expression (GTEx), and Chinese Glioma Genome Atlas (CGGA) were used. Immune-related genes were obtained from the Immunology Database and Analysis Portal (ImmPort). Univariate, multivariate cox regression, and Lasso regression were employed to identify differentially expressed immune-related genes (DEGs) and establish the signature. A nomogram was constructed, and its performance was evaluated by Harrell’s concordance index (C-index), receiver operating characteristic (ROC), and calibration curves. Relationships between the risk score and tumor-infiltrating immune cell abundances were evaluated using CIBERSORTx and TIMER.

Results

Noted, 277 immune-related DEGs were identified. Consecutively, 6 immune genes (CANX, HSPA1B, KLRC2, PSMC6, RFXAP, and TAP1) were identified as risk signature and Kaplan–Meier curve, ROC curve, and risk plot verified its performance in TCGA and CGGA datasets. Univariate and multivariate Cox regression indicated that the risk group was an independent predictor in primary LGG. The prognostic signature showed fair accuracy for 3- and 5-year overall survival in both internal (TCGA) and external (CGGA) validation cohorts. However, predictive performance was poor in the recurrent LGG cohort. The CIBERSORTx algorithm revealed that naïve CD4⁺ T cells were significant higher in low-risk group. Conversely, the infiltration levels of M1-type macrophages, M2-type macrophages, and CD8⁺T cells were significant higher in high-risk group in both TCGA and CGGA cohorts.

Conclusion

The present study constructed a robust six immune-related gene signature and established a prognostic nomogram effective in risk stratification and prediction of overall survival in primary LGG.