Molecular serum portraits - A step towards personalized medicine

Abstract: Antibody microarray technology has the potential for playing a large roll in identifying serological biomarker panels for personalized medicine. The aim of this thesis, based on four original papers, was to investigate if information in the serum proteome could be extracted and used for diagnostic, classificational, prognostic or treatment predictive purposes in a range of diseases. In two studies (paper I and paper IV), the diagnosis and prognosis of breast cancer was addressed, also being the main focus of this thesis. In paper I, we identified a biomarker panel capable of stratifying serum samples from metastatic breast cancer patients from those of healthy controls. In paper IV, another panel, pre-validated in the same study, was deciphered that could be used to identify patients destined for metastatic disease in a group of newly diagnosed breast cancer patients. Paper II and III targeted immunotherapy of glioblastoma multiforme and the diagnosis and sub- stratification of two autoimmune diseases (SLE and SSc), respectively. Also in these cases, multiple biomarker panels were identified, each capable of separating predefined cohorts of patients with relevance for applications within personalized medicine. In conclusion, this thesis introduces the concept of personalized medicine; details the antibody microarray technology in general and the platform used for the experiments in paper I to IV; and describes the subsequent microarray data analysis.