Analysis of the quantitative balance between insulin-like growth factor (IGF)-1 ligand, receptor, and binding protein levels to predict cell sensitivity and therapeutic efficacy

Tian, Dan; Kreeger, Pamela K.

doi:10.1186/s12918-014-0098-y

Cited by 17 publications

(19 citation statements)

References 92 publications

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“…It is possible that variations in the levels of other components of the cellular signaling network besides growth factor receptors could be responsible for the observed heterogeneity. For example, it has been shown that when predicting cell response, dimerization patterns of ErbB1 with other ErbB receptors is important to consider [ 60 ], as is the ratio of IGF1 to IGF1R and the level of the IGF binding proteins [ 61 ]. Likewise, previous work from our lab demonstrated that it was necessary to incorporate the levels of both ligands and receptors when predicting ovarian cancer cell response to an ErbB-targeted inhibitor [ 62 ].…”

Section: Discussionmentioning

confidence: 99%

High-grade serous ovarian cancer cell lines exhibit heterogeneous responses to growth factor stimulation

et al. 2015

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BackgroundThe factors driving the onset and progression of ovarian cancer are not well understood. Recent reports have identified cell lines that are representative of the genomic pattern of high-grade serous ovarian cancer (HGSOC), in which greater than 90 % of tumors have a mutation in TP53. However, many of these representative cell lines have not been widely used so it is unclear if these cell lines capture the variability that is characteristic of the disease.MethodsWe investigated six TP53-mutant HGSOC cell lines (Caov3, Caov4, OV90, OVCA432, OVCAR3, and OVCAR4) for migration, MMP2 expression, proliferation, and VEGF secretion, behaviors that play critical roles in tumor progression. In addition to comparing baseline variation between the cell lines, we determined how these behaviors changed in response to four growth factors implicated in ovarian cancer progression: HB-EGF, NRG1β, IGF1, and HGF.ResultsBaseline levels of each behavior varied across the cell lines and this variation was comparable to that seen in tumors. All four growth factors impacted cell proliferation or VEGF secretion, and HB-EGF, NRG1β, and HGF impacted wound closure or MMP2 expression in at least two cell lines. Growth factor-induced responses demonstrated substantial heterogeneity, with cell lines sensitive to all four growth factors, a subset of the growth factors, or none of the growth factors, depending on the response of interest. Principal component analysis demonstrated that the data clustered together based on cell line rather than growth factor identity, suggesting that response is dependent on intrinsic qualities of the tumor cell rather than the growth factor.ConclusionsSignificant variation was seen among the cell lines, consistent with the heterogeneity of HGSOC.Electronic supplementary materialThe online version of this article (doi:10.1186/s12935-015-0263-4) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

High-grade serous ovarian cancer cell lines exhibit heterogeneous responses to growth factor stimulation

et al. 2015

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“…Despite the increasing number and sophistication of the models, these studies have not considered insulin signaling. Conversely, computational models of insulin signaling exist [ 42 , 43 ], but have only been applied to other applications, including articular cartilage [ 44 ], ovarian cancer [ 45 ], and human skeletal muscle [ 46 ], and exclude molecules of interest for brain cancer cells [ 44 , 47 ]. Thus, we created for the first time, a computational chemical-kinetic model linking the insulin signaling pathway to glioblastoma growth.…”

Section: Introductionmentioning

confidence: 99%

Simulation Predicts IGFBP2-HIF1α Interaction Drives Glioblastoma Growth

2015

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Tremendous strides have been made in improving patients’ survival from cancer with one glaring exception: brain cancer. Glioblastoma is the most common, aggressive and highly malignant type of primary brain tumor. The average overall survival remains less than 1 year. Notably, cancer patients with obesity and diabetes have worse outcomes and accelerated progression of glioblastoma. The root cause of this accelerated progression has been hypothesized to involve the insulin signaling pathway. However, while the process of invasive glioblastoma progression has been extensively studied macroscopically, it has not yet been well characterized with regards to intracellular insulin signaling. In this study we connect for the first time microscale insulin signaling activity with macroscale glioblastoma growth through the use of computational modeling. Results of the model suggest a novel observation: feedback from IGFBP2 to HIF1α is integral to the sustained growth of glioblastoma. Our study suggests that downstream signaling from IGFI to HIF1α, which has been the target of many insulin signaling drugs in clinical trials, plays a smaller role in overall tumor growth. These predictions strongly suggest redirecting the focus of glioma drug candidates on controlling the feedback between IGFBP2 and HIF1α.

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“…e activities of IGF-1 are controlled by interaction of several high-a nity IGFBPs; especially IGFBP3 which directly carries IGF-1 to target tissues, prevents it from proteolytic degradation and regulates its interaction with IGF-1R. Its expression is negatively related to IGF-1 expression [17,18]. IGF1 and IGFBP3 gene polymorphisms may a ect circulation levels of IGF1 and IGFBP3, and high IGF1 level but low IGFBP3 level contributes to increased cancer risk [7,19].…”

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confidence: 99%

Meta-analysis of the association of IGFBP3 and IGF1 polymorphisms with susceptibility to colorectal cancer

Wang¹,

Bu-qiang²,

Chen³

et al. 2018

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e aim of this study is to comprehensively evaluate the associations of IGFBP3 and IGF1 polymorphisms with susceptibility to colorectal cancer (CRC). We searched the English and Chinese databases and recruited case-control studies based on strict inclusion and exclusion criteria. e statistical analysis was performed by the Comprehensive Metaanalysis 2.0 (CMA 2.0) so ware and this initially identi ed 251 studies. We then recruited 10 English studies to this metaanalysis detailed review which includes 9,415 CRC patients and 14,179 healthy controls. Our results demonstrated that IGFBP3 rs2854746 C>G polymorphism increases susceptibility to the CRC (allele model: OR=1.167, 95% CI=1.095~1.244, p<0.001 and to the dominant gene model: OR=1.226, 95% CI=1.113~1.350, p<0.001); but IGFBP3 rs2854744 A>C has no signi cant association with the CRC susceptibility (allele model: OR=0.970, 95% CI=0.932~1.010, p=0.138; dominant gene model: OR=0.995, 95% CI=0.936~1.057, p=0.874). Also, IGF1 rs35767 C>T polymorphism decreases susceptibility to CRC (allele model: OR=0.785, 95% CI=0.726~0.850, p<0.001 and also the dominant model: OR=0.730, 95% CI=0.661~0.806, p<0.001). However, IGFBP3 rs2854746 C>G is considered the susceptible CRC polymorphism and IGF1 rs35767 C>T is CRC protective.

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Analysis of the quantitative balance between insulin-like growth factor (IGF)-1 ligand, receptor, and binding protein levels to predict cell sensitivity and therapeutic efficacy

Cited by 17 publications

References 92 publications

High-grade serous ovarian cancer cell lines exhibit heterogeneous responses to growth factor stimulation

High-grade serous ovarian cancer cell lines exhibit heterogeneous responses to growth factor stimulation

Simulation Predicts IGFBP2-HIF1α Interaction Drives Glioblastoma Growth

Meta-analysis of the association of IGFBP3 and IGF1 polymorphisms with susceptibility to colorectal cancer

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