Melanoma is the most aggressive skin cancer. The specificity and sensitivity of clinical diagnosis varies from around 40% to 80%. Here, we investigated whether the chemical changes in the melanoma tissue detected by Raman spectroscopy and neural networks can be used for diagnostic purposes. Near-infrared Fourier transform Raman spectra were obtained from samples of melanoma (n=22) and other skin tumors that can be clinically confused with melanoma: pigmented nevi (n=41), basal cell carcinoma (n=48), seborrheic keratoses (n=23), and normal skin (n=89). A sensitivity analysis of spectral frequencies used by a neural network was performed to determine the importance of the individual components in the Raman spectra. Visual inspection of the Raman spectra suggested that melanoma could be differentiated from pigmented nevi, basal cell carcinoma, seborrheic keratoses, and normal skin due to the decrease in the intensity of the amide I protein band around 1660 cm-1. Moreover, melanoma and basal cell carcinoma showed an increase in the intensity of the lipid-specific band peaks around 1310 cm-1 and 1330 cm-1, respectively. Band alterations used in the visual inspection were also independently identified by a neural network for melanoma diagnosis. The sensitivity and specificity for diagnosis of melanoma achieved by neural network analysis of Raman spectra were 85% and 99%, respectively. We propose that neural network analysis of near-infrared Fourier transform Raman spectra could provide a novel method for rapid, automated skin cancer diagnosis on unstained skin samples.

Near-infrared Fourier transform Raman spectroscopy is an analytical, nondestructive technique that provides information about the molecular structure of the investigated sample. The molecular structure of proteins and lipids differ between neoplastic and normal tissues and therefore Raman spectroscopy has been considered promising for the diagnosis of cancer. We aimed to compare the molecular structure of normal skin, benign and malignant skin lesions by the near-infrared Fourier transform Raman spectroscopy. Biopsies were obtained from the following skin lesions: skin tag, dermatofibroma, seborrhoeic keratosis, actinic keratosis, keratoacanthoma, basal cell carcinoma, squamous cell carcinoma, nevus intradermalis, nevus compositus, dysplastic nevus and lentigo maligna. Control skin was harvested from the vicinity of these lesions. In the Raman spectra, the secondary structure of the proteins was reflected by the amide vibrations of peptide bonds. The principal lipid vibrations were twisting and wagging (CH2) and CH stretching vibrations. Histologically distinguishable lesions showed specific combinations of band changes indicating alterations in the protein conformation and in the molecular structure of the lipids. Histogenetically related lesions (actinic keratosis and sqamous cell carcinoma) produced similar but not identical patterns of spectral changes. Because the examined skin lesions produced reproducible and unique spectra, we suggest that Raman spectroscopy will be useful for diagnosis of skin lesions.

We examined seven patients with lichen planus pigmentosus (LPP) clinically and microscopically. Clinically, all patients had a striking predominance of lesions in an intertriginous location, with most of them in the axillae. Microscopically, two biopsies were of significance. Except for the regressive lichen planus, which is usual in LPP, the active inflammatory phase was also present. In these biopsies the very intensive hydropic degeneration of basal keratinocytes was combined with the absence of compensatory increased proliferation of keratinocytes, i.e. without acanthosis. The short duration of this process probably led to the quick transformation into a long noninflammatory regressive phase with incontinence of the pigment. These specific morphogenetic dynamics are possibly why most of the morphs of LPP present as brown, non-pruritic, small inflammatory macules. Because of the highly characteristic inverse location of the lesions in our patients we propose the designation LPP-inversus for this variant of the disease.

Psoriasis is a chronic inflammatory skin disease in which Th17 cells play a crucial role. Since indigenous gut microbiota influences the development and reactivity of immune cells, we analyzed the link among microbiota, T cells and the formation of psoriatic lesions in the imiquimod-induced murine model of psoriasis. To explore the role of microbiota, we induced skin inflammation in germ-free (GF), broad-spectrum antibiotic (ATB)-treated or conventional (CV) BALB/c and C57BL/6 mice. We found that both mice reared in GF conditions for several generations and CV mice treated with ATB were more resistant to imiquimod-induced skin inflammation than CV mice. The ATB treatment dramatically changed the diversity of gut bacteria, which remained stable after subsequent imiquimod application; ATB treatment resulted in a substantial increase in the order Lactobacillales and a significant decrease in Coriobacteriales and Clostridiales. Moreover, as compared to CV mice, imiquimod induced a lower degree of local and systemic Th17 activation in both GF and ATB-treated mice. These findings suggest that gut microbiota control imiquimod-induced skin inflammation by altering the T cell response.