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Changes of signal transductivity and robustness of gene regulatory network in the carcinogenesis of leukemic subtypes via microarray sample data.

ABSTRACT: Mutation accumulation and epigenetic alterations in genes are important for carcinogenesis. Because leukemogenesis-related signal pathways have been investigated and microarray sample data have been produced in acute myeloid leukemia (AML), myelodysplastic syndromes (MDS) and normal cells, systems analysis in coupling pathways becomes possible. Based on system modeling and identification, we could construct the coupling pathways and their associated gene regulatory networks using microarray sample data. By applying system theory to the estimated system model in coupling pathways, we can then obtain transductivity sensitivity, basal sensitivity and error sensitivity of each protein to identify the potential impact of genetic mutations, epigenetic alterations and the coupling of other pathways from the perspective of energy, respectively. By comparing the results in AML, MDS and normal cells, we investigated the potential critical genetic mutations and epigenetic alterations that activate or repress specific cellular functions to promote MDS or AML leukemogenesis. We suggested that epigenetic modification of ?-catenin and signal integration of CSLs, AP-2?, STATs, c-Jun and ?-catenin could contribute to cell proliferation at AML and MDS. Epigenetic regulation of ERK and genetic mutation of p53 could lead to the repressed apoptosis, cell cycle arrest and DNA repair in leukemic cells. Genetic mutation of JAK, epigenetic regulation of ERK, and signal integration of C/EBP? could result in the promotion of MDS cell differentiation. According to the results, we proposed three drugs, decitabine, genistein, and monorden for preventing AML leukemogenesis, while three drugs, decitabine, thalidomide, and geldanamycin, for preventing MDS leukemogenesis.

SUBMITTER: Li CW

PROVIDER: S-EPMC5955113 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Changes of signal transductivity and robustness of gene regulatory network in the carcinogenesis of leukemic subtypes via microarray sample data.

Li Cheng-Wei CW Lai Tzu-Ying TY Chen Bor-Sen BS

Oncotarget 20180504 34

Mutation accumulation and epigenetic alterations in genes are important for carcinogenesis. Because leukemogenesis-related signal pathways have been investigated and microarray sample data have been produced in acute myeloid leukemia (AML), myelodysplastic syndromes (MDS) and normal cells, systems analysis in coupling pathways becomes possible. Based on system modeling and identification, we could construct the coupling pathways and their associated gene regulatory networks using microarray samp ...[more]

PMID: 29805763

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Project description:Gastric Carcinoma is one of the most common cancers in the world. A large number of differentially expressed genes have been identified as being associated with gastric cancer progression, however, little is known about the underlying regulatory mechanisms. To address this problem, we developed a differential networking approach that is characterized by including a nascent methodology, differential coexpression analysis (DCEA), and two novel quantitative methods for differential regulation analysis. We first applied DCEA to a gene expression dataset of gastric normal mucosa, adenoma and carcinoma samples to identify gene interconnection changes during cancer progression, based on which we inferred normal, adenoma, and carcinoma-specific gene regulation networks by using linear regression model. It was observed that cancer genes and drug targets were enriched in each network. To investigate the dynamic changes of gene regulation during carcinogenesis, we then designed two quantitative methods to prioritize differentially regulated genes (DRGs) and gene pairs or links (DRLs) between adjacent stages. It was found that known cancer genes and drug targets are significantly higher ranked. The top 4% normal vs. adenoma DRGs (36 genes) and top 6% adenoma vs. carcinoma DRGs (56 genes) proved to be worthy of further investigation to explore their association with gastric cancer. Out of the 16 DRGs involved in two top-10 DRG lists of normal vs. adenoma and adenoma vs. carcinoma comparisons, 15 have been reported to be gastric cancer or cancer related. Based on our inferred differential networking information and known signaling pathways, we generated testable hypotheses on the roles of GATA6, ESRRG and their signaling pathways in gastric carcinogenesis. Compared with established approaches which build genome-scale GRNs, or sub-networks around differentially expressed genes, the present one proved to be better at enriching cancer genes and drug targets, and prioritizing disease-related genes on the dataset we considered. We propose this extendable differential networking framework as a promising way to gain insights into gene regulatory mechanisms underlying cancer progression and other phenotypic changes.

Dataset Information

Changes of signal transductivity and robustness of gene regulatory network in the carcinogenesis of leukemic subtypes via microarray sample data.

Publications

Changes of signal transductivity and robustness of gene regulatory network in the carcinogenesis of leukemic subtypes via microarray sample data.

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