MicroRNA-711 is a prognostic factor for poor overall survival and has an oncogenic role in breast cancer

Micro RNAs as a Diagnostic Marker between Glioma and Primary CNS Lymphoma: A Systematic Review

Differentiating glioma from primary central nervous system lymphoma (PCNSL) can be challenging, and current diagnostic measures such as MRI and biopsy are of limited efficacy. Liquid biopsies, which detect circulating biomarkers such as microRNAs (miRs), may provide valuable insights into diagnostic biomarkers for improved discrimination. This review aimed to investigate the role of specific miRs in diagnosing and differentiating glioma from PCNSL. A systematic search was conducted of PubMed, Scopus, Web of Science, and Embase for articles on liquid biopsies as a diagnostic method for glioma and PCNSL. Sixteen dysregulated miRs were identified with significantly different levels in glioma and PCNSL, including miR-21, which was the most prominent miR with higher levels in PCNSL, followed by glioma, including glioblastoma (GBM), and control groups. The lowest levels of miR-16 and miR-205 were observed in glioma, followed by PCNSL and control groups, whereas miR-15b and miR-301 were higher in both tumor groups, with the highest levels observed in glioma patients. The levels of miR-711 were higher in glioma (including GBM) and downregulated in PCNSL compared to the control group. This review suggests that using these six circulating microRNAs as liquid biomarkers with unique changing patterns could aid in better discrimination between glioma, especially GBM, and PCNSL.

A Tumor and Immune-Related Micro-RNA Signature Predicts Relapse-Free Survival of Melanoma Patients Treated with Ipilimumab

Despite the unprecedented advances in the treatment of melanoma with immunotherapy, there continues to be a major need for biomarkers of clinical benefits and immune resistance associated with immune checkpoint inhibitors; microRNA could play a vital role in these efforts. This study planned to identify differentially expressed miRNA molecules that may have prognostic value for clinical benefits. Patients with surgically operable regionally advanced melanoma were treated with neoadjuvant ipilimumab (10 mg/kg intravenously every 3 weeks × two doses) bracketing surgery. Tumor biospecimens were obtained at baseline and surgery, and microRNA (miRNA) expression profiling was performed on the tumor biopsies. We found that an expression profile consisting of a 4-miRNA signature was significantly associated with improved relapse-free survival (RFS). The signature consisted of biologically relevant molecules previously reported to have prognostic value in melanoma and other malignancies, including miR-34c, miR-711, miR-641, and miR-22. Functional annotation analysis of target genes for the 4-miRNA signature was significantly enriched for various cancer-related pathways, including cell proliferation regulation, apoptosis, the MAPK signaling pathway, and the positive regulation of T cell activation. Our results presented miRNAs as potential biomarkers that can guide the treatment of melanoma with immune checkpoint inhibitors. These findings warrant further investigation in relation to CTLA4 blockade and other immune checkpoint inhibitors. ClinicalTrials.gov NCT00972933.

Prognostic role of microRNAs in breast cancer: A systematic review

MicroRNAs (miRNAs) have been found to play an important role in breast cancer, functioning either as potential oncogenes or tumor suppressor genes, but their role in the prognosis of patients remains unclear. The aim of the present review study is to highlight recent preclinical and clinical studies performed on both circulating and tissue-specific miRNAs and their potential role as prognostic markers in breast cancer. We systematically searched the PubMed database to explore the prognostic value of miRNAs in breast cancer. After performing the literature search and review, 117 eligible studies were identified. We found that 110 aberrantly expressed miRNAs have been associated with prognosis in breast cancer. In conclusion, the collective data presented in this review indicate that miRNAs could serve as novel prognostic tools in breast cancer, while the clinical application of these findings has yet to be verified.

Inhibition of microRNA-711 limits angiopoietin-1 and Akt changes, tissue damage, and motor dysfunction after contusive spinal cord injury in mice

Spinal cord injury (SCI) causes neuronal cell death and vascular damage, which contribute to neurological dysfunction. Given that many biochemical changes contribute to such secondary injury, treatment approaches have increasingly focused on combined therapies or use of multi-functional drugs. MicroRNAs (miRs) are small (20-23 nucleotide), non-protein-coding RNAs and can negatively regulate target gene expression at the post-transcriptional level. As individual miRs can potentially modulate expression of multiple relevant proteins after injury, they are attractive candidates as upstream regulators of the secondary SCI progression. In the present study we examined the role of miR-711 modulation after SCI. Levels of miR-711 were increased in injured spinal cord early after SCI, accompanied by rapid downregulation of its target angiopoietin-1 (Ang-1), an endothelial growth factor. Changes of miR-711 were also associated with downregulation of the pro-survival protein Akt (protein kinase B), another target of miR-711, with sequential activation of glycogen synthase kinase 3 and the pro-apoptotic BH3-only molecule PUMA. Central administration of a miR-711 hairpin inhibitor after SCI limited decreases of Ang-1/Akt expression and attenuated apoptotic pathways. Such treatment also reduced neuronal/axonal damage, protected microvasculature and improved motor dysfunction following SCI. In vitro, miR-711 levels were rapidly elevated by neuronal insults, but not by activated microglia and astrocytes. Together, our data suggest that post-traumatic miR-711 elevation contributes to neuronal cell death after SCI, in part by inhibiting Ang-1 and Akt pathways, and may serve as a novel therapeutic target.

A network embedding-based multiple information integration method for the MiRNA-disease association prediction

BACKGROUND

MiRNAs play significant roles in many fundamental and important biological processes, and predicting potential miRNA-disease associations makes contributions to understanding the molecular mechanism of human diseases. Existing state-of-the-art methods make use of miRNA-target associations, miRNA-family associations, miRNA functional similarity, disease semantic similarity and known miRNA-disease associations, but the known miRNA-disease associations are not well exploited.

RESULTS

In this paper, a network embedding-based multiple information integration method (NEMII) is proposed for the miRNA-disease association prediction. First, known miRNA-disease associations are formulated as a bipartite network, and the network embedding method Structural Deep Network Embedding (SDNE) is adopted to learn embeddings of nodes in the bipartite network. Second, the embedding representations of miRNAs and diseases are combined with biological features about miRNAs and diseases (miRNA-family associations and disease semantic similarities) to represent miRNA-disease pairs. Third, the prediction models are constructed based on the miRNA-disease pairs by using the random forest. In computational experiments, NEMII achieves high-accuracy performances and outperforms other state-of-the-art methods: GRNMF, NTSMDA and PBMDA. The usefulness of NEMII is further validated by case studies. The studies demonstrate the great potential of network embedding method for the miRNA-disease association prediction, and SDNE outperforms other popular network embedding methods: DeepWalk, High-Order Proximity preserved Embedding (HOPE) and Laplacian Eigenmaps (LE).

CONCLUSION

We propose a new method, named NEMII, for predicting miRNA-disease associations, which has great potential to benefit the field of miRNA-disease association prediction.

Dual Convolutional Neural Network Based Method for Predicting Disease-Related miRNAs

Identification of disease-related microRNAs (disease miRNAs) is helpful for understanding and exploring the etiology and pathogenesis of diseases. Most of recent methods predict disease miRNAs by integrating the similarities and associations of miRNAs and diseases. However, these methods fail to learn the deep features of the miRNA similarities, the disease similarities, and the miRNA–disease associations. We propose a dual convolutional neural network-based method for predicting candidate disease miRNAs and refer to it as CNNDMP. CNNDMP not only exploits the similarities and associations of miRNAs and diseases, but also captures the topology structures of the miRNA and disease networks. An embedding layer is constructed by combining the biological premises about the miRNA–disease associations. A new framework based on the dual convolutional neural network is presented for extracting the deep feature representation of associations. The left part of the framework focuses on integrating the original similarities and associations of miRNAs and diseases. The novel miRNA and disease similarities which contain the topology structures are obtained by random walks on the miRNA and disease networks, and their deep features are learned by the right part of the framework. CNNDMP achieves the superior prediction performance than several state-of-the-art methods during the cross-validation process. Case studies on breast cancer, colorectal cancer and lung cancer further demonstrate CNNDMP’s powerful ability of discovering potential disease miRNAs.

Evaluation of miR-711 as Novel Biomarker in Prostate Cancer Progression

Objective:

MicroRNAs (miRs) are class of small non-coding regulatory RNA aberrantly expressed in various types of malignancies including prostate cancer and serves as potential targets to develop new diagnostic and therapeutic strategies. In this quiet we investigated miRNAs expression profile in benign prostatic hyperplasia (BPH) and prostate cancer (PCa) tissue samples and correlated their expression with clinicopathological parameters.

Methodology:

The miRNAs expression profile as well as their validation has been done by using Microarray and RT-PCR, respectively. Additionally, we also tried to speculate microRNA-mRNA regulatory module through computational target predictions by using Targetscan, Miranda and MirWalk and obtained results were analysed through DAVID software.

Result:

We observed that miR-711 is significantly deregulated in BPH and PCa, compared to controls. The lower expression of miR-711 was found to be significantly associated with high Gleason score and metastatic disease. Furthermore, the computational target prediction analysis explored miR-711 association to various cancer cells signalling cascade key molecules associated with cancer cell survival.

Conclusion:

From our observations we suggest that miR-711 may play a critical role in PCa progression, regulation of various cancer cell survival signalling cascades and that it may be a valuable biomarker for prediction of metastatic disease and poor prognosis in PCa.

Expression of miR-711 and mechanism of proliferation and apoptosis in human gastric carcinoma

MicroRNAs (miRs) are involved in many aspects of cell biology, including cell proliferation and apoptosis, two critical aspects of tumor biology. We investigated the effect of miR-711 on Bcl-2 expression in human MGC803 gastric cancer cells and the mechanism of cell proliferation, apoptosis, and invasion. Expression of miR-711 and Bcl-2 was significantly increased in gastric adenocarcinoma compared to adjacent normal tissue. Inhibition of miR-711 in MGC803 gastric cancer cells decreased the expression of Bcl-2, decreased cell proliferation, decreased the invasion ability, and increased apoptosis. The expression of Bcl-2 protein correlated with clinical staging, lymph node metastasis, and tumor differentiation in patients with gastric cancer. The expression of miR-711 positively correlated with the expression of Bcl-2, suggesting that miR-711 and Bcl-2 are co-regulated and involved in the development of gastric cancer.

G9A performs important roles in the progression of breast cancer through upregulating its targets

Breast cancer (BC) is the most common type of malignancy in females worldwide, however, its underlying mechanisms remain poorly understood. The present study aimed to investigate the mechanisms behind the development and progression of BC and identify potential biomarkers for it. The chromatin immunoprecipitation-DNA sequencing (ChIP-Seq) dataset GSM1642516 and gene expression dataset GSE34925 were downloaded from the Gene Expression Omnibus database. Affy and oligo packages were used for the background correction and normalization of the gene expression dataset. Based on Limma package and the criteria of a fold change >1.41 or <0.71, and a false discovery rate adjusted P-value <0.05, differentially-expressed genes (DEGs) in euchromatic histone lysine methyltransferase 2 (G9A) -knockout (KO) breast samples compared with control samples were identified. The Database for Annotation, Visualization and Integrated Analysis was used for the functional enrichment analysis of the DEGs. Bowtie 2 and model-based analysis of ChIP-Seq version 14 (macs14) were used for the mapping of raw reads and the identification of G9A binding sites (peaks), respectively. In addition, overlapping genes between the DEGs and genes in the peaks located in −3000 to 3000 bp centered in the transcription start sites (conpeaks) were screened out and microRNAs (miRNAs) believed to regulate those overlaps were identified through the TargetScan database. A total of 217 DEGs were identified in G9A-KO samples, which were mainly involved in the biological processes and pathways associated with the inflammatory response and cancer progression. A total of 10,422 peaks, containing 1,210 conpeaks involving 1,138 genes, were identified. Among the 1,138 genes, 15 were overlapped with the DEGs, and 35 miRNAs were identified to regulate those overlaps. Insulin-induced gene 1 was regulated by 9 genes in the miRNA-gene regulation network, which may indicate its importance in the progression of BC. The present study identified potential biomarkers of BC that may be useful in the diagnosis and treatment of patients with the disease.

MicroRNAs as biomarkers for early breast cancer diagnosis, prognosis and therapy prediction

Breast cancer is a major health problem that affects one in eight women worldwide. As such, detecting breast cancer at an early stage anticipates better disease outcome and prolonged patient survival. Extensive research has shown that microRNA (miRNA) are dysregulated at all stages of breast cancer. miRNA are a class of small noncoding RNA molecules that can modulate gene expression and are easily accessible and quantifiable. This review highlights miRNA as diagnostic, prognostic and therapy predictive biomarkers for early breast cancer with an emphasis on the latter. It also examines the challenges that lie ahead in their use as biomarkers. Noteworthy, this review addresses miRNAs reported in patients with early breast cancer prior to chemotherapy, radiotherapy, surgical procedures or distant metastasis (unless indicated otherwise). In this context, miRNA that are mentioned in this review were significantly modulated using more than one statistical test and/or validated by at least two studies. A standardized protocol for miRNA assessment is proposed starting from sample collection to data analysis that ensures comparative analysis of data and reproducibility of results.

Down-regulation of miR-199b-5p is correlated with poor prognosis for breast cancer patients

OBJECTIVES

The purpose of the present study was to evaluate the prognostic value of miR-199b-5p in breast cancer patients, as well as explore its effects on breast cancer cells.

METHODS

The expression level of miR-199b-5p in breast cancer tissues and paired non-cancerous tissues were detected by quantitative real-time polymerase chain reaction (qRT-PCR). Chi-square test was used to evaluate the relationship between miR-199b-5p expression and clinical parameters. Besides, overall survival analysis was carried out with Kaplan-Meier curve with log rank test, and the prognostic value of miR-199b-5p in breast cancer was evaluated by cox regression model. In addition, MTT and transwell assays in vitro were used to estimate the effects of miR-199b-5p on breast cancer cells.

RESULTS

MiR-199b-5p was down-regulated in breast cancer tissues, compared with adjacent normal tissues (P<0.05). Moreover, its decreased level was significantly correlated with advanced TNM stage (P=0.008) and positive lymph node metastasis (P=0.013). Cell experiments suggested that miR-199b-5p could regulate proliferation and invasion of breast cancer cells. In addition, we found that breast cancer patients with low miR-199b-5p expression level had poorer overall survival than those with high level (log rank test, P=0.021). MiR-199b-5p was an independent prognostic factor for breast cancer patients (HR=2.318, 95%CI=1.086-4.949, P=0.030).

CONCLUSION

Down-regulated miR-199b-5p in breast cancer patients is associated with malignant clinical characteristics. MiR-199b-5p may be a potential prognostic biomarker for breast cancer.

The novel miR-9501 inhibits cell proliferation, migration and activates apoptosis in non-small cell lung cancer

Accumulating evidences suggest that lots of microRNAs (miRNAs) play crucial roles in (patho-)physiological processes of lung cancer, including metastasis, drug-resistance or tumorigenesis. They mediate the progression of cell growth, migration and invasion by regulating the expression of special genes. MiRNA expression patterns could also serve as diagnostic/prognostic biomarkers. Cancer therapies mediated by miRNAs remain tremendous potential and challenges. Our previous small RNA-seq assay found that the novel miR-9501 was down-regulated in lung cancer tissues compared with adjacent non-cancer tissues. In this study, our results verified that miR-9501 was significantly down-regulated in lung cancer tissues and its expression levels were remarkably suppressed in non-small cell lung cancer cell lines. Then, we characterized and investigated the novel miR-9501 in A549 cells. Transient transfection of miR-9501 into cultured A549 cells led to remarkable decrease in cell proliferation, migration and increase apoptosis. These data demonstrated that miR-9501 might be a tumor suppressor for lung cancer therapy.