Systematic analysis of protein and enzyme function typically requires scale-up of protein expression and purification prior to assay development; this can often be limiting. Miniaturization of assays provides an alternative approach, but simple, generic methods are in short supply. Here we show how custom microarrays can be adapted to this purpose. We discuss the different routes to array fabrication and describe in detail one facile approach in which the purification and immobilization procedures are combined into a single step, significantly simplifying the array fabrication process. We illustrate this approach by reference to the creation of arrays of human protein kinases and of human cytochrome P450s. We discuss methods for both ligand-binding and turnover-based assays, as well as data analysis on such arrays.

The cancer-testis antigens are a group of unrelated proteins aberrantly expressed in various cancers in adult somatic tissues. This aberrant expression can trigger spontaneous immune responses, a phenomenon exploited for the development of disease markers and therapeutic vaccines. However, expression levels often vary amongst patients presenting the same cancer type, and these antigens are therefore unlikely to be individually viable as diagnostic or prognostic markers. Nevertheless, patterns of antigen expression may provide correlates of specific cancer types and disease progression. Herein, we describe the development of a novel, readily customizable cancer-testis antigen microarray platform together with robust bioinformatics tools, with which to quantify anti-cancer testis antigen autoantibody profiles in patient sera. By exploiting the high affinity between autoantibodies and tumor antigens, we achieved linearity of response and an autoantibody quantitation limit in the pg/mL range-equating to a million-fold serum dilution. By using oriented attachment of folded, recombinant antigens and a polyethylene glycol microarray surface coating, we attained minimal non-specific antibody binding. Unlike other proteomics methods, which typically use lower affinity interactions between monoclonal antibodies and tumor antigens for detection, the high sensitivity and specificity realized using our autoantibody-based approach may facilitate the development of better cancer biomarkers, as well as potentially enabling pre-symptomatic diagnosis. We illustrated the usage of our platform by monitoring the response of a melanoma patient cohort to an experimental therapeutic NY-ESO-1-based cancer vaccine; inter alia, we found evidence of determinant spreading in individual patients, as well as differential CT antigen expression and epitope usage.

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