MicroRNA-17 as a promising diagnostic biomarker of gastric cancer: An investigation combining TCGA, GEO, meta-analysis, and bioinformatics

Non-Coding RNA as Biomarkers and Their Role in the Pathogenesis of Gastric Cancer-A Narrative Review

Non-coding RNAs (ncRNAs) represent a broad family of molecules that regulate gene expression, including microRNAs, long non-coding RNAs and circular RNAs, amongst others. Dysregulated expression of ncRNAs alters gene expression, which is implicated in the pathogenesis of several malignancies and inflammatory diseases. Gastric cancer is the fifth most frequently diagnosed cancer and the fourth most common cause of cancer-related death. Studies have found that altered expression of ncRNAs may contribute to tumourigenesis through regulating proliferation, apoptosis, drug resistance and metastasis. This review describes the potential use of ncRNAs as diagnostic and prognostic biomarkers. Moreover, we discuss the involvement of ncRNAs in the pathogenesis of gastric cancer, including their interactions with the members of major signalling pathways.

Investigating the expression level of miR-17-3p, miR-101-3p, miR-335-3p, and miR-296-3p in the peripheral blood of patients with acute myocardial infarction

The role of inflammation has been proven in acute myocardial infarction (AMI) pathogenesis. Due to the effect of NLRP3 gene expression in the inflammation process of MI, we aimed to explore the expression changes and diagnostic power of four inflammation-related miRNAs including miR-17-3p, miR-101-3p, miR-335-3p, miR-296-3p and their potential target, NLRP3, in ST-segment elevation myocardial infarction (STEMI), and non-STEMI (NSTEMI) patients as two major classes of AMI. The expression level of these genes were evaluated in 300 participants equally divided into three groups of STEMI, NSTEMI, and control using quantitative real-time PCR. The expression level of NLRP3 was upregulated in STEMI and NSTEMI patients compared to control subjects. Besides, the expression levels of miR-17-3p, miR-101-3p, and miR-296-3p were significantly downregulated in STEMI and NSTEMI patients compared to controls. The increased expression of NLRP3 had a very strong inverse correlation with miR-17-3p in patients with STEMI and with miR-101-3p in the STEMI and NSTEMI patients. ROC curve analysis showed that the expression level of miR-17-3p had the highest diagnostic power for discrimination between STEMI patients and controls. Remarkably, the combination of all markers resulted in a higher AUC. In summary, there is a significant association between the expression levels of miR-17-3p, miR-101-3p, miR-335-3p, miR-296-3p, and NLRP3 and the incidence of AMI. Although the miR-17-3p expression level has the highest diagnostic power to distinguish between STEMI patients and control subjects, the combination of these miRNAs and NLRP3 could serve as a novel potential diagnostic biomarker of STEMI.

Pan-cancer characterization of cell-free immune-related miRNA identified as a robust biomarker for cancer diagnosis

Minimally invasive testing is essential for early cancer detection, impacting patient survival rates significantly. Our study aimed to establish a pioneering cell-free immune-related miRNAs (cf-IRmiRNAs) signature for early cancer detection. We analyzed circulating miRNA profiles from 15,832 participants, including individuals with 13 types of cancer and control. The data was randomly divided into training, validation, and test sets (7:2:1), with an additional external test set of 684 participants. In the discovery phase, we identified 100 differentially expressed cf-IRmiRNAs between the malignant and non-malignant, retaining 39 using the least absolute shrinkage and selection operator (LASSO) method. Five machine learning algorithms were adopted to construct cf-IRmiRNAs signature, and the diagnostic classifies based on XGBoost algorithm showed the excellent performance for cancer detection in the validation set (AUC: 0.984, CI: 0.980-0.989), determined through 5-fold cross-validation and grid search. Further evaluation in the test and external test sets confirmed the reliability and efficacy of the classifier (AUC: 0.980 to 1.000). The classifier successfully detected early-stage cancers, particularly lung, prostate, and gastric cancers. It also distinguished between benign and malignant tumors. This study represents the largest and most comprehensive pan-cancer analysis on cf-IRmiRNAs, offering a promising non-invasive diagnostic biomarker for early cancer detection and potential impact on clinical practice.

Identification of Key Prognostic-Related miRNA-mRNA Pairs in the Progression of Endometrial Carcinoma

OBJECTIVES

Endometrial carcinoma (EC) is one of the leading causes of death from gynecological cancer due to the high recurrence rate. However, the molecular mechanisms of EC progression are not well understood. This study aimed to identify critical genes and miRNAs associated with the progression and prognosis of EC and find the potential mRNA-miRNA regulatory relationship.

DESIGN

The mRNA and miRNA data were downloaded from The Cancer Genome Atlas (TCGA) database. Next, differentially expressed genes (DEGs) were identified. Subsequently, prognosis-related genes and miRNAs were identified, followed by co-expression analysis of these mRNAs and miRNAs. Materials, Setting, and Methods: Samples in the mRNA microarray were divided into normal (n = 35), early stage (n = 385), and advanced stage (n = 153). Next, DEGs in normal versus early stage and early stage versus advanced stage were, respectively, identified, followed by Venn analysis to screen overlapping DEGs in 2 comparison groups. Based on the expression level of these DEGs, univariate Cox regression analysis and Kaplan-Meier method were performed to obtain prognosis-related genes. Moreover, genes-related miRNAs were predicted, and miRNA-mRNA co-expressed pairs were identified. Then, survival analysis of co-expressed miRNA was performed. Finally, co-expressed genes of key genes were identified, and then functional enrichment analysis was conducted.

RESULTS

After integrating analysis, 326 overlapping (309 upregulated and 17 downregulated) DEGs were obtained. Univariate Cox regression analysis showed that 44 mRNAs and 8 miRNAs were associated with the prognosis of EC. Combined with the co-expressed analysis, only one prognosis-related hsa-miR-326/ELFN2 axis was obtained. In addition, functional enrichment analysis showed that co-expressed genes of ELFN2 were mainly involved in the PI3K-Akt signaling pathway.

LIMITATIONS

These findings were obtained via bioinformatics analysis, and thus further experimental studies are urgently demanded to validate our results.

CONCLUSIONS

One key miRNA-mRNA regulatory pair (hsa-miR-326-ELFN2) was screened. This study provided a bioinformatics basis for the molecular mechanism of EC progression and might contribute to the identification of novel therapeutic targets.

Emerging Role of Circulating Tumor Cells in Gastric Cancer

With over 1 million incidence cases and more than 780,000 deaths in 2018, gastric cancer (GC) was ranked as the 5th most common cancer and the 3rd leading cause of cancer deaths worldwide. Though several biomarkers, including carcinoembryonic antigen (CEA), cancer antigen 19-9 (CA19-9), and cancer antigen 72-4 (CA72-4), have been identified, their diagnostic accuracies were modest. Circulating tumor cells (CTCs), cells derived from tumors and present in body fluids, have recently emerged as promising biomarkers, diagnostically and prognostically, of cancers, including GC. In this review, we present the landscape of CTCs from migration, to the presence in circulation, biologic properties, and morphologic heterogeneities. We evaluated clinical implications of CTCs in GC patients, including diagnosis, prognosis, and therapeutic management, as well as their application in immunotherapy. On the one hand, major challenges in using CTCs in GC were analyzed, from the differences of cut-off values of CTC positivity, to techniques used for sampling, storage conditions, and CTC molecular markers, as well as the unavailability of relevant enrichment and detection techniques. On the other hand, we discussed future perspectives of using CTCs in GC management and research, including the use of circulating tumor microembolies; of CTC checkpoint blockade in immunotherapy; and of organoid models. Despite the fact that there are remaining challenges in techniques, CTCs have potential as novel biomarkers and/or a non-invasive method for diagnostics, prognostics, and treatment monitoring of GC, particularly in the era of precision medicine.

Candidate lncRNA-microRNA-mRNA networks in predicting non-small cell lung cancer and related prognosis analysis

PURPOSE

The role of non-coding RNA, once thought to be dark matter, is increasingly prominent in cancer. Our article explores the effect of non-coding RNA in lung adenocarcinoma and lung squamous cell carcinoma by mining TCGA public database.

METHODS

Download the data by applying the official TCGA software. The data were analyzed by R data analysis packages, 'edgeR', 'gplots' and 'survival'. We better illustrate the potential networks of lung cancer genes by constructing ceRNAs, using Cytoscape software.

RESULTS

We obtained genes which were differentially expressed in lung adenocarcinoma and lung squamous cell carcinoma analysis. Within these differentially expressed genes, we also conducted a survival analysis to find differentially expressed genes associated with prognosis in both lung adenocarcinoma and lung squamous cell carcinoma. Based on genes differentially expressed of both lung adenocarcinoma and lung squamous cell carcinoma, we constructed a ceRNA network to illustrate the mechanism of lung adenocarcinoma and lung squamous cell carcinoma. Our study analyzed genes which were differentially expressed in lung adenocarcinoma and lung squamous cell carcinoma using the TCGA database.

CONCLUSION

Based on this, the prognosis in both lung squamous cell carcinoma and lung adenocarcinoma was analyzed. We have also constructed a ceRNA network to provide a basis for the study of ceRNA in lung adenocarcinoma and lung squamous cell carcinoma.

Analysis of Differential Expression of microRNAs and Their Target Genes in Prostate Cancer: A Bioinformatics Study on Microarray Gene Expression Data

Early diagnosis of prostate cancer (PCa) as the second most common cancer in men is not associated with precise and specific results. Thus, alternate methods with high specificity and sensitivity are needed for accurate and timely detection of PCa. MicroRNAs regulate the molecular pathways involved in cancer by targeting multiple genes. The aberrant expression of the microRNAs has been reported in different cancer types including PCa. In this bioinformatics study, we studied differential expression profiles of microRNAs and their target genes in four PCa gene expression omnibus (GEO) databases. PCa diagnostic biomarker candidates were investigated using bioinformatics tools for analysis of gene expression data, microRNA target prediction, pathway and GO annotation, as well as ROC curves. The results of this study revealed significant changes in the expression of 14 microRNAs and 40 relevant target genes, which ultimately composed four combination panels (miR- 375+96+663/ miR- 133b+143- 3p + 205/ C2ORF72 + ENTPD5 + GLYAT11/LAMB3 + NTNG2+TSLP) as candidate biomarkers capable to distinguish between PCa tumor samples and normal prostate tissue samples. These biomarkers may be suggested for a more accurate early diagnosis of PCa patients along with current diagnostic tests.

Cell-free miR-17-5p as a diagnostic biomarker for gastric cancer inhibits dendritic cell maturation

Purpose

Gastric cancer (GC) patients display aberrant miRNA expression and defective dendritic cell function. However, the role of cancer cell-derived oncomiR in GC detection and dendritic cell (DC) maturation remains largely elusive.

Methods

Candidate miRNAs were selected by deep sequencing (8 GC plasma samples vs 8 control plasma samples; 8 GC tissues vs 8 adjacent normal gastric tissues) and confirmed by PCR with 164 plasma samples and 72 formalin-fixed paraffin-embedded GC tissue samples. Their diagnostic performance was evaluated by receiver operating characteristic curve. Cy3 fluorescence signals in DCs, exposed to conditioned medium obtained from BGC-823 cells pre-transfected with Cy3-miR-17-5p, were determined by flow cytometry and visualized by confocal microscopy. Functional and phenotypical alterations of DCs were assayed when DCs were transfected with miR-17-5p in vitro.

Results

Deep sequencing and RT-PCR confirmed that five shared miRNAs were upregulated in plasma and tissue samples of GC patients. Cell-free miR-17-5p was superior to others in GC detection with an area under the curve of 0.82, and correlated with lymphatic metastasis and poor overall survival. GC cell-shuttled miR-17-5p can be delivered to immature DCs, and they significantly inhibited LPS-stimulated phenotypic maturation by diminishing the expression of maturation markers (MHC II, CD80 and CD86 molecules). In line with those alterations in the phenotypic markers, functional experiments demonstrated that miR-17-5p triggered an inhibitory effect on DCs endocytic activity and decreased tumor necrosis factor-α and IL-12 secretion, while enhancing IL-10 production. Mixed lymphocyte reaction showed that miR-17-5p inhibited the T cell stimulating effect of DCs and favored regulatory T cells expansion.

Conclusion

GC cell-derived miR-17-5p is a potential biomarker for GC detection. Taken up by DCs, miR-17-5p weakened antitumor immune responses via inhibiting the maturation of dendritic cells.