In the last decades, incidence of melanoma has steadily increased worldwide. Once melanoma has metastasized, this advanced stage of disease is extremely difficult to treat and does not respond to current therapies . Numerous recent studies have emphasized the role of immune cells in the tumor progression [2, 3]. Moreover, some particular treatments such as immunotherapies enable to act on these immune cells to block tumor progression. A precise identification of the different immune actors in tissue sections is a preliminary step in the choice of these immunotherapies. Histological analysis of biological tissues achieved by pathologists allows a visualization of the immune cell types in the microenvironment. Yet, this step of vital importance is time-consuming, expensive and operator-dependent.
The aim of the study is to characterize the immunologic microenvironment of tumor cells in metastatic lymph nodes by FTIR imaging and to develop a tool of decision for the use of immunotherapies. FTIR imaging is an emerging technique in the domain of histopathology that provides spatially resolved information on the chemical composition of the tissue based on the vibrational signature of tissue components (protein, DNA, RNA, lipids…). Because of its potential to probe chemical constituents without dye or specific reagent, FTIR imaging could become a powerful tool in diagnostics to complement the existing methods.
34 biopsies from 13 patients enrolled in a vaccination study against metastatic melanoma were collected. These biopsies of metastatic lymph nodes were surgically removed before or after the vaccination. For each biopsie, several immunostainings were done to target immune infiltration (B cells, cytotoxic T cells, auxiliary T cells and T regulatory). A collection of infrared spectra from each cell types present in the tissue was accumulated (melanoma cells, lymphocytes B, T auxiliary, T cytotoxic, erythrocytes, fibroblasts, endothelial cells and the extracellular matrix). On basis of this spectral database and with supervised analysis (Partial Least Square Discriminant Analysis), we were able to obtain a predictive model for histological characterization of cancerous tissues on the basis of the IR images only. Finally, we validated this predictive model for histological component recognition on other patient tissues.
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Citation Format: Noémie Wald, Daniel E. Speiser, Pu Yan, Erik Goormaghtigh. Characterization of melanoma metastases and the immune microenvironment by infrared imaging. [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy: A New Chapter; December 1-4, 2014; Orlando, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2015;3(10 Suppl):Abstract nr B89.
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