complexity of receptor tyrosine kinase signal...

Complexity of Receptor Tyrosine KinaseSignal Processing

Natalia Volinsky and Boris N. Kholodenko

Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland

Correspondence: [email protected]

Our knowledge of molecular mechanisms of receptor tyrosine kinase (RTK) signaling ad-vanceswith ever-increasing pace. Yet our understanding of how the spatiotemporal dynamicsof RTK signaling control specific cellular outcomes has lagged behind. Systems-centeredexperimental and computational approaches can help reveal how overlapping networks ofsignal transducers downstream of RTKs orchestrate specific cell-fate decisions. We discusshow RTK network regulatory structures, which involve the immediate posttranslational anddelayed transcriptional controls by multiple feed forward and feedback loops together withpathway cross talk, adapt cells to the combinatorial variety of external cues and conditions.This intricate network circuitry endows cells with emerging capabilities for RTK signal pro-cessinganddecoding.Weillustratehowmathematicalmodeling facilitatesourunderstandingof RTK network behaviors by unraveling specific systems properties, including bistability,oscillations,excitable responses,andgenerationof intricate landscapesof signalingactivities.

Since the first cloning of the cDNA encodingthe epidermal growth factor (EGF) receptor

(EGFR), signaling by receptor tyrosine kinases(RTKs) has been in the limelight of scientificinterest owing to their central role in the regu-lation of development, cell motility, prolifera-tion, differentiation, glucose metabolism, andapoptosis (Hunter 2000; Schlessinger 2000;Lemmon and Schlessinger 2010). The RTK fam-ily comprises more than 50 cell-surface recep-tors with intrinsic tyrosine kinase activity. AllRTKs consist of three major domains: an extra-cellular domain for ligand binding, a mem-brane-spanning segment, and a cytoplasmic do-main, which possesses tyrosine kinase activityand contains phosphorylation sites with tyro-sine, serine, and threonine residues. Following

ligand binding, RTKs undergo dimerization(e.g., EGFR) or allosteric transitions (e.g., in-sulin receptor [IR] and insulin-like growth fac-tor-1 receptor [IGF-1R] that are associatedinto oligomers before the ligand binding), re-sulting in receptor activation. Auto- and/ortrans-phosphorylation of RTKs transmit bio-chemical signals to cytoplasmic adaptor pro-teins and enzymes, which contain characteristicprotein domains, such as Src homology (SH2and SH3), phosphotyrosine binding (PTB), andpleckstrin homology (PH) domains. These do-mains act as docking sites for phosphotyrosinesor phospholipids thereby triggering the mobi-lization of these proteins to the cell surface(Pawson and Nash 2003). Subsequently, signalspropagate through a tangled network of inter-

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connecting proteins and signaling cascadesto the nucleus, inducing transcriptional re-sponses of immediate early genes (IEG) and de-layed early genes (DEG) (Avraham and Yarden2011).

The idea of isolated linear pathways that re-late signals and receptors to specific genes hasgiven way to the concept of signaling networks,which allow a limited number of RTKs to gen-erate an exponentially larger number of func-tional outcomes as a result of combinatorial in-teractions. Although early genetic experimentsseem to support a linear pathway view, the cur-rent biochemical and imaging data suggest thatany given RTK, downstream adaptors, small G-proteins (small GTPases, such as Ras, Rac, Rho,or Cdc42), and activated kinases interact with alarge variety of signaling molecules resulting inhighly interconnected networks (von Krieg-sheim et al. 2009). These signaling networks notonly transmit but also process and integrate sig-nals. For instance, signals from different RTKsare integrated through common adaptor pro-teins and other points of pathway cross talkthat include small GTPases and cytoplasmic ki-nases, such as the Src family kinases, phosphati-dylinositol 3-kinase (PI3K), and mitogen acti-vated protein kinases (MAPK) (Kholodenkoet al. 2010).

Given that the protein complements ofadaptor proteins, small GTPases, and kinases,which mediate RTK-induced signal transduc-tion, overlap for all known RTKs (Lemmon andSchlessinger 2010), questions arise as to howcells can maintain specificity when activated bymultiple cues? Also how can coherent cellulardecisions, including whether to undergo prolif-eration, differentiation, or die, be made? Theconcept is emerging that for any RTK pathway,there is no single protein or gene responsible forsignaling specificity. Rather, specificity is deter-mined by the spatiotemporal dynamics of acti-vation of signaling proteins, IEGs, and DEGs,downstream of RTKs (Murphy et al. 2004; Kho-lodenko 2006; Nakakuki et al. 2010). Yet manysignaling events activated by RTKs are partiallyredundant, and different RTKs can compensatefor each other in many cellular functions (Xuand Huang 2010).

A hallmark of complex signaling and earlygene networks downstream of RTKs are multi-ple feed forward and feedback loops, both neg-ative and positive. These regulations operate ondifferent timescales, precisely tuning the signal-ing outcome and often convert analog inputsignals into digital outputs (Kholodenko et al.2010). Immediate feedback or feedforward reg-ulations occur through interactions betweentwo proteins or a protein and a lipid or throughposttranslational modifications, such as phos-phorylation that alters protein activity. For in-stance, active extracellular signal regulated ki-nase (ERK) phosphorylates and inactivates thekinase Raf-1, which is upstream of ERK in theRas/ERK signaling cascade (Dougherty et al.2005). These immediate feedforward and feed-back loops operate on the timescale of secondsto minutes, which are the characteristic times ofthe corresponding interactions or catalytic re-actions. Another large group of feedback reg-ulators, such as Sprouty, Spred, and Mitogen-inducible gene-6 (Mig-6)/receptor-associatedlate transducer (RALT) (Gotoh 2009; Murphyet al. 2010; Segatto et al. 2011) requires RTK-induced gene transcription and translation.These delayed feedbacks adapt cells to a morepermanent external stimulation, persisting onthe timescale of tens of minutes and hours. Forinstance, transcriptionally induced IEGs, suchas dual specificity phosphatases (DUSP), atten-uate RTK-induced MAPK signaling. Owing tothese multiple feedback and feedforward loops,the understanding of the spatiotemporal dy-namics of RTK networks requires more thanknowledge of binding partners, their structures,and interactions (Kholodenko 2009).

In this review, we focus on a systems-cen-tered view of the biology of RTK signaling net-works. We discuss cross talk between differentRTKs and pathways and illustrate how this crosstalk may alter the functional outcome of signal-ing by individual RTKs. We analyze feedforwardand feedback loops and show how this regula-tory circuitry can bring about the intricate dy-namic behavior of RTK networks, includingbistability, oscillations, and excitable overshoottransitions. We illustrate how computationalmodeling and systems analysis can facilitate our

N. Volinsky and B.N. Kholodenko

2 Cite this article as Cold Spring Harb Perspect Biol 2013;5:a009043



understanding of the complex spatiotemporalbehavior of RTK pathways based on the knowl-edge of molecular mechanisms of signal trans-duction. Finally, we discuss the challenges aheadthat will stimulate further research.

RTK PATHWAY CROSS TALK: FINEBALANCES AT MULTIPLE LEVELS

Cells in situ are exposed to a plethora of signal-ing cues that activate multiple RTKs. Althoughindividual RTKs have been extensively studied,how signaling networks integrate multiple cuesis less understood. How do cells integrate andprocess external information byexploiting path-way cross talk? Cross talk between RTK-stimu-lated pathways exists at different signaling levels,which include the level of receptors, adaptorproteins, scaffolds, small GTPases, downstreamkinases, and transcriptional responses (Pawsonet al. 2001).

Cross talk at the receptor level can be medi-ated by several mechanisms. An RTK can induceactivation of structurally unrelated RTKs, forinstance, stimulation of IGF-1R can lead toEGFR (Ahmad et al. 2004) or ErbB2 activity(Balana et al. 2001). At least two mechanismsof cross talk were suggested: direct dimerizationbetween structurally independent RTKs, such asIGF-1R or c-Met with ErbB family receptors(Balana et al. 2001; Ahmad et al. 2004; Tanizakiet al. 2011) and transactivation mediated by acytoplasmic tyrosine kinase, such as Src. In thelatter case, once activated by IGF-1R, Src bindsand phosphorylates EGFR, thus promotingEGFR catalytic activity (Jones et al. 2006). Usinghigh-throughput Western blotting and Bayes-ian interference techniques, different cross talkmechanisms were recently described (Ciaccioet al. 2010). Whereas EGF induced rapid phos-phorylation of multiple sites on EGFR, phos-phorylation of other RTKs, as well as someEGFR tyrosines, was detected at later timepoints. In particular, phosphorylation of the c-Met receptor was only detected after about 15min of the EGFR phosphorylation. These de-layed responses suggest the involvement ofdownstream signaling cascades in mediatingRTK cross activation (Ciaccio et al. 2010).

Cross talk between distinct RTKs was shownin non-small cell lung cancer-derived cell lines.Using specific inhibitors of EGFR and c-Met,it was shown that these two RTKs positively in-fluence each other, and that inhibition of onereceptor negatively regulates the other (Guoet al. 2008). Another example is a direct interac-tion between c-Met and insulin receptors in he-patocytes, which facilitate optimal activationof downstream signaling pathways and glucosemetabolism (Fafalios et al. 2011).

Different cross talk mechanisms, in whichinhibition of one RTK leads to activation of theother RTK have also been observed and sug-gested to be one of the causes of chemoresistancein cancer patients (Jones et al. 2006; Xu andHuang 2010). In fact, a cocktail of inhibitorstargeting several RTKs, such as EGFR, c-Met,and PDGF has been shown to be more effectivethan a single drug treatment (Stommel et al.2007). RTK cross talk can also be mediated solelyby downstream signaling interactions withoutaffecting the receptors themselves. In this case,costimulation by two ligands, which often oc-curs in vivo, can lead to synergic or mutuallyinhibiting responses (Borisov et al. 2009; Martinet al. 2009).

When signals propagate through differentbranches converging at a common target, bothbranches can add to the overall response of thetarget (Kholodenko et al. 1997). Feedforwardand feedback loops embracing interacting RTKpathways make the input–output response rela-tionships of one pathway dependent on the ac-tivity of the other pathway, thereby creating con-text-dependent signaling output. A recent studyexplored how a concordant interplay betweenRTK pathways stimulated by EGF and insulincan potentiate signaling by the ERK/MAPK atphysiological, low EGF levels in HEK293 cells(Borisov et al. 2009). Although the EGFR and IRnetworks share many downstream components,their responses to cognate stimuli are different.In HEK293 cells, EGF causes strong ERK acti-vation, whereas insulin poorly activates ERK.The main insulin function is metabolic, includ-ing the control of glucose metabolism, andstimulation of protein and lipid syntheses. Us-ing a combined experimental and computa-

Receptor Tyrosine Kinase Signal Processing

Cite this article as Cold Spring Harb Perspect Biol 2013;5:a009043 3



tional analysis, it was shown that at low physi-ological concentration of EGF, cross talk be-tween the EGFR and IR networks converts theinsulin-induced increase in the PIP3 concentra-tion into enhanced ERK activation, whereas atsaturating EGF levels the insulin effect becomesinsignificant (Borisov et al. 2009).

The data and computational modeling re-sults suggest that major cross talk mechanismsthat amplify ERK signaling by insulin are local-ized upstream of Ras and at the Ras/Raf level(Borisov et al. 2009). Among the variety of crosstalk interactions affecting multiple Ras activa-tion and inactivation routes, five key networknodes are shown to be crucial for the EGF-insulin synergy. These nodes involve the adap-tor proteins, Grb2-associated binder-1 (GAB1)and insulin receptor substrates (IRS), PI3K/PIP3 node, soluble tyrosine kinase Src, and theSH2-domain containing protein tyrosine phos-phatase-2 (SHP2) that is located upstream ofthe ERK kinase MEK. The computational mod-el reveals key features of the EGFR and IR net-work signal processing brought about by: (1)coincidence detection of EGF and insulin stim-uli through GAB1 phosphorylation response,(2) coherent feedforward loop from EGFR toRaf via Src (this is a network motif in whichan initial signal induces an intermediate input,and both the initial and intermediate inputs areneeded to generate the final output [Mangan

et al. 2003], see also below), and (3) multiplepositive (PI3K!PIP3!GAB1!PI3K) and neg-ative (ERK s GAB1, ERK s Son of Sevenless(SOS), mammalian target of rapamycin(mTOR) s IRS) feedback loops. The simplifiedscheme, shown in Figure 1, illustrates how insu-lin enhances EGF-induced mitogenesis throughtwo partially redundant and compensating sig-naling branches via IRS and GAB1.

Receptor cross activation can also be medi-ated via transcriptional induction of an RTK (orits ligands) by another RTK (Jones et al. 2006;Esposito et al. 2008; Gujral et al. 2012; Velpulaet al. 2012). For instance, in neuroblastoma-de-rived cell lines retinoic acid induces activation ofthe RTK Ret, leading to cell differentiation, asindicated by morphological changes and ex-pression of several differentiation markers. Sev-eral studies suggested that TrkB (another RTKand indicator of poor prognosis for neuro-blastoma tumors) can link retinoic acid stim-ulation and the phenotype change. Ret activa-tion induces expression of both TrkB and itsprimary ligand brain-derived neurotrophic fac-tor (BDNF) (Kaplan et al. 1993; Esposito et al.2008). Moreover, TrkB knockdown prevents celldifferentiation (Esposito et al. 2008). “Reverse”cross talk, in which TrkA and TrkB receptors in-duce activation of Ret, was also observed (Tsui-Pierchala et al. 2002; Esposito et al. 2008). Al-though in this case positive regulation of Ret

Ras

ERK

PIP3-pGAB1

PIP3-IRS

PIP3-pIRS

Alternative pathways via IRS/Grb2-SOS/SHP2

PIP3-GAB1GAB1

IR

WT

WT

IRS EGFR

Coincidencedetectionby GAB1

Src

SHP2 Grb2-SOS

Figure 1. Mechanisms of insulin-EGF signal integration. Synergistic ERK activation arises from coincidencedetection of insulin and EGF stimuli at the level of GAB1 adaptor protein. GAB1 is massively recruited to themembrane by IR signaling (GAB1!PIP3-GAB1) and subsequently phosphorylated by EGFR and activatedSrc (PIP3-GAB1!PIP3-pGAB1). (Modified from Borisov et al. 2009; reprinted, with permission, from theauthors.)





does not involve transcriptional regulation (Es-posito et al. 2008), TrkB!Ret!TrkB positivefeedback may lead to emerging systems proper-ties, such as bistability (see section below “In-tricate RTK Network Dynamics Are Broughtabout by Feedback Loops”).

In a recent study (Gujral et al. 2012), breastcancer samples were subjected to “reverse-phase” protein microarrays (Sevecka and Mac-Beath 2006) and phosphorylation or total pro-tein levels of multiple signaling molecules weretested. The resulted data were analyzed by unsu-pervised hierarchical clustering (Herrero et al.2001), revealing 12 major clusters of correlatingproteins. Interestingly, c-Met RTK phosphory-lated on Tyr1349 was clustered together withthe total protein level of Axl, which is a struc-turally independent RTK. This finding wasfurther experimentally validated; siRNA-medi-ated c-Met targeting resulted in a significant de-crease of Axl mRNA levels. These receptors werealso shown to interact on a protein level, c-Metstimulation with hepatocyte growth factor-in-duced activation of Axl. Moreover, both recep-tors physically interacted with each other, atleast when ectopically expressed. Surprisingly,

Axl down-regulation or stimulation did not af-fect c-Met function on any level, suggestingcomplex interplay of these two RTKs (Gujralet al. 2012).

Additional levels of complexity, which wedo not discuss here, involve cross talk betweenRTKs and other receptors, such as G-protein-coupled receptors, adhesion molecules, and nu-clear receptors.

RTK NETWORKS ARE TIGHTLYCONTROLLED BY FEEDBACK ANDFEEDFORWARD LOOPS

Coherent and Incoherent Feedforward Loops

A useful approach toward understanding ofsignaling and transcriptional networks is theanalysis of so-called network motifs (Milo et al.2002). In addition to the simplest linear sig-naling design in which the initial signal A reg-ulates the intermediate output B, and B regu-lates the output C, signaling networks containmore complicated motifs including feedforwardloops (FFL) where A regulates B, while A and Bjointly regulate C (Fig. 2) (Mangan and Alon

A

B

C

AND

A

A B C D

B

C

AND AND

AND

AND

c-fos mRNAc-fos mRNA

pRSK ZFP36

EGFRppERK

pc-Fos

Figure 2. Coherent and incoherent feedforward motifs. (A) Basic structure of coherent feed forward loop(coherent FFL [Mangan and Alon 2003]). (B) Schematic representation of ERK-induced c-Fos expressionand activation that includes a cascade of coherent FFLs. Active ERK (ppERK) and RSK (pRSK) activatetranscription factors required for c-Fos expression and therefore, c-fos mRNA expression. ERK and RSK stabilizeand activate the nascent c-Fos protein by phosphorylation making an additional AND gate (based on data fromNakakuki et al. 2010). (C) Basic structure of incoherent feed forward loop of type I (incoherent FFL [Manganand Alon 2003]). (D) Schematic representation of EGFR regulated c-fos mRNA availability in terms of inco-herent FFL. On stimulation, EGFR induces expression of c-fos (B). ZFP36 is also induced by EGFR and mediatesc-fos RNA degradation. (Based on data from Avraham and Yarden 2011.)





2003; Shoval and Alon 2010). In physiologicalsystems, FFL motifs may be combined into larg-er integrated structures, leading to complex sig-naling and transcriptional circuits (Shoval andAlon 2010).

In coherent FFLs, the initial input A activatesthe intermediate output B, while A and B formthe logical gates “AND” or “OR,” thereby pro-viding different regulation of the outcome C.This final outcome can be a downstream effectoror process, such as gene promoter or proteinactivation, that is responsive to two inputs, inwhich only one or both inputs are required inOR or AND gates, respectively. For an AND gate,increasing time delays related to accumulationof B may be required to activate C, and con-sequently, an AND motif shows delayed “ON”and immediate “OFF” responses (Mangan andAlon 2003). An OR gate motif is characterized byimmediate ON and delayed OFF responses(Shoval and Alon 2010). Interestingly, an ANDcoherent FFL motif distinguishes between tran-sient and sustained signals. This regulatory mo-tif is found in the networks stimulated by twodifferent RTK ligands, EGF and platelet-derivedgrowth factor (PDGF), which induce transientand sustained ERK activation, respectively(Murphyet al. 2002, 2004). Expression of severalIEGs, including c-fos, is induced by active ERKand its downstream effector, the p90 ribosomalS6 kinase (RSK). However, the nascent c-Fosprotein is unstable, and phosphorylation byERK and RSK is required for its stabilizationand activation. If ERK and RSK signals are tran-sient, there will be no appreciable kinase activityat the time when the c-Fos protein is de novosynthesized. Thus, c-Fos will not be phosphory-lated, and will be rapidly degraded. Therefore,only sustained ERK and RSK signaling can allowfor a strong c-Fos induction (Fig. 2B) (Murphyet al. 2002, 2004; Nakakuki et al. 2010). Thismechanism of discrimination between transientand sustained ERK activity at the IEG level iscommon for different RTKs and cell types andmay lead to distinct cell-fate decisions, such asproliferation or tumorigenicity (Nakakuki et al.2010).

Incoherent FFLs where A activates C, butalso activates B, which is the repressor of C, is

another common motif in network regulation(Fig. 2C). In case of an AND gate, both the pres-ence of an activator A and the lack of a repressorB are required for obtaining the outcome C. Forinstance, if two independent elements on a pro-moter bind an activator A and a repressor B,appreciable transcriptional response will onlybe observed when A is bound and B is absent(Mangan and Alon 2003). Depending on pa-rameters, this motif can endow the system withnoise filtering and adaptation (Goentoro et al.2009; Ma et al. 2009). The repressor B serves as a“memory” element keeping trackof the previouslevels of the activator A, and the output C detectsfold-changes of A rather than the absolute Avalues (Goentoro et al. 2009; Ma et al. 2009).For instance, a sustained input will result inpeak-like transient response, followed by fullor partial adaptation, because of accumulatinglevels of the repressor (Ma et al. 2009).

An incoherent FFL in EGFR-mediated tran-scriptional circuits was recently described (Amitet al. 2007). EGFR induces expression of theZink Finger Protein 36 (ZFP36), which bindsto AU-rich elements, predominantly found inthe 30-untranslated regions (30-UTR) of unsta-ble mRNA molecules, and promotes their de-adenylation and subsequent degradation (Chenet al. 2001). A systematic analysis of EGF-in-duced genes revealed that many of these genescontain such 30-UTRelements, thus suggesting awidespread role of ZFP36 in IEG and DEG reg-ulation (Amit et al. 2007). Although ZFP36 doesnot affect gene transcription directly, it regulatesthe availability of multiple mRNA molecules,thereby forming an incoherent FFL (Fig. 2D)(Amit et al. 2007; Avraham and Yarden 2011).

Positive and Negative Feedback Regulation

The concept of feedback control goes back tothe ancient Greeks who used float regulators tokeep a constant level of water in a tank or oil in alamp (Sauro and Kholodenko 2004). In biolog-ical control systems, negative and positive feed-back loops are the most fundamental features.Positive feedback amplifies the signal, whereasnegative feedback attenuates it. RTK networktopologies involve comprehensive and intricate





regulatory structures of immediate and delayedfeedback loops (Fig. 3) (Kiyatkin et al. 2006;Amit et al. 2007; Gotoh 2009; Lemmon andSchlessinger 2010; Sturm et al. 2010; Avrahamand Yarden 2011; Segatto et al. 2011).

Positive and Negative Feedbacks at theReceptor Level

In RTK pathways, both the receptor abundanceand ligand availability are tightly controlled by

positive and negative feedback loops. For in-stance, RTK ubiquitination by the E3 ubiquitinligase Cbl and subsequent degradation of thereceptor in lysosomes creates negative feedbackat the receptor level. Cbl is recruited to the phos-phorylated receptor either directly or via theGrb2 adaptor and is further phosphorylatedby RTK or c-Src to become activated (Zwangand Yarden 2009). Positive feedback can be me-diated by reactive oxygen species, which are pro-duced in response to RTK activation and inhibit

Cbl

MiG-6

Cbl

LRIG

1

SOSRas Raf

MEK

ERK

RKIP

DUSP

Plasma membrane

Ligand-bound EGFR

Cytoplasm

Nucleus

SRE

Elk-1MafF

Elk-1

SRF

SRF

ERK

DUSP

Myc

Egr-1Jun

Fos

ZFP36

Grb2

Figure 3. Simplified scheme presenting multiple feedback loops in the EGFR pathway. Upon EGFR ligation andactivation, protein complexes nucleated by scaffolds are formed at the plasma membrane. Activated Ras inducesactivation of the Raf-MEK-ERK signaling cascade. Active ERK phosphorylates several upstream signalingregulators, including Raf and SOS, forming negative feedback loops. However, ERK also phosphorylates andinhibits RKIP, which is a negative regulator of Raf, thus creating positive feedback. Active ERK translocates to thenucleus where it phosphorylates several transcription factors, inducing transcription of several IEGs that arenegative regulators of EGFR signaling. DUSPs are rapidly induced upon ERK activation, and some DUSPs alsorequire phosphorylation by ERK to become fully active in order to dephosphorylate ERK. Another inducibleinhibitor of EGFR, Mig-6, inhibits EGFR by blocking its kinase activity and mediating ubiquitin-independentdegradation of EGFR. Several transcription factors induced by EGFR, such as MafF, inhibit transcription ofgenes that contain SRE in the promoter. Additional mechanism of negative regulation is mediated by ZFP36 thatbinds to the AU-rich 30-UTR of mRNA molecules, such as c-fos mRNA and other IEG, targeting them fordegradation. Dashed arrows represent indirect or unknown regulation; blue arrows represent mechanismsinvolving transports between the cytoplasmic and nuclear compartments.





protein tyrosine phosphatases (PTPs) that inac-tivate RTKs. Internalization of active RTKs intoendosomes also creates feedback loops, whichserve as both positive and negative regulators(Kholodenko 2002; Wiley 2003; Polo and DiFiore 2006; Sorkin and von Zastrow 2009).

One of downstream targets of RTKs is theADAM (a disintegrin and metalloproteinase)family of proteases responsible for sheddingand release of growth factors such as heparin-binding EGF (Hynes and Schlange 2006; Zhouet al. 2006; Mendelson et al. 2010; Maretzky et al.2011a,b; Rao et al. 2011). A recent study of headand neck squamous cell carcinoma cell lines hasshown that ErbB2 and EGFR mediate ADAM12protease expression in a PI3K and mTORC1dependent manner (Rao et al. 2011). In turn,ADAM12 positively regulates ErbB2 expression,thus forming a positive feedback loop. ActivatedADAM proteins are also associated with recep-tor cross talk. Ligands such as vascular endothe-lial growth factor (VEGF) and fibroblast growthfactor (FGF) induce ERK1/2 activation andcell migration as a result of EGFR stimulationby heparin-binding EGF, which is released inADAM-dependent manner (Maretzky et al.2011a).

Positive and Negative Feedbacks at theSignaling Level

ERK, which is the terminal kinase in the three-layered MAPK/ERK cascade, phosphorylatesmultiple signaling molecules and transcriptionfactors (Yoon and Seger 2006; von Kriegsheimet al. 2009; Yang et al. 2013). An example of ERK-mediated negative feedback is the phosphoryla-tion of the guanine nucleotide exchange factorSOS. Upon RTK activation, the SOS-Grb2 com-plex is recruited to the plasma membrane whereSOS mediates Ras activation. SOS phosphoryla-tion by ERK or by its downstream kinase RSK-2leads to dissociation of the SOS–Grb2 complex,thereby terminating Ras activation (Langloiset al. 1995; Dong et al. 1996; Douville andDownward 1997).

Raf kinase inhibitor protein (RKIP) is anendogenous inhibitor of the ERK pathway. Bybinding both Raf-1 and MEK, RKIP prevents

their physical interaction and MEK phosphor-ylation (Yeung et al. 1999, 2000). Activated ERKforms a positive feedback loop by phosphory-lating RKIP and inhibiting its interaction withRaf-1. This positive feedback loop is imbeddedinto a long negative feedback loop from ERK toSOS and contributes to oscillations in ERK ac-tivity (Shin et al. 2009).

Disruption of RTK-mediated signalingcomplexes assembled on scaffolds is a commonmechanism of negative feedback. For instance,following IR or IGF-1R-mediated phosphoryla-tion of numerous tyrosine residues on the IRSscaffold proteins, these scaffolds become capa-ble of recruiting multiple signaling complexes,including PI3K (Schmitz-Peiffer and White-head 2003; Boura-Halfon and Zick 2009). Thisfacilitates PI3K activation, production of PIP3

and activation of the PI3K/AKT/mTOR cas-cade. Subsequent phosphorylation of IRS onserine residues by downstream kinases, such asmTOR, its effector S6K1, and MAPKs, disruptsthe signaling complexes assembled on IRS anddown-regulates the PI3K pathway (Gual et al.2005; Boura-Halfon and Zick 2009).

Feedback Loops via Transcription

RTK signaling induces transcriptional activa-tion of multiple IEGs and DEGs, which, inturn, creates multiple positive and negative feed-back loops (Avraham and Yarden 2011). Severalinduced proteins, including Mig-6/RALT andthe leucine-rich repeats and immunoglobu-lin-like domains protein 1 (LRIG1), generatefeedback by acting on the receptor. The trans-membrane protein LRIG1 is expressed severalhours after the onset of EGFR stimulation.While LRIG1 interacts with EGFR via the extra-cellular domain, the intracellular domain ofLRIG1 recruits Cbl, thereby providing addition-al mechanism of Cbl-mediated EGFR degrada-tion (Segatto et al. 2011). Whereas Cbl activa-tion depends on EGFR activity, LRIG1 reducesthe number of surface EGFR molecules both inbasal conditions and upon stimulation, suggest-ing additional mechanisms of EGFR down-reg-ulation (Segatto et al. 2011). Mig-6/RALT is ex-pressed within an hour after EGFR activation





and binds the kinase domain of all ErbB recep-tors in a ligand-dependent manner, suppressingtheir catalytic activities (Gotoh 2009; Segattoet al. 2011). Mig-6 targets EGFR to lysosomesand mediates EGFR degradation independentlyof receptor phosphorylation or ubiquitination,thus showing the second mechanism of negativeregulation (Segatto et al. 2011). The Mig-6 pro-tein also contains a Cdc42/Rac interaction andbinding (CRIB) domain that selectively binds anactive form of the small G protein Cdc42, whichis an important regulator of cell migration.Indeed, by sequestering Cdc42, Mig-6 inhibitshepatocyte growth factor (HGF)-induced cellmigration (Gotoh 2009).

DUSP proteins dephosphorylate and inac-tivate MAPKs. Different DUSPs have differentpreferred MAPK substrates and distinct intra-cellular localization. Also, often MAPK bindingselectively facilitates DUSP activation. For in-stance, binding of ERK but not JNK or p38MAPKs is required for catalytic activation ofthe cytoplasmic DUSP6 (Camps et al. 1998).The class I DUSPs (1/2/4/5) are inducible nu-clear phosphatases, whose expression can be de-tected within an hour after activation of theErbB receptors (Owens and Keyse 2007; Naka-kuki et al. 2010). A recent study found transientERK activity in the nucleus, whereas ERK ac-tivity in the cytoplasm was sustained. These dif-ferent ERK kinetics in the cytoplasm and thenucleus were explained by inducible expressionof several nuclear DUSPs since simultaneousknockdown of these phosphatases substantiallyprolonged ERK activation in the nucleus (Na-kakuki et al. 2010).

Sprouty, whose expression is also inducedby RTKs, is another regulator of upstream sig-naling. De novo synthesized Sprouty translo-cates to the plasma membrane where it is phos-phorylated by the Src family kinases (Masonet al. 2006; Edwin et al. 2009). This phosphor-ylation (at Tyr55 for the Sprouty2 sequence)induces a conformational change that allowsSprouty to bind Grb2, disrupting the Grb2–SOS complex and leading to inhibition of Rasactivation. The same phosphorylation at Tyr55triggers Sprouty–Cbl interaction that sequestersCbl from RTK, thereby preventing RTK degra-

dation. Because of this dual role in RTK regula-tion, Sprouty acts as an RTK signaling modula-tor rather than inhibitor (Edwin et al. 2009).

Additional example of positive feedback reg-ulation was observed in breast tumor initiat-ing cells (Aceto et al. 2012). Src-homology 2domain-containing phosphatase 2 (SHP2) canact as tumor promoter by facilitating RTK-in-duced mitogenic signaling (Ostman et al. 2006).In a recent study SHP2 was shown to activatetranscription factors ZEB1 and c-Myc. WhereasZEB1 drives epithelial-to-mesenchymal transi-tion (EMT) (Schmalhofer et al. 2009), c-mycinduces expression of lin-28 homolog B, a re-pressor of microRNA biogenesis (Chang et al.2009). This leads to let-7 microRNA repressionand, therefore, results in overexpression of let-7targets, including Ras and c-Myc itself (Acetoet al. 2012). Thus, SHP2-mediated positivefeedback loop is required for maintenance andinvasiveness of breast tumors (Aceto et al.2012). Importantly, this is only one example ofmany in which microRNA molecules takepart in signaling and transcriptional regulationdownstream to RTKs (Avraham and Yarden2012).

Feedback Loops Operating withinTranscriptional Circuits

Additional mechanisms of positive or negativeregulation involve de novo expression of pro-teins that affect mainly transcriptional eventsrather than upstream signaling. The first waveof the EGFR-induced transcriptional response(IEGs; immediate early genes) contains predom-inantly transcriptional activators; the second,delayed response wave (DEGs), involves multi-ple inhibitors of gene transcription that act atdifferent levels (Amit et al. 2007). For instance,the proteins MafF and Kruppel-like factor 2(KLF2) induced by RTKs (Amit et al. 2007; Dijk-mans et al. 2009; Dutta et al. 2011) are negativeregulators of several promoter elements, includ-ing the serum response element (SRE) (Amitet al. 2007). SRE is found within promoters ofmultiple IEG, such as transcription factors c-fosand egr-1, and a negative signaling regulatorDUSP6 (Christy and Nathans 1989; Rivera et al.





1990; Treisman 1995; Bluthgen et al. 2009). Al-though the molecular mechanism of MafF- andKLF2-mediated transcriptional inhibition is un-known, the diversity of SRE containing genesclearly indicates that this regulation might haveboth positive and negative impact on signalingand transcriptional events.

Feedback mediated by posttranslationalmodifications develops on the scale of min-utes, whereas feedback generated by de novo ex-pressed proteins is much slower and operates ona longer timescale ranging from 30 min to sev-eral hours and more. The delayed negative feed-back mechanisms may prevent permanent acti-vation by continuous or recurrent signals, if denovo expressed proteins are present in the sys-tem for a prolonged time. In this case, a refrac-tory period when cells are not responsive tostimuli is often observed. The refractory mech-anism might be necessary for preventing contin-uous proliferation of cells exposed to multiplepulses of growth factors.

INTRICATE RTK NETWORK DYNAMICSARE BROUGHT ABOUT BY FEEDBACKLOOPS: BISTABILITY, OSCILLATIONS,AND EXCITABILITY

Immediate and delayed feedback loops not onlychange steady-state input–output responses,but they also bring about dynamic instabilities.When a steady state becomes unstable, a systemcan jump to another stable state, start to oscil-late, or show chaotic behavior. For instance, sig-nals downstream of RTKs are often amplified bypositive feedback, but if the feedback is suffi-ciently strong and a part of the pathway withinthe feedback shows ultrasensitive behavior withrespect to the input signal, this system can be-come bistable (Ferrell 1999). A bistable systemcan switch between two distinct stable steadystates, but cannot rest in intermediate states.Because of the coexistence of two alternativestates, a bistable system displays hysteresis, mean-ing that the stimulus needs to exceed a thresholdvalue to flip the system to another steady state atwhich it may remain when the stimulus returnsto its initial value. In fact, hysteresis and bistabil-ity in MAPK cascades brought about by positive

feedback loops have been suggested to contrib-ute to cell differentiation and long-term synap-tic potentiation (Santos et al. 2007; Smolenet al. 2008). In addition, positive feedback eitheralone or in combination with negative feed-back can trigger oscillations. Such positive–negative feedback oscillations generally do nothave sinusoidal shapes and operate in a pulsa-tory manner: A part of a dynamic system is bi-stable, and there is a slow process induced bynegative feedback that periodically forces thesystem to jump between “Off” and “On” states,generating oscillations (Pomerening et al. 2003;Sha et al. 2003).

Negative feedback in the MAPK/ERK cas-cade endows robustness to variations of param-eters within the feedback loop and stabilizes theactive ERK concentration when demand foractive ERK fluctuates (Sauro and Kholodenko2004). Using a combination of modeling andvalidating experiments, it was shown that theintegration of a three-tier MAPK cascade struc-ture with negative feedback generates emergentsystems properties that resemble the features of anegative feedback amplifier (NFA), known fromengineering (Sturm et al. 2010). These proper-ties have decisive effects on the MAPK cascadedrug sensitivity and adaptation to perturba-tions. In particular, the active ERK concentra-tion was shown to be stabilized in response todrug-induced perturbations of the upstreamERK kinase, MEK (Sturm et al. 2010). Yet, abovea certain threshold strength, negative feedbackcan induce damped or sustained oscillations inthe system. These oscillations are caused by thetime delay within the negative feedback loopand also require some degree of ultrasensitivitywithin the cascade (Kholodenko 2000). In fact,oscillations in the MAPK/ERK pathway wererecently discovered experimentally, confirmingprevious theoretical predictions (Nakayamaet al. 2008; Shankaran et al. 2009; Shin et al.2009; Hu et al. 2013). An intriguing systemsproperty of protein modification cascades andeven simpler signaling systems is excitable andovershoot signaling responses to transient stim-uli (Kaimachnikov and Kholodenko 2009). Inthis case, the entire RTK pathway behaves asan excitable device with a built-in excitability





threshold. Depending on the magnitude andduration of a transient stimulus, activation re-sponses of key kinases and/or small GTPases fitinto one of two distinct classes of either low orhigh amplitude responses, whereas there are nointermediate responses, merely proportional tothe stimulus. For instance, the excitable behav-ior of small GTPases such as Rac or Rho, whichdoes not respond to under-threshold stimuli,but yields high-activity pulses in response toover-threshold stimuli, can precisely controlcell movement (Ridley 2001; Tsyganov et al.2012).

A fundamental question is how cell-to-cellvariability affects the RTK network functionand dynamics. In any cell, transcription andtranslation are inherently stochastic and giverise to large cell-to-cell variability in proteinlevels observed even in genetically identicalcells, such as clonal cell populations (McAdamsand Arkin 1997; Spencer et al. 2009). Theoret-ical findings suggest that nonlinear signal pro-cessing by signaling networks always broadensthe distribution of cellular responses to any sig-nal, perturbation, or drug. Although bimodaldistributions of cellular responses to input sig-nal are generally thought to manifest bistable orultrasensitive behavior in single cells, it has beenshown recently that such bimodal responses canoccur as a result of the protein abundance var-iability (Birtwistle et al. 2012; Kim and Sauro2012). In particular, experiments and computersimulations show that a simple MAPK/ERK-cascade model with negative feedback that dis-plays graded, analog ERK responses at a singlecell level may show bimodal responses to EGF atthe cell population level (Birtwistle et al. 2012).These results show that bimodal signaling re-sponse distributions do not necessarily implydigital (ultrasensitive or bistable) single cell sig-naling. The interplay between protein expres-sion noise and network topologies can bringabout digital population responses from ana-log single-cell dose responses. Thus, cells canretain the benefits of robustness arising fromnegative feedback, while simultaneously gener-ating population-level on/off responses that arethought to be critical for regulating cell-fate de-cisions.

The extremely rich repertoire of different dy-namic behaviors allow RTK signaling pathwaysto serve as analog-to-digital converters, trans-forming a transient or sustained growth factoractivation into distinct responses, such as all-or-none, oscillatory, and pulsatory responses.Subsequent deconvolution of these different re-sponses by the transcriptional machinery canbe translated into different cell-fate decisions(Murphy et al. 2004; Kholodenko et al. 2010;Nakakuki et al. 2010).

SPATIAL SIGNAL PROPAGATION

Imaging data and computational models sug-gest that the propagation of RTK signalingfrom the plasma membrane to targets in thenucleus is tightly controlled by a variety of reg-ulatory mechanisms (Kholodenko et al. 2010;Vartak and Bastiaens 2010; Grecco et al. 2011;Alam-Nazki and Krishnan 2012). RTK signalingpathways are highly spatially organized withincells. Activator enzymes, such as kinases or gua-nine nucleotide exchange factors (GEFs), andinactivating enzymes (e.g., phosphatases andGTPase-activating proteins [GAPs]) often lo-calize to different cellular locales (Kholodenko2009). For a protein phosphorylated by a mem-brane-bound kinase and dephosphorylated bya cytosolic phosphatase, it was predicted thatthere can be a gradient of the phosphorylatedform, which is high close to the membrane andlow within the cell (Brown and Kholodenko1999). Instructively, the shape of the gradientdepends mainly on the phosphatase activity. Ifthe phosphatase is not saturated, the concentra-tion profile of the active, phosphorylated formof the target protein decays almost exponential-ly with the distance from the membrane. Suchexponential decrease in the activity of G pro-teins can also be observed if GEF activity is as-sociated with a cellular structure, such as chro-matin, and when GAP activity is excluded fromthis structure (Kholodenko 2006). Spatial gra-dients of protein activities organize signalingaround cellular structures, such as membranes,chromosomes and scaffolds, and provide posi-tional cues for key processes, including cell di-vision. Such intracellular gradients of protein





activities have been detected in live cells usingimaging technologies based on fluorescence res-onance energy (Maeder et al. 2007).

Raf-1, the initial kinase in the MAPK/ERKcascade is activated near the plasma membranewhere activated downstream of RTKs, the smallGTPase Ras resides. How can the phosphoryla-tion signal that was initiated at the plasma mem-brane propagate through the cytoplasm where itis terminated by phosphatases? Central mecha-nisms of spatial signal propagation have beensuggested. First, a kinase cascade can be assem-bled on a scaffold protein that protects trans-mission of phosphorylation against phospha-tase activity. Second, even for a soluble cascadeof (de)phosphorylation cycles, the phosphory-lation signal reaches further into the cell interi-or, when the cascade has more levels, and thismight be one of the reasons that cascades exist(Munoz-Garcia et al. 2009). Third, kinesin mo-tor-mediated movement of the endosomes andkinase complexes along microtubules can trans-fer phosphorylation signals, guarding againstdephosphorylation (Kholodenko 2002; Perlsonet al. 2005, 2006). Finally, and most intriguingly,it was suggested that RTK signals can propagateas nonlinear traveling waves that create globalspatial switches or pulses of kinase and GTPase(in)activation (Munoz-Garcia and Kholodenko2010). These mechanisms facilitate signal prop-agation from activated RTKs across single cells.

CONCLUDING REMARKS AND FUTUREDIRECTIONS

Versatility and diversity of RTKs and their mal-functioning in major pathological conditionshave made RTK signaling a focus point of ex-tensive genetic and biochemical studies. Recentchanges in our perception of RTK signalingpathways from linear pipelines to combinatorialcomplex interaction networks have highlightedthe need for novel conceptual and technologicalapproaches to move forward our comprehen-sion of cell signaling by RTKs. An ever-growingcontribution of mathematical models helps usunderstand RTK signaling in a cell as an inte-grated system rather than a list of proteins andgenes.

Signaling from different RTKs leads to dis-tinct cellular outcomes, yet these signals aretransmitted through the overlapping cascadesof common signal transducers. As described inthis review, we have begun to realize that sig-nal specificity is generated by a multiplicity offeedforward and feedback loops, combinatorialprotein assemblies and their spatiotemporal dy-namics rather than by a large number of geneswith specific functions. However, many ques-tions remain open. For instance, how is specif-icity maintained, if activation of one RTK re-sults in cross talks with many other RTKs? Wecan speculate that whereas activation of a “pri-mary” RTK occurs almost immediately follow-ing the ligand binding, the activation of “sec-ondary” receptors is delayed. This time delay,combined with multiple negative feedbacksthat are initiated by “primary” receptor, is ex-pected to have a negative impact on the ampli-tude and duration of signals induced by the“secondary” receptor. Therefore, in a physiolog-ic system that contains intact feedbacks, second-ary activation is expected to serve only for fine-tuning of the responses.

Additional complexity arises from multipleprotein isoforms that can contribute to bothsignaling specificity and redundancy. For in-stance, the growing body of evidence suggeststhat ERK1 and ERK2 might also have isoformspecific, nonredundant functions in prolifera-tion, differentiation, and EMT (Li and Johnson2006; Vantaggiato et al. 2006; Shin et al. 2010).Future research will elaborate how different pro-tein isoforms, such as the phosphatase SHP1versus SHP2 or distinct isoforms of the scaffoldsIRS and GAB, contribute to specific signalingresponses and, thereby, to specific cellular phe-notypes.

A feature of RTK networks highlighted hereis the coexistence of multiple mechanisms thatoften play similar regulatory roles. For instance,negative feedback loops from ERK to SOS andfrom ERK to Raf-1 and EGFR degradation areredundant because each of these processes issufficient for signal termination (Orton et al.2008). In fact, mathematical models show thatthe system control is always distributed overmultiple processes (von Kriegsheim et al. 2009).





This high degree of redundancy is expected tomake the system robust toward a multitude ofperturbations. Although system robustness isimportant for cell survival, it also makes cancercells resistant to multiple drug treatments. Thisis the place where systems approach can be help-ful in predicting the fragility points of patholog-ical RTK networks to be exploited by combina-torial drug therapies.

ACKNOWLEDGMENTS

We thank David Croucher and Walter Kolch fordiscussions and critical reading of the manu-script. This work is supported by Science Foun-dation Ireland under grant No. 06/CE/B1129.We apologize that we could not cite many per-tinent contributions to the field because ofspace limitations.

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2013; doi: 10.1101/cshperspect.a009043Cold Spring Harb Perspect Biol Natalia Volinsky and Boris N. Kholodenko Complexity of Receptor Tyrosine Kinase Signal Processing

Subject Collection Signaling by Receptor Tyrosine Kinases

CSF-1 Receptor Signaling in Myeloid CellsE. Richard Stanley and Violeta Chitu

The Genesis of Tyrosine PhosphorylationTony Hunter

Tyrosine KinasesThe EGFR Family: Not So Prototypical Receptor

Kathryn M. FergusonMark A. Lemmon, Joseph Schlessinger and

the Plasma Membrane of Living CellsStructure-Function Relationships of ErbB RTKs in

Thomas M. JovinDonna J. Arndt-Jovin, Michelle G. Botelho and

and SignalingTie2 and Eph Receptor Tyrosine Kinase Activation

Seegar, et al.William A. Barton, Annamarie C. Dalton, Tom C.M.

Two DecadesReceptor Tyrosine Kinases: Legacy of the First

Joseph Schlessinger

Receptors: Insights from MicroscopyThe Spatiotemporal Organization of ErbB

LidkeChristopher C. Valley, Keith A. Lidke and Diane S.

Kinases in Wnt Signal TransductionThe Role of Ryk and Ror Receptor Tyrosine

AmerongenJennifer Green, Roel Nusse and Renée van

Insulin-Resistant StatesInsulin Receptor Signaling in Normal and

Ronald KahnJérémie Boucher, André Kleinridders and C.

ProcessingRegulation of Receptor Tyrosine Kinase Ligand

Colin Adrain and Matthew Freeman

Central Role of RET in Thyroid CancerMassimo Santoro and Francesca Carlomagno

Tyrosine Kinase SignalingPTB-Domain-Containing Proteins in Receptor Molecular Mechanisms of SH2- and

Liu, et al.Melany J. Wagner, Melissa M. Stacey, Bernard A.

Receptor Tyrosine Kinase-Mediated Angiogenesis

Saharinen, et al.Michael Jeltsch, Veli-Matti Leppänen, Pipsa

Eph Receptor Signaling and Ephrins

PasqualeErika M. Lisabeth, Giulia Falivelli and Elena B.

Biology of the TAM ReceptorsGreg Lemke Receptor Tyrosine Kinases

Effects of Membrane Trafficking on Signaling by

Marta Miaczynska

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