Biomarker Discovery in Cancer and Autoimmunity using an Affinity Proteomics Platform - a Tool for Personalized Medicine

Identification of novel biomarkers for early diagnosis, prognosis, and treatment decision will be instrumental for improving disease outcome for patients suffering from complex diseases, such as cancer and autoimmune disorders. Within personalized medicine, the use of circulating biomarkers will allow clinicians to tailor medical treatment based on individual characteristics of each patient, using minimally invasive sampling. Clinical biomarker discovery studies are faced with a number of challenges, including access to large cohorts of well-characterized samples and high-throughput analysis platforms that can target numerous proteins simultaneously, while using minute volumes of sample. To meet these demands, affinity proteomics have recently been evolved as a key platform for biomarker discovery. The aim of this thesis was to further optimize selected key features of our affinity proteomics platform, recombinant antibody microarrays, and to apply the platform in clinical studies. In the optimization studies I have i) evaluated and further developed the on-chip stability of antibodies included on the arrays, and ii) expanded and optimized the analysis protocol to now also enable targeting of urinary proteins. In the two application studies, I have demonstrated the feasibility of using antibody microarrays for identification of protein biomarker signatures in both cancer and auto-immunity. First, by analyzing urine and serum samples from patients with systemic lupus erythematosus, I have identified candidate biomarker signatures for monitoring of disease activity and renal involvement. Second, I have identified plasma protein patterns that potentially could be used for stratification of heterogeneous patient groups into sub-groups of high or low risk of having prostate cancer