<![CDATA[General Background: Accurate differentiation between melanoma and basal cell carcinoma (BCC) is essential due to their distinct biological characteristics and clinical management. Specific Background: Raman spectroscopy enables label-free biochemical profiling of tissues by detecting molecular vibrations within the 600–1800 cm⁻¹ fingerprint region. Knowledge Gap: However, systematic discrimination between melanoma and BCC using fresh ex vivo Raman spectra remains limited. Aims: This exploratory study assessed the capability of Raman spectral fingerprints to distinguish melanoma from BCC using standardized preprocessing and statistical analysis. Results: Analysis of 40 spectra (20 melanoma, 20 BCC) acquired at 790 nm identified over 1000 statistically significant Raman shifts (FDR < 0.05), grouped into key biochemical bands related to aromatic amino acids, amide structures, and lipid vibrations. Major peaks at 748–755, 1000–1005, 1440–1455, and 1655–1665 cm⁻¹ showed large effect sizes. Principal component analysis demonstrated clear class separation, with PC1 explaining 61.5% of total variance. Novelty: The study defines distinct Raman spectral biomarkers differentiating melanoma and BCC through integrated statistical and multivariate approaches. Implications: These findings support Raman spectroscopy as a rapid molecular profiling tool for skin cancer subtyping and a basis for future clinical translation. Highlights:• Over 1000 Significant Raman Shifts Clustered Into Major Biochemical Bands Distinguishing Tumour Types.• Aromatic Amino Acids, Amide Structures, and Lipid Vibrations Exhibited Large Effect Sizes Between Groups.• Multivariate Modelling Showed Distinct Clustering With Dominant Variance Captured by the First Principal Component. Keywords: Raman Spectroscopy, Melanoma, Basal Cell Carcinoma, Skin Cancer Diagnostics, Spectral Biomarkers]]>
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