title: Identifying the optimal gene and gene set in hepatocellular carcinoma based on differential expression and differential co-expression algorithm.
abstract: The objective of this study was to identify the optimal gene and gene set for hepatocellular carcinoma (HCC) utilizing differential expression and differential co-expression (DEDC) algorithm. The DEDC algorithm consisted of four parts: calculating differential expression (DE) by absolute t-value in t-statistics; computing differential co-expression (DC) based on Z-test; determining optimal thresholds on the basis of Chi-squared (χ2) maximization and the corresponding gene was the optimal gene; and evaluating functional relevance of genes categorized into different partitions to determine the optimal gene set with highest mean minimum functional information (FI) gain (Δ*G). The optimal thresholds divided genes into four partitions, high DE and high DC (HDE-HDC), high DE and low DC (HDE-LDC), low DE and high DC (LDE‑HDC), and low DE and low DC (LDE-LDC). In addition, the optimal gene was validated by conducting reverse transcription-polymerase chain reaction (RT-PCR) assay. The optimal threshold for DC and DE were 1.032 and 1.911, respectively. Using the optimal gene, the genes were divided into four partitions including: HDE-HDC (2,053 genes), HED-LDC (2,822 genes), LDE-HDC (2,622 genes), and LDE-LDC (6,169 genes). The optimal gene was microtubule‑associated protein RP/EB family member 1 (MAPRE1), and RT-PCR assay validated the significant difference between the HCC and normal state. The optimal gene set was nucleoside metabolic process (GO\GO:0009116) with Δ*G = 18.681 and 24 HDE-HDC partitions in total. In conclusion, we successfully investigated the optimal gene, MAPRE1, and gene set, nucleoside metabolic process, which may be potential biomarkers for targeted therapy and provide significant insight for revealing the pathological mechanism underlying HCC.
authors.affiliation: Department of Invasive Technology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai, Wenzhou, Zhejiang 325000, P.R. China.
authors.forename: Li-Yang
authors.initials: LY
authors.lastname: Dong
authors.affiliation: Department of Invasive Technology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai, Wenzhou, Zhejiang 325000, P.R. China.
authors.forename: Wei-Zhong
authors.initials: WZ
authors.lastname: Zhou
authors.affiliation: Department of Invasive Technology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai, Wenzhou, Zhejiang 325000, P.R. China.
authors.forename: Jun-Wei
authors.initials: JW
authors.lastname: Ni
authors.affiliation: Department of Invasive Technology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai, Wenzhou, Zhejiang 325000, P.R. China.
authors.forename: Wei
authors.initials: W
authors.lastname: Xiang
authors.affiliation: Department of Invasive Technology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai, Wenzhou, Zhejiang 325000, P.R. China.
authors.forename: Wen-Hao
authors.initials: WH
authors.lastname: Hu
authors.affiliation: Department of Invasive Technology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai, Wenzhou, Zhejiang 325000, P.R. China.
authors.forename: Chang
authors.initials: C
authors.lastname: Yu
authors.affiliation: Department of Rehabilitation, The First Affiliated Hospital of Wenzhou Medical University, Ouhai, Wenzhou, Zhejiang 325000, P.R. China.
authors.forename: Hai-Yan
authors.initials: HY
authors.lastname: Li
mesh_terms: D000465:Algorithms; D006528:Carcinoma, Hepatocellular / Q000235:genetics*; D020869:Gene Expression Profiling / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008113:Liver Neoplasms / Q000235:genetics*; D008869:Microtubule-Associated Proteins / Q000235:genetics
chemical_list: C500985:MAPRE1 protein, human; D008869:Microtubule-Associated Proteins