Identifying the optimal gene and gene set in hepatocellular carcinoma based on differential expression and differential co-expression algorithm
| Autor: | Wei Xiang, Chang Yu, Wen-Hao Hu, Haiyan Li, Wei-Zhong Zhou, Junwei Ni, Li-Yang Dong |
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| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Cancer Research Carcinoma Hepatocellular Biology 03 medical and health sciences 0302 clinical medicine Text mining Humans Gene Regulation of gene expression Oncogene business.industry Gene Expression Profiling Liver Neoplasms General Medicine Cell cycle Molecular medicine Gene expression profiling Gene Expression Regulation Neoplastic 030104 developmental biology Oncology 030220 oncology & carcinogenesis Nucleoside metabolic process business Algorithm Microtubule-Associated Proteins Algorithms |
| Zdroj: | Oncology reports. 37(2) |
| ISSN: | 1791-2431 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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