Intra-platform repeatability and inter-platform comparability of microRNA microarray technology

Systems biology of interstitial lung diseases: integration of mRNA and microRNA expression changes

Background

The molecular pathways involved in the interstitial lung diseases (ILDs) are poorly understood. Systems biology approaches, with global expression data sets, were used to identify perturbed gene networks, to gain some understanding of the underlying mechanisms, and to develop specific hypotheses relevant to these chronic lung diseases.

Methods

Lung tissue samples from patients with different types of ILD were obtained from the Lung Tissue Research Consortium and total cell RNA was isolated. Global mRNA and microRNA were profiled by hybridization and amplification-based methods. Differentially expressed genes were compiled and used to identify critical signaling pathways and potential biomarkers. Modules of genes were identified that formed a regulatory network, and studies were performed on cultured cells in vitro for comparison with the in vivo results.

Results

By profiling mRNA and microRNA (miRNA) expression levels, we found subsets of differentially expressed genes that distinguished patients with ILDs from controls and that correlated with different disease stages and subtypes of ILDs. Network analysis, based on pathway databases, revealed several disease-associated gene modules, involving genes from the TGF-β, Wnt, focal adhesion, and smooth muscle actin pathways that are implicated in advancing fibrosis, a critical pathological process in ILDs. A more comprehensive approach was also adapted to construct a putative global gene regulatory network based on the perturbation of key regulatory elements, transcription factors and microRNAs. Our data underscores the importance of TGF-β signaling and the persistence of smooth muscle actin-containing fibroblasts in these diseases. We present evidence that, downstream of TGF-β signaling, microRNAs of the miR-23a cluster and the transcription factor Zeb1 could have roles in mediating an epithelial to mesenchymal transition (EMT) and the resultant persistence of mesenchymal cells in these diseases.

Conclusions

We present a comprehensive overview of the molecular networks perturbed in ILDs, discuss several potential key molecular regulatory circuits, and identify microRNA species that may play central roles in facilitating the progression of ILDs. These findings advance our understanding of these diseases at the molecular level, provide new molecular signatures in defining the specific characteristics of the diseases, suggest new hypotheses, and reveal new potential targets for therapeutic intervention.

Translating tumor biology into personalized treatment planning: analytical performance characteristics of the Oncotype DX Colon Cancer Assay

BACKGROUND

The Oncotype DX Colon Cancer Assay is a new diagnostic test for determining the likelihood of recurrence in stage II colon cancer patients after surgical resection using fixed paraffin embedded (FPE) primary colon tumor tissue. Like the Oncotype DX Breast Cancer Assay, this is a high complexity, multi-analyte, reverse transcription (RT) polymerase chain reaction (PCR) assay that measures the expression levels of specific cancer-related genes. By capturing the biology underlying each patient's tumor, the Oncotype DX Colon Cancer Assay provides a Recurrence Score (RS) that reflects an individualized risk of disease recurrence. Here we describe its analytical performance using pre-determined performance criteria, which is a critical component of molecular diagnostic test validation.

RESULTS

All analytical measurements met pre-specified performance criteria. PCR amplification efficiency for all 12 assays was high, ranging from 96% to 107%, while linearity was demonstrated over an 11 log2 concentration range for all assays. Based on estimated components of variance for FPE RNA pools, analytical reproducibility and precision demonstrated low SDs for individual genes (0.16 to 0.32 CTs), gene groups (≤ 0.05 normalized/aggregate CTs) and RS (≤ 1.38 RS units).

CONCLUSIONS

Analytical performance characteristics shown here for both individual genes and gene groups in the Oncotype DX Colon Cancer Assay demonstrate consistent translation of specific biology of individual tumors into clinically useful diagnostic information. The results of these studies illustrate how the analytical capability of the Oncotype DX Colon Cancer Assay has enabled clinical validation of a test to determine individualized recurrence risk after colon cancer surgery.

Complexity of the microRNA repertoire revealed by next-generation sequencing

MicroRNAs (miRNAs) have been implicated to play key roles in normal physiological functions, and altered expression of specific miRNAs has been associated with a number of diseases. It is of great interest to understand their roles and a prerequisite for such study is the ability to comprehensively and accurately assess the levels of the entire repertoire of miRNAs in a given sample. It has been shown that some miRNAs frequently have sequence variations termed isomirs. To better understand the extent of miRNA sequence heterogeneity and its potential implications for miRNA function and measurement, we conducted a comprehensive survey of miRNA sequence variations from human and mouse samples using next generation sequencing platforms. Our results suggest that the process of generating this isomir spectrum might not be random and that heterogeneity at the ends of miRNA affects the consistency and accuracy of miRNA level measurement. In addition, we have constructed a database from our sequencing data that catalogs the entire repertoire of miRNA sequences (http://galas.systemsbiology.net/cgi-bin/isomir/find.pl). This enables users to determine the most abundant sequence and the degree of heterogeneity for each individual miRNA species. This information will be useful both to better understand the functions of isomirs and to improve probe or primer design for miRNA detection and measurement.

Systematical detection of significant genes in microarray data by incorporating gene interaction relationship in biological systems

Many methods, including parametric, nonparametric, and Bayesian methods, have been used for detecting differentially expressed genes based on the assumption that biological systems are linear, which ignores the nonlinear characteristics of most biological systems. More importantly, those methods do not simultaneously consider means, variances, and high moments, resulting in relatively high false positive rate. To overcome the limitations, the SWang test is proposed to determine differentially expressed genes according to the equality of distributions between case and control. Our method not only latently incorporates functional relationships among genes to consider nonlinear biological system but also considers the mean, variance, skewness, and kurtosis of expression profiles simultaneously. To illustrate biological significance of high moments, we construct a nonlinear gene interaction model, demonstrating that skewness and kurtosis could contain useful information of function association among genes in microarrays. Simulations and real microarray results show that false positive rate of SWang is lower than currently popular methods (T-test, F-test, SAM, and Fold-change) with much higher statistical power. Additionally, SWang can uniquely detect significant genes in real microarray data with imperceptible differential expression but higher variety in kurtosis and skewness. Those identified genes were confirmed with previous published literature or RT-PCR experiments performed in our lab.

The activity and expression of microRNAs in prostate cancers

Recent studies have shown that microRNA (miRNA) inhibitory activity can be quantified by examining their target mRNA expression levels. The accumulated evidence of differential miRNA activities between cancer subtypes necessitates the systematical comparison of miRNA expressions and activities. In this study, we integrated 8 mRNA microarray datasets to infer and compare the miRNA activities between prostate cancers (PCs) and normal tissues (NTs). Gene expression analyses show that miRNA activity is stronger in PCs. This conclusion is consolidated by target protein expression. We simultaneously collected 6 independent miRNA expression datasets, where great inconsistency is present in the expression difference between PCs and NTs. The overall correlation between miRNA activity and expression is very weak. However, meta-analysis demonstrated that the expressions of 114 individual miRNAs agree with their activities. Additionally, we detected two other factors associated with higher miRNA activity in PCs. One is deregulation of some key miRNA-repression related genes, such as the over-expression of Dicer, TRBP and Ago2, and the under-expression of IRP1 in PCs. The other is that miRNA-mRNA binding site efficacy has significant positive correlation with miRNA activity, whereas no correlation with miRNA expression. Furthermore, miRNA activity is more reproducible than miRNA expression across different datasets, which allows miRNA activity to be a good feature for the classification of cancer subtypes. We expect our analysis can improve the methods for inferring miRNA activity and further, provide some clues to the role of miRNA in tumorigenesis.

Let-7 microRNA family is selectively secreted into the extracellular environment via exosomes in a metastatic gastric cancer cell line

BACKGROUND

Exosomes play a major role in cell-to-cell communication, targeting cells to transfer exosomal molecules including proteins, mRNAs, and microRNAs (miRNAs) by an endocytosis-like pathway. miRNAs are small noncoding RNA molecules on average 22 nucleotides in length that regulate numerous biological processes including cancer pathogenesis and mediate gene down-regulation by targeting mRNAs to induce RNA degradation and/or interfering with translation. Recent reports imply that miRNAs can be stably detected in circulating plasma and serum since miRNAs are packaged by exosomes to be protected from RNA degradation. Thus, profiling exosomal miRNAs are in need to clarify intercellular signaling and discover a novel disease marker as well.

METHODOLOGY/PRINCIPAL FINDINGS

Exosomes were isolated from cultured cancer cell lines and their quality was validated by analyses of transmission electron microscopy and western blotting. One of the cell lines tested, a metastatic gastric cancer cell line, AZ-P7a, showed the highest RNA yield in the released exosomes and distinctive shape in morphology. In addition, RNAs were isolated from cells and culture media, and profiles of these three miRNA fractions were obtained using microarray analysis. By comparing signal intensities of microarray data and the following validation using RT-PCR analysis, we found that let-7 miRNA family was abundant in both the intracellular and extracellular fractions from AZ-P7a cells, while low metastatic AZ-521, the parental cell line of AZ-P7a, as well as other cancer cell lines showed no such propensity.

CONCLUSIONS/SIGNIFICANCE

The enrichment of let-7 miRNA family in the extracellular fractions, particularly, in the exosomes from AZ-P7a cells may reflect their oncogenic characteristics including tumorigenesis and metastasis. Since let-7 miRNAs generally play a tumor-suppressive role as targeting oncogenes such as RAS and HMGA2, our results suggest that AZ-P7a cells release let-7 miRNAs via exosomes into the extracellular environment to maintain their oncogenesis.

Concordance among digital gene expression, microarrays, and qPCR when measuring differential expression of microRNAs

Profiling microRNA (miRNA) expression is of widespread interest given the critical role of miRNAs in many cellular functions. Profiling can be achieved via hybridization-based (microarrays), sequencing-based, or amplification-based (quantitative reverse transcription-PCR, qPCR) technologies. Among these, microarrays face the significant challenge of accurately distinguishing between mature and immature miRNA forms, and different vendors have developed different methods to meet this challenge. Here we measure differential miRNA expression using the Affymetrix, Agilent, and Illumina microarray platforms, as well as qPCR (Applied Biosystems) and ultra high-throughput sequencing (Illumina). We show that the differential expression measurements are more divergent when the three types of microarrays are compared than when the Agilent microarray, qPCR, and sequencing technology measurements are compared, which exhibit a good overall concordance.

Cross-platform analysis of global microRNA expression technologies

Background

Although analysis of microRNAs (miRNAs) by DNA microarrays is gaining in popularity, these new technologies have not been adequately validated. We examined within and between platform reproducibility of four miRNA array technologies alongside TaqMan PCR arrays.

Results

Two distinct pools of reference materials were selected in order to maximize differences in miRNA content. Filtering for miRNA that yielded signal above background revealed 54 miRNA probes (matched by sequence) across all platforms. Using this probeset as well as all probes that were present on an individual platform, within-platform analyses revealed Spearman correlations of >0.9 for most platforms. Comparing between platforms, rank analysis of the log ratios of the two reference pools also revealed high correlation (range 0.663-0.949). Spearman rank correlation and concordance correlation coefficients for miRNA arrays against TaqMan qRT-PCR arrays were similar for all of the technologies. Platform performances were similar to those of previous cross-platform exercises on mRNA and miRNA microarray technologies.

Conclusions

These data indicate that miRNA microarray platforms generated highly reproducible data and can be recommended for the study of changes in miRNA expression.

miRNAs as biomarkers in colorectal cancer diagnosis and prognosis

Since the discovery of noncoding small miRNAs and their function in controlling mRNA translational rate, the small non-coding miRNA world has become a research wonderland for cancer and other human diseases. Due to the critical regulatory function, miRNA can act as an oncogene or a tumor-suppressor gene. This review will cover some of the recent discoveries of the potential of miRNAs as cancer biomarkers in colorectal cancer, future challenges and solutions.

Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression

RNA abundance and DNA copy number are routinely measured in high-throughput using microarray and next-generation sequencing (NGS) technologies, and the attributes of different platforms have been extensively analyzed. Recently, the application of both microarrays and NGS has expanded to include microRNAs (miRNAs), but the relative performance of these methods has not been rigorously characterized. We analyzed three biological samples across six miRNA microarray platforms and compared their hybridization performance. We examined the utility of these platforms, as well as NGS, for the detection of differentially expressed miRNAs. We then validated the results for 89 miRNAs by real-time RT-PCR and challenged the use of this assay as a "gold standard." Finally, we implemented a novel method to evaluate false-positive and false-negative rates for all methods in the absence of a reference method.

Standards affecting the consistency of gene expression arrays in clinical applications

The use of microarray technology to measure gene expression has created optimism for the feasibility of using molecular assessments of tumors routinely in the clinical management of cancer. Gene expression arrays have been pioneers in the development of standards; both for research use and now for clinical application. Some of the existing standards have been driven by the early perception that microarray technology was inconsistent and perhaps unreliable. More recent experimentation has shown that reproducible data can be achieved and clinical standards are beginning to emerge. For the transcriptional assessment of tumors, this means a system that correctly samples a tumor, isolates RNA and processes this for microarray analysis, evaluates the data, and communicates findings in a consistent and timely fashion. The most important standard is to show that a clinically important assessment can be made with microarray data. The standards emerging from work on various parts of the entire process could guide the development of a workable system. However, the final standard for each component of the process depends on the accuracy required when the assay becomes part of the clinical routine: a routine that now includes the molecular evaluation of tumors.

Development and validation of a resistance and virulence gene microarray targeting Escherichia coli and Salmonella enterica

A microarray was developed to simultaneously screen Escherichia coli and Salmonella enterica for multiple genetic traits. The final array included 203 60-mer oligonucleotide probes, including 117 for resistance genes, 16 for virulence genes, 25 for replicon markers, and 45 other markers. Validity of the array was tested by assessing inter-laboratory agreement among four collaborating groups using a blinded study design. Internal validation indicated that the assay was reliable (area under the receiver-operator characteristic curve=0.97). Inter-laboratory agreement, however, was poor when estimated using the intraclass correlation coefficient, which ranged from 0.27 (95% confidence interval 0.24, 0.29) to 0.29 (0.23, 0.34). These findings suggest that extensive testing and procedure standardization will be needed before bacterial genotyping arrays can be readily shared between laboratories.