Autofluorescence characterization for the early diagnosis of neoplastic changes in DMBA/TPA‐induced mouse skin carcinogenesis

Abstract

Squamous cell carcinoma (SCC), the second most common skin cancer, usually remains confined to the epidermis for some time but eventually penetrates the underlying tissues, if left untreated. The non-invasive early detection of the SCC is important for appropriate therapeutic strategies. In this study, we aim to characterize the tissue transformation in DMBA/TPA induced mouse skin tumor model using autofluorescence excitation emission matrix (EEM) in conjunction with a multivariate statistical method for early detection of the neoplastic changes. The fluorescence EEM from experimental group (n = 40; DMBA/TPA application), control group (n = 6; acetone application), and the blank group (n = 6; no application of DMBA/TPA or acetone) were measured every week using a spectrofluorometer coupled with a fiber optic bundle. The EEM was recorded at excitation wavelengths from 280 to 460 nm at 10 nm intervals and the fluorescence emission was scanned from 300 to 750 nm. The fluorescence emission characteristics corresponding to different fluorophores were extracted from the EEM and the spectral data were used in a multiple/linear discriminant statistical algorithm. The changes in the fluorescence emission intensity were observed as early as the 1st week of tumor initiation by DMBA. Morphological changes as well as differences in the gross appearance of the skin surface were observed during the entire tumor initiation and promotion period of 15 weeks. The statistical analysis was performed for each excitation wavelength in the EEM and better classification accuracy was obtained for 280 and 410 nm excitations, corresponding to tryptophan and endogenous porphyrins, respectively. The statistical analysis of the combination wavelengths resulted in 11.6% increase in the overall classification accuracy when compared to the highest classification accuracy obtained with single wavelength analysis. The intensity ratio mapping using the combination of emission intensities of key fluorophores such as tryptophan, collagen, NADH, and endogenous porphyrins from the measured EEM in conjunction with a simple multivariate statistical analysis can be used as a potential tool for the discrimination of early neoplastic changes with improved classification accuracy. Tryptophan and endogenous porphyrins may be used as biomarkers for the discrimination of early neoplastic changes when single wavelength excitations are used.