A ten-microRNA expression signature predicts survival in glioblastoma

Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients (n=222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (hazard ratio [HR]=2.4; 95% CI=1.4-3.8; p<0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set (HR=1.7; 95% CI=1.1-2.8; p=0.002). GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (HR=2.0; 95% CI=1.4-2.8; p<0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (HR=1.120; 95% CI=1.04-1.20; p=0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy.     

胃癌中显著下调的miR-433的作用靶点研究

目的为了筛选胃癌中miRNAs的表达标记,验证胃癌相关miRNAs的作用靶点,建立一种新的诊断和治疗胃癌的方法。方法运用基因芯片技术检测3个正常胃组织标本,24个胃癌组织标本,胃癌细胞SGC7901和正常胃黏膜细胞GES-1中328个miRNAs的表达情况。用以上方法检测出在胃癌组织和SGC7901中,miR-433的表达水平显著下调。为了确保结果的准确性,采用实时荧光定量PCR对其进行验证。并用基因克隆和Western印迹方法分析miR-433的作用靶点。结果共有26个miRNAs在胃癌标本（包括24个胃癌组织和SGC7901）中异常表达。其中19个miRNAs下调,7个miRNAs上调。实时荧光定量PCR检测出miR-433在胃癌标本中的表达水平显著下调,该结果和基因芯片检测结果一致。另外,在本实验中发现miR-433与Grb2（growth factor receptor—bound protein 2）的表达呈负相关。结论胃癌相关miRNAs已进行了初步筛选。其中,miR-433可能是胃癌中的标记性miRNAs之一,Grb2是其作用靶点。这为建立新的以miRNAs为基础的诊断和治疗胃癌的方法提供了相关信息。     

Identification of a 4-miRNA signature as a potential prognostic biomarker for pancreatic adenocarcinoma

An microRNA (miRNA) signature to predict the clinical outcome of pancreatic adenocarcinoma (PAAD) is still lacking. In the current study, we aimed at identifying and evaluating a prognostic miRNA signature for patients with PAAD. The miRNA expression profile and the clinical information regarding patients with PAAD were recruited from The Cancer Genome Atlas database. Differentially expressed miRNAs were identified between normal and tumor samples. By means of survival analysis, a 4-miRNA signature for predicting patients' with PAAD overall survival (OS) was constructed. Receiver operating characteristic (ROC) analysis was applied to determine the efficiency of survival prediction. Furthermore, the biological function of the predicted miRNAs was evaluated using a bioinformatics approach. Four (hsa-mir-126, hsa-mir-3613, hsa-mir-424, and hsa-mir-4772) out of 17 differentially expressed miRNAs were associated to the OS of patients with PAAD. Moreover, the area under the curve (AUC) of the constructed 4-miRNA signature associated to patients' with PAAD 2-year survival was 0.789. The multivariate Cox's proportional hazards regression model suggested that this 4-miRNA signature was an independent prognostic factor of other clinical parameters in patients with PAAD. Further pathway enrichment analyses revealed that the miRNAs in the 4-miRNA signature might regulate genes that affect focal adhesion, Wnt signaling pathway, and PI3K-Akt signaling pathway. Thus, these findings indicated that the 4-miRNA signature might be an effective independent prognostic biomarker in the prediction of PAAD patients' survival.     

A MiRNA Signature for Defining Aggressive Phenotype and Prognosis in Gliomas

Gliomas represent a disparate group of tumours for which there are to date no cure. Thus, there is a recognized need for new diagnostic and therapeutic approaches based on increased understanding of their molecular nature. We performed the comparison of the microRNA (miRNA) profile of 8 WHO grade II gliomas and 24 higher grade tumours (2 WHO grade III and 22 glioblastomas) by using the Affymetrix GeneChip miRNA Array v. 1.0. A relative quantification method (RT-qPCR) with standard curve was used to confirm the 22 miRNA signature resulted by array analysis. The prognostic performances of the confirmed miRNAs were estimated on the Tumor Cancer Genome Atlas (TCGA) datasets. We identified 22 miRNAs distinguishing grade II gliomas from higher grade tumours. RT-qPCR confirmed the differential expression in the two patients'' groups for 13 out of the 22 miRNAs. The analysis of the Glioblastoma Multiforme (GBM) and Lower Grade Glioma (LGG) datasets from TCGA demonstrated the association with prognosis for 6 of those miRNAs. Moreover, in the GBM dataset miR-21 and miR-210 were predictors of worse prognosis in both univariable and multivariable Cox regression analyses (HR 1.19, p = 0.04, and HR 1.18, p = 0.029 respectively). Our results support a direct contribution of miRNAs to glioma cancerogenesis and suggest that miR-21 and miR-210 may play a role in the aggressive clinical behaviour of glioblastomas.     

MicroRNA signature predicts survival in papillary thyroid carcinoma

Papillary thyroid cancer (PTC) accounts for the majority of malignant thyroid tumors. Recently, several microRNA (miRNA) expression profiling studies have used bioinformatics to suggest miRNA signatures as potential prognostic biomarkers in various malignancies. However, a prognostic miRNA biomarker has not yet been established for PTC. The aim of the present study was to identify miRNAs with prognostic value for the overall survival (OS) of patients with PTC by analyzing high-throughput miRNA data and their associated clinical characteristics downloaded from The Cancer Genome Atlas database. From our dataset, 150 differentially expressed miRNAs were identified between tumor and nontumor samples; of these miRNAs, 118 were upregulated and 32 were downregulated. Among the 150 differentially expressed miRNAs, a four miRNA signature was identified that reliably predicts OS in patients with PTC. This miRNA signature was able to classify patients into a high-risk group and a low-risk group with a significant difference in OS (P < .01). The prognostic value of the signature was validated in a testing set ( P < .01). The four miRNA signature was an independent prognostic predictor according to the multivariate analysis and demonstrated good performance in predicting 5-year disease survival with an area under the receiver operating characteristic curve area under the curve (AUC) score of 0.886. Thus, this signature may serve as a novel biomarker for predicting the survival of patients with PTC.     

MicroRNA Expression Signatures Determine Prognosis and Survival in Glioblastoma Multiforme—a Systematic Overview

Despite advances in our knowledge about glioblastoma multiforme (GBM) pathology, clinical challenges still lie ahead with respect to treatment in GBM due to high prevalence, poor prognosis, and frequent tumor relapse. The implication of microRNAs (miRNAs) in GBM is a rapidly expanding field of research with the aim to develop more targeted molecular therapies. This review aims to present a comprehensive overview of all the available literature, evaluating miRNA signatures as a function of prognosis and survival in GBM. The results are presented with a focus on studies derived from clinical data in databases and independent tissue cohorts where smaller samples sizes were investigated. Here, miRNA associated to longer survival (protective) and miRNA with shorter survival (risk-associated) have been identified and their signatures based on different prognostic attributes are described. Finally, miRNAs associated with disease progression or survival in several studies are identified and functionally described. These miRNAs may be valuable for future determination of patient prognosis and could possibly serve as targets for miRNA-based therapies, which hold a great potential in the treatment of this severe malignant disease.     

Dysregulated microRNAs in the pathogenesis and progression of cervical neoplasm

MicroRNAs (miRNAs) play an important role in a variety of physiological as well as pathophysiological processes, including carcinogenesis. The aim of this study is to identify a distinct miRNA expression signature for cervical intraepithelial neoplasia (CIN) and to unveil individual miRNAs that may be involved in the development of cervical carcinoma. Expression profiling using quantitative real-time RT-PCR of 202 miRNAs was performed on micro-dissected high-grade CIN (CIN 2/3) tissues and compared to normal cervical epithelium. Unsupervised hierarchical clustering of the miRNA expression pattern displayed a distinct separation between the CIN and normal cervical epithelium samples. Supervised analysis identified 12 highly differentially regulated miRNAs, including miR-518a, miR-34b, miR-34c, miR-20b, miR-338, miR-9, miR-512-5p, miR-424, miR-345, miR-10a, miR-193b and miR-203, which distinguished the high-grade CIN specimens from normal cervical epithelium. This miRNA signature was further validated by an independent set of high-grade CIN cases. The same characteristic signature can also be used to distinguish cervical squamous cell carcinoma from normal controls. Target prediction analysis revealed that these dysregulated miRNAs mainly control apoptosis signaling pathways and cell cycle regulation. These findings contribute to understanding the role of microRNAs in the pathogenesis and progression of cervical neoplasm at the molecular level.     

A Systematic Review of MicroRNA in Glioblastoma Multiforme: Micro-modulators in the Mesenchymal Mode of Migration and Invasion

Glioblastoma multiforme (GBM) is an incurable form of brain cancer with a very poor prognosis. Because of its highly invasive nature, it is impossible to remove all tumor cells during surgical resection, making relapse inevitable. Further research into the regulatory mechanism underpinning GBM pathogenesis is therefore warranted, and over the past decade, there has been an increased focus on the functional role of microRNA (miRNA). This systematic review aims to present a comprehensive overview of all the available literature on the expression profiles and function of miRNA in GBM. Here, we have reviewed 163 papers and identified 253 upregulated, 95 downregulated, and 17 disputed miRNAs with respect to expression levels; 85 % of these miRNAs have not yet been functionally characterized. A focus in this study has been 26 interesting miRNAs involved in the mesenchymal mode of migration and invasion, demonstrating the importance of miRNAs in the context of the cellular niche. Both oncogenic and tumor-suppressive miRNAs were found to affect target genes involved in cell migration, cytoskeletal rearrangement, invasiveness, and angiogenesis. Clearly, the distinct functional properties of these miRNAs need further investigation and might hold a great potential in future molecular therapies targeting GBM.     

MicroRNA expression aberration as potential peripheral blood biomarkers for schizophrenia

Since brain tissue is not readily accessible, a new focus in search of biomarkers for schizophrenia is blood-based expression profiling of non-protein coding genes such as microRNAs (miRNAs), which regulate gene expression by inhibiting the translation of messenger RNAs. This study aimed to identify potential miRNA signature for schizophrenia by comparing genome-wide miRNA expression profiles in patients with schizophrenia vs. healthy controls. A genome-wide miRNA expression profiling was performed using a Taqman array of 365 human miRNAs in the mononuclear leukocytes of a learning set of 30 cases and 30 controls. The discriminating performance of potential biomarkers was validated in an independent testing set of 60 cases and 30 controls. The expression levels of the miRNA signature were then evaluated for their correlation with the patients'' clinical symptoms, neurocognitive performances, and neurophysiological functions. A seven-miRNA signature (hsa-miR-34a, miR-449a, miR-564, miR-432, miR-548d, miR-572 and miR-652) was derived from a supervised classification with internal cross-validation, with an area under the curve (AUC) of receiver operating characteristics of 93%. The putative signature was then validated in the testing set, with an AUC of 85%. Among these miRNAs, miR-34a was differentially expressed between cases and controls in both the learning (P = 0.005) and the testing set (P = 0.002). These miRNAs were differentially correlated with patients'' negative symptoms, neurocognitive performance scores, and event-related potentials. The results indicated that the mononuclear leukocyte-based miRNA profiling is a feasible way to identify biomarkers for schizophrenia, and the seven-miRNA signature warrants further investigation.     

Regulatory MicroRNA Networks:Complex Patterns of Target Pathways for Disease-related and Housekeeping MicroRNAs

Blood-based micro RNA(mi RNA) signatures as biomarkers have been reported for various pathologies, including cancer, neurological disorders, cardiovascular diseases, and also infections. The regulatory mechanism behind respective mi RNA patterns is only partially understood. Moreover, ‘‘preserved' mi RNAs, i.e., mi RNAs that are not dysregulated in any disease,and their biological impact have been explored to a very limited extent. We set out to systematically determine their role in regulatory networks by defining groups of highly-dysregulated mi RNAs that contribute to a disease signature as opposed to preserved housekeeping mi RNAs. We further determined preferential targets and pathways of both dysregulated and preserved mi RNAs by computing multi-layer networks, which were compared between housekeeping and dysregulated mi RNAs. Of 848 mi RNAs examined across 1049 blood samples, 8 potential housekeepers showed very limited expression variations, while 20 mi RNAs showed highly-dysregulated expression throughout the investigated blood samples. Our approach provides important insights into mi RNAs and their role in regulatory networks. The methodology can be applied to systematically investigate the differences in target genes and pathways of arbitrary mi RNA sets.     

Identification of differentially expressed microRNAs by microarray: a possible role for microRNA genes in pituitary adenomas

MicroRNAs (miRNAs) are small non-coding RNAs that control gene expression by targeting mRNA. It has been demonstrated that miRNA expression is altered in many human cancers, suggesting that they may play a role in human neoplasia. To determine whether miRNA expression is altered in pituitary adenomas, we analyzed the entire miRNAome in 32 pituitary adenomas and in 6 normal pituitary samples by microarray and by Real-Time PCR. Here, we show that 30 miRNAs are differentially expressed between normal pituitary and pituitary adenomas. Moreover, 24 miRNAs were identified as a predictive signature of pituitary adenoma and 29 miRNAs were able to predict pituitary adenoma histotype. miRNA expression could differentiate micro- from macro-adenomas and treated from non-treated patient samples. Several of the identified miRNAs are involved in cell proliferation and apoptosis, suggesting that their deregulated expression may be involved in pituitary tumorigenesis. Predictive miRNAs could be potentially useful diagnostic markers, improving the classification of pituitary adenomas.     

Impact of miRNA Sequence on miRNA Expression and Correlation between miRNA Expression and Cell Cycle Regulation in Breast Cancer Cells

The miRNAs regulate cell functions by inhibiting expression of proteins. Research on miRNAs had usually focused on identifying targets by base pairing between miRNAs and their targets. Instead of identifying targets, this paper proposed an innovative approach, namely impact significance analysis, to study the correlation between mature sequence, expression across patient samples or time and global function on cell cycle signaling of miRNAs. With three distinct types of data: The Cancer Genome Atlas miRNA expression data for 354 human breast cancer specimens, microarray of 266 miRNAs in mouse Embryonic Stem cells (ESCs), and Reverse Phase Protein Array (RPPA) transfected by 776 miRNAs in MDA-MB-231 cell line, we linked the expression and function of miRNAs by their mature sequence and discovered systematically that the similarity of miRNA expression enhances the similarity of miRNA function, which indicates the miRNA expression can be used as a supplementary factor to predict miRNA function. The results also show that both seed region and 3'' portion are associated with miRNA expression levels across human breast cancer specimens and in ESCs; miRNAs with similar seed tend to have similar 3'' portion. And we discussed that the impact of 3'' portion, including nucleotides , is not significant for miRNA function. These results provide novel insights to understand the correlation between miRNA sequence, expression and function. They can be applied to improve the prediction algorithm and the impact significance analysis can also be implemented to similar analysis for other small RNAs such as siRNAs.     

Estimating survival time of patients with glioblastoma multiforme and characterization of the identified microRNA signatures

Background

Though glioblastoma multiforme (GBM) is the most frequently occurring brain malignancy in adults, clinical treatment still faces challenges due to poor prognoses and tumor relapses. Recently, microRNAs (miRNAs) have been extensively used with the aim of developing accurate molecular therapies, because of their emerging role in the regulation of cancer-related genes. This work aims to identify the miRNA signatures related to survival of GBM patients for developing molecular therapies.

Results

This work proposes a support vector regression (SVR)-based estimator, called SVR-GBM, to estimate the survival time in patients with GBM using their miRNA expression profiles. SVR-GBM identified 24 out of 470 miRNAs that were significantly associated with survival of GBM patients. SVR-GBM had a mean absolute error of 0.63 years and a correlation coefficient of 0.76 between the real and predicted survival time. The 10 top-ranked miRNAs according to prediction contribution are as follows: hsa-miR-222, hsa-miR-345, hsa-miR-587, hsa-miR-526a, hsa-miR-335, hsa-miR-122, hsa-miR-24, hsa-miR-433, hsa-miR-574 and hsa-miR-320. Biological analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the identified miRNAs revealed their influence in GBM cancer.

Conclusion

The proposed SVR-GBM using an optimal feature selection algorithm and an optimized SVR to identify the 24 miRNA signatures associated with survival of GBM patients. These miRNA signatures are helpful to uncover the individual role of miRNAs in GBM prognosis and develop miRNA-based therapies.

     

Identification of Metastamirs as Metastasis-associated MicroRNAs in Clear Cell Renal Cell Carcinomas

MicroRNAs (miRNAs) play a pivotal role in cancerogenesis and cancer progression, but their specific role in the metastasis of clear cell renal cell carcinomas (ccRCC) is still limited. Based on microRNA microarray analyses from normal and cancerous samples of ccRCC specimens and from bone metastases of ccRCC patients, we identified a set of 57 differentially expressed microRNAs between these three sample groups of ccRCC. A selected panel of 33 miRNAs was subsequently validated by RT-qPCR on total 57 samples. Then, 30 of the 33 examined miRNAs were confirmed to be deregulated. A stepwise down-regulation of miRNA expression from normal, over primary tumor to metastatic tissue samples, was found to be typical. A total of 23 miRNAs (miR-10b/-19a/-19b/-20a/-29a/-29b/-29c/-100/-101/-126/-127/-130/-141/-143/-145/-148a/-192/-194/-200c/-210/-215/-370/-514) were down-regulated in metastatic tissue samples compared with normal tissue. This down-regulated expression in metastatic tissue in comparison with primary tumor tissue was also present in 21 miRNAs. In cell culture experiments with 5-aza-2''-deoxycytidine and trichostatin A, epigenetic modifications were shown as one reason of this down-regulation. The altered miRNA profiles, comprising newly identified metastasis-associated miRNAs, termed metastamir and the predicted miRNA-target interactions together with the significant correlations of miRNAs that were either lost or newly appeared in the studied sample groups, afford a solid basis for further functional analyses of individual miRNAs in RCC metastatic progression.