Sphingomyelinase D (SMase D), the main toxic component of Loxosceles venom, has a well-documented role on dermonecrotic lesion triggered by envenomation with these species; however, the intracellular mechanisms involved in this event are still poorly known. Through differential transcriptomics of human keratinocytes treated with L. laeta or L. intermedia SMases D, we identified 323 DEGs, common to both treatments, as well as upregulation of molecules involved in the IL-1 and ErbB signaling. Since these pathways are related to inflammation and wound healing, respectively, we investigated the relative expression of some molecules related to these pathways by RT-qPCR and observed different expression profiles over time. Although, after 24 h of treatment, both SMases D induced similar modulation of these pathways in keratinocytes, L. intermedia SMase D induced earlier modulation compared to L. laeta SMase D treatment. Positive expression correlations of the molecules involved in the IL-1 signaling were also observed after SMases D treatment, confirming their inflammatory action. In addition, we detected higher relative expression of the inhibitor of the ErbB signaling pathway, ERRFI1, and positive correlations between this molecule and pro-inflammatory mediators after SMases D treatment. Thus, herein, we describe the cell pathways related to the exacerbation of inflammation and to the failure of the wound healing, highlighting the contribution of the IL-1 signaling pathway and the ERRFI1 for the development of cutaneous loxoscelism.

• MeSH
• erbB receptory metabolismus   MeSH
• fosfodiesterasy toxicita   MeSH
• interleukin-1 metabolismus   MeSH
• kousnutí pavoukem patologie   MeSH
• lidé MeSH
• pavoučí jedy * toxicita   MeSH
• pavouci chemie   metabolismus   MeSH
• sfingomyelinfosfodiesterasa * metabolismus   MeSH
• signální transdukce MeSH
• zánět MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Patients with squamous cell carcinoma of the head and neck (SCCHN) have a high-risk of recurrence. We aimed to develop machine learning methods to identify transcriptomic and proteomic features that provide accurate classification models for predicting risk of early recurrence in SCCHN patients. METHODS: Clinical, genomic, transcriptomic and proteomic features distinguishing recurrence risk were examined in SCCHN patients from The Cancer Genome Atlas (TCGA). Recurrence within one year after treatment was classified as high-risk and no recurrence as low-risk. RESULTS: No significant differences in individual clinicopathological characteristics, mutation profiles or mRNA expression patterns were seen between the groups using conventional statistical analysis. Using the machine learning algorithm, extreme gradient boosting (XGBoost), ten proteins (RAD50, 4E-BP1, MYH11, MAP2K1, BECN1, NF2, RAB25, ERRFI1, KDR, SERPINE1) and five mRNAs (PLAUR, DKK1, AXIN2, ANG and VEGFA) made the greatest contribution to classification. These features were used to build improved models in XGBoost, achieving the best discrimination performance when combining transcriptomic and proteomic data, providing an accuracy of 0.939 and an Area Under the ROC Curve (AUC) of 0.951. CONCLUSIONS: This study highlights machine learning to identify transcriptomic and proteomic factors that play important roles in predicting risk of recurrence in patients with SCCHN and to develop such models by iterative cycles to enhance their accuracy, thereby aiding the introduction of personalized treatment regimens.

• MeSH
• dlaždicobuněčné karcinomy hlavy a krku genetika   MeSH
• lidé MeSH
• messenger RNA genetika   MeSH
• nádory hlavy a krku * genetika   MeSH
• proteomika MeSH
• rab proteiny vázající GTP genetika   MeSH
• spinocelulární karcinom * genetika   MeSH
• transkriptom genetika   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH