An integrated analysis of miRNA and mRNA expressions in non-small cell lung cancers

Using DNA microarrays, we generated both mRNA and miRNA expression data from 6 non-small cell lung cancer (NSCLC) tissues and their matching normal control from adjacent tissues to identify potential miRNA markers for diagnostics. We demonstrated that hsa-miR-96 is significantly and consistently up-regulated in all 6 NSCLCs. We validated this result in an independent set of 35 paired tumors and their adjacent normal tissues, as well as their sera that are collected before surgical resection or chemotherapy, and the results suggested that hsa-miR-96 may play an important role in NSCLC development and has great potential to be used as a noninvasive marker for diagnosing NSCLC. We predicted potential miRNA target mRNAs based on different methods (TargetScan and miRanda). Further classification of miRNA regulated genes based on their relationship with miRNAs revealed that hsa-miR-96 and certain other miRNAs tend to down-regulate their target mRNAs in NSCLC development, which have expression levels permissive to direct interaction between miRNAs and their target mRNAs. In addition, we identified a significant correlation of miRNA regulation with genes coincide with high density of CpG islands, which suggests that miRNA may represent a primary regulatory mechanism governing basic cellular functions and cell differentiations, and such mechanism may be complementary to DNA methylation in repressing or activating gene expression.     

星形细胞瘤生存预后相关miRNA-mRNA调控关系对筛选

利用GEO数据库中的芯片数据,筛选与星形细胞瘤生存预后相关的miRNA-mRNA调控关系对,为后续研究提供理论支持.下载芯片数据利用R语言进行差异表达分析,得到星形细胞瘤较正常组织表达显著改变的miRNA与mRNA;通过miRNA靶基因预测,将靶基因与差异表达mRNA取交集,明确mRNA与miRNA之间的关系;利用GE...     

Identifying functional miRNA-mRNA regulatory modules with correspondence latent dirichlet allocation

MOTIVATION: MicroRNAs (miRNAs) are small non-coding RNAs that cause mRNA degradation and translational inhibition. They are important regulators of development and cellular homeostasis through their control of diverse processes. Recently, great efforts have been made to elucidate their regulatory mechanism, but the functions of most miRNAs and their precise regulatory mechanisms remain elusive. With more and more matched expression profiles of miRNAs and mRNAs having been made available, it is of great interest to utilize both expression profiles to discover the functional regulatory networks of miRNAs and their target mRNAs for potential biological processes that they may participate in. RESULTS: We present a probabilistic graphical model to discover functional miRNA regulatory modules at potential biological levels by integrating heterogeneous datasets, including expression profiles of miRNAs and mRNAs, with or without the prior target binding information. We applied this model to a mouse mammary dataset. It effectively captured several biological process specific modules involving miRNAs and their target mRNAs. Furthermore, without using prior target binding information, the identified miRNAs and mRNAs in each module show a large proportion of overlap with predicted miRNA target relationships, suggesting that expression profiles are crucial for both target identification and discovery of regulatory modules.     

Genome-wide screen for aberrantly expressed miRNAs reveals miRNA profile signature in breast cancer

Dysregulation in the expression of miRNAs contributes to the occurrence and development of many human cancers. We herein attempted to obtain the potential association between miRNA expression profile and breast cancer by applying high-throughput sequencing technology. Small RNAs from seven paired tumor and adjacent normal tissue samples were sequenced. To determine the miRNA expression profiles in tissues and sera, another five equally pooled serum samples from 20 patients and 30 normal women were sequenced. Despite a similar number in abundantly expressed miRNAs across samples, we detected varying miRNA expression profiles. Some miRNAs showed inconsistent or opposite dysregulation trends across different tumor tissues, including some abundantly expressed miRNA gene clusters and gene families. Wilcoxon sign-rank test for paired samples analysis revealed that abnormal miRNAs showed a higher level of variation across the seven tumor samples. We also completely surveyed abnormal miRNAs expressed in tumor and serum tissues in the mixed datasets based on the relative expression levels. Most of these miRNAs were significantly down-regulated in tumor samples, but nine abnormal miRNAs (miR-18a, 19a, 20a, 30a, 103b, 126, 126*, 192, 1287) were consistently expressed in tumor tissues and serum samples. Based on experimentally validated target mRNAs, functional enrichment analysis indicated that these abnormal miRNAs and miRNA groups (miRNA gene clusters and gene families) have important roles in multiple biological processes. Dynamic miRNA expression profiles, various abnormal miRNA profiles and complexity of the miRNA regulatory network reveal that the miRNA expression profile is a potential biomarker for classifying or detecting human disease.     

Quantitative differential expression analysis reveals miR-7 as major islet microRNA

MicroRNAs (miRNAs) are non-coding gene products that regulate gene expression through specific binding to target mRNAs. Cell-specific patterns of miRNAs are associated with the acquisition and maintenance of a given phenotype, such as endocrine pancreas (islets). We hypothesized that a subset of miRNAs could be differentially expressed in the islets. Using miRNA microarray technology and quantitative RT-PCR we identified a subset of miRNAs that are the most differentially expressed islet miRNAs (ratio islet/acinar > 150-fold), miR-7 being the most abundant. A similarly high ratio for miR-7 was observed in human islets. The ratio islet/acinar for miR-375, a previously described islet miRNA, was <10 and is 2.5× more abundant in the islets than miR-7. Therefore, we conclude that miR-7 is the most abundant endocrine miRNA in islets while miR-375 is the most abundant intra-islet miRNA. Our results may offer new insights into regulatory pathways of islet gene expression.     

Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets

We predict regulatory targets of vertebrate microRNAs (miRNAs) by identifying mRNAs with conserved complementarity to the seed (nucleotides 2-7) of the miRNA. An overrepresentation of conserved adenosines flanking the seed complementary sites in mRNAs indicates that primary sequence determinants can supplement base pairing to specify miRNA target recognition. In a four-genome analysis of 3' UTRs, approximately 13,000 regulatory relationships were detected above the estimate of false-positive predictions, thereby implicating as miRNA targets more than 5300 human genes, which represented 30% of our gene set. Targeting was also detected in open reading frames. In sum, well over one third of human genes appear to be conserved miRNA targets.