Expression of insulin-like growth factor family genes in clear cell renal cell carcinoma

Braczkowski, R; Białożyt, Michał; Plato, Marta; Mazurek, Urszula; Braczkowska, Bogumiła

doi:10.5114/wo.2016.58720

Cited by 8 publications

(9 citation statements)

References 45 publications

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“…4(I)] is the 'Pathway of regulation of IGF activity by IGFBP' . Studies show that insulin-like growth factors (IGFs) and insulin play a stimulatory role for renal cancer cells 34,35 . Patients with IGF-1 receptor overexpression have a 70% increased risk of death 36 .…”

Section: (Vi)]mentioning

confidence: 99%

Identification of miRNA signatures for kidney renal clear cell carcinoma using the tensor-decomposition method

Taguchi

2020

Sci Rep

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Cancer is a highly complex disease caused by multiple genetic factors. MicroRNA (miRNA) and mRNA expression profiles are useful for identifying prognostic biomarkers for cancer. Kidney renal clear cell carcinoma (KIRC), which accounts for more than 70% of all renal malignant tumour cases, was selected for our analysis. Traditional methods of identifying cancer prognostic markers may not be accurate. Tensor decomposition (TD) is a useful method uncovering the underlying low-dimensional structures in the tensor. The TD-based unsupervised feature extraction method was applied to analyse mRNA and miRNA expression profiles. Biological annotations of the prognostic miRNAs and mRNAs were examined utilizing the pathway and oncogenic signature databases DIANA-miRPath and MSigDB. TD identified the miRNA signatures and the associated genes. These genes were found to be involved in cancer-related pathways, and 23 genes were significantly correlated with the survival of KIRC patients. We demonstrated that the results are robust and not highly dependent upon the databases we selected. Compared with traditional supervised methods tested, TD achieves much better performance in selecting prognostic miRNAs and mRNAs. These results suggest that integrated analysis using the TD-based unsupervised feature extraction technique is an effective strategy for identifying prognostic signatures in cancer studies.

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Section: (Vi)]mentioning

confidence: 99%

Identification of miRNA signatures for kidney renal clear cell carcinoma using the tensor-decomposition method

Taguchi

2020

Sci Rep

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“…We also evaluated the identified 11 miRNAs by DIANAmirpath. Figure 6 (see also insulin play a stimulatory role for renal cancer cells [34,35]. Patients with IGF-1 receptor overexpression have a 70% increased risk of death [36].…”

Section: Resultsmentioning

confidence: 99%

Identification of miRNA signatures for kidney renal clear cell carcinoma using the tensor-decomposition method

Taguchi

2019

Preprint

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AbstractCancer is a highly complex disease caused by multiple genetic factors. MicroRNA (miRNA) and mRNA expression profiles are useful for identifying prognostic biomarkers for cancer. Kidney renal clear cell carcinoma (KIRC), which accounts for more than 70% of all renal malignant tumour cases, was selected for our analysis.Traditional methods of identifying cancer prognostic markers may not be accurate. Tensor decomposition (TD) is a useful method uncovering the underlying low-dimensional structures in the tensor. The TD-based unsupervised feature extraction method was applied to analyse mRNA and miRNA expression profiles. Biological annotations of the prognostic miRNAs and mRNAs were examined utilizing the pathway and oncogenic signature databases DIANA-miRPath and MSigDB.TD identified the miRNA signatures and the associated genes. These genes were found to be involved in cancer-related pathways, and 23 genes were significantly correlated with the survival of KIRC patients. We demonstrated that the results are robust and not highly dependent upon the databases we selected. Compared with traditional supervised methods tested, TD achieves much better performance in selecting prognostic miRNAs and mRNAs.These results suggest that integrated analysis using the TD-based unsupervised feature extraction technique is an effective strategy for identifying prognostic signatures in cancer studies.

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“…Compared with normal kidney tissue, RCC tissue indicated high expression levels of IGF-1R. 22 IGF-1R activation is considered as prerequisite for malignant transformation. 23 Transgenic overexpression of IGF-1R can induce mammary epithelial hyperplasia and tumor formation in vivo.…”

Section: Discussionmentioning

confidence: 99%

Estrogen affects cell growth and IGF-1 receptor expression in renal cell carcinoma

Sun

Gao

Luo

et al. 2018

OTT

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PurposeBoth obesity and gender are important etiological factors in renal cell carcinoma (RCC) development, suggesting a pivotal role of sex hormone signaling pathway and insulin-like growth factor (IGF) family in RCC carcinogenesis. Here, we aimed to investigate the effect of estrogen on RCC growth and the possible interaction between estrogen/estrogen receptor (ER) signaling pathway and the IGF axis.MethodsER-α and ER-β were detected in four human RCC cell lines. Cells were treated with 17β-estradiol (E2), and cell proliferation was determined using the cell counting kit-8 assay. Using siRNA, ER-β was downregulated in RCC cells and the effect of E2 on cell growth and IGF-1 receptor (IGF-1R) expression was examined.ResultsE2 inhibited 786-O cell but not A498 cell growth significantly. After the downregulation of ER-β, E2 showed no obvious inhibitory role in 786-O cells. E2 stimulation increased the expression of IGF-1R in 786-O cells. Downregulation of ER-β, as well as fulvestrant, attenuated the stimulatory effect of E2 on IGF-1R expression.ConclusionOur results revealed that estrogen induced RCC growth inhibition via an ER-β-dependent pathway. Estrogen also upregulated the expression of IGF-1R, suggesting a link between estrogen/ER and IGF axis.

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Expression of insulin-like growth factor family genes in clear cell renal cell carcinoma

Cited by 8 publications

References 45 publications

Identification of miRNA signatures for kidney renal clear cell carcinoma using the tensor-decomposition method

Identification of miRNA signatures for kidney renal clear cell carcinoma using the tensor-decomposition method

Identification of miRNA signatures for kidney renal clear cell carcinoma using the tensor-decomposition method

Estrogen affects cell growth and IGF-1 receptor expression in renal cell carcinoma

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