Plasma miR‑15b‑5p and miR‑590‑5p for distinguishing patients with bladder cancer from healthy individuals

Tölle, Angelika; Buckendahl, Laura; Jung, Klaus

doi:10.3892/or.2019.7247

Cited by 11 publications

(4 citation statements)

References 62 publications

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“…Investigation of the mechanisms underlying the regulation of breast cancer by miRNAs is essential (9). The miRNA miR-15b-5p, a mature miRNA which is spliced from the 5 ′ -end of pre-miR-15b (10), has been reported to be expressed in many cancers, including gastric cancer (11), colorectal cancer (12), prostate cancer (13), bladder cancer (14), and hepatocellular carcinoma (15). In these tumors, miR-15b-5p promotes proliferation, decreases apoptosis, induces tumor metastasis and recurrence, and is associated with poor patient prognosis.…”

Section: Introductionmentioning

confidence: 99%

miR-15b-5p Promotes Growth and Metastasis in Breast Cancer by Targeting HPSE2

Liu

Jin

et al. 2020

Front. Oncol.

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MicroRNAs (miRNAs) can participate in many behaviors of various tumors. Prior studies have reported that miR-15b-5p in different tumors can either promote or inhibit tumor progression. In breast cancer, the role of miR-15b-5p is unclear. The main objective of this paper is to explore miR-15b-5p effects and their mechanisms in breast cancer using both in vitro and in vivo experiments. This study showed that miR-15b-5p expression was upregulated in breast cancer compared with normal breast tissue and was positively correlated with poor overall survival in patients. Knockdown of miR-15b-5p in MCF-7 and MD-MBA-231 breast cancer cells restrained cell growth and invasiveness and induced apoptosis, whereas overexpression of miR-15b-5p achieved the opposite effects. We next revealed a negative correlation between miR-15b-5p and heparanase-2 (HPSE2) expression in breast cancer. Knockdown of miR-15b-5p significantly increased HPSE2 expression at both mRNA and protein levels in breast cancer cells in vitro. The underlying mechanisms of miR-15-5p in breast cancer were investigated using luciferase activity reporter assay and rescue experiments. In addition, miR-15b-5p knockdown significantly inhibited tumor growth in a xenograft model in mice. In summary, we showed that miR-15b-5p promotes breast cancer cell proliferation, migration, and invasion by directly targeting HPSE2. Accordingly, miR-15b-5p may serve both as a tool for prognosis and as a target for therapy of breast cancer patients.

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Section: Introductionmentioning

confidence: 99%

miR-15b-5p Promotes Growth and Metastasis in Breast Cancer by Targeting HPSE2

Liu

Jin

et al. 2020

Front. Oncol.

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“…or HIF-1α expression [30,31] . Increased miR-15b-5p has also been detected as a biomarker of more aggressive cancers [32] , and miR-150-5p upregulation has previously been reported in liver cancer [33] . It is thus important the functional roles of these miRNAs in HCV-related HCC be further studied.…”

Section: Discussionmentioning

confidence: 83%

Construction of Novel mRNA-miRNA-lncRNA Regulatory Networks Associated with Prognosis of HCV Related HCC

Ma¹,

Shao

Shi

et al. 2021

Preprint

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Background: Infection with hepatitis C virus (HCV) can cause hepatic fibrosis and cirrhosis, thereby significantly increasing the risk of HCC development. Many prior studies have shown that oncogenesis and cancer progression are governed by competing endogenous RNA (ceRNA) networks composed of long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs. As such, we herein sought to identify and evaluate the prognostic relevance of novel ceRNA network related to HCC associated with HCV. Methods: Differentially expressed genes (DEGs) in the GSE140845 Gene Expression Omnibus (GEO) dataset were identified using NetworkAnalyst, and were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Gene, Genome (KEGG) pathway, and Reactome analyses. In addition, a protein-protein interaction (PPI) network was generated, and key hub genes were detected. Hub gene expression levels, as well as those of their upstream lncRNAs and miRNAs and associated survival analyses were conducted using appropriate bioinformatics databases. Predicted target relationships were additionally used to establish putative ceRNA networks for HCV-related HCC. Results: 372 and 360 upregulated and downregulated significant DEGs were identified, respectively. Functional enrichment analyses suggested that DE-mRNAs were associated with nuclear division, the cell cycle, and ATPase activity. The top 11 genes with the greatest degree of connectivity among these DE-mRNAs were selected for subsequent prognostic evaluation. The differential expression of six of these candidate mRNAs (BUB1, BUB1B, CDC20, CDC45, CDK1, NDC80) in liver tissue was validated. After further analyses of the expression and prognostic relevance of the miRNAs and lncRNAs predicted to lie upstream of these DE-mRNAs, we identified 22 miRNAs and 4 lncRNAs significantly associated with poorer-HCV-related HCC prognosis. By combining the results of these analyses, we also identified the BUB1-hsa-miR-193a-3p-MALAT1 ceRNA sub-network as being related to the survival of these patients. Conclusion: This study providing novel insights into the mRNA-miRNA-lncRNA ceRNA network and reveals potential lncRNA biomarkers in HCV related HCC.

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“…For example, the expression level of miR-203a-3p has been verified to be decreased in cancer [ 42 ]. The decreased expression of miR-10b-5p is markedly linked to cancer [ 43 ]. In the context of cancer, miR-181c-5p experiences specific inhibition through targeted action by the highly expressed LUCAT1, resulting in its diminished expression level [ 44 ].…”

Section: Resultsmentioning

confidence: 99%

IDMIR: identification of dysregulated miRNAs associated with disease based on a miRNA–miRNA interaction network constructed through gene expression data

Wu,

Zhao,

et al. 2024

Briefings in Bioinformatics

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Micro ribonucleic acids (miRNAs) play a pivotal role in governing the human transcriptome in various biological phenomena. Hence, the accumulation of miRNA expression dysregulation frequently assumes a noteworthy role in the initiation and progression of complex diseases. However, accurate identification of dysregulated miRNAs still faces challenges at the current stage. Several bioinformatics tools have recently emerged for forecasting the associations between miRNAs and diseases. Nonetheless, the existing reference tools mainly identify the miRNA-disease associations in a general state and fall short of pinpointing dysregulated miRNAs within a specific disease state. Additionally, no studies adequately consider miRNA–miRNA interactions (MMIs) when analyzing the miRNA-disease associations. Here, we introduced a systematic approach, called IDMIR, which enabled the identification of expression dysregulated miRNAs through an MMI network under the gene expression context, where the network’s architecture was designed to implicitly connect miRNAs based on their shared biological functions within a particular disease context. The advantage of IDMIR is that it uses gene expression data for the identification of dysregulated miRNAs by analyzing variations in MMIs. We illustrated the excellent predictive power for dysregulated miRNAs of the IDMIR approach through data analysis on breast cancer and bladder urothelial cancer. IDMIR could surpass several existing miRNA-disease association prediction approaches through comparison. We believe the approach complements the deficiencies in predicting miRNA-disease association and may provide new insights and possibilities for diagnosing and treating diseases. The IDMIR approach is now available as a free R package on CRAN (https://CRAN.R-project.org/package=IDMIR).

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Plasma miR‑15b‑5p and miR‑590‑5p for distinguishing patients with bladder cancer from healthy individuals

Cited by 11 publications

References 62 publications

miR-15b-5p Promotes Growth and Metastasis in Breast Cancer by Targeting HPSE2

miR-15b-5p Promotes Growth and Metastasis in Breast Cancer by Targeting HPSE2

Construction of Novel mRNA-miRNA-lncRNA Regulatory Networks Associated with Prognosis of HCV Related HCC

IDMIR: identification of dysregulated miRNAs associated with disease based on a miRNA–miRNA interaction network constructed through gene expression data

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