Quantitative and qualitative differences in the activation of a fibroblast growth factor receptor by different FGF ligands.

The FGF system is the most complex of all receptor tyrosine kinase signaling networks with 18 FGF ligands and four FGFRs that deliver morphogenic signals to pattern most embryonic structures. Even when a single FGFR is expressed in the tissue, different FGFs can trigger dramatically different biological responses via this receptor. Here we show both quantitative and qualitative differences in the signaling of one of the FGF receptors, FGFR1c, in response to different FGFs. We provide an overview of the recent discovery that FGFs engage in biased signaling via FGFR1c. We discuss the concept of ligand bias, which represents qualitative differences in signaling as it is a measure of differential ligand preferences for different downstream responses. We show how FGF ligand bias manifests in functional data in cultured chondrocyte cells. We argue that FGF-ligand bias contributes substantially to FGF-driven developmental processes, along with known differences in FGF expression levels, FGF-FGFR binding coefficients and differences in FGF stability in vivo.

Ligand bias underlies differential signaling of multiple FGFs via FGFR1.

The differential signaling of multiple FGF ligands through a single fibroblast growth factor (FGF) receptor (FGFR) plays an important role in embryonic development. Here, we use quantitative biophysical tools to uncover the mechanism behind differences in FGFR1c signaling in response to FGF4, FGF8, and FGF9, a process which is relevant for limb bud outgrowth. We find that FGF8 preferentially induces FRS2 phosphorylation and extracellular matrix loss, while FGF4 and FGF9 preferentially induce FGFR1c phosphorylation and cell growth arrest. Thus, we demonstrate that FGF8 is a biased FGFR1c ligand, as compared to FGF4 and FGF9. Förster resonance energy transfer experiments reveal a correlation between biased signaling and the conformation of the FGFR1c transmembrane domain dimer. Our findings expand the mechanistic understanding of FGF signaling during development and bring the poorly understood concept of receptor tyrosine kinase ligand bias into the spotlight.

Quantitative assessment of ligand bias from bias plots: The bias coefficient "kappa".

The current methods for quantifying ligand bias involve the construction of bias plots and the calculations of bias coefficients that can be compared using statistical methods. However, widely used bias coefficients can diverge in their abilities to identify ligand bias and can give false positives. As the empirical bias plots are considered the most reliable tools in bias identification, here we develop an analytical description of bias plot trajectories and introduce a bias coefficient, kappa, which is calculated from these trajectories. The new bias coefficient complements the tool-set in ligand bias identification in cell signaling research.

Pondering the mechanism of receptor tyrosine kinase activation: The case for ligand-specific dimer microstate ensembles.

Receptor tyrosine kinases (RTKs) are single-pass membrane proteins that regulate cell growth, differentiation, motility, and metabolism. Here, we review recent advancements in RTK structure determination and in the understanding of RTK activation. We argue that further progress in the field will necessitate new ways of thinking, and we introduce the concept that RTK dimers explore ensembles of microstates, each characterized by different kinase domain dimer conformations, but the same extracellular domain dimer structure. Many microstates are phosphorylation-competent and ensure the phosphorylation of one specific tyrosine. The prevalence of each microstate correlates with its stability. A switch in ligand will lead to a switch in the extracellular domain configuration and to a subsequent switch in the ensemble of microstates. This model can explain how different ligands produce specific phosphorylation patterns, how receptor overexpression leads to enhanced signaling even in the absence of activating ligands, and why RTK kinase domain structures have remained unresolved in cryogenic electron microscopy studies.

A cancer mutation promotes EphA4 oligomerization and signaling by altering the conformation of the SAM domain.

The Eph receptor tyrosine kinases and their ephrin ligands regulate many physiological and pathological processes. EphA4 plays important roles in nervous system development and adult homeostasis, while aberrant EphA4 signaling has been implicated in neurodegeneration. EphA4 may also affect cancer malignancy, but the regulation and effects of EphA4 signaling in cancer are poorly understood. A correlation between decreased patient survival and high EphA4 mRNA expression in melanoma tumors that also highly express ephrinA ligands suggests that enhanced EphA4 signaling may contribute to melanoma progression. A search for EphA4 gain-of-function mutations in melanoma uncovered a mutation of the highly conserved leucine 920 in the EphA4 sterile alpha motif (SAM) domain. We found that mutation of L920 to phenylalanine (L920F) potentiates EphA4 autophosphorylation and signaling, making it the first documented EphA4 cancer mutation that increases kinase activity. Quantitative Föster resonance energy transfer and fluorescence intensity fluctuation (FIF) analyses revealed that the L920F mutation induces a switch in EphA4 oligomer size, from a dimer to a trimer. We propose this switch in oligomer size as a novel mechanism underlying EphA4-linked tumorigenesis. Molecular dynamics simulations suggest that the L920F mutation alters EphA4 SAM domain conformation, leading to the formation of EphA4 trimers that assemble through two aberrant SAM domain interfaces. Accordingly, EphA4 wild-type and the L920F mutant are affected differently by the SAM domain and are differentially regulated by ephrin ligand stimulation. The increased EphA4 activation induced by the L920F mutation, through the novel mechanism we uncovered, supports a functional role for EphA4 in promoting pathogenesis.

Ligand bias in receptor tyrosine kinase signaling.

Ligand bias is the ability of ligands to differentially activate certain receptor signaling responses compared with others. It reflects differences in the responses of a receptor to specific ligands and has implications for the development of highly specific therapeutics. Whereas ligand bias has been studied primarily for G protein-coupled receptors (GPCRs), there are also reports of ligand bias for receptor tyrosine kinases (RTKs). However, the understanding of RTK ligand bias is lagging behind the knowledge of GPCR ligand bias. In this review, we highlight how protocols that were developed to study GPCR signaling can be used to identify and quantify RTK ligand bias. We also introduce an operational model that can provide insights into the biophysical basis of RTK activation and ligand bias. Finally, we discuss possible mechanisms underpinning RTK ligand bias. Thus, this review serves as a primer for researchers interested in investigating ligand bias in RTK signaling.