Cutaneous T-cell lymphoma (CTCL), especially its mycosis fungoides (MF) subtype, is difficult to diagnose due to its similarity to inflammatory skin conditions and the lack of specific biomarkers. This often leads to delayed diagnosis and advanced disease stages, reducing life expectancy. To tackle this challenge, we examined proteomic changes in formalin-fixed paraffin-embedded (FFPE) samples of CTCL lesions, focusing on the epidermal layer.
Using laser-capture microdissection and data-independent acquisition mass spectrometry (DIA-MS), we analysed proteomic profiles of the epidermal layer in various MF stages (patches, plaques, and tumours; n=18) compared to normal epidermis (n=8). Differential abundance, classification and bioinformatics analyses were performed on the data to explore molecular changes between the lesions.
We identified 2673 proteins, with distinct proteomic profiles for different MF stages. Proteins differentially abundant between MF and normal dermis were linked to tumour suppression, protein homeostasis, and cell organization. Further analysis using principal component analysis (PCA) and support vector machine (SVM) algorithms categorised patient samples by disease stage. Functional network analysis using Ingenuity Pathway Analysis (IPA) showed dysregulation in cell survival and apoptosis processes in MF, while canonical pathway analysis indicated disruptions in cell signalling and cytoskeleton organisation pathways.
Overall, this study highlights potential proteomic diagnostic markers and therapeutic targets for MF.