Evolvable signaling networks of receptor tyrosine kinases: relevance of robustness to malignancy and to cancer therapy

Abstract

Robust biological signaling networks evolved, through gene duplications, from simple, relatively fragile cascades. Architectural features such as layered configuration, branching and modularity, as well as functional characteristics (e.g., feedback control circuits), enable fail-safe performance in the face of internal and external perturbations. These universal features are exemplified here using the receptor tyrosine kinase (RTK) family. The RTK module is richly mutated and overexpressed in human malignancies, and pharmaceutical interception of its signaling effectively retards growth of specific tumors. Therapy-induced interception of RTK-signaling pathways and the common evolvement of drug resistance are respectively considered here as manifestations of fragility and plasticity of robust networks. The systems perspective we present views pathologies as hijackers of biological robustness and offers ways for identifying fragile hubs, as well as strategies to overcome drug resistance.

Figure 1

RTKs associated with cancer. The structures of several cancer-relevant RTKs are schematically presented, including conserved domains and information on involvement in malignancies. The horizontal gray bar represents the plasma membrane. VEGFR, vascular endothelial growth factor receptor; HGFR, hepatocyte growth factor receptor; RET, rearranged during transfection.

Figure 2

The evolution and expansion of RTK signaling. The number of kinases and MAPKs in several representative species are listed for vertebrates and for key invertebrate phyla, or other eukaryotes with whole-genome data. The number of CTKs (cytoplasmic tyrosine kinases) and RTKs were derived from published total tyrosine kinase counts, except where marked and noted below, as were counts of EGFRs/ErbB (EGFRs) and MAPKs. The ratio of vertebrate to average invertebrate counts of each protein category was calculated, as weighted for total proteome size. Asterisks indicate that the RTK, EGFR and MAPK ratios show the most significant departures from a ratio of one, each with a P-value <0.0001. The counts were derived from the respective published genomes and the following references: urochordate (Satou et al, 2003); sea urchin (Bradham et al, 2006); fruit fly (Morrison et al, 2000); slime mold (Goldberg et al, 2006); a choanoflagellate [assembly version 1.0 (genome.jgi-psf.org/Monbr1/)] and (Shiu and Li, 2004). The notable departures from published counts are as follows: † the 22 Caenorhabditis elegans CTKs do not include 37 genes of the expanded 38 gene FER family, nor 19 of the 21 paralogs of the nematode specific expansion of Kin-9 and Kin-16 genes; ††, the two EGFRs in Ciona intetinalis reflect a duplication event that took place after urochordates split and diverged from the vertebrate lineage.

Figure 3

From a vertical RTK cascade to a signaling network. The boxed cascade (left) represents an invertebrate primordial signaling pathway comprising a growth factor, an RTK and a signaling cascade culminating in regulation of gene expression (horizontal arrows). Two RTK expansion scenarios are presented. According to Option A, two events of RTK duplication generate four vertical cascades that gradually diverge, but they remain isolated from each other. According Option B, the four cascades richly interact and ultimately establish a layered signaling network. The lines of evidence we describe herein propose that the evolution of RTKs in vertebrates preferred Option B, because it imparts robustness and guarantees output reproducibility.

Figure 4

Dense feedback circuits define the window of RTK activity. The timeline (left) indicates the window of growth factor (GF) activity following binding to an RTK. Receptor phosphorylation (denoted by P) is followed by sequential activation of a kinase cascade culminating in MAPK activation through double phosphorylation. MAPK translocation to the nucleus enables direct phopshorylation of transcription factors (TF1), which activate transcription of IEGs (e.g., the AP-1 components JUN and FOS). IEGs regulate a second wave of transcription. The DEGs encode a broad range of proteins, including negative regulators. The signaling arm (orange line) is regulated at the tier of MAPKs by the group of DUSPs, whereas transcription is regulated by the induction of transcriptional repressors (blue line; e.g. KLF2 and ATF3) and RNA-binding proteins (green line; e.g. ZFP-36), which regulate mRNA stability. Collectively, these feedback loops shut the window of RTK signaling. Boxed are three diagrams of mixed feedback circuits potentially forming stable expression profiles of late-induced genes (e.g., gene Z; solid lines represent transcriptional edges, and a dashed line indicates protein–protein interactions). I: Transcription factor x immediately activates a transcriptional activator A and slowly activates, after an intrinsic delay τ, a transcriptional repressor R. This module enables pulsed induction of a target gene Z. II: A negative feedback loop comprising a transcription activator x, whose activity is attenuated by its target gene A, resulting in a defined window of expression of gene Z. III, A negative feedback loop comprising a repressor R, which is connected by a transcriptional edge to the immediate-early transcriptional activator A, thus defining the temporal activity of A by the transcription of both R and the output gene Z.

Figure 5

Examples of composite feedback loops defining windows of activity of various extracellular ligands. Ligand–receptor interactions (left) are followed by rapid activation of a signaling protein (e.g., MAPK), which induces in a delayed manner (see clock) an inhibitory protein (e.g., DUSP; solid lines define transcriptional edges and dashed lines represent protein–protein interactions). The coupling of a slow transcriptional arm and a rapid protein interaction arm sets the interval of window opening (∼30 min in the case for EGF and MAPK). A longer (∼90 min) window of transcriptional activity is achieved when a relay of two transcriptional processes (e.g., EGR1 and NAB2) is needed to produce the negative regulator (NAB2) downstream of the nerve growth factor (NGF). NFκB serves as a target of several growth factors and cytokines. Two examples of pulsed NFκB activation are presented: a short window of activity is generated by the circuit of the negative regulator IKBalpha, which inhibits NFκB activity downstream of the TNFR. A relatively long (∼120 min) activation of NFκB is induced by lipopolysacharide (LPS): an initial weak activation of NFκB produces a feed-forward element (TNF) and the second is a strong activation of NFκB by TNF, which activates the transcription of the inhibitor IκBalpha.