Peroxiredoxins and Immune Infiltrations in Colon Adenocarcinoma: Their Negative Correlations and Clinical Significances, an In Silico Analysis

Emerging Roles of Using Small Extracellular Vesicles as an Anti-Cancer Drug

Small extracellular vesicles (sEVs) are emerging as a novel therapeutic strategy for cancer therapy. Tumor-cell-derived sEVs contain biomolecules that can be utilized for cancer diagnosis. sEVs can directly exert tumor-killing effects or modulate the tumor microenvironment, leading to anti-cancer effects. In this review, the application of sEVs as a diagnostic tool, drug delivery system, and active pharmaceutical ingredient for cancer therapy will be highlighted. The therapeutic efficacies of sEVs will be compared to conventional immune checkpoint inhibitors. Additionally, this review will provide strategies for sEV engineering to enhance the therapeutic efficacies of sEVs. As a bench-to-bedside application, we will discuss approaches to encourage good-manufacturing-practice-compliant industrial-scale manufacturing and purification of sEVs.

Characteristics of circadian rhythm-related genes and establishment of a prognostic scoring system for lung adenocarcinoma with experimental verification: a bioinformatics analysis

BACKGROUND

Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors worldwide. Lung adenocarcinoma (LUAD), the main subtype of NSCLC, has a poor prognosis. In recent years, circadian rhythm (CR)-related genes (CRRGs) have demonstrated associations with tumor occurrence and development, but the relationship between CRRGs and LUAD is not clear. Because of the correlation between CRRGs and tumors, we have reason to believe that CRRGs will become an important prognostic indicator for LUAD and guide the treatment of LUAD prognosis.

METHODS

Based on data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we explored the biological function and immune cell infiltration of LUAD in different CR clusters and quantified CR genes using principal component analysis (PCA). Then, we built a CR scoring system (CRscore) to explore the relationship between CRRGs and LUAD prognosis.

RESULTS

Patients were divided into three clusters (A, B, and C). Biological characteristics, such as survival, immune cell infiltration, and gene enrichment, were significantly different among the three clusters (P<0.001). We then established the usefulness of the CR score, which could probably predict the prognosis of LUAD. Specifically, patients with a high CR score had a better prognosis and were more sensitive to chemotherapy than those with a low CR score.

CONCLUSIONS

It is possible to use CRRGs to assess the prognosis of patients with LUAD. Quantification of CR using the CRscore tool in patients with LUAD maybe help to guide personalized cancer immunotherapy strategies in the future. Thus, the CRscore may be a prognostic tool for LUAD.

Autophagy characteristics and establishment of autophagy prognostic models in lung adenocarcinoma and lung squamous cell carcinoma

Background

Non-small cell lung cancer (NSCLC), which makes up the majority of lung cancers, remains one of the deadliest malignancies in the world. It has a poor prognosis due to its late detection and lack of response to chemoradiaiton. Therefore, it is urgent to find a new prognostic marker.

Methods

We evaluated biological function and immune cell infiltration in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients from TCGA and GEO databases between different clusters based on autophagy related hub genes. Autophagy scores were used to assess the degree of autophagy in each individual by using component analysis.

Results

Three different clusters were obtained. Gene set variation analysis, single-sample gene set enrichment analysis and survive analysis showed differences among these three clusters. We demonstrated that the autophagy score of each patient could predict tumor stage and prognosis. Patients with a high autophagy score had a better prognosis, higher immune infiltration, and were more sensitive to immunotherapy and conventional chemotherapy.

Conclusion

It was uncovered that autophagy played an irreplaceable role in NSCLC. Quantified autophagy scores for each NSCLC patient would help guide effective treatment strategies.

Comprehensive analysis of the expression levels and prognostic values of PRDX family genes in glioma

Gliomas are a histologically and molecularly heterogeneous group of neoplasms accounting for 80% of malignant primary brain tumors. Growing evidence suggests that production of reactive oxygen species (ROS) is linked to glioma pathogenesis, although it is still unclear whether it is a cause or an effect of this process. Peroxiredoxins (PRDXs), a family of six antioxidant proteins, may promote or inhibit carcinogenesis, depending on the tumor type and stage. The current knowledge on their expression, regulation and functions in glioma is scarce. In this study, a comprehensive analysis of PRDXs expression in distinct glioma subtypes and non-tumor brain tissues was conducted using gene expression data from The Cancer Genome Atlas (TCGA), REpository for Molecular BRAin NeoplasiaDaTa (REMBRANDT), The Chinese Glioma Atlas (CGGA) and Gene Expression Omnibus (GEO) datasets. The association between gene expression and patient survival was investigated. DNA methylation, mutations, copy number alterations of deregulated PRDXs as well as the correlation between gene expression and tumor-infiltrating immune cells were assessed. The analysis revealed overexpression of PRDX1, PRDX4, and PRDX6 in most histological glioma types compared to the non-tumor tissues, while PRDX2, PRDX3 and PRDX5 expression remained unaltered. The expression of PRDX4 and PRDX6 was higher in mesenchymal than proneural and classical glioma subtypes. Moreover, lower expression of PRDX1, PRDX4 and PRDX6 was observed in tumors with a glioma CpG island methylator phenotype (G-CIMP) compared to non-G-CIMP tumors, as well as in isocitrate dehydrogenase (IDH) mutant and 1p/19q co-deleted gliomas compared to the wild-type counterparts. High expression of PRDX1, PRDX4 or PRDX6 correlated with poor survival of glioma patients. PRDX1 and PRDX6 displayed a positive correlation with different immune cell population in low grade gliomas and, to a lesser extent, in glioblastoma. PRDX1 expression exhibited negative correlation with DNA methylation. These results indicate that high expression of PRDX1, PRDX4 and PRDX6 is associated with poor outcome in gliomas.