부산대학교 도서관

Background: An effective diagnostic and prognostic marker based on the gene expression profile of classic Hodgkin lymphoma (cHL) has not yet been developed. The aim of the present study was to investigate potential markers for the diagnosis and prediction of cHL prognosis. Methods: The gene expression profiles with all available clinical features were downloaded from the Gene Expression Omnibus (GEO) database. Then, multiple machine learning algorithms were applied to develop and validate a diagnostic signature by comparing cHL with normal control. In addition, we identified prognostic genes and built a prognostic model with them to predict the prognosis for 130 patients with cHL which were treated with first-line treatment (ABVD chemotherapy or an ABVD-like regimen). Results: A diagnostic prediction signature was constructed and showed high specificity and sensitivity (training cohort: AUC=0.981,95% CI 0.933-0.998, P Conclusion: The new markers found in this study may be helpful for the diagnosis and prediction of the prognosis of cHL. Keywords: novel markers, diagnosis, prognosis, classic Hodgkin lymphoma
Introduction Classic Hodgkin lymphoma (cHL) is a kind of B-cell neoplasm which characterized by the paucity of Hodgkin/Reed-Sternberg (HRS) cells in conjunction with a microenvironment which contains abundant infltrating reactive [...]