Tivate translation under certain environmental conditions [5]. MiRNAs are usually transcribed from intergenic regions or the antisense strands of genes [9,10]. However, significant numbers of miRNAs have been discovered in introns and even exons of protein encoding genes [10]. Precursor miRNAs undergo extensive enzyme-mediated processing which results in a single-stranded molecule that is approximately 22 nucleotides in length. In the human genome, more than 1,500 mature miRNA transcripts have been characterized thus far [11]. Functionally, miRNAs can target mRNA molecules involved in many biological processes, including cell growth and development, cell fate, and apoptosis [12,13,14]. Given that miRNA transcripts affect nearly every aspect of cellular function, it is not surprising that they play a critical role in the etiology of a wide variety ofdisease manifestations [15]. Indeed, miRNAs have been implicated in many types of cancers, as well as specific cardiac and neurologic diseases [16,17,18,19,20,21,22,23]. Furthermore, studies have identified tissue-specific miRNA signatures that have the potential to act as diagnostic markers in human disease [19,24,25]. For this reason, it is critical that methods for detection and quantification of miRNAs in a clinical setting are sufficiently sensitive and specific in order to distinguish healthy and 
disease states. Research studies have characterized several different platforms for miRNA expression profiling by assaying synthetic RNA or RNA from commercially available cell lines and tissues [26,27,28,29]. Others have described the detection and quantification of miRNA transcripts in samples from both fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) tissues from human patients [30,31]. These studies have highlighted the 11967625 great diversity of methods that are available for miRNA expression analysis. Notably, these technologies exhibit different dynamic ranges and resolution capabilities, making it difficult to determine true miRNA expression levels.Multi-Platform Analysis of MicroRNA ExpressionGene expression microarrays are relatively inexpensive and are useful for profiling the miRNA transcriptome in a single experiment. However, studies have shown significant variability between different microarray platforms for miRNA profiling [26,28]. The evolution of digital counting techniques provides a new way to profile miRNA expression. NanoString technology employs unique fluorescent agging of individual miRNA species followed by two-dimensional display and optical 842-07-9 web scanning and counting of miRNA molecules [32]. More recently, advances in Next Generation Sequencing (NGS) have enabled a comprehensive evaluation of the miRNA transcriptome that allows for the characterization of novel transcripts [33]. Although the cost of NGS technology is decreasing, it remains prohibitive for many laboratories, and data analysis pipelines are still maturing. Therefore, researchers continue to use microarrays and other hybridization-based technologies to MedChemExpress Lixisenatide measure miRNA expression, prompting questions about how data from these platforms can be compared. In this study, we compared Affymetrix, Agilent, and Illumina microarray platforms with each other and with NanoString miRNA counting and NGS miRNA-Seq technologies by analyzing miRNA expression in total RNA samples from FF and FFPE lung tissues 
as well as a lung cancer cell line. A subset of these data was also compared to real-time PCR data generated from.Tivate translation under certain environmental conditions [5]. MiRNAs are usually transcribed from intergenic regions or the antisense strands of genes [9,10]. However, significant numbers of miRNAs have been discovered in introns and even exons of protein encoding genes [10]. Precursor miRNAs undergo extensive enzyme-mediated processing which results in a single-stranded molecule that is approximately 22 nucleotides in length. In the human genome, more than 1,500 mature miRNA transcripts have been characterized thus far [11]. Functionally, miRNAs can target mRNA molecules involved in many biological processes, including cell growth and development, cell fate, and apoptosis [12,13,14]. Given that miRNA transcripts affect nearly every aspect of cellular function, it is not surprising that they play a critical role in the etiology of a wide variety ofdisease manifestations [15]. Indeed, miRNAs have been implicated in many types of cancers, as well as specific cardiac and neurologic diseases [16,17,18,19,20,21,22,23]. Furthermore, studies have identified tissue-specific miRNA signatures that have the potential to act as diagnostic markers in human disease [19,24,25]. For this reason, it is critical that methods for detection and quantification of miRNAs in a clinical setting are sufficiently sensitive and specific in order to distinguish healthy and disease states. Research studies have characterized several different platforms for miRNA expression profiling by assaying synthetic RNA or RNA from commercially available cell lines and tissues [26,27,28,29]. Others have described the detection and quantification of miRNA transcripts in samples from both fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) tissues from human patients [30,31]. These studies have highlighted the 11967625 great diversity of methods that are available for miRNA expression analysis. Notably, these technologies exhibit different dynamic ranges and resolution capabilities, making it difficult to determine true miRNA expression levels.Multi-Platform Analysis of MicroRNA ExpressionGene expression microarrays are relatively inexpensive and are useful for profiling the miRNA transcriptome in a single experiment. However, studies have shown significant variability between different microarray platforms for miRNA profiling [26,28]. The evolution of digital counting techniques provides a new way to profile miRNA expression. NanoString technology employs unique fluorescent agging of individual miRNA species followed by two-dimensional display and optical scanning and counting of miRNA molecules [32]. More recently, advances in Next Generation Sequencing (NGS) have enabled a comprehensive evaluation of the miRNA transcriptome that allows for the characterization of novel transcripts [33]. Although the cost of NGS technology is decreasing, it remains prohibitive for many laboratories, and data analysis pipelines are still maturing. Therefore, researchers continue to use microarrays and other hybridization-based technologies to measure miRNA expression, prompting questions about how data from these platforms can be compared. In this study, we compared Affymetrix, Agilent, and Illumina microarray platforms with each other and with NanoString miRNA counting and NGS miRNA-Seq technologies by analyzing miRNA expression in total RNA samples from FF and FFPE lung tissues as well as a lung cancer cell line. A subset of these data was also compared to real-time PCR data generated from.
