ErbB receptors: new insights on mechanisms and biology

The ErbB family of four receptor tyrosine kinases occupies a central role in a wide variety of biological processes from neuronal development to breast cancer. New information continues to expand their biologic significance and to unravel the molecular mechanisms that underlie the signaling capacity of these receptors. Here, we review several aspects of ErbB receptor physiology for which new and significant information is available. These include ligand-dependent receptor dimerization and kinase activation, which is a prerequisite for all subsequent growth factor-dependent cell responses. We also address novel roles of receptor fragments in signaling, trafficking to intracellular sites, such as the nucleus, and ErbB roles in non-cancer disease processes, including schizophrenia, chronic renal disease, hypertension, and the cellular entry of infectious pathogens.     

Cancer cell stiffness: integrated roles of three-dimensional matrix stiffness and transforming potential

While significant advances have been made toward revealing the molecular mechanisms that influence breast cancer progression, much less is known about the associated cellular mechanical properties. To this end, we use particle-tracking microrheology to investigate the interplay among intracellular mechanics, three-dimensional matrix stiffness, and transforming potential in a mammary epithelial cell (MEC) cancer progression series. We use a well-characterized model system where human-derived MCF10A MECs overexpress either ErbB2, 14-3-3ζ, or both ErbB2 and 14-3-3ζ, with empty vector as a control. Our results show that MECs possessing ErbB2 transforming potential stiffen in response to elevated matrix stiffness, whereas non-transformed MECs or those overexpressing only 14-3-3ζ do no exhibit this response. We further observe that overexpression of ErbB2 alone is associated with the highest degree of intracellular sensitivity to matrix stiffness, and that the effect of transforming potential on intracellular stiffness is matrix-stiffness-dependent. Moreover, our intracellular stiffness measurements parallel cell migration behavior that has been previously reported for these MEC sublines. Given the current knowledge base of breast cancer mechanobiology, these findings suggest that there may be a positive relationship among intracellular stiffness sensitivity, cell motility, and perturbed mechanotransduction in breast cancer.     

Dysregulation of ErbB Receptor Trafficking and Signaling in Demyelinating Charcot-Marie-Tooth Disease

Charcot-Marie-Tooth (CMT) disease is the most common inherited peripheral neuropathy with the majority of cases involving demyelination of peripheral nerves. The pathogenic mechanisms of demyelinating CMT remain unclear, and no effective therapy currently exists for this disease. The discovery that mutations in different genes can cause a similar phenotype of demyelinating peripheral neuropathy raises the possibility that there may be convergent mechanisms leading to demyelinating CMT pathogenesis. Increasing evidence indicates that ErbB receptor-mediated signaling plays a major role in the control of Schwann cell-axon communication and myelination in the peripheral nervous system. Recent studies reveal that several demyelinating CMT-linked proteins are novel regulators of endocytic trafficking and/or phosphoinositide metabolism that may affect ErbB receptor signaling. Emerging data have begun to suggest that dysregulation of ErbB receptor trafficking and signaling in Schwann cells may represent a common pathogenic mechanism in multiple subtypes of demyelinating CMT. In this review, we focus on the roles of ErbB receptor trafficking and signaling in regulation of peripheral nerve myelination and discuss the emerging evidence supporting the potential involvement of altered ErbB receptor trafficking and signaling in demyelinating CMT pathogenesis and the possibility of modulating these trafficking and signaling processes for treating demyelinating peripheral neuropathy.     

Ligand-induced ErbB receptor dimerization

Structural studies have provided important new insights into how ligand binding promotes homodimerization and activation of the EGF receptor and the other members of the ErbB family of receptor tyrosine kinases. These structures have also suggested possible explanations for the unique properties of ErbB2, which has no known ligand and can cause cell transformation (and tumorigenesis) by simple overexpression. In parallel with these advances, studies of the EGF receptor at the cell surface increasingly argue that the structural studies are missing key mechanistic components. This is particularly evident in the structural prediction that EGF binding linked to receptor dimerization should be positively cooperative, whereas cell-surface EGF-binding studies suggest negative cooperativity. In this review, I summarize studies of ErbB receptor extracellular regions in solution and of intact receptors at the cell surface, and attempt to reconcile the differences suggested by the two approaches. By combining results obtained with receptor ‘parts’, it is qualitatively possible to explain some models for the properties of the whole receptor. These considerations underline the need to consider the intact ErbB receptors as intact allosterically regulated enzymes, and to combine cellular and structural studies into a complete picture.     

A Dominant Role for p53-Dependent Cellular Senescence in Radiosensitization of Human Prostate Cancer Cells

Amplification and overexpression of ErbB2 (HER2/Neu) is one of the most common alterations associated with breast cancer. Activation of ErbB2 via homodimerization in a non-transformed human mammary epithelial cell line, MCF-10A, in basement membrane cultures leads to formation of proliferative structures that share properties with non-invasive early stage lesions. Recently, we have shown that activation of ErbB2 homodimers combined with expression of transforming growth factor (TGF)-beta induces invasive and migratory activity in MCF-10A cells. In this system, migration requires inputs from numerous cellular pathways. We discuss this data and a model for migration induced by ErbB2 and TGF-beta. Concurrent studies by other groups have also shown that ErbB2 and TGF-beta can cooperate to increase metastatic and invasive behavior in murine mammary tumors. Here we discuss these studies and the potential implications of this research on breast cancer therapeutics.     

ErbB2 and TGF-beta: a cooperative role in mammary tumor progression?

Amplification and overexpression of ErbB2 (HER2/Neu) is one of the most common alterations associated with breast cancer. Activation of ErbB2 via homodimerization in a non-transformed human mammary epithelial cell line, MCF-10A, in basement membrane cultures leads to formation of proliferative structures that share properties with non-invasive early stage lesions. Recently, we have shown that activation of ErbB2 homodimers combined with expression of transforming growth factor (TGF)-beta induces invasive and migratory activity in MCF-10A cells. In this system, migration requires inputs from numerous cellular pathways. We discuss this data and a model for migration induced by ErbB2 and TGF-beta. Concurrent studies by other groups have also shown that ErbB2 and TGF-beta can cooperate to increase metastatic and invasive behavior in murine mammary tumors. Here we discuss these studies and the potential implications of this research on breast cancer therapeutics.     

Development and application of site-specific proteomic approach for study protein S-nitrosylation

Protein S-nitrosylation is the covalent redox-related modification of cysteine sulfhydryl groups with nitric oxide, creating a regulatory impact similar to phosphorylation. Recent studies have reported a growing number of proteins to be S-nitrosylated in vivo resulting in altered functions. These studies support S-nitrosylation as a critical regulatory mechanism, fine-tuning protein activities within diverse cellular processes and biochemical pathways. In addition, S-nitrosylation appears to have key roles in the etiology of a broad range of human diseases. In this review, we discuss recent advances in proteomic approaches for the enrichment, identification, and quantitation of cysteine S-nitrosylated proteins and peptides. These advances have provided analytical tools with the power to interpret the impact of S-nitrosylation at the system level, providing a new platform for drug discovery and the identification of diagnostic markers for human diseases.     

A multiscale modeling approach to investigate molecular mechanisms of pseudokinase activation and drug resistance in the HER3/ErbB3 receptor tyrosine kinase signaling network

Multiscale modeling provides a powerful and quantitative platform for investigating the complexity inherent in intracellular signaling pathways and rationalizing the effects of molecular perturbations on downstream signaling events and ultimately, on the cell phenotype. Here we describe the application of a multiscale modeling scheme to the HER3/ErbB3 receptor tyrosine kinase (RTK) signaling network, which regulates critical cellular processes including proliferation, migration and differentiation. The HER3 kinase is a topic of current interest and investigation, as it has been implicated in mechanisms of resistance to tyrosine kinase inhibition (TKI) of EGFR and HER2 in the treatment of many human malignancies. Moreover, the commonly regarded status of HER3 as a catalytically inactive 'pseudokinase' has recently been challenged by our previous study, which demonstrated robust residual kinase activity for HER3. Through our multiscale model, we investigate the most significant molecular interactions that contribute to potential mechanisms of HER3 activity and the physiological relevance of this activity to mechanisms of drug resistance in an ErbB-driven tumor cell in silico. The results of our molecular-scale simulations support the characterization of HER3 as a weakly active kinase that, in contrast to its fully-active ErbB family members, depends upon a unique hydrophobic interface to coordinate the alignment of specific catalytic residues required for its activity. Translating our molecular simulation results of the uniquely active behavior of the HER3 kinase into a physiologically relevant environment, our HER3 signaling model demonstrates that even a weak level of HER3 activity may be sufficient to induce AKT signaling and TKI resistance in the context of an ErbB signaling-dependent tumor cell, and therefore therapeutic targeting of HER3 may represent a superior treatment strategy for specific ErbB-driven cancers.     

Endocytic downregulation of ErbB receptors: mechanisms and relevance in cancer

ErbB receptors (EGFR (ErbB1), ErbB2, ErbB3, and ErbB4) are important regulators of normal growth and differentiation, and they are involved in the pathogenesis of cancer. Following ligand binding and receptor activation, EGFR is endocytosed and transported to lysosomes where the receptor is degraded. This downregulation of EGFR is a complex and tightly regulated process. The functions of ErbB2, ErbB3, and ErbB4 are also regulated by endocytosis to some extent, although the current knowledge of these processes is sparse. Impaired endocytic downregulation of signaling receptors is frequently associated with cancer, since it can lead to increased and uncontrolled receptor signaling. In this review we describe the current knowledge of ErbB receptor endocytic downregulation. In addition, we outline how ErbB receptors can escape endocytic downregulation in cancer, and we discuss how targeted anti-cancer therapy may induce endocytic downregulation of ErbB receptors.     

Computational modelling of ErbB family phosphorylation dynamics in response to transforming growth factor alpha and heregulin indicates spatial compartmentation of phosphatase activity

Members of the ErbB receptor family are associated with several cancers and appear to be providing useful targets for pharmacological therapeutics for tumours of the lung and breast. Further improvements of these therapies may be guided by a quantitative, dynamic integrative systems understanding of the complexities of ErbB dimerisation, trafficking and activation, for it is these complexities that render difficult intuiting how perturbations such as drug intervention will affect ErbB signalling activities. Towards this goal, we have developed a computational model implementing commonly accepted principles governing ErbB receptor interaction, trafficking, phosphorylation and dephosphorylation. Using this model, we are able to investigate several hypotheses regarding the compartmental localisation of dephosphorylation. Model results applied to experimental data on ErbB 1, ErbB2 and ErbB3 phosphorylation in H292 human lung carcinoma cells support a hypothesis that key dephosphorylation activity for these receptors occurs largely in an intracellular, endosomal compartment rather than at the cell surface plasma membrane. Thus, the endocytic trafficking-related compartmentalisation of dephosphorylation may define a critical aspect of the ErbB signalling response to ligand.     

A Simple Regression-Based Method to Map Quantitative Trait Loci Underlying Function-Valued Phenotypes

Most statistical methods for quantitative trait loci (QTL) mapping focus on a single phenotype. However, multiple phenotypes are commonly measured, and recent technological advances have greatly simplified the automated acquisition of numerous phenotypes, including function-valued phenotypes, such as growth measured over time. While methods exist for QTL mapping with function-valued phenotypes, they are generally computationally intensive and focus on single-QTL models. We propose two simple, fast methods that maintain high power and precision and are amenable to extensions with multiple-QTL models using a penalized likelihood approach. After identifying multiple QTL by these approaches, we can view the function-valued QTL effects to provide a deeper understanding of the underlying processes. Our methods have been implemented as a package for R, funqtl.     

Polar growth in pollen tubes is associated with spatially confined dynamic changes in cell mechanical properties

Cellular morphogenesis involves changes to cellular size and shape which in the case of walled cells implies the mechanical deformation of the extracellular matrix. So far, technical challenges have made quantitative mechanical measurements of this process at subcellular scale impossible. We used micro-indentation to investigate the dynamic changes in the cellular mechanical properties during the onset of spatially confined growth activities in plant cells. Pollen tubes are cellular protuberances that have a strictly unidirectional growth pattern. Micro-indentation of these cells revealed that the initial formation of a cylindrical protuberance is preceded by a local reduction in cellular stiffness. Similar cellular softening was observed before the onset of a rapid growth phase in cells with oscillating growth pattern. These findings provide the first quantitative cytomechanical data that confirm the important role of the mechanical properties of the cell wall for local cellular growth processes. They are consistent with a conceptual model that explains pollen tube oscillatory growth based on the relationship between turgor pressure and tensile resistance in the apical cell wall. To further confirm the significance of cell mechanics, we artificially manipulated the mechanical cell wall properties as well as the turgor pressure. We observed that these changes affected the oscillation profile and were able to induce oscillatory behavior in steadily growing tubes.     

Image-based cell phenotyping with deep learning

A cell's phenotype is the culmination of several cellular processes through a complex network of molecular interactions that ultimately result in a unique morphological signature. Visual cell phenotyping is the characterization and quantification of these observable cellular traits in images. Recently, cellular phenotyping has undergone a massive overhaul in terms of scale, resolution, and throughput, which is attributable to advances across electronic, optical, and chemical technologies for imaging cells. Coupled with the rapid acceleration of deep learning–based computational tools, these advances have opened up new avenues for innovation across a wide variety of high-throughput cell biology applications. Here, we review applications wherein deep learning is powering the recognition, profiling, and prediction of visual phenotypes to answer important biological questions. As the complexity and scale of imaging assays increase, deep learning offers computational solutions to elucidate the details of previously unexplored cellular phenotypes.     

Quantitative phosphoproteomics to characterize signaling networks

Reversible protein phosphorylation is involved in the regulation of most, if not all, major cellular processes via dynamic signal transduction pathways. During the last decade quantitative phosphoproteomics have evolved from a highly specialized area to a powerful and versatile platform for analyzing protein phosphorylation at a system-wide scale and has become the intuitive strategy for comprehensive characterization of signaling networks. Contemporary phosphoproteomics use highly optimized procedures for sample preparation, mass spectrometry and data analysis algorithms to identify and quantify thousands of phosphorylations, thus providing extensive overviews of the cellular signaling networks. As a result of these developments quantitative phosphoproteomics have been applied to study processes as diverse as immunology, stem cell biology and DNA damage. Here we review the developments in phosphoproteomics technology that have facilitated the application of phosphoproteomics to signaling networks and introduce examples of recent system-wide applications of quantitative phosphoproteomics. Despite the great advances in phosphoproteomics technology there are still several outstanding issues and we provide here our outlook on the current limitations and challenges in the field.     

NNAlign: a web-based prediction method allowing non-expert end-user discovery of sequence motifs in quantitative peptide data

Recent advances in high-throughput technologies have made it possible to generate both gene and protein sequence data at an unprecedented rate and scale thereby enabling entirely new "omics"-based approaches towards the analysis of complex biological processes. However, the amount and complexity of data that even a single experiment can produce seriously challenges researchers with limited bioinformatics expertise, who need to handle, analyze and interpret the data before it can be understood in a biological context. Thus, there is an unmet need for tools allowing non-bioinformatics users to interpret large data sets. We have recently developed a method, NNAlign, which is generally applicable to any biological problem where quantitative peptide data is available. This method efficiently identifies underlying sequence patterns by simultaneously aligning peptide sequences and identifying motifs associated with quantitative readouts. Here, we provide a web-based implementation of NNAlign allowing non-expert end-users to submit their data (optionally adjusting method parameters), and in return receive a trained method (including a visual representation of the identified motif) that subsequently can be used as prediction method and applied to unknown proteins/peptides. We have successfully applied this method to several different data sets including peptide microarray-derived sets containing more than 100,000 data points. NNAlign is available online at http://www.cbs.dtu.dk/services/NNAlign.     

Localization and modulation of ErbB receptor tyrosine kinases

The ErbB family of receptor tyrosine kinases serves as a model for understanding the propagation of growth factor signals across the plasma membrane and the interpretation of those signals into a cellular response. Recent studies point to a critical role for the accumulation of ErbBs at specific cell-surface locations in the fidelity of ErbB signaling. The past year has witnessed significant advances in our understanding of the molecular mechanisms of ErbB localization and the role of PDZ-domain-containing proteins and cell-surface glycoproteins in directly modulating signaling through ErbBs.     

Transmembrane helix-helix interactions involved in ErbB receptor signaling

Among the many transmembrane receptor classes, the receptor tyrosine kinases represent an important superfamily, involved in many cellular processes like embryogenesis, development and cell division. Deregulation and dysfunctions of these receptors can lead to various forms of cancer and other diseases. Mostly, only fragmented knowledge exists about functioning of the whole receptors, and many studies have been performed on isolated receptor domains. In this review we focus on the function of the ErbB family of receptor tyrosine kinases with a special emphasis on the role of the transmembrane domain and on the mechanisms underlying regulated and deregulated signaling. Many general aspects of ErbB receptor structure and function have been analyzed and described. All human ErbBs appear to form homo- and heterodimers within cellular membranes and the single transmembrane domain of the receptors is involved in dimerization. Additionally, only defined structures of the transmembrane helix dimer allows signaling of ErbB receptors.     

Genome comparisons and analysis

As we enter the post-genomic era, with the accelerating availability of complete genome sequences, new theoretical approaches and new experimental techniques, our ability to dissect cellular processes at the molecular level continues to expand. Recent advances include the application of RNA interference methods to characterize loss-of-function phenotype genes in higher eukaryotes, comparative analysis of the human and mouse genome sequences, and methods for reconciling contradictory phylogenetic reconstructions. New developments feed into the increasingly rich content of databases such as the COG database. The next phase of research will be increasingly dominated by efforts to integrate the deluge of data into our understanding of biological systems.