The constitutive activity of epidermal growth factor receptor vIII leads to activation and differential trafficking of wild-type epidermal growth factor receptor and erbB2

To Investigate Growth Factor Receptor Targets and Generate Cancer Targeting Inhibitors

Receptor tyrosine kinase (RTK) regulates multiple pathways, including Mitogenactivated protein kinases (MAPKs), PI3/AKT, JAK/STAT pathway, etc. which has a significant role in the progression and metastasis of tumor. As RTK activation regulates numerous essential bodily processes, including cell proliferation and division, RTK dysregulation has been identified in many types of cancers. Targeting RTK is a significant challenge in cancer due to the abnormal upregulation and downregulation of RTK receptors subfamily EGFR, FGFR, PDGFR, VEGFR, and HGFR in the progression of cancer, which is governed by multiple RTK receptor signalling pathways and impacts treatment response and disease progression. In this review, an extensive focus has been carried out on the normal and abnormal signalling pathways of EGFR, FGFR, PDGFR, VEGFR, and HGFR and their association with cancer initiation and progression. These are explored as potential therapeutic cancer targets and therefore, the inhibitors were evaluated alone and merged with additional therapies in clinical trials aimed at combating global cancer.

Updated Insights on EGFR Signaling Pathways in Glioma

Nowadays, due to recent advances in molecular biology, the pathogenesis of glioblastoma is better understood. For the newly diagnosed, the current standard of care is represented by resection followed by radiotherapy and temozolomide administration, but because median overall survival remains poor, new diagnosis and treatment strategies are needed. Due to the quick progression, even with aggressive multimodal treatment, glioblastoma remains almost incurable. It is known that epidermal growth factor receptor (EGFR) amplification is a characteristic of the classical subtype of glioma. However, targeted therapies against this type of receptor have not yet shown a clear clinical benefit. Many factors contribute to resistance, such as ineffective blood-brain barrier penetration, heterogeneity, mutations, as well as compensatory signaling pathways. A better understanding of the EGFR signaling network, and its interrelations with other pathways, are essential to clarify the mechanisms of resistance and create better therapeutic agents.

Inhibition of oncogenic Src induces FABP4-mediated lipolysis via PPARγ activation exerting cancer growth suppression

Background

c-Src is a driver oncogene well-known for tumorigenic signaling, but little for metabolic function. Previous reports about c-Src regulation of glucose metabolism prompted us to investigate its function in other nutrient modulation, particularly in lipid metabolism.

Methods

Oil-red O staining, cell growth assay, and tumor volume measurement were performed to determine lipid amount and growth inhibitory effect of treatments in lung cancer cells and xenograft model. Gene expression was evaluated by immunoblotting and relative RT-PCR. Transcriptional activity of peroxisome proliferator-activated receptor gamma (PPARγ) was assessed by luciferase assay. Reactive oxygen species (ROS) was measured using ROS sensing dye. Oxygen consumption rate was evaluated by Seahorse XF Mito Stress Test. Clinical relevance of candidate proteins was examined using patient samples and public database analysis.

Findings

Inhibition of Src induced lipolysis and increased intracellular ROS. Src inhibition derepressed PPARγ transcriptional activity leading to induced expression of lipolytic gene fatty acid binding protein (FABP) 4 which accompanies reduced lipid droplets and decreased tumor growth. The reverse correlation of Src and FABP4 was confirmed in pair-matched lung cancer patient samples, and further analysis using public datasets revealed upregulation of lipolytic genes is associated with better prognosis of cancer patients.

Interpretation

This study provides an insight of how oncogenic factor Src concurrently regulates both cellular signaling pathways and metabolic plasticity to drive cancer progression.

Fund

National Research Foundation of Korea and Korea Health Industry Development Institute.

The EGFR-HER2 module: a stem cell approach to understanding a prime target and driver of solid tumors

The epidermal growth factor receptor (EGFR) and a coreceptor denoted HER2/ERBB2 are frequently overexpressed or mutated in solid tumors, such as carcinomas and gliomas. In line with driver roles, cancer drugs intercepting EGFR or HER2 currently outnumber therapies targeting other hubs of signal transduction. To explain the roles for EGFR and HER2 as prime drivers and targets, we take lessons from invertebrates and refer to homeostatic regulation of several mammalian tissues. The model we infer ascribes to the EGFR-HER2 module pivotal functions in rapid clonal expansion of progenitors called transient amplifying cells (TACs). Accordingly, TACs of tumors suffer from replication stress, and hence accumulate mutations. In addition, several lines of evidence propose that in response to EGF and related mitogens, TACs might undergo dedifferentiation into tissue stem cells, which might enable entry of oncogenic mutations into the stem cell compartment. According to this view, antibodies or kinase inhibitors targeting EGFR-HER2 effectively retard some solid tumors because they arrest mutation-enriched TACs and possibly inhibit their dedifferentiation. Deeper understanding of the EGFR-HER2 module and relations between cancer stem cells and TACs will enhance our ability to control a broad spectrum of human malignancies.

Magnetic nanoparticles as mediators of ligand-free activation of EGFR signaling

BACKGROUND

Magnetic nanoparticles (NPs) are of particular interest in biomedical research, and have been exploited for molecular separation, gene/drug delivery, magnetic resonance imaging, and hyperthermic cancer therapy. In the case of cultured cells, magnetic manipulation of NPs provides the means for studying processes induced by mechanotransduction or by local clustering of targeted macromolecules, e.g. cell surface receptors. The latter are normally activated by binding of their natural ligands mediating key signaling pathways such as those associated with the epidermal growth factor (EGFR). However, it has been reported that EGFR may be dimerized and activated even in the absence of ligands. The present study assessed whether receptor clustering induced by physical means alone suffices for activating EGFR in quiescent cells.

METHODOLOGY/PRINCIPAL FINDINGS

The EGFR on A431 cells was specifically targeted by superparamagnetic iron oxide NPs (SPIONs) carrying either a ligand-blocking monoclonal anti-EGFR antibody or a streptavidin molecule for targeting a chimeric EGFR incorporating a biotinylated amino-terminal acyl carrier peptide moiety. Application of a magnetic field led to SPION magnetization and clustering, resulting in activation of the EGFR, a process manifested by auto and transphosphorylation and downstream signaling. The magnetically-induced early signaling events were similar to those inherent to the ligand dependent EGFR pathways. Magnetization studies indicated that the NPs exerted magnetic dipolar forces in the sub-piconewton range with clustering dependent on Brownian motion of the receptor-SPION complex and magnetic field strength.

CONCLUSIONS/SIGNIFICANCE

We demonstrate that EGFR on the cell surface that have their ligand binding-pocket blocked by an antibody are still capable of transphosphorylation and initiation of signaling cascades if they are clustered by SPIONs either attached locally or targeted to another site of the receptor ectodomain. The results suggest that activation of growth factor receptors may be triggered by ligand-independent molecular crowding resulting from overexpression and/or sequestration in membrane microdomains.

Epidermal growth factor receptor as a therapeutic target in glioblastoma

Glioblastoma represents one of the most challenging problems in neurooncology. Among key elements driving its behavior is the transmembrane epidermal growth factor receptor family, with the first member epidermal growth factor receptor (EGFR) centered in most studies. Engagement of the extracellular domain with a ligand activates the intracellular tyrosine kinase (TK) domain of EGFR, leading to autophosphorylation and signal transduction that controls proliferation, gene transcription, and apoptosis. Oncogenic missense mutations, deletions, and insertions in the EGFR gene are preferentially located in the extracellular domain in glioblastoma and cause constitutive activation of the receptor. The mutant EGFR may also transactivate other cell surface molecules, such as additional members of the EGFR family and the platelet-derived growth factor receptor, which ignite signaling cascades that synergize with the EGFR-initiated cascade. Because of the cell surface location and increased expression of the receptor along with its important biological function, EGFR has triggered much effort for designing targeted therapy. These approaches include TK inhibition, monoclonal antibody, vaccine, and RNA-based downregulation of the receptor. Treatment success requires that the drug penetrates the blood-brain barrier and has low systemic toxicity but high selectivity for the tumor. While the blockade of EGFR-dependent processes resulted in experimental and clinical treatment success, cells capable of using alternative signaling ultimately escape this strategy. A combination of interventions targeting tumor-specific cell surface regulators along with convergent downstream signaling pathways will likely enhance efficacy. Studies on EGFR in glioblastoma have revealed much information about the complexity of gliomagenesis and also facilitated the development of strategies for targeting drivers of tumor growth and combination therapies with increasing complexity.

Linking proteomic and transcriptional data through the interactome and epigenome reveals a map of oncogene-induced signaling

Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118–310, targeting β-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets.

The ways in which cells respond to changes in their environment are controlled by networks of physical links among the proteins and genes. The initial signal of a change in conditions rapidly passes through these networks from the cytoplasm to the nucleus, where it can lead to long-term alterations in cellular behavior by controlling the expression of genes. These cascades of signaling events underlie many normal biological processes. As a result, being able to map out how these networks change in disease can provide critical insights for new approaches to treatment. We present a computational method for reconstructing these networks by finding links between the rapid short-term changes in proteins and the longer-term changes in gene regulation. This method brings together systematic measurements of protein signaling, genome organization and transcription in the context of protein-protein and protein-DNA interactions. When used to analyze datasets from an oncogene expressing cell line model of human glioblastoma, our approach identifies key nodes that affect cell survival and functional transcriptional regulators.