Identification of circRNA Biomarker for Gastric Cancer through Integrated Analysis

Extracellular vesicle-delivered hsa_circ_0090081 regulated by EIF4A3 enhances gastric cancer tumorigenesis

BACKGROUND

Circular RNA (circRNA) and extracellular vesicles (EVs) in tumors are crucial for the malignant phenotype of tumor cells. Nevertheless, the mechanisms and clinical effects of EV-delivered hsa_circ_0090081 in gastric cancer (GC) are unclear. This study aimed to reveal the effect of eukaryotic translation initiation factor 4A3 (EIF4A3)-mediated hsa_circ_0090081 expression and EV-delivered hsa_circ_0090081 on GC progression.

METHODS

qRT-PCR was conducted to clarify hsa_circ_0090081 and EIF4A3 levels in GC tissues. Transmission electronic microscopy (TEM), nanoparticle tracking analysis (NTA), and Western blotting identified the EVs isolated from GC cells by ultracentrifugation. The roles of hsa_circ_0090081, EIF4A3, and EV-delivered hsa_circ_0090081 in GC cells were analyzed using Transwell, EdU, and CCK-8 assays. The regulatory role between EIF4A3 and hsa_circ_0090081 was investigated using RIP, qRT-PCR, and Pearson's analysis.

RESULTS

Our study showed that hsa_circ_0090081 and EIF4A3 were highly expressed in GC, and hsa_circ_0090081 was associated with poor prognosis. Data revealed that hsa_circ_0090081 inhibition restrained GC cell proliferation, invasion, and migration. Additionally, EIF4A3 could bind to the pre-mRNA of PHEX (linear form of hsa_circ_0090081) to enhance hsa_circ_0090081 expression in GC cells. Moreover, EIF4A3 overexpression nullified the malignant phenotypic suppression caused by hsa_circ_0090081 silencing in GC cells. Furthermore, EVs secreted by GC cells delivered hsa_circ_0090081 to facilitate the malignant progression of targeted GC cells.

CONCLUSION

This study showed that hsa_circ_0090081 was enhanced by EIF4A3 to play a promotive role in GC development. The results may help understand the mechanism of EIF4A3 and EV-delivered hsa_circ_0090081 and offer a valuable GC therapeutic target.

CircRNA_0044556 affects the sensitivity of triple-negative breast cancer cells to paclitaxel by regulating miR-665

CircRNAs have been implicated in the development of resistance in triple-negative breast cancer (TNBC). However, the association between circRNA_0044556 and paclitaxel (PTX) resistance in TNBC is still limited. Therefore, the purpose of this study was to investigate the effect of circRNA_0044556 on biological function and PTX resistance in TNBC cells. PTX-resistant TNBC cells (MDA-MB-231/PTX) were obtained by continuously exposing MDA-MB-231 cells to increasing paclitaxel levels. The expression levels of circRNA_0044556 and miR-665 were measured by qRT-PCR. The regulatory relationship between miR-665 and circRNA_0044556 was verified by biological information website analysis and double-luciferase reporter gene detection experiments. MTT assay, clone assay, flow cytometry and Western blot analysis were used to evaluate the influence of cell biological function. Elevated circRNA_0044556 was observed in TNBC, and paclitaxel increased the expression of circRNA_0044556 in TNBC cells. In TNBC, circRNA_0044556 acted as a ceRNA for miR-665. In addition, low expression of circRNA_0044556 combined with miR-665 inhibited the proliferation of TNBC cells and paclitaxel-resistant TNBC cells while inducing cell death. Our study demonstrated that the downregulation of circRNA_0044556 inhibits the malignant progression of TNBC cells and paclitaxel resistance via miR-665. Thus, circRNA_0044556 may be a potential therapeutic target for PTX-resistance TNBC.

Circular RNAs Variously Participate in Coronary Atherogenesis

Over the past decade, numerous studies have shown that circular RNAs (circRNAs) play a significant role in coronary artery atherogenesis and other cardiovascular diseases. They belong to the class of non-coding RNAs and arise as a result of non-canonical splicing of premature RNA, which results in the formation of closed single-stranded circRNA molecules that lack 5'-end caps and 3'-end poly(A) tails. circRNAs have broad post-transcriptional regulatory activity. Acting as a sponge for miRNAs, circRNAs compete with mRNAs for binding to miRNAs, acting as competing endogenous RNAs. Numerous circRNAs are involved in the circRNA-miRNA-mRNA regulatory axes associated with the pathogenesis of cardiomyopathy, chronic heart failure, hypertension, atherosclerosis, and coronary artery disease. Recent studies have shown that сirc_0001445, circ_0000345, circ_0093887, сircSmoc1-2, and circ_0003423 are involved in the pathogenesis of coronary artery disease (CAD) with an atheroprotective effect, while circ_0002984, circ_0029589, circ_0124644, circ_0091822, and circ_0050486 possess a proatherogenic effect. With their high resistance to endonucleases, circRNAs are promising diagnostic biomarkers and therapeutic targets. This review aims to provide updated information on the involvement of atherogenesis-related circRNAs in the pathogenesis of CAD. We also discuss the main modern approaches to detecting and studying circRNA-miRNA-mRNA interactions, as well as the prospects for using circRNAs as biomarkers and therapeutic targets for the treatment of cardiovascular diseases.

Novel biomarkers for early detection of gastric cancer

Gastric cancer (GC) remains a leading cause of cancer-related death worldwide. Less than half of GC cases are diagnosed at an advanced stage due to its lack of early symptoms. GC is a heterogeneous disease associated with a number of genetic and somatic mutations. Early detection and effective monitoring of tumor progression are essential for reducing GC disease burden and mortality. The current widespread use of semi-invasive endoscopic methods and radiologic approaches has increased the number of treatable cancers: However, these approaches are invasive, costly, and time-consuming. Thus, novel molecular noninvasive tests that detect GC alterations seem to be more sensitive and specific compared to the current methods. Recent technological advances have enabled the detection of blood-based biomarkers that could be used as diagnostic indicators and for monitoring postsurgical minimal residual disease. These biomarkers include circulating DNA, RNA, extracellular vesicles, and proteins, and their clinical applications are currently being investigated. The identification of ideal diagnostic markers for GC that have high sensitivity and specificity would improve survival rates and contribute to the advancement of precision medicine. This review provides an overview of current topics regarding the novel, recently developed diagnostic markers for GC.

EIF4A3 induced circABCA5 promotes the gastric cancer progression by SPI1 mediated IL6/JAK2/STAT3 signaling

Gastric cancer is one of the most common malignancies of the digestive system with high mortality rates. Recent studies have demonstrated that circRNAs are novel noncoding RNAs that play vital roles in the tumorigenesis and development of gastric cancer. Our study found a novel circRNA, namely, hsa_circ_0107595 (also called circABCA5), that is overexpressed in gastric cancer based on circRNA sequencing. qPCR demonstrated its overexpression in gastric cancer specimens. The overexpression or knockdown of circABCA5 in gastric cancer cell lines was achieved by lentiviral-mediated transfection. All MTS, EdU, Transwell and migration assays and xenograft experiments demonstrated that circABCA5 could promote gastric cancer proliferation, invasion, and migration in vitro and in vivo. Mechanistically, both RIP and RNA pulldown assays confirmed that circABCA5 could bind to the SPI1 protein, upregulate SPI1 expression, and promote its nuclear translocation. SPI1 could further promote the malignant phenotype of gastric cancer by activating IL6/JAK2/STAT3 signaling. In addition, EIF4A3 could directly bind to circABCA5, promoting its stability and expression. Our study reveals that circABCA5 plays a vital role in the diagnosis and prognosis of gastric cancer and may even be developed as a molecular target for the treatment of gastric cancer.

alpha2,3 sialic acid processing enzymes expression in gastric cancer tissues reveals that ST3Gal3 but not Neu3 are associated with Lauren's classification, angiolymphatic invasion and histological grade

Gastric cancer (GC) is one of the leading causes of cancer-related deaths worldwide. Despite progress in the last decades, there are still no reliable biomarkers for the diagnosis of and prognosis for GC. Aberrant sialylation is a widespread critical event in the development of GC. Neuraminidases (Neu) and sialyltransferases (STs) regulate the ablation and addition of sialic acid during glycoconjugates biosynthesis, and they are a considerable source of biomarkers in various cancers. This study retrospectively characterized Neu3 and ST3Gal3 expression by immunohistochemistry in 71 paraffin-embedded GC tissue specimens and analyzed the relationship between their expression and the clinicopathological parameters. Neu3 expression was markedly increased in GC tissues compared with non-tumoral tissues (p<0.0001). Intratumoral ST3Gal3 staining was significantly associated with intestinal subtype (p=0.0042) and was negatively associated with angiolymphatic invasion (p=0.0002) and higher histological grade G3 (p=0.0066). Multivariate analysis revealed that ST3Gal3 positivity is able to predict Lauren's classification. No associations were found between Neu3 staining and clinical parameters. The in silico analysis of mRNA expression in GC validation cohorts corroborates the significant ST3Gal3 association with higher histological grade observed in our study. These findings suggest that ST3Gal3 expression may be an indicator for aggressiveness of primary GC.

Circ_CEA promotes the interaction between the p53 and cyclin-dependent kinases 1 as a scaffold to inhibit the apoptosis of gastric cancer

Circular RNAs (circRNAs) have been reported to play essential roles in tumorigenesis and progression. This study aimed to identify dysregulated circRNAs in gastric cancer (GC) and investigate the functions and underlying mechanism of these circRNAs in GC development. Here, we identify circ_CEA, a circRNA derived from the back-splicing of CEA cell adhesion molecule 5 (CEA) gene, as a novel oncogenic driver of GC. Circ_CEA is significantly upregulated in GC tissues and cell lines. Circ_CEA knockdown suppresses GC progression, and enhances stress-induced apoptosis in vitro and in vivo. Mechanistically, circ_CEA interacts with p53 and cyclin-dependent kinases 1 (CDK1) proteins. It serves as a scaffold to enhance the association between p53 and CDK1. As a result, circ_CEA promotes CDK1-mediated p53 phosphorylation at Ser315, then decreases p53 nuclear retention and suppresses its activity, leading to the downregulation of p53 target genes associated with apoptosis. These findings suggest that circ_CEA protects GC cells from stress-induced apoptosis, via acting as a protein scaffold and interacting with p53 and CDK1 proteins. Combinational therapy of targeting circ_CEA and chemo-drug caused more cell apoptosis, decreased tumor volume and alleviated side effect induced by chemo-drug. Therefore, targeting circ_CEA might present a novel treatment strategy for GC.

Identification of key candidate genes for IgA nephropathy using machine learning and statistics based bioinformatics models

Immunoglobulin-A-nephropathy (IgAN) is a kidney disease caused by the accumulation of IgAN deposits in the kidneys, which causes inflammation and damage to the kidney tissues. Various bioinformatics analysis-based approaches are widely used to predict novel candidate genes and pathways associated with IgAN. However, there is still some scope to clearly explore the molecular mechanisms and causes of IgAN development and progression. Therefore, the present study aimed to identify key candidate genes for IgAN using machine learning (ML) and statistics-based bioinformatics models. First, differentially expressed genes (DEGs) were identified using limma, and then enrichment analysis was performed on DEGs using DAVID. Protein-protein interaction (PPI) was constructed using STRING and Cytoscape was used to determine hub genes based on connectivity and hub modules based on MCODE scores and their associated genes from DEGs. Furthermore, ML-based algorithms, namely support vector machine (SVM), least absolute shrinkage and selection operator (LASSO), and partial least square discriminant analysis (PLS-DA) were applied to identify the discriminative genes of IgAN from DEGs. Finally, the key candidate genes (FOS, JUN, EGR1, FOSB, and DUSP1) were identified as overlapping genes among the selected hub genes, hub module genes, and discriminative genes from SVM, LASSO, and PLS-DA, respectively which can be used for the diagnosis and treatment of IgAN.