APIP, an ERBB3-binding partner, stimulates erbB2-3 heterodimer formation to promote tumorigenesis

Hong, Seung Wook; Lee, Won Jae; Kim, Young Doo; Kim, Hyun‐Joo; Jeon, Young-Jun; Lim, Bitna; Cho, Dong‐Hyung; Heo, Won Do; Yang, Doo-Hyun; Kim, Chan Young; Yang, Han‐Kwang; Yang, Jin Kuk; Jung, Yong‐Keun

doi:10.18632/oncotarget.7802

Cited by 12 publications

(12 citation statements)

References 51 publications

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“…The increase in APIP expression in the cardiomyocytes under hypoxia and in human patients with heart failure led us to investigate the role of APIP in MI. To address this, we generated APIP transgenic ( APIP Tg/+ ) mice with ubiquitous expression of human APIP under the control of the β-actin-CMV promoter 17 . Compared to levels in age-matched wild-type (WT) littermates, the levels of APIP were approximately 3- to 5-fold higher in the hearts of APIP Tg/+ mice (Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

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Cardioprotective role of APIP in myocardial infarction through ADORA2B

et al. 2019

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In ischemic human hearts, the induction of adenosine receptor A2B (ADORA2B) is associated with cardioprotection against ischemic heart damage, but the mechanism underlying this association remains unclear. Apaf-1-interacting protein ( APIP) and ADORA2B transcript levels in human hearts are substantially higher in patients with heart failure than in controls. Interestingly, the APIP and ADORA2B mRNA levels are highly correlated with each other ( R = 0.912). APIP expression was significantly increased in primary neonatal cardiomyocytes under hypoxic conditions and this induction reduced myocardial cell death via the activation of the AKT-HIF1α pathway. Accordingly, infarct sizes of APIP transgenic mice after left anterior descending artery ligation were significantly reduced compared to those of wild-type mice. Strikingly, knockdown of APIP expression impaired the cytoprotective effects of ADORA2B during hypoxic damage. Immunoprecipitation and proximity ligation assays revealed that APIP interacts with ADORA2B, leading to the stabilization of both proteins by interfering with lysosomal degradation, and to the activation of the downstream PKA-CREB signaling pathways. ADORA2B levels in the hearts of APIP Tg/Tg , APIP Tg/+ , and Apip +/- mice were proportionally downregulated. In addition, ADORA2B D296G derived from the rs200741295 polymorphism failed to bind to APIP and did not exert cardioprotective activity during hypoxia. Moreover, Adora2b D296G knock-in mice were more vulnerable than control mice to myocardial infarction and intentional increases in APIP levels overcame the defective protection of the ADORA2B SNP against ischemic injury. Collectively, APIP is crucial for cardioprotection against myocardial infarction by virtue of binding to and stabilizing ADORA2B, thereby dampening ischemic heart injury.

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Section: Resultsmentioning

confidence: 99%

“…APIP transgenic ( APIP Tg/+ ) and Apip knockout ( Apip +/− ) mice were generated as previously described 17 . Adora2b D296G KI/KI mice were generated by Dr. HW Lee (Yonsei University, Korea) and the mice were interbred and maintained in a pathogen-free condition.…”

Section: Methodsmentioning

confidence: 99%

Cardioprotective role of APIP in myocardial infarction through ADORA2B

et al. 2019

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“…Another interesting SNP rs1326941 located in the APIP gene (11p13), although APIP was not reported to be associated with the susceptibility of T2D. However, the gene APIP involves in many physiological and pathophysiological activities through affecting ERK1/2 signaling pathway activation [33, 34]. For example, ERK1/2 signaling pathway has an important influence on the pathogenesis of T2D by controlling phosphorylation amount of cAMP-responsive element-binding protein, which plays an important role in glucose-mediated pancreatic beta-cell survival [34].…”

Section: Discussionmentioning

confidence: 99%

Identification of novel genetic variants for type 2 diabetes, childhood obesity, and their pleiotropic loci

et al. 2019

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Obesity has result in increased prevalence of type 2 diabetes (T2D) in children. The genetic mechanisms underlying their relationship, however, are not fully understood. Here, we aim to identify novel SNPs associated with T2D and childhood obesity (CO), especially their pleiotropic loci. We integrated the summary statistics for two independent GWASs of T2D (n = 149,821) and childhood body mass index (CBMI) (n = 35,668) using the pleiotropy-informed conditional false discovery rate (cFDR) method. By leveraging the information of different levels of association for CBMI, we observed a strong enrichment of genetic variants associated with T2D. We identified 139 T2D-associated SNPs with 125 novel ones (cFDR< 0.05). Conditioned on T2D, we identified 37 significant SNPs for CBMI (cFDR<0.05), including 25 novel ones. The conjunctional cFDR (ccFDR) analysis showed ten novel pleiotropic loci for T2D and CBMI (ccFDR < 0.05). Interestingly, the novel SNP rs1996023 is located at protein coding gene GNPDA2 (ccFDR = 1.28E-02), which has been reported to influence the risk of T2D and CO through central nervous system. Our findings may help to explain a greater proportion of the heritability for human traits and advance the understanding of the common pathophysiology between T2D and CO.

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“…[58] The ERBB family also has roles in "normal embryonic development, angiogenesis, metastasis, cell proliferation and apoptosis resistance." [29] Activated EGFR also prevents apoptosis (cell death) [58] and play a role in cellular differentiation [4]. Proper EGF signaling helps control proper haploid cell generation [11].…”

Section: Deriving Effective Non-spatial Kinetics From a Spatial Modelmentioning

confidence: 99%

“…[57] This is partial because of a correlation between EGF and endocrine resistant breast cancer. [57] Over expression of ERBB2 has been linked to gastric cancer [29]. Not only is the EGF family involved in tumor progression, but also survival under the harsh conditions of chemotherapy and radiotherapy [38].…”

Section: Deriving Effective Non-spatial Kinetics From a Spatial Modelmentioning

confidence: 99%

Reducing Spatial Stochastic Models of Membrane Receptors to Approximately Equivalent Chemical Reaction Networks through Coarse Graining

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Computational models are necessary for understanding how biological functionality emerges from a complex network of molecular interactions such as in cell signaling. Due to the complexity of biological systems, the normal scientific method of hypothesizing then testing predictions is becoming increasingly difficult. The large number of processes limits the level of modeling detail; signaling models typically adopt a non-spatial representation where each molecular process is characterized by a few parameters. However, modern microscopic imaging of receptors on cell membranes reveals an intricate structure of microdomains. Receptors, such as epidermal growth factor receptor (EGFR), vascular endothelial growth factor receptor (VEGFR), and others, tend to be grouped in the microdomains as clusters that range from a few to hundreds of biomolecules. While the origin of these clusters is not well understood, a likely explanation is the existence of microdomains with an affinity for the receptors. Using this hypothesis, we can ignore the underlying cause of the microdomains. The size and geometry of these domains can be inferred directly from microscopy; however, the relevant physical properties can only be verified through simulations. In this thesis, I propose a flexible approach to performing such simulations in a coarse grained model that is validated through solving the differential equations when possible and through equilibrium calculations when not. Due to the non-trivial nature of these cell membrane features, fully spatial models need to be used to address these issues. However, fully spatial models are computationally intense and little insight can be gained from them, because of this I propose a method to construct the well-mixed model from the spatial one. The primary issue is the difficulty of extracting the correct kinetic coefficients and that limits the predictive power of spatial models due to the inherent challenges of estimating dynamical parameters. I will use the Metropolis-Hastings Algorithm to extract these parameters from the fully spatial simulations. I use the spatial model as an intermediary step because the spatial simulations can be matched to experimental techniques that provide molecular level resolution, such as single particle tracking (SPT) data. I will then discuss issues that emerge from a baseline comparison between spatial and non-spatial simulations of a simple reversible dimerization process; the spatial simulation employed an algorithm similar to Smoldyn.

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APIP, an ERBB3-binding partner, stimulates erbB2-3 heterodimer formation to promote tumorigenesis

Cited by 12 publications

References 51 publications

Cardioprotective role of APIP in myocardial infarction through ADORA2B

Cardioprotective role of APIP in myocardial infarction through ADORA2B

Identification of novel genetic variants for type 2 diabetes, childhood obesity, and their pleiotropic loci

Reducing Spatial Stochastic Models of Membrane Receptors to Approximately Equivalent Chemical Reaction Networks through Coarse Graining

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