ABSTRACT
Background@#The purpose of this research was to assess the role of heparanase (HPSE)/syndecan1 (SDC1)erve growth factor (NGF) on cancer pain from melanoma. @*Methods@#The influence of HPSE on the biological function of melanoma cells and cancer pain in a mouse model was evaluated. Immunohistochemical staining was used to analyze HPSE and SDC1. HPSE, NGF, and SDC1 were detected using western blot. Inflammatory factors were detected using ELISA assay. @*Results@#HPSE promoted melanoma cell viability, proliferation, migration, invasion, and tumor growth, as well as cancer pain, while SST0001 treatment reversed the promoting effect of HPSE. HPSE up-regulated NGF, and NGF feedback promoted HPSE. High expression of NGF reversed the inhibitory effect of HPSE down-regulation on melanoma cell phenotype deterioration, including cell viability, proliferation, migration, and invasion. SST0001 down-regulated SDC1 expression. SDC1 reversed the inhibitory effect of SST0001 on cancer pain. @*Conclusions@#The results showed that HPSE promoted melanoma development and cancer pain by interacting with NGF/SDC1. It provides new insights to better understand the role of HPSE in melanoma and also provides a new direction for cancer pain treatment.
ABSTRACT
Objective:To establish a classification model for rapid identification of hypervirulent subtype ST17 clones of Group B Streptococcus (GBS) using matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS).Methods:In a retrospective study, 235 strains of GBS strains were selected from multiple centers in China during 2015-2018. For model generation,45 strains of ST17 and 50 strains of non-ST17 (20 ST19, 15 ST12 and 15 ST10 strains) were enrolled as the modeling group. The remaining 90 main ST strains (40 ST17, 16 ST10, 17 ST12 and 17 ST19) were served as validation group. 50 GBS strains classified as other minor ST subtypes were regarded as taxonomic groups. MS spectra were collected by Bruker mass spectrometry, and then loaded for model generation and verification, and screening of differential peptide peaks by genetic algorithm (GA) and model verification on ClinProTools 3.0 software.Results:The recognition rate for ST17-GA model were 99.4% with cross validation value of 96.9%. Among the ten differential peptide peaks for the classification model, the weights of both two main peptide peaks m/z 2 956 and m/z 5 912 were greater than 1, while the weights of the all other eight peptide peaks were less than 0.5. Model validation showed only one of the ST17 was misjudged as non-ST17 strain, resulting in diagnostic accuracy of 98.9%, sensitivity of 97.5% and specificity of 100%, positive predictive value of 100% and negative predictive value of 98.0%, respectively. For other sporadic STs, 42.0% (21/50) of them were misdiagnosed as ST17 subtype.Conclusion:A MALDI-TOF MS classification model for hypervirulent subtype of ST17 GBS strains has been successfully established with good diagnostic efficacy.