Gene expression dynamic analysis reveals co-activation of Sonic Hedgehog and epidermal growth factor followed by dynamic silencing
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Vahed Maroufy1,*, Pankil Shah2,*, Arvand Asghari3, Nan Deng1, Rosemarie N.U. Le3, Juan C. Ramirez4, Ashraf Yaseen1, W. Jim Zheng5, Michihisa Umetani3,6 and Hulin Wu1
1 Department of Biostatistics and Data Science, School of Public Heath, University of Texas Health Science Center at Houston, Houston, TX, USA
2 Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
3 Center for Nuclear Receptors and Cell Signaling, Department of Biology and Biochemistry, University of Houston, Houston, TX, USA
4 Facultad de Ingeniería de Sistemas, Universidad Antonio Nariño, Bogota, Colombia
5 School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA
6 HEALTH Research Institute, University of Houston, Houston, TX, USA
* These authors contributed equally to this work
Keywords: pathway cross-talk; gene expression dynamics; gene regulatory network; Sonic Hedgehog; epidermal growth factor
Received: November 25, 2019 Accepted: March 14, 2020 Published: April 14, 2020
Aberrant activation of the Sonic Hedgehog (SHH) gene is observed in various cancers. Previous studies have shown a “cross-talk” effect between the canonical Hedgehog signaling pathway and the Epidermal Growth Factor (EGF) pathway when SHH is active in the presence of EGF. However, the precise mechanism of the cross-talk effect on the entire gene population has not been investigated. Here, we re-analyzed publicly available data to study how SHH and EGF cooperate to affect the dynamic activity of the gene population. We used genome dynamic analysis to explore the expression profiles under different conditions in a human medulloblastoma cell line. Ordinary differential equations, equipped with solid statistical and computational tools, were exploited to extract the information hidden in the dynamic behavior of the gene population. Our results revealed that EGF stimulation plays a dominant role, overshadowing most of the SHH effects. We also identified cross-talk genes that exhibited expression profiles dissimilar to that seen under SHH or EGF stimulation alone. These unique cross-talk patterns were validated in a cell culture model. These cross-talk genes identified here may serve as valuable markers to study or test for EGF co-stimulatory effects in an SHH+ environment. Furthermore, these cross-talk genes may play roles in cancer progression, thus they may be further explored as cancer treatment targets.
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