Infrared imaging of primary melanomas reveals hints of regional and distant metastases

Abstract

Melanoma is the deadliest form of skin cancer. Metastatic melanomas are resistant to almost all existing adjuvant therapies such as chemotherapy and radiotherapy, so detection of metastases remains a challenge, and no biomarkers are currently available to detect primary tumors with the highest risk of metastasis. Results presented in this paper show that Fourier Transform Infrared (FTIR) imaging of histological sections followed by supervised partial least squares discriminant analysis (PLS-DA) can accurately (>90%) identify the main cell types commonly found in melanoma tumors. Here we define six cell types: melanoma cells, erythrocytes, connective tissue (includes blood vessel walls, dermis and collagen regions), keratinocytes, lymphocytes and necrotic cells. Interestingly, more than 98% of the melanoma cells are correctly identified. The spectra of the cells identified as melanomas were then further analyzed. First, we compared melanoma cells in primary tumors (from 26 patients) with melanoma cells from metastases (from 25 patients). Neither supervised nor unsupervised analyses revealed any significant difference. Similarly, we found no significant correlation between the infrared spectra of melanoma cells and the number of proliferative cells assessed by Ki67 immunostaining. Finally, we compared the infrared spectra of primary tumors from patients diagnosed at different stages of the disease. Infrared spectroscopy was capable of pointing out differences between primary tumors of patients at stage I or II and patients at stage III or IV, even by unsupervised analysis. We then developed a supervised PLS-DA model capable of predicting whether tumor cells belonged to one of the two aggregated disease stage groups. The model predicted a high rate of true positives (sensitivity of 88.9%) and a good rate of true negatives (specificity of 70.6%) in external validation. These results demonstrate that infrared spectroscopy can be used to help identify melanoma characteristics related to the cells’ invasive capability.