**1. Introduction**

Despite the tremendous advances in the understanding of the molecular basis of diseases (such as cancer, Alzheimer, genetic diseases), there are some crucial gaps that difficult us to understand disease pathogenesis and develop effective strategies for early diagnosis and treatment [1].

The current interest in protein microarrays due, mostly in part, to the prospects that proteomics assays, based on them, allow: deciphering the altered protein expression in different

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levels (tissue, cells, subcellular structures, body fluids, protein complexes,…); the development of novel biomarkers for diagnosis or early detection of diseases; the identification of new targets for therapeutics; and accelerating drug development through more effective strategies to evaluate therapeutic effect and toxicity [1].

Mainly based on the proteome alterations in disease may occur in many different ways that are not predictable from genomics analysis, and it is clear that a better understanding from genomic analysis together with an substantial impact in biomedicine.

Recently, there is a large amount of protein microarray approaches available for applications related to disease because the employment of these technologies is very useful for better diagnostics and to shorten the path for developing effective therapy. In general, protein microarrays allow to increase sensitivity, reduce sample requirement, increase high-throughput and identify protein alterations (quantitative and qualitative), such as post-translational modifications.-

If we want to quantify thousands of proteins in a small number of samples, a typical proteomics discovery experiment employs a non-targeted approach (shot-gun proteomics). The hundreds of proteins that result from the comparative analysis, are differentially expressed between healthy and diseased samples. After discovery phase, the potential biomarkers proteins are reduced by performing studies on additional patients or at more time points, and/ or by using another technique. Then, these potential biomarkers are verified on a set of 10–50 clinical samples. In the final step, a small number of biomarkers is "validated" on 100–500 clinical samples. Bearing in mind this conventional biomarker workflow, high-throughput assays are required in order to overcome the gap between translational research and clinical needs (from bench to the bedside) [1] (**Figure 1**).

**Figure 1.** Stages in the development of a biomarker.

Biomarkers or biological markers are defined as measurable characteristics that indicate the state of a biological process, differentiating if it is normal or pathological. They are all those molecules that are found in body fluids in low abundance and that are associated with specific health or disease processes [2]. The methodology to establish that a biomarker is good for clinical application is divided into three steps: discovery, verification and validation as it has been said before [3, 4].

Proteomics, the scientific discipline that studies proteins, has identified several proteins that can act as biomarkers. There are several techniques that use biomarkers and that allow an early diagnosis of the disease. These include new generation sequencing, mass spectrometry and protein arrays [5, 6]. In this chapter we will focus on the study of arrays.-

Microarray technology is a term that refers to the miniaturization of thousands of assays in a single device, allowing the simultaneous and massive analysis of a large number of biomolecules in a single biological sample. They allow the study of a large number of parameters in a single test with a minimum requirement of sample and reagents, which is why they constitute a simple, fast and very sensitive sampling technique [7, 8].

The microarrays present several innovative strategies for their applications such as the identification of biomarkers and the interactions between proteins that may help in the future to routine clinical analysis.

There is a great variety of arrays which can be classified according to their content in protein microarrays, functional protein arrays and reverse phase arrays; according to their shape in planes and spheres; and also according to their detection method.

In this chapter we will explain all these types of arrays, some of their applications in biomarker discovery as well as validation/verification.-
