Identify Gene-gene Regulatory Modules for Patients with Renal Clear Cell Tumor Metastasis - Cong, Nguyen Manh; Liu, Hsueh-Chuan; Mekala, Venugopala Reddy; Zaenudin, Efendi; Wijaya, Ezra Bernardus; Ng, Ka-Lok (Lecture notes in engineering and computer science, 2023)
Network biology employs two methods: top-down or bottom-up approach to explore the topological characteristics of biological networks. Genes do not function independently of one another. Instead, gene expression is controlled by the cooperative efford of individual gene working together. The bottom-up approach involves examining the network's local properties, this means that the network can be broken down into smaller modules known as network subgraphs/motifs.. Tumor metastasis represents the leading cause of patient mortality and constitutes a matter of significant concern for patients with cancer. Based on our current understanding, the existing approaches for predicting gene regulatory modules related to tumor metastasis do not utilize information from biological pathway databases. In the present investigation, we used the sub-graphs approach to evaluate the impacts of gene-gene regulatory modules on renal clear cell carcinoma in the kidney (KIRC). Our results suggested that the combined impacts of cancer-causing genes, such as tumor suppressor genes, oncogene genes, and DNA repair genes, considerably raise the probability of developing tumor metastasis. In summary, we have developed a novel method for constructing gene-gene regulatory modules using a directed sub-graph approach. By utilizing this approach, it is possible to not only reduce false positives but also identify highly relevant regulation modules for tumor metastasis research.