Regulatory mechanisms and clinical perspectives of miRNA in tumor radiosensitivity
CARCINOGENESIS
Authors: Zhao, Luqing; Bode, Ann M.; Cao, Ya; Dong, Zigang
Abstract
MicroRNA (miRNA) influences carcinogenesis at multiple stages and it can effectively control tumor radiosensitivity by affecting DNA damage repair, cell cycle checkpoint, apoptosis, radio-related signal transduction pathways and tumor microenvironment. MiRNA also efficiently modulates tumor radiosensitivity at multiple levels by blocking the two essential non-homologous end-joining repair and homologous recombination repair pathways in the DNA damage response. It interferes with four radio-related pathways in ionizing radiation, including the PI3-K/Akt, NF-kappa B, MAPK and TGF beta signaling pathways. Moreover, the regulatory effect of miRNA in radiosensitivity can be enhanced when interacting with various key molecules, including H2AX, BRCA1, ATM, DNA-PK, RAD51, Chk1, Cdc25A, p53, PLK1, HIF-1 and VEGF, which are involved in these processes. Therefore, thoroughly understanding the mechanism of miRNA in tumor radiosensitivity could assist in finding novel targets to improve the radiotherapeutic effects and provide new clinical perspectives and insights for developing effective cancer treatments.
Bayesian Network Inference Modeling Identifies TRIB1 as a Novel Regulator of Cell-Cycle Progression and Survival in Cancer Cells
CANCER RESEARCH
Authors: Gendelman, Rina; Xing, Heming; Mirzoeva, Olga K.; Sarde, Preeti; Curtis, Christina; Feiler, Heidi S.; McDonagh, Paul; Gray, Joe W.; Khalil, Iya; Korn, W. Michael
Abstract
Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate nonintuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed a model comprised of an ensemble of networks using multidimensional data from cell line models of cell-cycle arrest caused by inhibition of MEK1/2. Through simulation of a reverse-engineered Bayesian network model, we generated predictions of G1-S transition. The model identified known components of the cell-cycle machinery, such as CCND1, CCNE2, and CDC25A, as well as revealed novel regulators ofG1-S transition, IER2, TRIB1, TRIM27. Experimental validation of model predictions confirmed 10 of 12 predicted genes to have a role in G1-S progression. Further analysis showed that TRIB1 regulated the cyclin D1 promoter via NFkB and AP-1 sites and sensitized cells to TRAIL-induced apoptosis. In clinical specimens of breast cancer, TRIB1 levels correlated with expression of NFkB and its target genes (IL8, CSF2), and TRIB1 copy number and expression were predictive of clinical outcome. Together, our results establish a critical role of TRIB1 in cell cycle and survival that is mediated via the modulation of NFkB signaling.