Background: Australia has one of the highest incidences of melanoma skin cancer in the world. If caught early, malignancy can be successfully prevented. Currently, there are no molecular markers that can differentiate between the common mole or nevi, and melanoma. Therefore, resulting in an increase in unnecessary biopsies in order to remove the offending lesion.
Aim & Objectives: To investigate potential differences in protein content between nevi and early invasive melanoma.
Method: The epidermis layer of the skin was extracted via laser capture microdissection from archived de-identified formalin fixed paraffin embedded (FFPE) human skin tissues. Samples consisted of normal non-lesional (n=5), benign junctional nevi (n=5), dysplastic nevi (n=5), melanoma in situ (n=4), and minimally invasive melanomas of less than 1 mm deep (n=5). All samples were collected from non-chronic sun exposed areas of the torso and proximal limbs. Following preparation and proteolytic digestion, the samples’ proteome was analysed in a TripleTOF mass spectrometer using Sequential Acquisition Window Theoretical Fragment Ion Spectra (SWATH MS) workflow. Differential abundance and bioinformatics analysis were then performed on the proteomic data using ingenuity pathway analysis (IPA) and Human Protein Atlas (HPA) database.
Results: We identified 3119 proteins across the 24 samples studied. Our differential abundance analysis subsequently identified a number of proteins that are significantly changed between the normal skin and the lesions as well as between the lesion groups. Bioinformatics analysis predicted a majority of the altered proteins are involved in cell cycle progression, cellular proliferation, apoptosis and differentiation as well as inflammation and oxidative stress.
Conclusion: This pilot study demonstrates the successful detection of proteins in FFPE samples of benign nevi, dysplastic nevi, melanoma in situ, and early melanoma using SWATH-MS methodology. Exploration of this technique further will allow the identification of novel biomarkers for the detection of melanoma in its early stages.