1. Cell Biology
  2. Structural Biology and Molecular Biophysics

EGFR transactivates RON to drive oncogenic crosstalk

  1. Carolina Franco Nitta
  2. Ellen W Green
  3. Elton D Jhamba
  4. Justine M Keth
  5. Iraís Ortiz-Caraveo
  6. Rachel M Grattan
  7. David J Schodt
  8. Aubrey C Gibson
  9. Ashwani Rajput
  10. Keith A Lidke
  11. Bridget S Wilson
  12. Mara P Steinkamp
  13. Diane S Lidke  Is a corresponding author
  1. Department of Pathology, University of New Mexico, United States
  2. Department of Physics & Astronomy, University of New Mexico, United States
  3. Department of Surgery, University of New Mexico, United States
  4. Comprehensive Cancer Center, University of New Mexico, United States
https://doi.org/10.7554/eLife.63678
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Cite this article
  1. Carolina Franco Nitta
  2. Ellen W Green
  3. Elton D Jhamba
  4. Justine M Keth
  5. Iraís Ortiz-Caraveo
  6. Rachel M Grattan
  7. David J Schodt
  8. Aubrey C Gibson
  9. Ashwani Rajput
  10. Keith A Lidke
  11. Bridget S Wilson
  12. Mara P Steinkamp
  13. Diane S Lidke
(2021)
EGFR transactivates RON to drive oncogenic crosstalk
eLife 10:e63678.
https://doi.org/10.7554/eLife.63678
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Abstract

Crosstalk between different receptor tyrosine kinases (RTKs) is thought to drive oncogenic signaling and allow therapeutic escape. EGFR and RON are two such RTKs from different subfamilies, which engage in crosstalk through unknown mechanisms. We combined high-resolution imaging with biochemical and mutational studies to ask how EGFR and RON communicate. EGF stimulation promotes EGFR-dependent phosphorylation of RON, but ligand stimulation of RON does not trigger EGFR phosphorylation – arguing that crosstalk is unidirectional. Nanoscale imaging reveals association of EGFR and RON in common plasma membrane microdomains. Two-color single particle tracking captured formation of complexes between RON and EGF-bound EGFR. Our results further show that RON is a substrate for EGFR kinase, and that transactivation of RON requires formation of a signaling competent EGFR dimer. These results support a role for direct EGFR/RON interactions in propagating crosstalk, such that EGF-stimulated EGFR phosphorylates RON to activate RON-directed signaling.

Editor's evaluation

The study by Nitta et al., brings a sophisticated understanding of the mechanisms behind crosstalk between two mitogenic growth factor receptor tyrosine kinases – EGFR and RON. While earlier studies indicated that the receptors interact, this work provides evidence that the EGFR-RON crosstalk is unidirectional. They also show that this interaction takes place specifically at the membrane, rule out other intermediary molecules and locations between EGFR and RON. Consistent with this they find that, in vitro, RON acts as a substrate of the EGFR kinase domain. The study therefore identifies many mechanistic details about this particular interaction that could be relevant from a clinical standpoint to develop better drugs that can reduce the oncogenic potential of these receptors. From a fundamental biology standpoint, the study reveals novel mechanisms of signal transduction at the membrane.

https://doi.org/10.7554/eLife.63678.sa0

Introduction

There is growing evidence demonstrating that crosstalk between members of distinct receptor tyrosine kinase (RTK) subfamilies can drive tumorigenesis and therapeutic resistance. Understanding these complicated interactions is critical for the development of novel dual-targeting therapeutics to improve patient outcomes (Arteaga, 2007; Bardelli et al., 2013; Choudhary et al., 2016; Engelman et al., 2007; Follenzi et al., 2000; Hsu et al., 2006; Lai et al., 2009; Prahallad and Bernards, 2016). Here, we focus on the coordinated signaling between the Epidermal Growth Factor Receptor (EGFR, the canonical member of the EGFR/ErbB/HER subfamily) and Recepteur d’Origine Nantais (RON, also known as MST1R and a member of the MET subfamily). Prior evidence has implicated EGFR/RON crosstalk in the modulation of important cellular responses, notably migration and invasiveness in cancer (Keller et al., 2013; Maggiora et al., 2003; Yao et al., 2013). RON expression combined with EGFR correlates with poorer outcomes for cancer patients. In head and neck cancer, EGFR/RON co-expression is associated with decreased event-free survival, while in bladder cancer, co-expression correlates with increased tumor invasion, increased recurrence after first-line therapy, and decreased patient survival (Hsu et al., 2006; Keller et al., 2013). Direct interactions between RON and EGFR have been inferred from co-immunoprecipitation studies (Hsu et al., 2006; Peace et al., 2003), as well as observations that EGFR/RON complexes can translocate into the nucleus to act as transcription factors (Liu et al., 2010). These previous studies demonstrate EGFR/RON crosstalk, but do not provide details on the nature of the interaction between the receptors that can be used to understand mechanism.

Since the extracellular domains of EGFR and RON are so structurally distinct, it is difficult to explain their interactions through traditional dimerization models (Chao et al., 2012; Ogiso et al., 2002). For EGFR, ligand binding introduces structural rearrangements that promote dimerization and kinase activity. These include rotation of the extracellular domain exposing the dimerization arm to stabilize receptor dimers (Burgess et al., 2003; Chung et al., 2010; Freed et al., 2017; Low-Nam et al., 2011; Valley et al., 2015), dimerization of the transmembrane domains, formation of helical dimers between the juxtamembrane domains (Jura et al., 2009), and asymmetric orientation of the kinase domains that allows for allosteric activation (Zhang et al., 2006). While EGFR has been shown to form ligand-independent dimers, the shorter lived interactions and maintenance of the autoinhibitory mechanisms prevents these short-lived dimers from initiating signaling (Chung et al., 2010; Jura et al., 2009; Low-Nam et al., 2011; Valley et al., 2015; Yu et al., 2002). Although the mechanisms of RON activation and potential dimerization are not as well studied, crystallographic studies of the RON extracellular domain have suggested that RON homodimers can form in the absence of ligand (Chao et al., 2012).

Here, we combined high-resolution imaging with rigorous biochemical measurements to dissect the mechanisms underlying EGFR/RON crosstalk and to understand the nature of their interactions. We provide evidence of unidirectional crosstalk between EGFR and RON. Activation of EGFR by EGF leads to RON phosphorylation via direct phosphorylation of RON by EGFR’s integral kinase, which is then further enhanced by RON’s own catalytic activity. Importantly, EGFR activator or receiver mutants are incapable of promoting RON phosphorylation, demonstrating that RON cannot substitute for either partner of the EGFR asymmetric dimer. Taken together, our results support a molecular mechanism for crosstalk where RON, independent of its ligand MSP, acts as a co-receptor for EGF-bound EGFR dimers to promote RON activation and support RON-directed signaling outcomes.

Results

Generation of human cell lines co-expressing full-length RON and EGFR

We introduced full-length RON into two well-characterized human cell lines, A431 and HEK-293, to generate model systems. A431 squamous carcinoma cells have high levels of endogenous EGFR expression, and provide a model for tumors with high EGFR expression and modest levels of RON. HEK-293 human embryonic kidney cells have negligible levels of endogenous EGFR or RON, and provide a test bed for balanced expression of combinations of RON plus either wildtype or mutated forms of EGFR. The low levels of endogenous RON expression in these cell lines allowed us to stably express full-length HA-tagged RON (A431RON and HEKRON), while avoiding potential complications from endogenous alternatively spliced RON isoforms (Bardella et al., 2004; Chen et al., 2000; Collesi et al., 1996; Wang et al., 2000; Zhou et al., 2003). ACP-tagged EGFR was also stably introduced into HEKRON cells to generate a HEK-293 cell line expressing comparable levels of EGFR and RON (HEKRON/EGFR). Expression levels were evaluated by flow cytometry for both cell models. A431RON cells display ~2.2 million EGFR molecules and only ~92,000 RON receptors on the cell surface (~24:1 EGFR:RON ratio), whereas HEKRON/EGFR cells express EGFR and RON at a ratio of ~2:1 (~600,000 EGFR; ~275,000 RON).

Crosstalk between EGFR and RON is EGF-driven

We evaluated EGFR/RON crosstalk based on changes in receptor phosphorylation in response to each of their cognate ligands. EGF treatment led to the expected EGFR phosphorylation in both A431RON and HEKRON/EGFR cells (Figure 1A). MSP treatment induced RON phosphorylation in both cell lines (Figure 1B). Importantly, whereas MSP did not activate EGFR, treatment of cells with EGF promoted robust phosphorylation of RON (Figure 1A and B). This effect was dose-dependent and detectable at doses of EGF as low as 2 nM (Figure 1—figure supplement 1). In contrast, neither physiological levels (2–5 nM) nor high doses (50 nM) of MSP could induce EGFR phosphorylation at PY1068 or other EGFR phospho-tyrosine sites (Figure 1—figure supplements 2 and 3). This was the first indication that crosstalk is unidirectional in our two model systems, with crosstalk occurring from EGF-bound EGFR to RON but not from MSP-bound RON to EGFR. Note that our western blots resolved the mature RON (bottom RON band) from the pro-form (upper band; see Figure 1—figure supplement 4).

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Crosstalk between EGFR and RON is EGF-driven.

(A and B) HEKRON/EGFR or A431RON cells were treated with ± 5 nM MSP or 50 nM EGF for 5 min at 37 °C. Representative immunoblots showing PY1068 and EGFR on cell lysates (A) or pan-phosphotyrosine (PY) and RON on samples immunoprecipitated (IP) with anti-HA antibody (B). (C and D) A431RON cells were stimulated with ± 20 nM EGF, 20 nM MSP or both for 5 min at 37 °C and immunoblotted as in (A and B). Triplicate biological experiments are quantified in the bar graphs to the right, shown as mean ± SD. (E) Representative immunoblots of a phosphorylation time course for A431RON cells treated with 5 nM EGF or 5 nM MSP and immunoblotted as in (A and B). Graphed values (right) are from triplicate biological experiments, normalized to maximal activation, and presented as mean ± SD. * p < 0.05; ** p < 0.01.

Figure 1—source data 1

Full raw western blots and blots with relevant bands labeled, corresponding to Figure 1A, B, C, D and E.

https://cdn.elifesciences.org/articles/63678/elife-63678-fig1-data1-v2.zip
Figure 1—source data 2

Source data for quantification of blots in Figure 1C, D, and E.

https://cdn.elifesciences.org/articles/63678/elife-63678-fig1-data2-v2.xlsx

Dual stimulation with EGF and MSP did not increase EGFR phosphorylation beyond EGF alone (Figure 1C). However, combining EGF and MSP led to a synergistic enhancement in RON phosphorylation that is higher than expected from the additive effects of either ligand alone (Figure 1D). These results further support the conclusion that crosstalk occurs between full-length RON and EGFR, is unidirectional, and is EGF-driven. EGFR was often detected in RON immunoprecipitates, in both resting and stimulated cells, as a band co-migrating with pro-RON at 180 kDa via western blot analysis (using EGFR or EGFR-PY1068 antibodies) or identified by mass spectrometry, (Figure 1—figure supplement 1 and Supplementary file 1). Co-immunoprecipitation of RON and EGFR in unstimulated cells has been reported previously (Hsu et al., 2006; Peace et al., 2003). In contrast to that previous work, we do not observe an increase in co-precipitation with ligand stimulation. However, we note that co-IP was not always evident, suggesting weak interactions, and our experiments were performed at earlier time points (5 min) than the previous studies (30 min).

EGF induces similar phosphorylation kinetics for EGFR and RON

We next evaluated the early phosphorylation kinetics of RON and EGFR in response to physiological levels of ligand, either 5 nM MSP or 5 nM EGF. EGF-induced EGFR-PY1068 phosphorylation was rapid, peaking by 1 min (Figure 1E; top left blot and green line), as previously demonstrated (Hsieh et al., 2010; Kovacs et al., 2015a). RON phosphorylation after EGF treatment was similarly rapid, again reaching maximum phosphorylation levels by 1–2 min (Figure 1E; bottom left blot and blue line). In contrast, RON phosphorylation in response to MSP was slower, peaking at 2 min or later (Figure 1E; right blot and magenta line). The faster kinetics of EGF-driven RON phosphorylation when compared to MSP-driven RON phosphorylation may be a result of the higher affinity of EGF for EGFR (Kauder et al., 2013; Lemmon, 2009). However, the closely aligned EGF-induced EGFR and RON phosphorylation kinetics led us to postulate that RON is a substrate and co-receptor for the EGF-activated EGFR kinase.

RON and EGFR co-cluster in plasma membrane nanodomains

Considering the rapid (< 5 min) time scale of crosstalk, we considered that EGF-induced phosphorylation of RON must be occurring at the plasma membrane. Given that we found crosstalk to be EGF-dependent, we focused on comparing receptor distributions in resting and EGF-stimulated cells. As a first step, we confirmed that RON and EGFR have similar distributions on the plasma membrane of HEKRON/EGFR (Figure 2A) and A431RON cells (Figure 2—figure supplement 1) using confocal microscopy.

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RON and EGFR co-cluster in plasma membrane nanodomains.

(A) HEKRON/EGFR cells were first labeled for RON using ⍺-HA-FITC Fab fragment (green), treated with 10 nM EGF-AF647 (magenta) for 5 min on ice and then fixed. Representative images from three biological replicates show colocalization of RON and EGFR at the plasma membrane. Scale bars, 10 μm (cross-section) and 2 μm (apical membrane). (B) Top row: Membrane sheets were prepared from A431RON cells ± 50 nM EGF for 2 and 5 min. Sheets were labeled on the cytoplasmic face using antibodies to RON (6 nm gold) and EGFR (12 nm gold). Circles indicate co-clusters of RON and EGFR in representative images from three biological replicates; arrowheads indicate clusters containing RON (green) or EGFR (magenta) only. Scale bar, 100 nm. Bottom row: Ripley’s K bivariant function was used to evaluate co-clustering. The experimental values for L(r)-r (corresponding to EM image directly above) are shown in magenta and the 99% confidence window for complete spatial randomness is plotted as dashed lines. In each case, experimental values are seen to fall above the confidence window, indicating co-clustering.

We also applied our established transmission electron microcopy (TEM) technique with immunogold-labeled membrane sheets (Yang et al., 2007) to evaluate the nano-organization of RON with respect to EGFR. Receptor spatial distributions were determined from resting or EGF-stimulated A431RON cells and imaged by TEM (Figure 2B). TEM images show that RON and EGFR frequently co-reside in mixed clusters in untreated cells (circles, Figure 2B, left panels). The co-clustering of the two receptors on resting membranes was confirmed by Ripley’s K co-variant statistical test (Wilson et al., 2004; Yang et al., 2007; Figure 2B, bottom panels). EGFR/RON co-clustering was maintained after 2 min and 5 min of treatment with 50 nM EGF (Figure 2B, middle and right panels). While EM results demonstrate co-clustering of these molecules, the static EM image cannot reveal whether or not the receptors are physically interacting or merely co-confined. Taken together with the observation that co-immunoprecipitation occurs in the absence of ligand, these data suggest that pre-existing protein complexes may be key contributors in EGFR-to-RON crosstalk.

Crosstalk occurs at the plasma membrane

Given their co-localization at the plasma membrane and the rapid (< 5 min) unidirectional crosstalk discussed above, we hypothesized that RON and EGFR form hetero-oligomeric complexes to alter EGF-driven signaling output. Using single particle tracking (SPT) of Quantum Dot (QD)-labeled receptors, we evaluated the mobility of HA-RON on the surface of live A431RON cells using a monovalent anti-HA Fab fragment conjugated to QD probes (QD605-HA-RON) (Valley et al., 2015). Previous work by ourselves and others has shown that mobility is a read-out for receptor phosphorylation status, such that a shift to slower mobility is correlated with receptor dimerization, signaling, and subsequent recruitment of downstream signaling molecules and/or signaling-induced alterations in the local environment (Chung et al., 2010; Erasmus et al., 2016; Low-Nam et al., 2011). Figure 3A shows the mean squared displacement (MSD) versus time lag (Δt) for tracking of QD605-HA-RON under different stimulation conditions. The distribution of Diffusion Coefficients (D) for individual cells is shown in Figure 3B. Consistent with ligand-induced phosphorylation and/or oligomerization, we observed that RON mobility is decreased upon MSP stimulation (Figure 3A, B and Figure 3—figure supplement 1). Notably, RON mobility is also decreased with EGF addition (Figure 3A, B and Figure 3—figure supplement 1). This EGF-induced mobility change was prevented when cells were treated with an EGFR kinase inhibitor (PD153035) (Figure 3A, B). In Figure 3C and D, confocal images show the location of RON and EGFR in HEKRON/EGFR cells after 10 min of EGF stimulation. As expected, EGF-bound EGFR is rapidly endocytosed and shows obvious co-localization with the early endosome marker, EEA1. In contrast, RON receptors are not readily found in the early endosomes, and co-endocytosis of EGFR and RON within endosomes is rare (see Figure 3—figure supplement 2 for quantification). The lack of RON co-endocytosis is further supported by TEM images from A431RON cells, where EGFR, but not RON, was found in clathrin-coated pits 5 min after EGF addition (Figure 3E). These results suggest that EGFR/RON interactions are either sufficiently transient that EGFR is sorted for endocytosis, while RON remains on the surface, or that EGFR complexed with RON is retained longer on the cell surface. These data support the premise that EGFR-mediated activation of RON occurs rapidly at the plasma membrane, rather than in endosomes, and is dependent on EGFR kinase activity.

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Crosstalk occurs at the plasma membrane.

(A) Single particle tracking of QD605-HA-RON was used to quantify RON mobility on A431RON cells ± ligand. Ensemble mean squared displacement (MSD) shows reduction in slope of the MSD with ligand stimulation, indicating a reduced mobility. Treatment with EGFR kinase inhibitor prevents RON slow down with EGF. The number of jumps fit for each condition range from 42,183 to 898,300. (B) Corresponding distribution of diffusion coefficients, D, for individual cells is plotted for arange of 39 to 517 cells per condition; *** p < 0.001. (C) HEKRON/EGFR cells were labeled for RON with anti-HA-FITC Fab fragment (green), treated with 10 nM EGF-AF647 (magenta) for 5 min on ice followed by 10 min at 37°C, then fixed and labeled with an antibody to EEA1 (early endosomes, blue). Representative images from three biological replicates show that EGF-positive endosomes (arrows) primarily do not contain RON. Pearson’s coefficient for the image shown and colocalization with EEA1 is shown in the bottom left corner. (D) Alternative labeling method for monitoring endosome content where HEKRON/EGFR cells were treated with 50 nM EGF for 10 min at 37°C, fixed and then antibodies were used to label RON (anti-HA, green) or EGFR (magenta). Further quantification for C, D is in Figure 3—figure supplement 2. (E) Membrane sheets prepared from A431RON cells ± 50 nM EGF for 5 min were labeled for RON (6 nm gold) or EGFR (12 nm gold). TEM images show clathrin-coated pit lattices on the cell membranes containing EGFR, but not RON. Scale bars, 50 nm.

Figure 3—source data 1

Source data for diffusion coefficient distributions in Figure 3B.

https://cdn.elifesciences.org/articles/63678/elife-63678-fig3-data1-v2.xlsx

EGF-bound EGFR and RON engage in direct interactions

To confirm that EGFR and RON interact at the cell membrane, we used simultaneous two-color QD tracking that allows direct detection and quantification of protein-protein interactions on live cells, as we have described previously (Erasmus et al., 2016; Low-Nam et al., 2011; Steinkamp et al., 2014; Valley et al., 2015). Figure 4 demonstrates the visualization of receptor interactions by tracking of individual receptors in spectrally distinct channels at high spatiotemporal resolution. QDs were conjugated to either a monovalent anti-HA Fab fragment (Steinkamp et al., 2014; Valley et al., 2015) for RON (QD-HA-RON) or to EGF (Lidke et al., 2004; Low-Nam et al., 2011) to follow ligand-bound EGFR (QD-EGF-EGFR). We monitored RON/RON homo-interactions in A431RON cells by labeling receptors with a mixture of anti-HA-QD605 and anti-HA-QD655 (Figure 4A). Figure 4B and Figure 4—video 1 shows an example of a long-lived interaction between two QD-tagged RON receptors lasting for ~5 s before breaking apart. A range of dimer lifetimes was observed, and additional examples and videos of RON homo-interactions are found in Figure 4—figure supplements 1–4. Two-color tracking was next used to determine if RON and EGFR form hetero-complexes. Here, HA-RON was tracked using anti-HA-QD655 and endogenous EGFR was tracked using QD605-EGF (Figure 4D). This live cell imaging approach directly captures pairs of QD-labeled RON and EGF-bound EGFR that engage as complexes and move with correlated motion on the cell membrane. The example in Figure 4E and Figure 4—video 2 shows a more transient interaction with a duration of ~1.5 sec (see further examples and videos in Figure 4—videos 1–6).

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Two-color single QD tracking captures interactions between RON and EGFR.

Two color SPT results for resting RON receptor interactions (A–C) and ligand-bound EGFR interactions with RON (D–F). (A) Schematic representation of two-color (anti-HA-QD605 and anti-HA-QD655) RON SPT. (B) Representative 3D trajectory (top) and time series (bottom) for a RON homo-interaction lasting ~5 s (blue) with accompanying Figure 4—video 1. Scale bar, 500 nm. (C) Ensemble correlated motion plot for all two-color RON tracking. The number of jumps for each data point range from 2,068–15,649. (D) Schematic representation of two-color SPT of EGF-bound EGFR (QD655-EGF) and RON (anti-HA-QD605). (E) Sample 3D trajectory (top) and time series (bottom) showing EGF-EGFR and RON interacting for ~1.5 s (blue) with accompanying Figure 4—video 2. Scale bar, 500 nm. (F) Ensemble correlated motion plot for all EGF-EGFR and RON tracking. The number of jumps for each data point range from 1,500–16,794.

Quantification of correlated motion between receptors confirmed the formation of bona fide receptor complexes (Low-Nam et al., 2011). The presence of correlated motion was assessed over the full data set of the two-color trajectories (Figure 4C and F), reporting on the behavior of the overall population. Correlated motion was observed when two RON receptors were in close proximity, as indicated by the reduction in the uncorrelated jump distance at small separation seen in Figure 4C. Jump magnitude also decreases at small separation, indicating that RON homo-complexes are moving more slowly than monomers. Importantly, correlated motion is also clearly observed for RON and EGF-bound EGFR, confirming direct interactions between these disparate receptors (Figure 4F).

Using a two-state hidden Markov model (HMM) similar to that described in Low-Nam et al (Low-Nam et al., 2011), we estimated the dimerization kinetics between interacting receptors. In the absence of ligand, we found an off-rate (koff) for RON/RON homo-interactions of 0.18 ± 0.02 s–1 (average lifetime of ~5.5 s). Together with the correlated motion analysis, these results are consistent with the idea that RON can homodimerize independent of ligand, as was proposed by others based on the crystal structure of the RON extracellular domain (Chao et al., 2012) and the evidence for ligand-independent activation with RON overexpression or mutations in cancer (Liu et al., 2011; Santoro et al., 1998; Wang et al., 2007). Two-color tracking of QD655-HA-RON and QD605-EGF-EGFR returned an off-rate of 0.49 ± 0.05 s–1 for hetero-interactions. This more transient (average lifetime of ~2 s) interaction is consistent with the ability of EGFR to phosphorylate RON without subsequent co-endocytosis. The cellular environment, including the availability of binding partners and ligand, may influence dimer stability. We note that the experiments described here are performed at low QD-EGF concentration and the frequency of interactions and off-rates may be altered with higher ligand dose or changes in receptor expression.

Maximal EGF-induced RON phosphorylation requires kinase activity of both receptors

Treatment of A431RON cells with the reversible EGFR-selective kinase inhibitor, PD153035, blocks EGF-induced changes in RON mobility (Figure 3A, B). To follow-up these results implicating EGFR kinase activity as the primary driver of EGFR/RON crosstalk, we treated both A431RON and HEKRON/EGFR cells with the irreversible pan-ErbB kinase inhibitor, afatinib. Afatinib treatment completely blocks EGF-dependent phosphorylation of EGFR (Figure 5A) and RON (Figure 5B), but does not inhibit MSP-dependent RON phosphorylation (Figure 5B). Cells pretreated with BMS777607, a RON/Met-family kinase inhibitor, blocked MSP-dependent RON phosphorylation, but only partially blocked EGF-dependent RON phosphorylation (Figure 5B). As expected, BMS777607 did not affect EGF-dependent EGFR phosphorylation. These results indicate that both EGFR and RON kinase activity contribute to EGF-mediated RON phosphorylation.

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Maximal EGF-induced RON phosphorylation requires kinase activity of both receptors.

(A and B) A431RON cells were pre-treated with 10 μM afatinib (Afat, pan-ErbB inhibitor) or 1 μM BMS777607 (BMS, Met family kinase inhibitor) for 20 or 15 min, respectively. Cells were then treated ± EGF or MSP for 5 min. (A) Cell lysates were used for PY1068 and EGFR immunoblots. (B) Lysates were immunoprecipitated (IP) with an anti-HA antibody and then immunoblotted for PY and RON. All samples are from the same blot, but an extraneous lane was removed for clarity. Bar graphs are corresponding mean ± SD from triplicate biological experiments. * p < 0.05; ** p < 0.01; *** p < 0.001.

Figure 5—source data 1

Full raw western blots and blots with relevant bands labelled, corresponding to Figure 5A,B.

https://cdn.elifesciences.org/articles/63678/elife-63678-fig5-data1-v2.zip
Figure 5—source data 2

Source data for quantification of blots in Figure 5A,B.

https://cdn.elifesciences.org/articles/63678/elife-63678-fig5-data2-v2.xlsx

To confirm the differential contributions of the EGFR and RON kinases in crosstalk, we expressed the kinase dead mutant of RON (RON-K1114M) in A431 cells (Figure 5—figure supplements 1 and 2). EGF-driven phosphorylation of RON-K1114M was observed and afatinib treatment abrogated this phosphorylation (Figure 5—figure supplement 1). The reduction in RON phosphorylation by BMS777607, as seen in RON-WT, is not observed for RON-K1114M since this mutant inherently lacks kinase activity. Consistent with the observed phosphorylation, HA-RON-K1114M undergoes significant reduction in mobility with EGF stimulation in SPT experiments (Figure 5—figure supplement 2). RON’s family member Met has been shown to transphosphorylate RON, as well as engage in crosstalk with EGFR (Harwardt et al., 2020; Jo et al., 2000). However, our results show that EGF-induced phosphorylation of HA-RON-K1114M is not reduced in the presence of BMS777607, indicating that Met is not involved in EGFR/RON crosstalk. These results underscore the importance of EGFR kinase activity in crosstalk and rule out Met as a possible contributor.

EGFR/RON crosstalk does not require downstream signaling molecules

Thus far, our data indicate the critical role for EGFR kinase activity in EGF-dependent RON phosphorylation. While this could be attributed to direct phosphorylation of RON by EGFR in hetero-oligomeric complexes, an alternative mechanism could involve recruitment of EGFR-associated kinases such as the tyrosine kinase Src (Danilkovitch-Miagkova et al., 2000; Sato et al., 1995). To rule out the possibility that Src is an intermediary in propagating EGFR/RON crosstalk, A431RON cells were pre-treated with the Src family kinase inhibitor dasatinib prior to stimulation with 50 nM EGF. Low doses of dasatinib (10 nM) were used to ensure Src family specificity (Nam et al., 2005) while achieving 70% reduction in basal Src PY416 phosphorylation (Figure 6—figure supplement 1). Dasatinib treatment did not alter EGF-induced RON phosphorylation (Figure 6A), arguing that EGFR/RON crosstalk does not depend on Src kinase activity, and is likely to reflect direct action of the EGFR kinase (unaffected by dasatinib) on RON.

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Crosstalk occurs through direct phosphorylation of RON by EGFR.

(A) A431RON cells were pre-treated with dasatinib (Das, Src inhibitor) for 30 min prior to stimulation with EGF for 5 min at 37 °C. Representative immunoblots of cell lysates detecting PY1068 and total EGFR (top), or PY and RON after IP with anti-HA (RON) (bottom). (B) HEKRON cells transiently transfected with EGFR-WT or EGFR-Δ998 ± EGF for 5 min. Representative immunoblots detecting PY and RON after IP with anti-RON or detection of total EGFR on cell lysates (bottom inset). (C) Kinase assay using the purified EGFR kinase domain (EGFR-KD) co-incubated with RON-K1114M IP samples ± ATP. Representative immunoblot detecting total phosphorylation (PY) of RON. All bar graphs represent mean ± SD from triplicate biological experiments. ** p < 0.01; *** p < 0.001.

Figure 6—source data 1

Full raw western blots and blots with relevant bands labelled, corresponding to Figure 6A, B, and C.

https://cdn.elifesciences.org/articles/63678/elife-63678-fig6-data1-v2.zip
Figure 6—source data 2

Source data for quantification of blots in Figure 1C, D and E.

https://cdn.elifesciences.org/articles/63678/elife-63678-fig6-data2-v2.xlsx

In addition to Src, EGFR also recruits a number of other cytoplasmic signaling molecules to phosphotyrosines in its C-terminal tail. We expressed in HEKRON cells a version of EGFR truncated at amino acid 998 (HEKRON/EGFR-Δ998), which lacks most of the phosphotyrosine binding sites that recruit downstream adaptor molecules (Kovacs et al., 2015a). In a previous study, EGFR-Δ998 exhibited decreased phosphorylation of the remaining tyrosine residues 845, 974, and 992 compared to full length EGFR suggesting that phosphorylation at these sites might depend on downstream binding partners (Kovacs et al., 2015a). Unexpectedly, stimulating HEKRON/EGFR-Δ998 cells with EGF led to enhanced phosphorylation of RON compared to HEKRON/EGFR-WT (Figure 6B). We speculated that the EGFR tail might compete for phosphorylation by the kinase domain, explaining why its deletion enhances RON phosphorylation.

These results confirm that recruitment of downstream signaling molecules to the C-terminal tail of EGFR is not required for EGF-driven RON phosphorylation, while raising a new question as to the mechanism of this enhanced crosstalk. We considered the possibility that truncation of the EGFR tail could prevent recruitment of EGFR-associated phosphatases that normally dampens downstream signals (Kleiman et al., 2011; McCabe Pryor et al., 2015). HEKRON cells with EGFR-WT or EGFR-Δ998 treated with EGF followed by afatinib (to irreversibly inhibit subsequent rounds of phosphorylation) were examined for RON and EGFR phosphorylation (Figure 6—figure supplement 2). Independent of full-length or truncated EGFR, RON lacked phosphorylation after 20 s of afatinib treatment, confirming that the dephosphorylation kinetics are similar. Thus, while a third-party signaling molecule is not required to mediate crosstalk in our model systems, the unstructured EGFR tail or its binding partners appear to have a role in limiting EGFR-mediated phosphorylation of RON.

RON is a substrate for EGFR kinase activity

Having ruled out a role for downstream signaling molecules, we hypothesized that the RON C-terminal tail is a substrate for EGFR kinase activity. To further test this possibility, we designed an in vitro kinase assay to allow for detection of EGFR phosphorylation of RON without background from other cellular components. In these experiments, we used immunoprecipitated kinase dead RON (RON-K1114M) as a substrate, removing potential contributions from RON kinase activity, and recombinant EGFR kinase domain (EGFR-KD) as the active kinase. We found that EGFR-KD directly phosphorylated RON-K1114M, in an ATP-dependent and EGFR-KD concentration-dependent manner (Figure 6C).

RON cannot substitute as activator or receiver in EGFR dimers

Structural studies have established the critical role for the orientation of EGFR kinase domains in asymmetric dimers (activator and receiver) for EGFR kinase activity (Zhang et al., 2006). We set out to determine if RON can substitute for either activator or receiver to form an active EGFR/RON heterodimer. HEKRON cells were transfected with EGFR mutants that are either receiver-impaired (I682Q) or activator-impaired (V924R) (Zhang et al., 2006). For EGFR-WT, EGF stimulation resulted in the expected EGF-driven EGFR and RON phosphorylation patterns in HEKRON cells (Figure 7). In contrast, neither EGFR-I682Q nor EGFR-V924R were capable of crosstalk with RON or EGFR autophosphorylation. As in previous studies (Zhang et al., 2006), restoring functional EGFR kinase domain dimers by co-expressing EGFR-I682Q and EGFR-V924R rescued EGFR autophosphorylation and – importantly – RON cross-phosphorylation. These data demonstrate that, unlike other ErbB family members that can form functional heterodimers with EGFR (Kovacs et al., 2015b), RON cannot serve as a substitute for the EGFR activator or receiver. Therefore, although EGFR can directly phosphorylate RON, this is not achieved through a simple hetero-dimerization event. Rather, these data indicate that the first step in crosstalk is for EGFR to form a signaling competent dimer in order to activate the EGFR kinase domain before phosphorylation of RON.

Figure 7
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Functional EGFR dimers are necessary for EGFR/RON crosstalk.

(A and B) HEKRON cells transiently expressing EGFR-WT, EGFR-I682Q (receiver-impaired), EGFR-V924R (activator-impaired) or both mutants (EGFR-I682Q + V924 R) were treated ± EGF for 5 min at 37 °C. (A) Representative immunoblot detecting PY1068 and EGFR in cell lysates. (B) Representative immunoblot showing PY and RON after IP with anti-RON. Triplicate biological experiments from (A and B) are quantified and graphed as mean ± SD. *** p < 0.001.

Figure 7—source data 1

Full raw western blots and blots with relevant bands labelled, corresponding to Figure 7A, B.

https://cdn.elifesciences.org/articles/63678/elife-63678-fig7-data1-v2.zip
Figure 7—source data 2

Source data for quantification of blots in Figure 7.

https://cdn.elifesciences.org/articles/63678/elife-63678-fig7-data2-v2.xlsx

Discussion

Our studies reveal that crosstalk between EGFR and RON occurs through direct receptor interaction, where EGFR transactivates RON within hetero-complexes. We also provide definitive evidence that crosstalk is EGF-driven and propagates in a unidirectional manner from EGFR to RON. Others have suggested that EGFR and RON can transactivate each other (Hsu et al., 2006; Peace et al., 2003). One explanation for the previous findings could be cross-reactivity of the anti-phosphotyrosine antibodies used, since we found the commercially available phospho-RON ‘receptor-specific’ antibodies that we tested to be cross-reactive with phospho-RON and phospho-EGFR (see Figure 1—figure supplement 4). We avoided this potential artifact by ensuring that our protein analysis methods effectively resolved the contributions of RON separately from EGFR. We also considered the possibility that crosstalk could be dependent on the ratio of EGFR/RON levels, developing cell lines where EGFR is highly overexpressed compared to RON (~24:1) or where the expression is similar (~2:1). Notably, these model cell lines lack endogenous expression of other RON splice variants, allowing us to focus on interactions between wild type EGFR and wild type RON. In both cases, crosstalk was found to be unidirectional and EGF-dependent. Future studies are needed to define the role of crosstalk in situations where RON is more abundant than EGFR or different isoforms of RON are present.

An important outcome of our study is the first direct detection and quantification of the dynamic hetero-interactions between EGFR and RON. The use of two-color SPT allowed us to capture the formation and dissociation of EGFR/RON complexes on live cells and hetero-oligomerization was confirmed by correlated motion analysis. Other studies of EGFR/Met family crosstalk have inferred this interaction by co-IP or co-clustering in super-resolution imaging (Harwardt et al., 2020; Jo et al., 2000; Peace et al., 2003). Studies of EGFR/MET have also suggested that adaptor proteins downstream of the receptors, specifically c-Src, may mediate crosstalk (Mueller et al., 2008). It is also conceivable that adaptor proteins recruited to the EGFR tail (Biscardi et al., 1999; Yamauchi et al., 1998) could subsequently phosphorylate RON. However, we found that neither inhibition of c-Src activity nor removal of the EGFR cytoplasmic tail (EGFR-Δ998) prevented crosstalk with RON. Adaptor proteins may explain the enhanced phosphorylation of RON that was seen in cells expressing EGFR-Δ998. For instance, Grb2 has been reported to inhibit RON autophosphorylation (Chaudhuri et al., 2011) raising the possibility that loss of Grb2 recruitment by EGFR-Δ998 could reduce local Grb2 concentration and increase RON phosphorylation. Alternatively, removal of the EGFR C-terminal tail diminishes the recruitment of downstream EGFR substrates, limiting substrate competition and making the RON C-terminal tail the preferred substrate in the hetero-oligomeric complexes. Together, along with the identification of RON as a substrate for EGFR kinase, our results establish that crosstalk is mediated by receptor-receptor interactions. It is particularly intriguing that these interactions allow for EGFR to stimulate RON signaling in the absence of MSP and even when RON kinase activity is inhibited. A potential future direction is to examine whether disruption of EGFR/RON interactions might provide a therapeutic advantage in tumors that co-express EGFR and RON.

The structural requirements for direct interactions between EGFR and RON are yet unresolved, but our studies have revealed important constraints governing these interactions. We found that RON cannot serve as an activator or receiver kinase in an EGFR/RON heterodimer. Instead, formation of a signaling-competent EGFR homodimer appears to be first required to initiate EGF-driven RON phosphorylation. Further study is needed to establish the exact stoichiometry and activity of the EGFR/RON complex. However, considering that RON homo-interactions were observed by two-color SPT in both resting and liganded states, we postulate that the hetero-complex consists of a RON dimer interacting with EGFR. Our studies with the EGFR dimer mutants suggest that the interaction involves either a ligand-bound EGFR dimer or an activated EGFR monomer that has recently dissociated from a homodimer.

Our findings suggest intriguing similarities between the interactions of EGFR with RON and those described for EGFR with ErbB3, a member of the EGFR subfamily. Studies from the Jura lab have proposed unidirectional receptor phosphorylation of unliganded ErbB3 by ligand-bound EGFR in which hetero-interactions are also thought to require EGFR dimers (van Lengerich et al., 2017). Furthermore, like EGFR and RON, EGFR and ErbB3 do not readily co-endocytose after EGF stimulation (Lidke et al., 2004). Therefore, the underlying mechanisms of EGFR/RON crosstalk are likely applicable to our understanding of other receptor interactions.

Materials and methods

Cell lines and reagents

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Cell culture medium was from Thermo Fisher Scientific and Poly-L-lysine (PLL) from Sigma (cat # P4707). Afatinib and BMS777607 were from Selleck Chemicals (cat # S1011 and S1561, respectively), dasatinib from Santa Cruz Biotechnology (cat # sc-358114), and PD153035 from EMD Millipore (cat # 234491). Human recombinant EGF was from Invitrogen (cat # PHG0311) or PeproTech (cat # AF-100–15), biotin-conjugated and AF647-conjugated EGF from Thermo Fisher Scientific (cat # E3477 and E35351), and MSP from R&D Systems (cat # 4306 MS-010). Halt protease and phosphatase inhibitor (PPI) cocktail was from Pierce (cat # 78446) and the protease inhibitor cocktail set V, EDTA-free was from Calbiochem (cat # 539137). QD605 and QD655 streptavidin conjugates were from Thermo Fisher Scientific (cat # Q10101MP and Q10121MP, respectively). For western blotting, BCA protein assay kit (cat # 23225) and ECL blotting substrate (cat # 32106) were from Pierce. Immunoprecipitation was based on use of protein A/G magnetic beads from Pierce (cat # 88802). See Key Resources Table for a list of primary and secondary antibodies used in these studies.

Human epidermoid carcinoma A431 cells (ATCC, CRL-1555) were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% HyClone cosmic calf serum (CCS; GE Healthcare Life Sciences), 2 mM L-glutamine (Life Technologies), and penicillin/streptomycin (Life Technologies). Human embryonic kidney HEK-293 cells were cultured in Minimum Essential Medium (MEM) with 10% fetal bovine serum (FBS; Atlanta Biologicals), 2 mM L-glutamine, and penicillin/streptomycin. Cell lines were authenticated using STR profiling (ATCC) and free from mycoplasma (MycoAlert Mycoplasma Detection Kit; Lonza).

Plasmid cloning, site directed mutagenesis and cell transfections

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The vector containing RON (MST1R) pDONR223-MST1R was a gift from William Hahn and David Root (Addgene plasmid # 23942; http://n2t.net/addgene:23942; RRID:Addgene_23942) (Johannessen et al., 2010). HA-tagged RON was cloned into the expression vector pcDNA3.1/V5-His-TOPO (Invitrogen) by fusion PCR. An ultramer containing the CACC ligation sequence, start codon, RON signal peptide, HA-tag, and alanine linker 5’ of the mature RON coding region and a reverse primer were used to synthesize HA-RON. DNA oligos were from Integrated DNA Technologies. Ultramer sequencing and mutagenesis primers are listed in Key Resources Table. The kinase dead RON variant (HA-RON-K1114M) was generated by site-directed mutagenesis (Danilkovitch-Miagkova et al., 2000) (Key Resources Table). To establish cell lines stably expressing HA-RON (HEKRON and A431RON), cells were transfected with the pcDNA3.1 HA-RON plasmid by electroporation using the AMAXA Nucleofector System (Lonza). Briefly, 5 × 106 HEK-293 cells were transfected with 8 µg of plasmid DNA using Nucleofection Solution V and program Q-001. A431 cells were transfected with HA-RON or HA-RON-K1114M using solution T and program X-001. Transfected cells were selected for stable integration by growth in 1 mg/ml G418 (Caisson Labs) for 7 days, then sorted for RON expression with a fluorescently-conjugated anti-HA antibody using a iCyt SY3200 cell sorter (Sony Biotechnology).

For co-expression of RON and EGFR, HEKRON cells were transfected with an ACP-tagged EGFR plasmid (Valley et al., 2015) by electroporation using the same conditions as above. Transfected cells were selected with zeocin (300 µg/ml; Gibco/Life Technologies) and sorted for double positive cells (anti-HA-AF488 and anti-EGFR-AF647) on the iCyt SY3200.

For kinase assays, a C-terminal SBP-tagged construct of EGFR encoding the transmembrane domain, kinase domain, and cytoplasmic tail (EGFR-KD) was amplified from full-length EGFR by PCR (Key Resources Table) and cloned into the pCTAP backbone via Gibson assembly. EGFR-KD and RON-K1114M proteins were produced using the Expi293 cell Expression System (Thermo Fisher Scientific) according to the manufacturer’s recommendations.

Receiver-impaired and activator-impaired EGFR variants, EGFR-I682Q and EGFR-V924R, were engineered from the pcDNA3.1 HA-EGFR WT plasmid using site-directed mutagenesis (Valley et al., 2015) (Key Resources Table). The truncated EGFR-Δ998 plasmid, which lacks the C-terminal phosphorylation sites, was generated by amplifying the truncated EGFR from pcDNA3.1-EGFR WT plasmid using standard PCR and cloning techniques (Key Resources Table). HEKRON cells were transiently transfected with the resulting plasmids and experiments performed at 18–24 hr post-transfection.

Flow cytometry – receptor quantification

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Quantification of cell surface EGFR and RON expression was performed by flow cytometry using Quantum MESF kits. Briefly, cells were incubated with a range of concentrations (0–40 µg/ml) of anti-EGFR-AF647 (dye/protein ratio of 2.74 or 3.84) or anti-HA-AF488 (dye/protein ratio of 3.34) for 1 hr on ice. Cells were rinsed with PBS, fixed in 4 % PFA (paraformaldehyde) for 10 min on ice, washed with 10 mM Tris-PBS and resuspended in PBS. Fluorescent calibrator beads, Quantum AlexaFluor 647 or 488 MESF (Bangs Laboratories, cat # 647 A and 488 A, respectively) were used to generate a standard curve of fluorescence intensity. Samples and beads were run on the Accuri C6 Plus cytometer (BD Biosciences), and receptor levels calculated based on the dye:protein ratio of the individual antibodies and values determined using the QuickCal spreadsheet (Bangs Laboratories).

Immunofluorescence staining

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HEKRON/EGFR cells were plated onto glow-discharged (EMS 150T ES, Quorum Technologies), PLL-coated glass coverslips overnight. RON labeling was performed in live cells with an anti-HA-FITC Fab fragment for 30 min in Tyrodes buffer (135 mM NaCl, 10 mM KCl, 0.4 mM MgCl2, 1 mM CaCl2, 10 mM HEPES, 20 mM glucose, 0.1% BSA, pH 7.2) on ice. Cells were treated with 10 nM EGF-AF647 on ice for 5 min, fixed in 4% PFA for 15 min at RT, and washed with 10 mM Tris/PBS buffer. Samples were rinsed, incubated with DAPI, and mounted with Prolong Gold (Thermo Fisher Scientific). Confocal images were acquired using a 63×/1.40 oil objective on a Zeiss LSM800 microscope in channel mode and appropriate diode lasers were used for excitation of the fluorophores.

For endocytosis experiments, RON was pre-labeled with anti-HA-FITC Fab and cells were stimulated with EGF-AF647 for 10 min at 37 °C prior to fixation. Samples were simultaneously blocked and permeabilized with 0.1% Triton X-100/3% BSA/PBS for 20 min and stained with anti-EEA1 in 0.1% Triton X-100/0.1% BSA/PBS solution for 30 min at 37 °C followed by anti-Rabbit-AF555 secondary for 30 min at 37 °C before DAPI staining and mounting.

Transmission electron microscopy of native membrane sheets

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Standard ‘rip-flip’ membrane sheets were prepared as previously described (Wilson et al., 2007). In brief, A431RON cells were treated or not with 50 nM EGF for 2 or 5 min and fixed in 0.5% PFA. Coverslips were flipped, cells down, onto PLL-coated formvar and carbon-coated nickel finder grids and pressure was applied to adhere apical cell membranes before removing the coverslip. Grids with membrane sheets were fixed with 2% PFA in HEPES buffer (25 mM HEPES, 25 mM KCl, and 2.5 mM Mg Acetate) for 20 min and sequentially labeled with antibodies against RON or EGFR in 0.1% BSA/PBS for 1 h at RT. Secondary antibodies conjugated to colloidal gold were added for 30 min at RT. Samples were post-fixed with 2% glutaraldehyde for 20 min and negatively stained with 0.3% tannic acid for 1 min and 2% uranyl acetate for 9 min. Digital images were acquired on a Hitachi H-7650 Transmission Electron Microscope equipped with a mid-mount digital imaging system (Advanced Microscopy Techniques, Corp) and Image J (NIH) was used to crop images. Ripley’s bivariate K test was used to determine if co-clustering of species is significant (Wilson et al., 2004; Yang et al., 2007), with a critical interaction distance of 50 nm. Data within the confidence window are not significantly co-clustered. When the experimental values are found above the confidence window the deviation from complete spatial randomness is statistically significant and indicates that the two labels are co-clustering.

Cell activation and lysis

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Transiently transfected or stable cell lines were seeded into 100 mm dishes and allowed to adhere overnight. For inhibition studies, cells were pretreated with 10 μM afatinib for 20 min, 1 μM BMS777607 for 15 min, or 1–10 nM dasatinib for 30 min, where indicated. They were subsequently treated with different doses of EGF, MSP, or both, for varying times (0–5 min). Cells were rinsed in cold PBS and lysed on ice for 20 min with NP-40 lysis buffer (150 nM NaCl, 50 mM Tris, 1% NP-40) containing PPI. Lysates were cleared and protein concentrations in the supernatant were determined by BCA protein assay.

Immunoprecipitation

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Cell lysates (1 mg total protein) were immunoprecipitated (IP) overnight using anti-HA coupled to magnetic or sepharose beads or anti-RON overnight at 4 °C, rotating. For samples incubated with the RON antibody, protein A/G magnetic beads were added the next day and incubated for 1 h, rotating at 4 °C. Beads were washed with 0.05% Tween-20/ PBS containing PPI.

Multiplex immunoblotting

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Whole lysates (20 μg) or IP samples were boiled with reducing sample buffer, subject to SDS-PAGE, and transferred to nitrocellulose membranes using the iBlot2 system (Life Technologies). Membranes were blocked for 30 min in 3% BSA / 0.1% Tween-20/ TBS, and probed overnight with primary antibodies at 4 °C (Key Resources Table). Membranes were incubated with IRDye fluorescent secondary antibodies for 1 h at RT (Key Resources Table), washed, and dual color detection was performed using the Odyssey Fc Imaging System (Li-Cor). Band intensities were analyzed with Image Studio (Li-Cor, version 5.2) and normalized PY to total protein (PY1068/EGFR or PY/RON).

Single particle tracking (SPT)

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Single- and dual-color SPT and analysis was conducted as previously described (Low-Nam et al., 2011; Steinkamp et al., 2014; Valley et al., 2015). Briefly, A431RON (Figures 3A, B , and 4) or A431RON-K1114M (Figure 5—figure supplement 2) cells were seeded in eight-well chamber slides (Nunc Lab-Tek) at a density of 30,000/well and allowed to adhere overnight. Where indicated, EGFR kinase activity was inhibited by pretreating with 1 μM PD153035 for 2 hr and maintained throughout the experiment. RON was tracked via QD conjugated to biotinylated anti-HA Fab fragments that bind to the N-terminal HA-tag on HA-RON (as indicated). Cells were incubated with 200 pM anti-HA-QDs (605 or 655) for 15 min at 37 °C to obtain single-molecule density on the apical surface. After washing with Tyrodes buffer cells were treated with 5 nM MSP for 5 min or 50 nM EGF for 30 s and imaged. For dual EGFR and RON tracking, cells were incubated with 200 pM anti-HA-QD655 for 15 min at 37 °C, washed, and then stimulated with 50 pM QD605-conjugated EGF-biotin. Particle tracking was done for up to 15 min. Imaging was performed on an Olympus IX71 inverted widefield microscope with a 60× 1.2 numerical aperture water objective as in Valley et al., 2015 (Valley et al., 2015). QD emissions were collected using a 600 nm dichroic (Chroma) and the appropriate bandpass filters, 600/52 nm and 676/37 (Semrock). Physiological temperature (34–36°C) was maintained using an objective heater (Bioptechs). Images were acquired at a rate of 20 frames per sec for a total movie length of 1000 frames.

MATLAB (MathWorks) was used for image processing and analysis in conjunction with DIPImage (Delft University of Technology). Diffusion was computed using mean square displacement (MSD) (de Keijzer et al., 2008; Low-Nam et al., 2011; Valley et al., 2015). Dimer off-rates and events were identified using a two-state HMM, similar to previous work (Low-Nam et al., 2011; Steinkamp et al., 2014). For more details, see Supplementary Methods.

Protein purification and kinase assay

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EGFR-KD, which begins at amino acid 637 and continues through the C-terminal tail, was expressed in Expi293 cells. Cell lysate was bound to streptavidin resin and eluted in biotin buffer according to manufacturer’s recommendations (InterPlay Mammalian TAP System; Agilent Technologies). Typical protein yield was between 30–70 μg. RON-K1114M was immunoprecipitated from Expi293 cell lysates (2 mg total protein) with sepharose anti-HA beads. Immunoprecipitated RON-K1114M was resuspended in kinase assay buffer (200 mM HEPES, pH 7.4; 300 mM MgCl2; 20 mM MnCl2; 0.5 % Triton X-100; 1.5 % Brij 35; 10 % glycerol; 1 X Protease inhibitor cocktail Set V; and 2 mM activated Na3VO4) in the presence or absence of purified EGFR-KD (1:12 or 1:35 dilution). Samples were incubated with 400 µM ATP (or no ATP, as a control; Cell Signaling Technology, cat # 9804) and held at 30 °C for 30 min, shaking. Reactions were terminated by addition of ice cold buffer. RON-K1114M bound to beads was recovered by centrifugation at 2500 x g for 2 min at 4 °C and washed 3 x with 0.05 % Tween-20/ PBS containing PPI. Samples were boiled with reducing sample buffer, subject to SDS-PAGE, and western blotting with HRP-conjugated anti-PY20 and anti-PY99.

Mass spectrometry

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A431RON cells were harvested with lysis buffer and immunoprecipitated with an anti-HA antibody. Samples were run in a reducing 4–20% polyacrylamide gel for separation, washed in distilled water for 15 min, and incubated with GelCode Blue stain reagent (Thermo Fisher Scientific, cat # 24590) for 1 hr at RT. Both top and bottom RON bands were excised from the gel and samples sent to the Proteomics Core at UT Southwestern.

Dephosphorylation assay

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HEKRON cells were transiently transfected with WT or Δ998-EGFR and allowed to attach and recover overnight. Cells were activated with 50 nM EGF for 2 min followed by 10 μM afatinib for 20 or 40 s. Media was removed and reactions were stopped by placing plates on top of a layer of liquid nitrogen. Protein lysates were harvested and quantified by BCA. RON protein was immunoprecipitated from the lysates with anti-RON antibody, and immunoblotted.

Statistical analysis

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All values from quantitative western blot experiments are plotted as mean ± SD. For quantitative experiments, statistical analysis was performed using GraphPad Prism (Prism 4, GraphPad) with a two-way analysis of variance (ANOVA) from three biological replicates (performed on separate days). For immunoblot analysis, phosphorylated protein levels were normalized to total protein levels (RON or EGFR) detected from the same sample. For phosphorylation time course experiments, the maximum stimulation level was set at one for triplicate experiments and plotted as mean ± SD. Differences among means were tested using the Bonferroni multiple comparison test post hoc. Values of p < 0.05 were considered significant. Errors in values of diffusion coefficients are reported as 95 % confidence intervals from fitting a Brownian diffusion model (linear) to the first 5 points of the MSD.

Appendix 1

Appendix 1—key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
cell line (Homo sapiens)A431 (female)ATCCATCC Cat# CRL-1555, RRID:CVCL_0037
cell line (Homo sapiens)HEK-293ATCCATCC Cat# CRL-1573, RRID:CVCL_0045
cell line (Homo sapiens)A431RONThis paperA431 cells stably transfected with pcDNA3.1 HA-RON plasmid
cell line (Homo sapiens)A431RON-K1114MThis paperA431 cells stably transfected with pcDNA3.1 HA-RON-K1114M plasmid
cell line (Homo sapiens)HEKRONThis paperHEK-293 cells stably transfected with pcDNA3.1 HA-RON plasmid
cell line (Homo sapiens)HEKRON/EGFRThis paperHEKRON cells stably transfected with ACP-EGFR plasmid
transfected construct (human)pcDNA3.1 HA-RONThis paperGenerated using pcDNA3.1
transfected construct (human)ACP-EGFRZiomkiewicz et al., Cytometry A, 2013
transfected construct (human)pcDNA3.1 HA-RON-K1114MThis paper
antibodyAnti-EEA1 (Rabbit monoclonal)Cell Signaling TechnologyCat# 3288 RRID:AB_2096811Clone C5B10 IF (1:200)
antibodyAnti-EGFR (Rabbit monoclonal)Cell Signaling TechnologyCat# 4267 RRID:AB_2246311Clone D38B1 WB (1:2000)
antibodyAnti-EGFR (Goat polyclonal)R&D SystemsCat# AF231 RRID:AB_355220WB (1:1000) Used when blotting for EGFR-Δ998
antibodyAnti-EGFR (Rabbit monoclonal)Cell Signaling TechnologyCat# 4405 RRID:AB_331380Clone 15 F8 WB (1:2000)
antibodyAnti-EGFR PY1068 (Mouse monoclonal)Cell Signaling TechnologyCat# 2236 RRID:AB_331792Clone 1 H12 WB (1:2000)
antibodyAnti-EGFR PY845 (Rabbit polyclonal)Santa Cruz BiotechnologyCat# sc-23420 RRID:AB_653168WB (1:500)
antibodyAnti-EGFR PY1148 (Rabbit polyclonal)Cell Signaling TechnologyCat# 4404 RRID:AB_331127WB (1:2000)
antibodyAnti-EGFR AF647 (Mouse monoclonal)Santa Cruz BiotechnologyCat# sc-101 AF647Clone R-1 FACS (5–40 ug/mL)
antibodyAnti-EGFR (Goat polyclonal)Santa Cruz BiotechnologyCat# sc-31156 RRID:AB_2096710Clone D-20 EM (1:20)
antibodyAnti-HA AF488 (Mouse Monoclonal)Cell Signaling TechnologyCat# 2350 RRID:AB_491023Clone 6E2 FACS (5–40 ug/mL)
antibodyAnti-HA magnetic bead (Rabbit monoclonal)Cell Signaling TechnologyCat# 11846 RRID:AB_2665471Clone C29F4 IP (1:100)
antibodyAnti-HA sepharose bead (Rabbit monoclonal)Cell Signaling TechnologyCat# 3956 RRID:AB_10695091Clone C29F4 IP (1:100)
antibodyAnti-HA FITC (Fab; Rat monoclonal)RocheCat# 11988506001 RRID:AB_390916Clone 3 F10 IF (1:20)
antibodyAnti-HA Biotin (Fab; Rat monoclonal)RocheCat# 12158167001 RRID:AB_390915Clone 3 F10 SPT (200 pM)
antibodyAnti-PY20 (Mouse monoclonal)Santa Cruz BiotechnologyCat# sc-508 RRID:AB_628122WB (1:500)
antibodyAnti-PY20 HRP (Mouse monoclonal)Santa Cruz BiotechnologyCat# sc-508 HRPKinase assay (1:500)
antibodyAnti-PY99 (Mouse monoclonal)Santa Cruz BiotechnologyCat# sc-7020 RRID:AB_628123WB (1:500)
antibodyAnti-PY99 HRP (Mouse monoclonal)Santa Cruz BiotechnologyCat# sc-7020 HRPKinase assay (1:500)
antibodyAnti-RON (Goat polyclonal)R&D SystemsCat# AF691 RRID:AB_355527IP (1:100)
antibodyAnti-RONβ (Rabbit polyclonal)Santa Cruz BiotechnologyCat# sc-322 RRID:AB_677390Clone C-20 WB (1:500) EM (1:20) Discontinued antibody; remainder of experiments done with Cell Signaling Technology Cat# 2,654
antibodyAnti- RONβ (Rabbit monoclonal)Cell Signaling TechnologyCat# 2654 RRID:AB_2298153Clone C81H9 WB (1:2000)
antibodyAnti- RONβ (Mouse monoclonal)Santa Cruz BiotechnologyCat# sc-74588 RRID:AB_2235711Clone E-3 WB (1:500) Used with the PY1238/39 RON antibody (R&D Systems Cat# AF1947)
antibodyAnti-RON PY1238/39 (Rabbit polyclonal)R&D SystemsCat# AF1947 RRID:AB_1152159WB (1:2000)
antibodyAnti-Src (Mouse monoclonal)Cell Signaling TechnologyCat# 2110 RRID:AB_10691385Clone L4A1 WB (1:2000)
antibodyAnti-Src PY416 (Rabbit polyclonal)Cell Signaling TechnologyCat# 2101 RRID:AB_331697WB (1:2000)
antibodyAnti-Goat IgG IRDye 800CW (Donkey polyclonal)Li-CorCat# 926–32214 RRID:AB_621846WB (1:20000)
antibodyAnti-Goat IgG 12 nm colloidal gold (Donkey polyclonal)Jackson Immuno ResearchCat# 705-205-147 RRID:AB_2340418EM (1:20)
antibodyAnti-Mouse IgG IRDye 680RD (Goat polyclonal)Li-CorCat# 926–68070 RRID:AB_10956588WB (1:20000)
antibodyAnti-Mouse IgG IRDye 680RD (Donkey polyclonal)Li-CorCat# 926–68072 RRID:AB_10953628WB (1:20000)
antibodyAnti-Rabbit IgG IRDye 800CW (Goat polyclonal)Li-CorCat# 926–32211 RRID:AB_621843WB (1:20000)
antibodyAnti-Rabbit IgG IRDye 680RD (Donkey polyclonal)Li-CorCat# 926–68073 RRID:AB_10954442WB (1:20000)
antibodyAnti-Rabbit IgG AF555 (Fab; Goat polyclonal)Thermo Fisher ScientificCat# A-21430 RRID:AB_2535851IF (1:500)
antibodyAnti-Rabbit IgG 6 nm colloidal gold (Donkey polyclonal)Jackson Immuno ResearchCat# 711-195-152 RRID:AB_2340609EM (1:20)
recombinant DNA reagentpDONR223-MST1RAddgeneRRID:Addgene_23942 Johannessen et al., 2010RON sequence used to make the HA-tagged RON plasmid
recombinant DNA reagentpcDNA3.1/V5-His-TOPOInvitrogenUsed as a backbone for HA-tagged RON plasmid (HA-RON and HA-RON-K1114M)
recombinant DNA reagentpcTAPAgilent
recombinant DNA reagentpcDNA3.1 HA-EGFR WTValley et al., 2015Plasmid used for generating EGFR-I682Q, EGFR-V924R, and EGFR-Δ998 with primers below
sequence-based reagentUltramer to generate HA-tagged RON plasmidThis paperCACCATGGAGCTCCTC CCGCCTCAGTCCTTCC TGTTGCTGCTGCTGTT GCCTGACAAGCCCGCG GCGGGCTATCCTTACG ACGTGCCTGACTACGCC GCAGCAGCAGAGGACT GGCAGTGCCCGCACA Has CACC ligation sequence, start codon, RON signal peptide, HA-tag, and alanine linker 5’ of the mature RON coding region
sequence-based reagentPrimers to generate RON-K1114M mutagenesisThis paperDanilkovitch-Miagkova et al., 2000Forward: GTGATGCGAC TTAGTGACATGATGGC ACATTGGATTC Reverse: GAATCCAATG TGCCATCATGTCACTAA GTCGCATCAC
sequence-based reagentPrimers to generate EGFR-KDThis paperForward: CGCCGGATCC CCAACGAATGGGCCTA AG Reverse: CGAGGTCGAC GGTATCGATAAGCTTTG CTCCAATAAATTCACTGC
sequence-based reagentPrimers to generate EGFR-I682Q mutagenesisThis paperForward: CAACCAAGCT CTCTTGAGGCAGTTG AAGGAAACTGAATTC Reverse: GAATTCAGT TTCCTTCAACTGCCTC AAGAGAGCTTGGTTGG
sequence-based reagentPrimers to generate EGFR-V924R mutagenesisThis paperForward: GATGTCTACA TGATCATGCGCAAGT GCTGGATGATA Reverse: TATCATCCAG CACTTGCGCATGATC ATGTAGACATC
sequence-based reagentPrimers to generate truncated EGFR-Δ998This paperForward: GTTAAGCTTG GTACCGAGCTCGGAT CCAGTACCCTTCACC ATGCGACCCTCCGGG AC Reverse: CCCTCTAGA CTCGAGCGGCCGCCT AGAAGTTGGAGTCTGTAGGACTTGGC
peptide, recombinant proteinHuman recombinant EGFInvitrogenCat# PHG0311
peptide, recombinant proteinHuman recombinant EGFPeproTechCat# AF-100–15
peptide, recombinant proteinHuman recombinant EGF-biotinThermo Fisher ScientificCat# E3477
peptide, recombinant proteinHuman recombinant EGF-AF647Thermo Fisher ScientificCat# E35351
peptide, recombinant proteinHuman recombinant MSPR&D SystemsCat# 4306 MS-010
commercial assay or kitBCA protein assay kitPierceCat# 23,225
commercial assay or kitECL blotting substratePierceCat# 32,106
commercial assay or kitExpi293 Expression System KitThermo Fisher ScientificCat# A14635Used for producing EGFR-KD and RON-K1114M proteins for use in kinase assay
chemical compound, drugAfatinibSelleck ChemicalsCat# S1011
chemical compound, drugBMS777607Selleck ChemicalsCat# S1561
chemical compound, drugDasatinibSanta Cruz BiotechnologyCat# sc-358114
chemical compound, drugPD153035EMD MilliporeCat# 234,491
software, algorithmMATLABMathworksRRID:SCR_001622
software, algorithmDIPImageDelf University of Technology
otherQD605 streptavidinThermo Fisher ScientificCat# Q10101MPFor use in SPT
otherQD655 streptavidinThermo Fisher ScientificCat# Q10121MPFor use in SPT
otherprotein A/G magnetic beadsPierceCat# 88,802For use in IP
otherQuantum AlexaFluor 647Bangs LaboratoriesCat# 647 AFor use in receptor quantification on FACS
otherQuantum AlexaFluor 488Bangs LaboratoriesCat# 488 AFor use in receptor quantification on FACS

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting files. Source data for the quantitative plots and gels have been provided.

References

Decision letter

  1. Satyajit Mayor
    Reviewing Editor; Marine Biological Laboratory, United States
  2. Jonathan A Cooper
    Senior Editor; Fred Hutchinson Cancer Research Center, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Decision letter after peer review:

Thank you for submitting your article "EGFR transactivates RON to drive oncogenic crosstalk" for consideration by eLife. Your article has been reviewed by 2 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Jonathan Cooper as the Senior Editor. The reviewers have opted to remain anonymous.

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Summary:

The study by Nitta et al., tries to understand the mechanisms behind the reports of crosstalk between the receptor tyrosine kinases – EGFR and RON. Earlier studies using immunoprecipitation showed that the receptors interact. This new paper provides evidence that the EGFR-RON crosstalk is unidirectional. They also show that this interaction takes place specifically at the membrane, rule out other intermediary molecules between EGFR and RON, and find that, in vitro, RON acts as a substrate of the EGFR kinase domain. The study therefore identifies many mechanistic details about this particular interaction that could be relevant from a clinical standpoint to develop better drugs that can reduce the oncogenic potential of these receptors. From a fundamental biology standpoint, the study reveals novel mechanisms of signal transduction at the membrane. Nevertheless, there are several major concerns.

Essential revisions:

1) The physiological relevance of the experimental system chosen to explore interactions between FGFR and RON is questionable. A431RON cells express approximately 2.2 million EGFR and approximately 92,000 RON receptors per cell. The HEKRON/EGFR cells express approximately 600,000 EGFR per cell and approximately 275,000 RON molecules per cell. The experimental system is therefore too artificial and too synthetic to reveal physiologically relevant quantitative insights for how EGF stimulation induce RON phosphorylation and how the dynamic properties of EGFR are linked to cellular responses that take place in a more physiologically relevant cellular contexts. Moreover, over-expression of EGFR and RON in these cells results in excessive sensitivity and responsiveness towards EGF or MSP stimulation which may not be detected in cells which express lower physiologically relevant levels of the two RTKs. In other words, over-expression may skew the true balance of the trans-phosphorylation reaction and yield flawed conclusions about the dynamic nature of the cellular system that is explored. Key results from this study should be verified in systems that have more physiological levels of the receptors. In particular: Is it possible to detect tyrosine phosphorylation of RON induced by EGF stimulation in cells expressing endogenous RON and EGFR which do not dramatically overexpress at least one of the two receptors ? Are RON and EGFR naturally expressed in the same cells or tissues or is their co-expression taking place only in certain cancer cells ?

2) Is transphosphorylation of RON by EGFR controlled by a tyrosine phosphatase? Does treatment of A431 or HEK cells a tyrosine phosphatase inhibitor also stimulate EGFR induced RON tyrosine phosphorylation ?

3) Colocalization and co-association:

(3a) Fluorescence and EM based-studies: Oligomerization of EGF-R has been a subject of many studies, and it appears from these works that at least a fraction of EGFR exists in oligomeric states in the absence of its ligand. Here the authors show large scale colocalization of RON with EGFR upon stimulation, however the EM-data show a significant fraction of RON- and EGFR co-exist in co-clusters at the resting state.

EM-based colocalization of RON and EGFR before and after stimulation by EGF is not properly quantified. The authors use Ripley's K-co-variate analysis and it is not clear what is being monitored in the lower panel in 1B. A more thorough analysis of the different modes present in this data would be necessary. Homo and hetero oligomer analysis at each time and concentration; EGFR-EGFR analysis, versus RON-RON as well as their co-variance, under all three conditions.

It would be important to understand how homogenous clusters of RON and EGFR change upon EGF and MSP stimulation, as the authors later in the manuscript find a cooperative action of MSP and EGF in activating RON. EM images in 1B quantify only the co-clustering. It will be especially interesting to see how RON homo-clusters change upon EGF stimulation.

Independently, it would be important to see how RON-EGFR co-clusters appear in the absence of ligand-induced activation at a larger spatial scale of the fluorescence based colocalization analysis. This could be achieved by labelling utilizing a fluorescently labelled EGFR and not detecting EGFR with a fluorescent probe that its ligand.

(3b) Immunoprecipitation studies: Separately, in the IP experiments shown in Supplementary Figure 1D, there is no evidence that addition of ligand induces co-association of RON and EGFR. This is in discordance with earlier studies. In fact, the data shown support the opposite; similar levels of co-IP of RON with EGFR with or without 50nM EGF. That phosphorylated RON co-IPs with EGFR after EGF addition is also evident, but this does not mean that kinase active EGFR is associating with RON after ligation. This must be discussed.

(3c) Endosomal Colocalization?:

RON-EGFR, RON-EAA and EGFR-EAA colocalization should be shown before and after activation with EGF, and quantified in order to draw conclusions. Figure 3C does not have a quantification of the colocalization indices that are essential to interpret these results. The authors are implying that the preferential association of EAA (in endosome) with EGFR as compared to RON might be an indication of the kinetics of the dissociation of RON and EGFR. This is not obvious from the data as one can still see a significant colocalization between RON and EGFR visually- presumably at the cell surface. This co-localization also needs to be better quantified, using more sophisticated analysis than simply 'visually looking' at correlated structures. It is also possible that there is an entirely different population of EGFR at the membrane that is being endocytosed that maybe never interacts with RON at all. Hence the conclusion does not follow from the given data.

4) Homo and hetero-oligomers:

Figure 4 clearly provides evidence for the existence of RON homo oligomers at the cell surface in the absence of a ligand, and hetero-dimers with EGF-ligated RON. The results show that EGFR and RON form transient complexes (Figure 4 D-F) and adding to the static picture from the EM data (when properly quantified), this experiment allows the authors to extract a koff for the RON-EGFR interaction, but it is unclear if this koff changes upon ligand activation by either MSP or EGF.

In the methods the authors state "For dual EGFR and RON tracking, cells were incubated with 200 pM 549 anti-HA-QD655 for 15 min at 37{degree sign}C, washed, and then stimulated with 50 pM QD605- 550 conjugated EGF-biotin". If the authors want to understand the interactions between 'activated' EGFR and RON, then it would be useful to introduce 50pM QD-EGF in the backdrop of 50 nM EGF, to visualize the role of activated EGFR. If the authors want a low labelling density to perform SPT, they should use unlabelled EGF at 50nM during the labelling. As the effect of the concentration of EGF is dose dependent, there might be larger changes in the membrane microenvironment caused by the EGFR activation (at 50nM EGF) which might change the rate constants the authors find for this interaction(at 50pM EGF). Ideally, the rate constant should be determined for the RON-EGFR complex in the presence and absence of ligand: a general criticism of this study.

5) Interaction with EGFR:

By citing evidence that receiver or acceptor mutants of EGFR (Zhang et al., 2006) are unable to facilitate RON activation, the authors claim that this is because RON cannot heterodimerize with EGFR monomers, and therefore it is necessary to invoke signalling from higher order clusters like heterotrimers etc. It is entirely possible that activated EGFR monomers which dissociate from activated EGFR dimers with an off rate of about 1.1 per second as determined from their own work (Coban et al., 2015) could be responsible for activating RON monomers or dimers. Though it is clear that EGFR and RON can homo-dimerize and that they can exist in higher order mixed clusters, it is not clear from the experiments in the manuscript whether it's the monomers or the dimers or higher order structures are responsible for this interaction, and hence potentiation of RON activation. However, once again the dimers are short lived and once activated and they may dissociate to form short-lived heterodimers with other membrane molecules, as observed with RON and EGF-liganded EGFR. The results provided only show that inactive EGFR cannot phosphorylate RON. This data is somewhat at odds with EGFR-Δ998 mutant which if anything potentiates RON much better than EGFR. Clearly this part of the manuscript requires a much better explanation.

6) General comments on statistics and data representation:

The authors have used bar plots throughout the manuscript, and this can lead to an inaccurate and incomplete representation of the data. As detailed here:

http://blogs.nature.com/methagora/2014/01/bring-on-the-box-plots-boxplotr.html

https://pagepiccinini.com/2016/02/23/boxplots-vs-barplots/

It would be best if the data is represented as box plots with the all the data points so that the entire distribution can be seen.

The red and green LUTs used in the manuscript might be hard for colour blind readers to understand and it would better if colour blind friendly LUT choices can be made.

7) Finally, the strong statements at the end of the discussion about the identification "of new mechanistic insights into therapeutic resistance" are not warranted and should be toned down.

https://doi.org/10.7554/eLife.63678.sa1

Author response

Essential revisions:

1) The physiological relevance of the experimental system chosen to explore interactions between FGFR and RON is questionable. A431RON cells express approximately 2.2 million EGFR and approximately 92,000 RON receptors per cell. The HEKRON/EGFR cells express approximately 600,000 EGFR per cell and approximately 275,000 RON molecules per cell. The experimental system is therefore too artificial and too synthetic to reveal physiologically relevant quantitative insights for how EGF stimulation induce RON phosphorylation and how the dynamic properties of EGFR are linked to cellular responses that take place in a more physiologically relevant cellular contexts. Moreover, over-expression of EGFR and RON in these cells results in excessive sensitivity and responsiveness towards EGF or MSP stimulation which may not be detected in cells which express lower physiologically relevant levels of the two RTKs. In other words, over-expression may skew the true balance of the trans-phosphorylation reaction and yield flawed conclusions about the dynamic nature of the cellular system that is explored.

We would like to emphasize that the goal of this work was to study RON/EGFR crosstalk in the context of cancers where receptor tyrosine kinases are frequently overexpressed and can number in the millions of receptors per cell. RON and EGFR are indeed found to be co-overexpressed and linked to poor outcomes or resistance to targeted therapies in a number of tumor types including, colon (Graves-Deal 2019 PMC6407678), head and neck (Keller, 2013 PMC3721396) and bladder cancers (Hsu 2006 PMID: 17070309). Previous work in this area that we build upon has also focused on the cancer setting and has predominantly relied on cell lines with receptor overexpression to interrogate RON-EGFR interactions (Hsu 2006 PMID: 17070309; Peace 2003 PMID: 14499632). To ensure that the crosstalk was not an artifact of a single cell type, we studied two different cell lines (A431 and HEK-293) with different expression levels/ratios. Notably, RON isoforms or EGFR oncogenic mutants, which may be present in cell lines endogenously expressing these receptors, have also been shown to play roles in cancer and could influence RON/EGFR interactions (Krishnaswamy 2015 PMC4723846; Krishnaswamy 2017 PMC5679369). We chose to focus here on the interaction of full-length wildtype receptors. Therefore, while our work does not directly address the question of how RON and EGFR interact under normal physiological levels, we do provide support for the ability of RON and EGFR to interact in cancer systems, and importantly, we provide new insight into the molecular mechanisms of this interaction.

Key results from this study should be verified in systems that have more physiological levels of the receptors. In particular: Is it possible to detect tyrosine phosphorylation of RON induced by EGF stimulation in cells expressing endogenous RON and EGFR which do not dramatically overexpress at least one of the two receptors ? Are RON and EGFR naturally expressed in the same cells or tissues or is their co-expression taking place only in certain cancer cells ?

The reviewer raises an interesting and important point. RON and EGFR are both found in epithelial cells including skin, colon, bladder, breast and lung (Sakamoto 1997 PMID: 9045873, Wang 2007 PMID: 17955509, Chen 2016 PMID: 33003261), so there is potential for interactions under normal physiological conditions. We agree with the reviewer that it would be important to explore RON/EGFR interactions under more physiological conditions. We attempted to pursue this suggestion, however, as described below, the results were inconsistent.

We first identified several cell lines that endogenously co-express EGFR and RON at low/more physiological levels, based on RNA expression from the Human Protein Atlas database. These included MCF7, A549, HEK, HCT116 and SKBR3. Of these, we only found HCT and SKBR3 to show detectable expression of EGFR and RON by western blot (example blots shown in Author response image 1). Immunoprecipitation of RON with an anti-RON antibody revealed a phosphotyrosine (pY99) band in the unstimulated HCT116 cells. However, this band was only visible in about half of the blots and when visible its intensity was reduced with ligand stimulation (Author response image 1A) . This suggested to us that the band may not truly be related to RON. By using two-color Western Blot analysis, it was made clear that the pY99 band was not aligned with pro-RON (Author response image 1B) , since it was located just below the total RON bands. This result highlights the importance of our two-color western blot approach used throughout the manuscript, where all phosphorylation was confirmed to overlay with the proper total protein band. It also demonstrates that detection of endogenous/low-level RON protein will be complicated given the current available reagents and requires more time to follow up thoroughly.

Author response image 1
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Detection of RON and EGFR in human cancer cell lines with low, endogenous expression of both receptors.

HCT116 colorectal carcinoma cells, SKBR3 breast cancer cells and A549 lung carcinoma cells were cultured overnight and then stimulated with 50 nM EGF or 5 nM MSP for 5 min. (A) RON receptor was IP’d with an anti-RON antibody and phosphorylated proteins in the IP were detected using a pY99 antibody. Here, detection was with HRP-antibodies. (B) Total cell lysates were run on a western blot and phosphoEGFR (pY1068) and total EGFR were detected. (C) Two-color detection using fluorescently-labeled antibodies for western using HCT116 cells. The phosphorylated protein does not overlap with full-length RON in the IP samples. The phosphorylated protein could be a truncated RON isoform or a different protein that co-Ips with RON in these cells. (D) The phospho-EGFR band does overlap with the full-length EGFR band.

While it was difficult to detect endogenous RON phosphorylation in these cells, the detection of EGFR phosphorylation was consistent and further confirms that MSP does not lead to EGFR phosphorylation under these cellular conditions Author response image 1B, D. We feel that understanding EGFR/RON crosstalk at physiological expression levels, while interesting and important, is beyond the scope of this paper. Determining the similarities or differences in physiological versus oncogenic signaling does not preclude the results of our paper or the previous work showing crosstalk in the oncogenic/overexpression context.

2) Is transphosphorylation of RON by EGFR controlled by a tyrosine phosphatase? Does treatment of A431 or HEK cells a tyrosine phosphatase inhibitor also stimulate EGFR induced RON tyrosine phosphorylation ?

We believe that the reviewers are asking whether crosstalk could be due to an indirect mechanism where an EGFR-controlled phosphatase is regulating RON. For example, recruitment of a phosphatase to EGFR could remove it from RON, allowing for RON phosphorylation. In general, all phosphorylation is regulated by phosphatases and phosphatase inhibition will result in increased phosphorylation of both RON and EGFR. However, we would not be able to parse out the difference between EGFR-controlled phosphatases and general phosphatase activity. Therefore, this experiment would not be able to directly identify an EGFR-controlled phosphatase regulation of RON. While it is possible that phosphatases are playing a role, our in vitro kinase assay (Figure 6C) shows that phosphatases are not required because the EGFR kinase domain alone can phosphorylate the RON tail.

We note also that in Figure 6—figure supplement 2, we show that RON has similar dephosphorylation kinetics whether transactivated by WT EGFR or EGFR-Δ998 (that lacks the major sites for cytosolic protein recruitment and signal propagation). If EGFR signaling was needed to recruit or activate phosphatases, we would have expected RON dephosphorylation to be altered with EGFR-Δ998, but no difference was seen.

(3) Colocalization and co-association:

(3a) Fluorescence and EM based-studies: Oligomerization of EGF-R has been a subject of many studies, and it appears from these works that at least a fraction of EGFR exists in oligomeric states in the absence of its ligand. Here the authors show large scale colocalization of RON with EGFR upon stimulation, however the EM-data show a significant fraction of RON- and EGFR co-exist in co-clusters at the resting state.

In this study, we have used confocal and electron microscopy to demonstrate the potential for RON and EGFR interactions. Due to their limitations, both methods suggest, but neither prove, the existence of homo- or hetero-oligomers. For example, confocal microscopy is limited by a resolution of ~250 nm. Therefore, while two distinctly labeled receptors may show colocalization, this does not confirm interactions, since proteins are ~ a factor of 10 smaller than this diffraction limit. That being said, if no colocalization is seen, then it would strongly suggest a low probability of interaction. In a similar manner, EM can provide higher resolution evidence of protein proximity, indicating clustering or exclusion. However, observation of protein (co-) clustering does not confirm physical oligomerization/interactions. It is well appreciated that the membrane can form domains (actin corrals, lipid rafts, protein islands) that can organize proteins into clusters, even in the resting state, without the proteins themselves directly interacting. Therefore, while RON and EGFR appear to homo- and hetero-cluster in the EM images, we cannot use this as proof of oligomerization. The intent of these data was to determine, as a first step, whether the two receptors are within close enough proximity to potentially interact. We turned to other methods, in particular two-color SPT, to detect the direct interactions of receptors.

EM-based colocalization of RON and EGFR before and after stimulation by EGF is not properly quantified. The authors use Ripley's K-co-variate analysis and it is not clear what is being monitored in the lower panel in 1B.

We thank the reviewers for pointing out our insufficient description of the EM analysis. The method presented is the Ripley’s K bivariate test (also called cross-type Ripley’s K Function) that is used to define the spatial relationship of two different sizes of gold particles (i.e., two different protein species). In the analysis presented in (revised) Figure 2B, the experimental values for L(r)-r (red line) is plotted as a function of distance (r). The dashed lines represent the values of L(r) for complete spatial randomness with a 99% confidence envelope (estimated from 100 Monte Carlo simulations for each ROI analyzed). When the experimental values fall above the confidence interval, the deviation from complete spatial randomness is statistically significant and indicates that the two labels show co-clustering. This has been used by our group in a number of previous publications (Wilson 2004 PMC420084; Yang et al., JCS 2007 PMID 17652160) and is distinct from Ripley’s K test that determines L(r)-r for a single species. We have expanded the description in the figure legend and methods to make this clearer.

We have added the following to the legend of Figure 2:

“Ripley’s K bivariant function was used to evaluate co-clustering. The experimental values for L(r)-r (corresponding to EM image directly above) are shown in magenta and the 99% confidence window for complete spatial randomness is plotted as dashed lines. In each case, experimental values are seen to fall above the confidence window, indicating co-clustering.”

As well as adding the following to the Methods (p. 32):

“Ripley's bivariate K test was used to determine if co-clustering of species is significant (Wilson et al., 2004; Yang et al., 2007), with a critical interaction distance of 50 nm. Data within the confidence window are not significantly co-clustered. When the experimental values are found above the confidence window the deviation from complete spatial randomness is statistically significant and indicates that the two labels are co-clustering.”

A more thorough analysis of the different modes present in this data would be necessary. Homo and hetero oligomer analysis at each time and concentration; EGFR-EGFR analysis, versus RON-RON as well as their co-variance, under all three conditions.

It would be important to understand how homogenous clusters of RON and EGFR change upon EGF and MSP stimulation, as the authors later in the manuscript find a cooperative action of MSP and EGF in activating RON. EM images in 1B quantify only the co-clustering. It will be especially interesting to see how RON homo-clusters change upon EGF stimulation.

We agree that further study of the lateral organization of RON and EGFR under a range of activation conditions would be of interest. However, a full examination of all possible combinations is not needed for the current manuscript’s focus on understanding whether EGFR and RON are capable of undergoing direct interactions. We also realize that the initial order of the figures may have been distracting, since we showed a focus on EGF stimulation of cells, before we explained that the crosstalk only occurs with EGF and not MSP stimulation. We have re-ordered the manuscript so that biochemical analysis of the crosstalk is the first figure, followed by confocal and EM imaging.

We have included additional analysis of the existing EM data in Figure 2—figure supplement 2. We provide a larger view of an EM sheet for each condition, along with the corresponding Hopkin’s statistical test for homoclustering. The Hopkin’s statistic confirms that each receptor is already found to homocluster in the resting state. We also provide mean statistics across multiple images for Hopkin’s, percent of receptors found in homoclusters and percent of receptors found in coclusters. We do not observe a significant change in these quantities as a function of EGF activation, however the clustering/coclustering is quite high to start with in the A431RON cells. Future studies would be better performed on cells with a lower expression level in order to determine if subtle changes could be detected. This, however, requires generation of new cell lines and is ongoing work.

Independently, it would be important to see how RON-EGFR co-clusters appear in the absence of ligand-induced activation at a larger spatial scale of the fluorescence based colocalization analysis. This could be achieved by labelling utilizing a fluorescently labelled EGFR and not detecting EGFR with a fluorescent probe that its ligand.

We thank the reviewers for the suggestion to expand the colocalization analysis. We have now included further immunofluorescence experiments and analysis comparing RON colocalization with either fluorescent EGF or an anti-EGFR antibody (Figure 2—figure supplement Figure 1). Quantification of colocalization for the confocal images is also included. This shows that RON is colocalized with both resting (unliganded) EGFR and EGF-bound EGFR on the plasma membrane. This is consistent with the observation in EM that shows co-clustering in both resting and EGF-activated cells.

(3b) Immunoprecipitation studies: Separately, in the IP experiments shown in Supplementary Figure 1D, there is no evidence that addition of ligand induces co-association of RON and EGFR. This is in discordance with earlier studies. In fact, the data shown support the opposite; similar levels of co-IP of RON with EGFR with or without 50nM EGF. That phosphorylated RON co-IPs with EGFR after EGF addition is also evident, but this does not mean that kinase active EGFR is associating with RON after ligation. This must be discussed.

In our results, we report that EGFR can co-IP with RON even in the absence of ligand. This is consistent with earlier studies (Peace 2003 PMID: 14499632, Hsu 2006 PMID: 17070309) where they also show co-IP in the absence of ligand. Where there is some difference, is in the fact that we do not see a consistent increase in EGFR pulldown with RON after ligand stimulation. However, there are significant differences in our approaches that likely account for this. Peace et al. does not emphasize an increase with ligand, but does highlight the pre-association in the absence of ligand (Peace 2003, Figures 4 and 5), as we have also seen. Hsu suggests an increase in co-IP between RON and EGFR with MSP stimulation (Figure 1A of Hsu 2006), yet only a single blot is shown and the blots are not quantified. It is also important to point out that these blots used the strip-and-reprobe approach, while we used simultaneous two-color imaging that removes potential stripping artifacts. Furthermore, both of these studies performed co-IPs at 30 min post-stimulation. We are looking at early events and perform most biochemical experiments at 5 min post-stimulation. Finally, we note that we could not always see evidence of co-IP, suggesting a weak interaction. We have modified the text on p. 7 to highlight these points:

“EGFR was often detected in RON immunoprecipitates, in both resting and stimulated cells, as a band co-migrating with pro-RON at 180 kDa via western blot analysis (using EGFR or EGFRPY1068 antibodies) or identified by mass spectrometry, (Figure 1 – Supplementary Figure 1D and Supplementary Table 1). Co-immunoprecipitation of RON and EGFR in unstimulated cells has been reported previously (Hsu et al., 2006; Peace et al., 2003). In contrast to that previous work, we do not observe an increase in co-precipitation with ligand stimulation. However, we note that co-IP was not always evident, suggesting weak interactions, and our experiments were performed at earlier time points (5 min) than the previous studies (30 min).”

We have mentioned in the discussion that the dynamics of the EGFR-RON interaction in the absence of ligand remain to be determined. However, even without that information, it is clear from our data that crosstalk occurs via EGFR interacting with RON such that the EGFR kinase can phosphorylate RON.

(3c) Endosomal Colocalization?:

RON-EGFR, RON-EAA and EGFR-EAA colocalization should be shown before and after activation with EGF, and quantified in order to draw conclusions. Figure 3C does not have a quantification of the colocalization indices that are essential to interpret these results. The authors are implying that the preferential association of EAA (in endosome) with EGFR as compared to RON might be an indication of the kinetics of the dissociation of RON and EGFR. This is not obvious from the data as one can still see a significant colocalization between RON and EGFR visually- presumably at the cell surface. This co-localization also needs to be better quantified, using more sophisticated analysis than simply 'visually looking' at correlated structures. It is also possible that there is an entirely different population of EGFR at the membrane that is being endocytosed that maybe never interacts with RON at all. Hence the conclusion does not follow from the given data.

Thank you for this suggestion. We have now confirmed the lack of RON found in early endosomes with colocalization analysis (Figure 3—figure supplement 2). We have also performed additional experiments to examine EGFR and RON localization using a second labeling method (Figure 2D). The conclusion that we take from the results in Figure 3 (including the SPT and EM) is that productive EGFR and RON interactions occur soon after EGF addition – while both receptors are still at the plasma membrane. This was important to determine since earlier studies (Hsu, et al.; Peace et al.) were performed at 30 min post-stimulation, a time at which most stimulated receptors would be expected to have endocytosed, so location of crosstalk was not clear. It is intriguing to consider, as suggested by the reviewer, that EGFR bound to RON is held longer on the membrane. We have expanded the text on p. 12 to indicate this possibility:

“These results suggest that EGFR/RON interactions are either sufficiently transient that EGFR is sorted for endocytosis, while RON remains on the surface, or that EGFR complexed with RON is retained longer on the cell surface.”

We assert that either way our conclusion is not changed: EGFR and RON interact at the plasma membrane and signaling from endosomes is not required.

4) Homo and hetero-oligomers:

Figure 4 clearly provides evidence for the existence of RON homo oligomers at the cell surface in the absence of a ligand, and hetero-dimers with EGF-ligated RON. The results show that EGFR and RON form transient complexes (Figure 4 D-F) and adding to the static picture from the EM data (when properly quantified), this experiment allows the authors to extract a koff for the RON-EGFR interaction, but it is unclear if this koff changes upon ligand activation by either MSP or EGF.

In the methods the authors state "For dual EGFR and RON tracking, cells were incubated with 200 pM 549 anti-HA-QD655 for 15 min at 37{degree sign}C, washed, and then stimulated with 50 pM QD605- 550 conjugated EGF-biotin". If the authors want to understand the interactions between 'activated' EGFR and RON, then it would be useful to introduce 50pM QD-EGF in the backdrop of 50 nM EGF, to visualize the role of activated EGFR. If the authors want a low labelling density to perform SPT, they should use unlabelled EGF at 50nM during the labelling. As the effect of the concentration of EGF is dose dependent, there might be larger changes in the membrane microenvironment caused by the EGFR activation (at 50nM EGF) which might change the rate constants the authors find for this interaction(at 50pM EGF). Ideally, the rate constant should be determined for the RON-EGFR complex in the presence and absence of ligand: a general criticism of this study.

We have focused this manuscript on EGF-bound EGFR because this is the condition where crosstalk was observed. While adding to the overall picture, quantifying interactions between unliganded EGFR and RON is not necessary to the new insights already provided here: EGFRRON undergo bona fide interactions under the conditions where signaling is happening (ie, the presence of EGF). We do agree that this is important information to continue to pursue and such work is ongoing in the lab. We are working on developing orthogonal labeling methods (including QD-MSP) to allow for capturing of EGFR and RON interactions in the absence of EGF or in response to MSP. One could imagine a large number of experiments to exhaustively quantify RON-RON, RON-EGFR and EGFR-EGFR interactions across multiple ligands and doses. This would warrant a separate publication. Showing the direct interaction between EGF-bound EGFR and unliganded RON (the situation where crosstalk occurs), as we have done here, is a critical step forward in our mechanistic understanding of crosstalk.

We understand the experiment to use a high dose dark EGF that is being suggested. However, there are difficulties in performing and interpreting the proposed experiments. That high amount of ligand activation leads to rapid cell morphology changes and endocytosis of EGFR that makes capturing dimer events on the cell surface difficult. Also, the saturation of all receptors with ligand, the majority of which are dark, make it much less probable that two QD-labeled receptors will find each other and form dimers when they have an abundance of dark EGF-EGFR with which to interact. Therefore, we are not confident in the interpretation of this approach and prefer to follow up with new technologies currently under development to address this sort of question.

5) Interaction with EGFR:

By citing evidence that receiver or acceptor mutants of EGFR (Zhang et al., 2006) are unable to facilitate RON activation, the authors claim that this is because RON cannot heterodimerize with EGFR monomers, and therefore it is necessary to invoke signalling from higher order clusters like heterotrimers etc. It is entirely possible that activated EGFR monomers which dissociate from activated EGFR dimers with an off rate of about 1.1 per second as determined from their own work (Coban et al., 2015) could be responsible for activating RON monomers or dimers. Though it is clear that EGFR and RON can homo-dimerize and that they can exist in higher order mixed clusters, it is not clear from the experiments in the manuscript whether it's the monomers or the dimers or higher order structures are responsible for this interaction, and hence potentiation of RON activation. However, once again the dimers are short lived and once activated and they may dissociate to form short-lived heterodimers with other membrane molecules, as observed with RON and EGF-liganded EGFR. The results provided only show that inactive EGFR cannot phosphorylate RON. This data is somewhat at odds with EGFR-Δ998 mutant which if anything potentiates RON much better than EGFR. Clearly this part of the manuscript requires a much better explanation.

We thank the reviewer for pointing out our limited interpretation of the results. Crosstalk certainly could be happening as described, where an EGFR dimer forms, activates and dissociates to then interact with RON.

We have modified the discussion on p. 26 to reflect this possibility:

“We found that RON cannot serve as an activator or receiver kinase in an EGFR/RON heterodimer. Instead, formation of a signaling-competent EGFR homodimer appears to be first required to initiate EGF-driven RON phosphorylation. Considering that RON homo-interactions were observed by two-color SPT in both resting and liganded states, we postulate that the heterocomplex consists of a RON dimer interacting with a ligand-bound EGFR dimer or EGFR monomer that has recently dissociated from a homodimer after kinase activation.”

Either way, it seems that RON cannot act as the activator to EGFR. Therefore, RON cannot simply substitute for an activator or receiver in a possible EGFR-RON pair.

This data is not necessarily at odds with the EGFR-Δ998, as that mutant retains an active kinase. We have added discussion about how the removal of the EGFR tail might augment RON phosphorylation (p. 26):

“It is also conceivable that adaptor proteins recruited to the EGFR tail (Biscardi et al., 1999; Yamauchi et al., 1998) could subsequently phosphorylate RON. However, we found that neither inhibition of c-Src activity nor removal of the EGFR cytoplasmic tail (EGFR-Δ998) prevented crosstalk with RON. Adaptor proteins may explain the enhanced phosphorylation of RON that was seen in cells expressing EGFR-Δ998. For instance, Grb2 has been reported to inhibit RON autophosphorylation, raising the possibility that loss of Grb2 recruitment by EGFR-Δ998 could reduce local Grb2 concentration and increase RON phosphorylation. Alternatively, removal of the EGFR C-terminal tail diminishes the recruitment of downstream EGFR substrates, limiting substrate competition and making the RON C-terminal tail the preferred substrate in the heterooligomeric complexes. Together, along with the identification of RON as a substrate for EGFR kinase, our results establish that crosstalk is mediated by receptor-receptor interactions.”

6) General comments on statistics and data representation:

The authors have used bar plots throughout the manuscript, and this can lead to an inaccurate and incomplete representation of the data. As detailed here:

http://blogs.nature.com/methagora/2014/01/bring-on-the-box-plots-boxplotr.html

https://pagepiccinini.com/2016/02/23/boxplots-vs-barplots/

It would be best if the data is represented as box plots with the all the data points so that the entire distribution can be seen.

The red and green LUTs used in the manuscript might be hard for colour blind readers to understand and it would better if colour blind friendly LUT choices can be made.

We thank the reviewers for these excellent suggestions. All bar graphs have been reformatted to include individual data points overlayed with the mean +/- SD.

The images have been changed to color blind friendly LUT throughout.

7) Finally, the strong statements at the end of the discussion about the identification "of new mechanistic insights into therapeutic resistance" are not warranted and should be toned down.

We have toned down this section, modifying the discussion on p. 26-27:

“While further study is needed to determine the exact stoichiometry of the EGFR/RON complex, the molecular mechanisms governing EGFR/RON crosstalk described here suggest that disruption of interactions between RON and EGFR could provide a therapeutic advantage. In particular, we have shown that RON signaling outcomes can be stimulated by EGFR in the absence of MSP and even if RON kinase activity is inhibited.”

https://doi.org/10.7554/eLife.63678.sa2

Article and author information

Author details

  1. Carolina Franco Nitta

    Department of Pathology, University of New Mexico, Albuquerque, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Writing – original draft, Software
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9122-5453

  2. Ellen W Green

    Department of Pathology, University of New Mexico, Albuquerque, United States
    Contribution
    Conceptualization, Investigation, Methodology, Resources, Software
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2083-522X

  3. Elton D Jhamba

    Department of Pathology, University of New Mexico, Albuquerque, United States
    Contribution
    Formal analysis, Investigation, Methodology, Software
    Competing interests
    No competing interests declared

  4. Justine M Keth

    Department of Pathology, University of New Mexico, Albuquerque, United States
    Contribution
    Investigation, Methodology, Software
    Competing interests
    No competing interests declared

  5. Iraís Ortiz-Caraveo

    Department of Pathology, University of New Mexico, Albuquerque, United States
    Contribution
    Investigation, Methodology, Software
    Competing interests
    No competing interests declared

  6. Rachel M Grattan

    Department of Pathology, University of New Mexico, Albuquerque, United States
    Contribution
    Formal analysis, Investigation, Methodology, Software
    Competing interests
    No competing interests declared

  7. David J Schodt

    Department of Physics & Astronomy, University of New Mexico, Albuquerque, United States
    Contribution
    Data curation, Formal analysis, Supervision, Software
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8986-2736

  8. Aubrey C Gibson

    Department of Pathology, University of New Mexico, Albuquerque, United States
    Contribution
    Investigation, Methodology, Software
    Competing interests
    No competing interests declared

  9. Ashwani Rajput

    1. Department of Surgery, University of New Mexico, Albuquerque, United States
    2. Comprehensive Cancer Center, University of New Mexico, Albuquerque, United States
    Contribution
    Conceptualization, Software
    Competing interests
    No competing interests declared

  10. Keith A Lidke

    1. Department of Physics & Astronomy, University of New Mexico, Albuquerque, United States
    2. Comprehensive Cancer Center, University of New Mexico, Albuquerque, United States
    Contribution
    Data curation, Formal analysis, Supervision, Funding acquisition, Software
    Competing interests
    No competing interests declared

  11. Bridget S Wilson

    1. Department of Pathology, University of New Mexico, Albuquerque, United States
    2. Comprehensive Cancer Center, University of New Mexico, Albuquerque, United States
    Contribution
    Conceptualization, Project administration, Funding acquisition, Writing – original draft, Software
    Competing interests
    No competing interests declared

  12. Mara P Steinkamp

    1. Department of Pathology, University of New Mexico, Albuquerque, United States
    2. Comprehensive Cancer Center, University of New Mexico, Albuquerque, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Resources, Funding acquisition, Writing – original draft, Software
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1226-9325

  13. Diane S Lidke

    1. Department of Pathology, University of New Mexico, Albuquerque, United States
    2. Comprehensive Cancer Center, University of New Mexico, Albuquerque, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Project administration, Writing – review and editing, Funding acquisition, Writing – original draft, Software
    For correspondence
    dlidke@salud.unm.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8533-6029

Funding

National Institutes of Health (R35GM126934)

  • Diane S Lidke

National Institutes of Health (R21GM132716)

  • Keith Lidke

New Mexico Spatiotemporal Modeling Center (P50GM085273)

  • Bridget S Wilson
  • Diane S Lidke

University of New Mexico (Undergraduate Pipeline Network P30CA118100)

  • Justine M Keth
  • Aubrey C Gibson

ASERT-IRACDA (K12GM088021)

  • Elton D Jhamba

National Institutes of Health (R01CA248166)

  • Diane S Lidke

University of New Mexico (MARC Program 2T34GM008751)

  • Justine M Keth

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Dr. Peter Cooke of the Electron Microscopy Laboratory at New Mexico State University for access to a Hitachi H-7650 TEM. Mass spectrometry data was generated at the UT Southwestern Proteomics Core. We thank Shayna Lucero for assistance with cell culture and flow cytometry, Dr. Michael Wester for assistance with EM analysis, Dr. Mohamad Fazel for assistance with single particle tracking analysis, Eric Burns for assistance with SPT data collection, Danielle Burke for western blot assistance, and Dr. Chris Valley and Russell Hunter for plasmid preparations. We thank Dr. Mark Lemmon for helpful discussions and suggestions on the manuscript. We gratefully acknowledge use of the University of New Mexico Comprehensive Cancer Center fluorescence microscopy and flow cytometry facilities, as well as the NIH P30CA118100 support for these cores.

Senior Editor

  1. Jonathan A Cooper, Fred Hutchinson Cancer Research Center, United States

Reviewing Editor

  1. Satyajit Mayor, Marine Biological Laboratory, United States

Version history

  1. Preprint posted: August 12, 2020 (view preprint)
  2. Received: October 2, 2020
  3. Accepted: November 24, 2021
  4. Accepted Manuscript published: November 25, 2021 (version 1)
  5. Version of Record published: December 8, 2021 (version 2)

Copyright

© 2021, Franco Nitta et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Carolina Franco Nitta
  2. Ellen W Green
  3. Elton D Jhamba
  4. Justine M Keth
  5. Iraís Ortiz-Caraveo
  6. Rachel M Grattan
  7. David J Schodt
  8. Aubrey C Gibson
  9. Ashwani Rajput
  10. Keith A Lidke
  11. Bridget S Wilson
  12. Mara P Steinkamp
  13. Diane S Lidke
(2021)
EGFR transactivates RON to drive oncogenic crosstalk
eLife 10:e63678.
https://doi.org/10.7554/eLife.63678

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