Antibody microarray

[1][2][3][4] The concept and methodology of antibody microarrays were first introduced by Tse Wen Chang in 1983 in a scientific publication[5] and a series of patents,[6][7][8] when he was working at Centocor in Malvern, Pennsylvania.

Their first product in development was an assay, termed “immunosorbent cytometry”,[9] which could be employed to monitor the immune status, i.e., the concentrations and ratios of CD3+, CD4+, and CD8+ T cells, in the blood of HIV-infected individuals.

Other solid supports, such as glass slides and nitrocellulose membranes, were subsequently utilized to develop arrays which could accommodate larger panels of antibodies.

[13] Nitrocellulose membrane-based arrays are flexible, easy to handle, and have increased protein binding capacity, but are less amenable to high throughput or automated processing.

Glass slide-based arrays, owing to their smooth and rigid structure, can also be easily fitted to high-throughput liquid handling systems.

[23][24][25] The first approach to simultaneously detect multiple cytokines from physiological samples using antibody array technology was by Ruo-Pan Huang and colleagues in 2001.

In the last ten years, the sensitivity of the method was improved by an optimization of the surface chemistry as well as dedicated protocols for their chemical labeling.

[35] Also in 2010, an antibody array comprising 507 cytokines, chemokines, adipokines, growth factors, angiogenic factors, proteases, soluble receptors, soluble adhesion molecules, and other proteins was used to screen the serum of ovarian cancer patients and healthy individuals and found a significant difference in protein expression between normal and cancer samples.

[36] More recently, antibody arrays have helped determine specific allergy-related serum proteins whose levels are associated with glioma and can reduce the risk years before diagnosis.

A cost-effective fabrication platform (using OSTE polymers) for such microwell arrays has been recently demonstrated and the bio-assay model system has been successfully characterised.