Theoretical and in silico Analyses Reveal MYC as a Dynamic Network Biomarker in Colon and Rectal Cancer - Tong, Yanqiu; Song, Yang; Xia, Chuanhui; Deng, Shixiong (Frontiers in Genetics, 2020)
In this paper, we make a theoretical and in-silico study for uncovering and evaluating biomarkers in CRC by dynamic network biomarker (DNB) theory. We propose a strategy to employ the theoretical concept of UICC TNM classification in CRC. To reveal the critical transition of CRC, the DNB algorithm was implemented to analyze the genome-wide dynamic network through temporal gene expression data. The relationship between gene sets and clinical features was evaluated by weighted gene co-expression network analysis (WGCNA). The result show that MYC was significantly associated with tumor amplification, tumor immune cells, and survival times. The candidate tumor suppressor genes were ZBTB16, MAL, LIFR, and SLIT2. Protein-protein interaction (PPI) analysis show that these candidate tumor suppressor genes were significant in immune cells. Data form the Human Protein Atlas showed that high expression of these candidate tumor suppressor genes were associated with favorable prognosis in TNM stage I-IV. In conclusion, this work provides significant and novel information regarding the TNM stage, cause and consequences of elevated MYC expression in CRC. MYC expression levels had significant negative correlations with tumor suppressor genes and immune cells.