RESUMO
Recent developments of molecular biology have revealed diverse mechanisms of skin diseases, and precision medicine considering these mechanisms requires the frequent objective evaluation of skin phenotypes. Transepidermal water loss (TEWL) is commonly used for evaluating skin barrier function; however, direct measurement of TEWL is time-consuming and is not convenient for daily clinical practice. Here, we propose a new skin barrier assessment method using skin images with topological data analysis (TDA). TDA enabled efficient identification of structural features from a skin image taken by a microscope. These features reflected the regularity of the skin texture. We found a significant correlation between the topological features and TEWL. Moreover, using the features as input, we trained machine-learning models to predict TEWL and obtained good accuracy (R2 = 0.524). Our results suggest that assessment of skin barrier function by topological image analysis is promising.
Assuntos
Análise de Dados , Processamento de Imagem Assistida por Computador , Pele/anatomia & histologia , Pele/diagnóstico por imagem , HumanosRESUMO
The human epidermal growth factor receptor 2 (HER2) is recognized as an oncogene as well as a therapeutic target in various cancers. Certain patients with advanced extramammary Paget's disease (EMPD) have also been reported to express HER2, which is therefore considered a therapeutic target for EMPD. However, an accurate methodology to determine HER2-positive EMPD has not been established. To assess the optimal methods for detection of HER2-positive EMPD, 73 EMPD samples were analyzed by immunohistochemical (IHC) staining, fluorescence in situ hybridization (FISH), and the HER2 testing algorithm for breast cancer of the American Society of Clinical Oncology/College of American Pathologists, which combined the results of IHC staining and FISH. The results showed discordance in the rate of positive IHC staining and FISH results. While 68.6% (24/35) of the metastatic samples showed equivocal or positive IHC staining, only 37.1% (13/35) were positive by FISH. To assess the accuracy of these methods, the degree of HER2 expression detected by each method was correlated with the staining profiles of activated downstream signaling pathways involving phosphorylated p44/42 MAPK (Thr202/Tyr204) (p-ERK1/2) and phosphorylated AKT (Ser473) (p-AKT). Among 16 lymph node metastasis samples, all HER2-positive samples as determined by the testing algorithm stained positively for both p-ERK1/2 and p-AKT. On the other hand, 10-14.3% of the samples determined by FISH or IHC showed negative staining for p-ERK1/2 and p-AKT. The results showed that combining the results of IHC and FISH according to the HER2 testing algorithm is a useful method for accurately evaluating HER2-positive EMPD.