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Measures of association for identifying microRNA-mRNA pairs of biological interest.

ABSTRACT: MicroRNAs are a class of small non-protein coding RNAs that play an important role in the regulation of gene expression. Most studies on the identification of microRNA-mRNA pairs utilize the correlation coefficient as a measure of association. The use of correlation coefficient is appropriate if the expression data are available for several conditions and, for a given condition, both microRNA and mRNA expression profiles are obtained from the same set of individuals. However, there are many instances where one of the requirements is not satisfied. Therefore, there is a need for new measures of association to identify the microRNA-mRNA pairs of interest and we present two such measures. The first measure requires expression data for multiple conditions but, for a given condition, the microRNA and mRNA expression may be obtained from different individuals. The new measure, unlike the correlation coefficient, is suitable for analyzing large data sets which are obtained by combining several independent studies on microRNAs and mRNAs. Our second measure is able to handle expression data that correspond to just two conditions but, for a given condition, the microRNA and mRNA expression must be obtained from the same set of individuals. This measure, unlike the correlation coefficient, is appropriate for analyzing data sets with a small number of conditions. We apply our new measures of association to multiple myeloma data sets, which cannot be analyzed using the correlation coefficient, and identify several microRNA-mRNA pairs involved in apoptosis and cell proliferation.

SUBMITTER: Jayaswal V

PROVIDER: S-EPMC3256172 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Measures of association for identifying microRNA-mRNA pairs of biological interest.

Jayaswal Vivek V Lutherborrow Mark M Yang Yee Hwa YH

PloS one 20120111 1

MicroRNAs are a class of small non-protein coding RNAs that play an important role in the regulation of gene expression. Most studies on the identification of microRNA-mRNA pairs utilize the correlation coefficient as a measure of association. The use of correlation coefficient is appropriate if the expression data are available for several conditions and, for a given condition, both microRNA and mRNA expression profiles are obtained from the same set of individuals. However, there are many inst ...[more]

PMID: 22253745

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Project description:BACKGROUND: MicroRNAs are a class of noncoding RNA molecules that co-regulate the expression of multiple genes via mRNA transcript degradation or translation inhibition. Since they often target entire pathways, they may be better drug targets than genes or proteins. MicroRNAs are known to be dysregulated in many tumours and associated with aggressive or poor prognosis phenotypes. Since they regulate mRNA in a tissue specific manner, their functional mRNA targets are poorly understood. In previous work, we developed a method to identify direct mRNA targets of microRNA using patient matched microRNA/mRNA expression data using an anti-correlation signature. This method, applied to clear cell Renal Cell Carcinoma (ccRCC), revealed many new regulatory pathways compromised in ccRCC. In the present paper, we apply this method to identify dysregulated microRNA/mRNA mechanisms in ovarian cancer using data from The Cancer Genome Atlas (TCGA). METHODS: TCGA Microarray data was normalized and samples whose class labels (tumour or normal) were ambiguous with respect to consensus ensemble K-Means clustering were removed. Significantly anti-correlated and correlated genes/microRNA differentially expressed between tumour and normal samples were identified. TargetScan was used to identify gene targets of microRNA. RESULTS: We identified novel microRNA/mRNA mechanisms in ovarian cancer. For example, the expression level of RAD51AP1 was found to be strongly anti-correlated with the expression of hsa-miR-140-3p, which was significantly down-regulated in the tumour samples. The anti-correlation signature was present separately in the tumour and normal samples, suggesting a direct causal dysregulation of RAD51AP1 by hsa-miR-140-3p in the ovary. Other pairs of potentially biological relevance include: hsa-miR-145/E2F3, hsa-miR-139-5p/TOP2A, and hsa-miR-133a/GCLC. We also identified sets of positively correlated microRNA/mRNA pairs that are most likely result from indirect regulatory mechanisms. CONCLUSIONS: Our findings identify novel microRNA/mRNA relationships that can be verified experimentally. We identify both generic microRNA/mRNA regulation mechanisms in the ovary as well as specific microRNA/mRNA controls which are turned on or off in ovarian tumours. Our results suggest that the disease process uses specific mechanisms which may be significant for their utility as early detection biomarkers or in the development of microRNA therapies in treating ovarian cancers. The positively correlated microRNA/mRNA pairs suggest the existence of novel regulatory mechanisms that proceed via intermediate states (indirect regulation) in ovarian tumorigenesis.

Project description:The E6 and E7 proteins are the major oncogenic drivers encoded by high-risk human papillomaviruses (HPVs). While many aspects of the transforming activities of these proteins have been extensively studied, there are fewer studies that have investigated how HPV E6/E7 expression affects the expression of cellular noncoding RNAs. The goal of our study was to investigate HPV16 E6/E7 modulation of cellular microRNA (miR) levels and to determine the potential consequences for cellular gene expression. We performed deep sequencing of small and large cellular RNAs in primary undifferentiated cultures of human foreskin keratinocytes (HFKs) with stable expression of HPV16 E6/E7 or a control vector. After integration of the two data sets, we identified 51 differentially expressed cellular miRs associated with the modulation of 1,456 potential target mRNAs in HPV16 E6/E7-expressing HFKs. We discovered that the degree of differential miR expression in HFKs expressing HPV16 E6/E7 was not necessarily predictive of the number of corresponding mRNA targets or the potential impact on gene expression. Additional analyses of the identified miR-mRNA pairs suggest modulation of specific biological activities and biochemical pathways. Overall, our study supports the model that perturbation of cellular miR expression by HPV16 E6/E7 importantly contributes to the rewiring of cellular regulatory circuits by the high-risk HPV E6 and E7 proteins that contribute to oncogenic transformation.ImportanceHigh-risk human papillomaviruses (HPVs) are the causative agents of almost all cervical cancers and many other cancers, including anal, vaginal, vulvar, penile, and oropharyngeal cancers. Despite the availability of efficacious HPV vaccines, it is critical to determine how HPVs cause cancer, as many people remain unvaccinated and the vaccine does not prevent cancer development in individuals who are already infected. Two HPV proteins, E6 and E7, are the major drivers of cancer development, and much remains to be learned about how the expression of these viral proteins reprograms infected cells, ultimately resulting in cancer development. Small, noncoding human RNAs, termed microRNAs (miRs), regulate gene expression and have been implicated in almost all human cancers, including HPV-associated cancers. Our study provides a comprehensive analysis of how E6 and E7 alter the expression of human miRs and how this potentially impacts cellular gene expression, which may contribute to cancer development.

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Measures of association for identifying microRNA-mRNA pairs of biological interest.

Publications

Measures of association for identifying microRNA-mRNA pairs of biological interest.

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