**4. Conclusion**

of different normalization approaches. GeneChip array data are normalized by the use of a tool that uses Robust Multichip Analysis (RAM) plus detection above background (DABG) algorithms, as default analysis. RAM is a robust linear normalization model, to minimize the effect of probe-specific affinity differences, and consists of three steps: background adjustment, quantile normalization and summarization. DABG is a detection metric generated by

miRNA profiling experiments typically involve comparisons between two or more groups, and therefore the next stage of analysis is usually the calculation of differential miRNA expression between groups. The degree of fold difference that constitutes a meaningful difference depends on the experimental context, although it is always useful to assess the statistical significance and false discovery rate that is associated with the differential miRNA expression. This comparison yields a p-value, which is, then, combined into a probe set level p-value using the Fischer equation. Statistical analysis is performed using TAC and a fold change of

Circulating exosome miRNAs are surprisingly stable and show distinct expression profiles among different fluids. Given the instability of most RNA molecules in the extracellular environment, the presence and apparent stability of miRNAs in body fluids such as serum and other body fluids, that are known to contain ribonucleases, suggest that secreted miRNAs are packaged in some manner to protect them against RNase digestion. miRNAs could be shielded from degradation by packaging in lipid vesicles, like exosomes, in complexes with RNA-binding proteins or both [47]. This view supports the idea that extracellular miRNAs are prepared for export in one cell. They can be recognized, taken up and utilized by another cell, working as mediators of cell-cell communication [48–50]. The growing interest in developing circulating miRNAs as blood-based biomarkers requires very careful consideration of the effects of various pre-analytical procedures, such as handling and storage conditions of the sample before processing, which can affect the reliability and reproducibility of circulating miRNA quantification. The main technical difficulty to study miRNA expression profiles is the efficient extraction of miRNAs from biological samples, because of their small size and their attachment to lipids and proteins. The use of commercial extraction kits has become available to optimize the extraction of small RNAs and normalize sample-to-sample variations in isolation procedures. Therefore, it is important to establish standardized protocols for blood collection, sample storage conditions, inclusion of exogenous and endogenous miRNA controls for each clinical sample and standardized calculations for normalization of the results to ensure the reproducible and accurate quantification of circulating miRNA levels so that miRNA analysis

miRNA microarrays are less expensive but inclined to have a lower sensitivity and dynamic range and are therefore best used as discovery tools rather than as quantitative assay platforms. Current publication guidelines require that all microarray results are confirmed by

comparing perfect match probes to a distribution of background probes.

two is commonly adopted to describe the signal changes between groups.

**3.5. Circulating miRNA profiling challenges**

40 Biomarker - Indicator of Abnormal Physiological Process

can be implemented in the clinical laboratory setting.

**3.6. Validation of microarray results by qRT-PCR**

Circulating miRNAs are attractive as clinical biomarkers for diagnostic purposes, as well as for monitoring disease progression and response to treatment. However, the nature of circulating miRNAs places several challenges. The success of the circulating miRNA profiling requires rigorous control of pre-analytic and analytic variables, specifically when investigating potential circulating miRNA markers. Here, we provided a consistent and reproducible method for circulating miRNA detection, profiling and analysis. We discussed the main issues associated with miRNA measurement that is crucial for miRNA profiling, especially for exosomal circulating miRNA. In addition, it needs to take into account that it is difficult to measure specific miRNA levels because they are short and conserved sequences, paralogs or distinguish between precursor and mature forms. In our work experience, the use of standard protocols for sample preparation, and of exogenous synthetic miRNA as the standard control, helps to solve a part of these problems. Microarray data processing such as normalization procedures among different samples is challenging especially for extracellular miRNA. In our work experience, it can be concluded that the use of robust algorithms and software may avoid errors and false positive discovery. However, the validation of array results by the use of an alternative methodology, especially when using different protocols and platforms for profiling purposes, is mandatory.

Objective assessment of these technical metrics is an important step toward understanding the appropriate use of microarray technology application in general and more specifically for circulating miRNA to be used as clinical markers as well as in regulatory settings.

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Circulating MicroRNA Profiling in Cancer Biomarker Discovery

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