The overall objective of this proposal is to identify, in serum and urine samples from melanoma patients, specific marker proteins or patterns of protein expression, which are diagnostic of cancer. As with many malignancies, early detection is critical for successful treatment of melanoma. Recent innovations in mass spectrometry make it a powerful technology that has the potential to revolutionize the identification of diagnostic markers for cancer. We aim to use this technology to identify diagnostic proteomic patterns in samples from melanoma patients. To that end, the following specific aims are proposed: 1. Perform mass spectrometry experiments on serum samples from three melanoma patients and three normal controls. 2. Perform mass spectrometry experiments on urine samples from three melanoma patients and three normal controls. 3. For additional biomarker discovery, samples will be fractionated with additional procedures (glycosylation capture and affinity matrices such as Protein A and dye chromatography) prior to mass spectrometry. 4. Confirm biomarker expression with a larger panel of 15 melanoma samples by an alternative method (e.g. Western blots or ELISA for markers with available antibodies or enzymatic activity for characterized enzymes). Relative expression levels of newly identified proteins will also be compared with known melanoma markers such as lactate dehydrogenase. Preliminary proteomic experiments described herein demonstrate that proteins characteristic of different physiological conditions can be identified using isotope-coded affinity tags (ICAT) coupled with tandem mass spectrometry. The specific aims of this proposal will apply this technology to identification of early markers of malignant melanoma.
Thesaurus Terms: biomarker, blood chemistry, diagnosis design /evaluation, mass spectrometry, melanoma, neoplasm /cancer diagnosis, urinalysis early diagnosis, oncoprotein affinity labeling, enzyme linked immunosorbent assay, human tissue, patient oriented research, proteomics, western blotting
