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Laryngeal squamous cell carcinoma (LSCC) is an aggressive malignancy which lacks early predictors of prognosis. Here, we hypothesized that expression and prognostic characterization of the critical mediators of epithelial to mesenchymal transition (EMT) may provide key information in this regard. Linear regression and multiple correspondence analyses were performed on immunohistochemical data obtained from 20 invasive tumors. Principal component and unsupervised hierarchical clustering were used to analyze the dataset patterns associating with LSCC metastatic profile. Survival and death risk assessments were performed using Kaplan–Meier and hazard ratio tests. Data mining analysis using CHAID decision tree and logistic regression analysis was applied to define the predictive value of the risk factors of tumor aggressiveness. Our analyses showed, that in invasive LSCC tumors, cells associating with a mesenchymal profile were likely to exhibit enhanced NOS2, TGF-β, and IL-17A expression levels, concomitantly to NF-κB nuclear translocation. IHC data deciphering determined that EMT induction was also linked to the enrichment of the tumors with CD68+ populations and IL-10 signal. Strikingly, dataset cluster analysis showed that these signatures could define distinct patterns of invasive tumors, where NOS2 associated with IL-10 expression, and TGF-β and IL-17A signals associated with MMP-9 activation. Decision tree analysis identified IL-17A as a possible predictor of LSCC aggressiveness. Altogether, our results show that distinct immunological patterns would support the acquisition of EMT features in invasive LSCC and suggest that IL-17A may be useful in the early identification of patients “at-risk” of therapeutic failure.

Expression Analysis of the Mediators of Epithelial to Mesenchymal Transition and Early Risk Assessment of Therapeutic Failure in Laryngeal Carcinoma