Epidermal growth factor receptor and EGFRvIII in glioblastoma: signaling pathways and targeted therapies

An, Zhenyi; Aksoy, Ozlem; Zheng, Tina; Fan, Qi-Wen; Weiss, William A.

doi:10.1038/s41388-017-0045-7

Cited by 436 publications

(366 citation statements)

References 140 publications

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“…As a known oncogene of glioma, EGFR overexpression usually occurs as a result of copy number amplification, while in other cases where there is no copy number variation, EGFR has the ability for ligand-independent activation by some point mutations or frame-shifting insertions/deletions. Thus, the activation of EGFR in glioma can be achieved by multiple independent pathways, whether co-exists or not [20,21].…”

Section: Discussionmentioning

confidence: 99%

Integrating Genomic Data with Transcriptomic Data for Improved Survival Prediction for Adult Diffuse Glioma

et al. 2020

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Background: Glioma is the most common type of primary central nervous system tumors. However, the relationship between gene mutations and transcriptome is unclear in diffuse glioma, and there are no systemic analyses with regard to the genotype-phenotype association currently. Methods: We performed the multi-omics analysis in large glioblastoma multiforme (GBM, n=126) and low-grade glioma (LGG, n=481) cohorts obtained from The Cancer Genome Atlas (TCGA) database. We used multivariate linear models to evaluate associations between driver gene mutations and global gene expression. We developed generalized linear models to evaluate associations between genetic/expression factors with clinicopathologic features. Multivariate Cox proportional hazards models were used to predict the overall survival. Results: The potential relationship between genotype and genetics, clinical as well as pathologic features, on diffused glioma was observed. At least one driver mutation correlated with expression changes of about 10% of genes in GBMs while about 80% of genes in LGGs. The strongest association between mutations and expression changes was observed for DRG2 and LRCC41 gene in GBMs and LGGs, respectively. Additionally, the association between genomics features and clinicopathologic features suggested the different underlying molecular mechanisms in molecular subtypes or histology subtypes. For predicting survival, among genetics, transcriptome and clinical variables, transcriptome features made the largest contribution. By combining all the available data, the accuracy in predicting the prognosis of diffuse glioma in patients was also improved. Conclusion: Our study results revealed the influences of driver gene mutations on global gene expression in diffuse glioma patients. A more accurate model in predicting the prognosis of patients was achieved when combining with all the available data than just transcriptomic data.

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Section: Discussionmentioning

confidence: 99%

Integrating Genomic Data with Transcriptomic Data for Improved Survival Prediction for Adult Diffuse Glioma

et al. 2020

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“…The epidermal growth factor receptor (EGFR), a glycoprotein with intrinsic tyrosine kinase function, is activated by seven peptide growth factors, such as amphiregulin . The EGFR system has a significant role in several cellular pathological and physiological processes, including motility, differentiation, and proliferation …”

Section: Exosomes and MMmentioning

confidence: 99%

“…106 The EGFR system has a significant role in several cellular pathological and physiological processes, including motility, differentiation, and proliferation. 107 It has been recently observed that this signaling mechanism has a critical role in bone metabolism through influencing both OCs and OBs. 108 Further investigations have found that EGFR ligands can trigger the formation of OCs through decreasing in OBs the expression of OPG.…”

Section: Exosomes and MMmentioning

confidence: 99%

MicroRNAs and exosomes: Small molecules with big actions in multiple myeloma pathogenesis

et al. 2019

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Multiple myeloma (MM), an incurable hematologic malignancy of plasma cells increasing in the bone marrow (BM), has a complex microenvironment made to support proliferation, survival, and drug resistance of tumor cells. MicroRNAs (miRNAs), short non‐coding RNAs regulating genes expression at posttranscriptional level, have been indicated to be functionally deregulated or abnormally expressed in MM cells. Moreover, by means of miRNAs, tumor microenvironment also modulates the function of MM cells. Consistently, it has been demonstrated that miRNA levels regulation impairs their interaction with the microenvironment of BM as well as create considerable antitumor feature even capable of overcoming the protective BM milieu. Communication between cancer stromal cells and cancer cells is a key factor in tumor progression. Finding out this interaction is important to develop effective approaches that reverse bone diseases. Exosomes, nano‐vehicles having crucial roles in cell‐to‐cell communication, through targeting their cargos (i.e., miRNAs, mRNAs, DNAs, and proteins), are implicated in MM pathogenesis.

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“…The altered EGFR activates the RTK/RAS/PI3K pathway causing excessive proliferation . Experimental therapies, targeting EGFR, such as monoclonal antibodies, EGFRvIII vaccines and small molecular inhibitors, have so far not proven effective . Intratumoral heterogeneity, suboptimal blood barrier penetration, compensatory signaling pathways and secondary mutations are probable causes of resistance toward EGFR targeting drugs .…”

Section: Diffuse Astrocytomas and Oligodendrogliomasmentioning

confidence: 99%

Biomarkers in tumors of the central nervous system – a review

Scheie

Kufaishi

Broholm

et al. 2019

APMIS

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Until recently, diagnostics of brain tumors were almost solely based on morphology and immunohistochemical stainings for relatively unspecific lineage markers. Although certain molecular markers have been known for longer than a decade (combined loss of chromosome 1p and 19q in oligodendrogliomas), molecular biomarkers were not included in the WHO scheme until 2016. Now, the classification of diffuse gliomas rests on an integration of morphology and molecular results. Also, for many other central nervous system tumor entities, specific diagnostic, prognostic and predictive biomarkers have been detected and continue to emerge. Previously, we considered brain tumors with similar histology to represent a single disease entity. We now realize that histologically identical tumors might show alterations in different molecular pathways, and often represent separate diseases with different natural history and response to treatment. Hence, knowledge about specific biomarkers is of great importance for individualized treatment and follow‐up. In this paper we review the biomarkers that we currently use in the diagnostic work‐up of brain tumors.

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Epidermal growth factor receptor and EGFRvIII in glioblastoma: signaling pathways and targeted therapies

Cited by 436 publications

References 140 publications

Integrating Genomic Data with Transcriptomic Data for Improved Survival Prediction for Adult Diffuse Glioma

Integrating Genomic Data with Transcriptomic Data for Improved Survival Prediction for Adult Diffuse Glioma

MicroRNAs and exosomes: Small molecules with big actions in multiple myeloma pathogenesis

Biomarkers in tumors of the central nervous system – a review

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