Development of gene expression panels to determine prostate cancer - Gerashchenko, G.V.; Rynditch, A.V.; Kashuba, V.I. (Reports of the National Academy of Sciences of Ukraine, 2019)
The aim of this investigation is to prove a modified algorithm for statistical approaches to develop gene expression panels for the detection of prostate tumors. According to Classification and Regression tree models and RE differences between adenocarcinoma (T) and adenoma (A) groups, we have chosen 31 transcripts for MDR analysis. Among them, there were 15 transcripts of (epithelial-mesenchymal transition (EMT) and prostate-cancer associated (PrCa-associated) genes and 16 transcripts of cancer-associated fibroblasts (CAF), tumor-associated macrophages (TAM), immune-associated genes (IAG)), which have shown some datasets with high statistical parameters. The highest diagnostic levels are manifested by expression panels developed from all 5 gene groups: PCA3, HOTAIR, ESR1, IL1R1 (Se = 0.97, Sp = 0.85, Ac = 0.93, OR = 204); CDH2, KRT18, PCA3, HOTAIR, ESR1, IL1R1 (Se = 1.0, Sp = 0.8, Ac = 0.93, OR > 500). We propose an improved algorithm for the gene expression data analysis to develop diagnostic panels with good and excellent diagnostic levels for the prostate tumor stratification in a group of patients from the Ukrainian population. Our data require a more detailed analysis and a larger cohort of patients with prostate tumor.