AUTHOR=Liu Shuying , Ge Jiaying , Chu Yiting , Cai Shuangyu , Gong Aixiu , Wu Jun , Zhang Jinghan 

TITLE=Identification of hub cuproptosis related genes and immune cell infiltration characteristics in periodontitis

JOURNAL=Frontiers in Immunology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1164667

DOI=10.3389/fimmu.2023.1164667

ISSN=1664-3224

ABSTRACT=Periodontitis is an inflammatory disease and its molecular mechanisms is not clear. A recently discovered cell death pathway called cuproptosis, initiated by copper ion clusters may related to the disease. The datasets GSE10334 of human periodontitis and control were retrieved from the Gene Expression Omnibus database(GEO) for analysis. 15 periodontitis-related differentially expressed cuproptosis related genes (DE-CRGs) were found. A 11-CRG-based signature was discovered after the application of two machine learning techniques, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE). The major 11-CRG gene signature's discriminatory ability was assessed using receiver operating characteristic (ROC) curves, which also supported the value of the signature. The link between hub genes and distinct types of immune cells was studied with CIBERSORT deconvolution algorithm, as well as differential immune cell infiltration. The relationship between the 11 CRGs and immune cells in periodontitis was next examined. The relevant clusters of cuproptosis were found using consensus clustering. The link between various clusters was ascertained using the GSVA and CIBERSORT deconvolution algorithm. Finally, we assessed these potential values in predicting periodontitis risks. An external dataset(GSE16134) was used to confirm the diagnosis capacity of the identified biomarkers. In addition, clinical samples were examined using qRT-PCR and immunohistochemistry to verifiy the expression of genes related to cuprotosis in periodontitis and the signature may better predict the prognosis of periodontitis patients.