Identification of novel mutations of Insulin Receptor Substrate 1 (IRS1) in tumor samples of non-small cell lung cancer (NSCLC): Implications for aberrant insulin signaling in development of cancer

Görgişen, Gökhan; Hapil, Fatma Zehra; Yilmaz, Ozlem; Çetin, Zafer; Pehlivanoğlu, Süray; Özbudak, İrem Hicran; Erdoğan, Abdullah; Özeş, Osman N.

doi:10.1590/1678-4685-gmb-2017-0307

Cited by 18 publications

(12 citation statements)

References 38 publications

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“…And, MET may serve a role in regulating PD-L1 expression in hepatocellular carcinoma ( Chun & Hong, 2019 ) Meanwhile, MET is also involved in high-risk metastasis progression in thyroid cancer ( Garcia et al, 2019 ). Insulin receptor substrate 1 (IRS1) can be phosphorylated to activate AKT kinase, which promotes the development of lung cancer ( Gorgisen et al, 2019 ). The low expression of decorin (DCN) has been demonstrated to contribute to be as a potential biomarker in colon cancer ( Li et al, 2017 ).…”

Section: Discussionmentioning

confidence: 99%

Identifying hub genes of papillary thyroid carcinoma in the TCGA and GEO database using bioinformatics analysis

Wang

Zhang²,

Leng³

et al. 2020

PeerJ

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Background Thyroid carcinoma (THCA) is a common endocrine malignant tumor. Papillary carcinoma with low degree of malignancy and good prognosis is the most common. It can occur at any age, but it is more common in young adults. Although the mortality rate is decreased due to early diagnosis, the survival rate varies depending on the type of tumor. Therefore, the purpose of this study is to identify hub biomarkers and novel therapeutic targets for THCA. Methods The GSE3467, GSE3678, GSE33630 and GSE53157 were obtained from the GEO database, including 100 thyroid tumors and 64 normal tissues to obtain the intersection of differentially expressed genes, and a protein-protein interaction network was constructed to obtain the HUB gene. The corresponding overall survival information from The Cancer Genome Atlas Project-THCA was then included in this research. The signature mechanism was studied by analyzing the gene ontology and the Kyoto Encyclopedia of Genes and Genome database. Results In this research, we identified eight candidate genes (FN1, CCND1, CDH2, CXCL12, MET, IRS1, DCN and FMOD) from the network. Also, expression verification and survival analysis of these candidate genes based on the TCGA database indicate the robustness of the above results. Finally, our hospital samples validated the expression levels of these genes. Conclusion The research identified eight mRNA (four up–regulated and four down–regulated) which serve as signatures and could be a potential prognostic marker of THCA.

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Section: Discussionmentioning

confidence: 99%

Identifying hub genes of papillary thyroid carcinoma in the TCGA and GEO database using bioinformatics analysis

Wang

Zhang²,

Leng³

et al. 2020

PeerJ

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“…Researches showed that genomic changes of IRS1 could lead to development of lung cancer [56]. Silencing IRS1 caused lung cancer cell proliferation and induced phosphorylation of anaplastic lymphoma kinase(AKT) [57]. Importantly, Paxillin played a crucial role in the progression of lung cancer [58].…”

Section: Discussionmentioning

confidence: 99%

Construction and Validation of a Protein Prognostic Model for Lung Squamous Cell Carcinoma

Fang¹,

Liu²,

Weng³

et al. 2020

Int. J. Med. Sci.

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Lung squamous cell carcinoma (LUSCC), as the major type of lung cancer, has high morbidity and mortality rates. The prognostic markers for LUSCC are much fewer than lung adenocarcinoma. Besides, protein biomarkers have advantages of economy, accuracy and stability. The aim of this study was to construct a protein prognostic model for LUSCC. The protein expression data of LUSCC were downloaded from The Cancer Protein Atlas (TCPA) database. Clinical data of LUSCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. A total of 237 proteins were identified from 325 cases of LUSCC patients based on the TCPA and TCGA database. According to Kaplan-Meier survival analysis, univariate and multivariate Cox analysis, a prognostic prediction model was established which was consisted of 6 proteins (CHK1_pS345, CHK2, IRS1, PAXILLIN, BRCA2 and BRAF_pS445). After calculating the risk values of each patient according to the coefficient of each protein in the risk model, the LUSCC patients were divided into high risk group and low risk group. The survival analysis demonstrated that there was significant difference between these two groups (p= 4.877e−05). The area under the curve (AUC) value of the receiver operating characteristic (ROC) curve was 0.699, which suggesting that the prognostic risk model could effectively predict the survival of LUSCC patients. Univariate and multivariate analysis indicated that this prognostic model could be used as independent prognosis factors for LUSCC patients. Proteins co-expression analysis showed that there were 21 proteins co-expressed with the proteins in the risk model. In conclusion, our study constructed a protein prognostic model, which could effectively predict the prognosis of LUSCC patients.

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“…As shown in Figure 3, IRS1 overexpression significantly increased the viability of U-87 MG cells. Previous studies have shown the role of IRS1 in cell proliferation and viability [9,14,17].…”

Section: Discussionmentioning

confidence: 97%

Insulin receptor substrate 1 overexpression promotes survival of glioblastoma cells through AKT1 activation

Görgişen¹,

Yaren²

2020

Self Cite

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Glioblastoma multiforme (GBM) is the most common and malignant type of central nervous system tumours in adults. Strict regulation of glucose homeostasis has a significant role in GBM pathogenesis. Insulin receptor substrate 1 (IRS1) protein is the most important adaptor molecule involved in the regulation of glucose metabolism. It interacts with many cancer-related receptors and its overexpression is strongly associated with cell proliferation and survival. Our study was aimed to understand the role of IRS1 proteins in GBM cell viability. U-87 MG cells were transfected with pcDNA3.1-flagtagged-human IRS1 expression vector. Insulin induced phosphorylation levels of IRS1, AKT1 and ERK1/2 and Grb2 expression were examined to determine the effects of ectopic IRS1 overexpression on insulin signalling and the viability levels of U-87 MG cells were determined by MTT analysis. Overexpression of IRS1 in U-87 MG cells led to an increase in cell viability. Its overexpression also increased Grb2 expression and phosphorylation of AKT1 through elevation of IRS1 tyrosine phosphorylation in IRS1-transfected U-87 MG cells compared to control and mock transfected groups. Our study showed that increased IRS1 expression and activation may promote the cell viability via AKT1 activation. IRS1 signalling may be considered as a therapeutic target for further studies.

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Identification of novel mutations of Insulin Receptor Substrate 1 (IRS1) in tumor samples of non-small cell lung cancer (NSCLC): Implications for aberrant insulin signaling in development of cancer

Cited by 18 publications

References 38 publications

Identifying hub genes of papillary thyroid carcinoma in the TCGA and GEO database using bioinformatics analysis

Identifying hub genes of papillary thyroid carcinoma in the TCGA and GEO database using bioinformatics analysis

Construction and Validation of a Protein Prognostic Model for Lung Squamous Cell Carcinoma

Insulin receptor substrate 1 overexpression promotes survival of glioblastoma cells through AKT1 activation

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