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Hyperactivation of ERK by multiple mechanisms is toxic to RTK-RAS mutation-driven lung adenocarcinoma cells

  1. Arun M Unni  Is a corresponding author
  2. Bryant Harbourne
  3. Min Hee Oh
  4. Sophia Wild
  5. John R Ferrarone
  6. William W Lockwood  Is a corresponding author
  7. Harold Varmus  Is a corresponding author
  1. Weill Cornell Medicine, United States
  2. British Columbia Cancer Agency, Canada
  3. University of British Columbia, Canada
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Cite this article as: eLife 2018;7:e33718 doi: 10.7554/eLife.33718

Abstract

Synthetic lethality results when mutant KRAS and EGFR proteins are co-expressed in human lung adenocarcinoma (LUAD) cells, revealing the biological basis for mutual exclusivity of KRAS and EGFR mutations. We have now defined the biochemical events responsible for the toxic effects by combining pharmacological and genetic approaches and to show that signaling through extracellular signal-regulated kinases (ERK1/2) mediates the toxicity. These findings imply that tumors with mutant oncogenes in the RAS pathway must restrain the activity of ERK1/2 to avoid toxicities and enable tumor growth. A dual specificity phosphatase, DUSP6, that negatively regulates phosphorylation of (P)-ERK is up-regulated in EGFR- or KRAS-mutant LUAD, potentially protecting cells with mutations in the RAS signaling pathway, a proposal supported by experiments with DUSP6-specific siRNA and an inhibitory drug. Targeting DUSP6 or other negative regulators might offer a treatment strategy for certain cancers by inducing the toxic effects of RAS-mediated signaling.

https://doi.org/10.7554/eLife.33718.001

Introduction

Extensive characterization of cancer genomes has begun to change the classification of neoplasms and the choice of therapies (Garraway and Lander, 2013). The genetic profiles of most cancers are notoriously heterogeneous, often including thousands of mutations affecting genes with a wide range of credentials---from those well-known to drive oncogenic behavior to those not known to have a role in pathogenesis. Moreover, cancers continue to accumulate mutations during carcinogenesis, producing tumor subclones with selectable features such as drug resistance or enhanced growth potential (McGranahan and Swanton, 2017).

Despite this heterogeneity, consistent patterns have been observed, such as the high frequency of gain-of-function or loss-of-function mutations affecting specific proto-oncogenes or tumor suppressor genes in cancers that arise in certain cell lineages. Conversely, coincident mutations in certain genes are rare, even when those genes are frequently mutated individually in specific types of cancer (Kandoth et al., 2013). Examples of these ‘mutually exclusive’ pairs of mutations have been reported in a variety of cancers (Yoshida et al., 2011; Unni et al., 2015; Petti et al., 2006; Sensi et al., 2006; Varmus et al., 2016); the mutual exclusivity has usually been attributed either to a loss of a selective advantage of a mutation in one gene after a change in the other has occurred (‘functional redundancy’) or to the toxicity (including ‘synthetic lethality’) conferred by the coexistence of both mutations in the same cells.

We recently reported that the mutual exclusivity of gain-of-function mutations of EGFR and KRAS, two proto-oncogenes often individually mutated in lung adenocarcinomas (LUADs), can be explained by such synthetic toxicity, despite the fact that products of these two genes operate in overlapping signaling pathways and might have been mutually exclusive because of functional redundancies (Unni et al., 2015). Support for the idea that the mutual exclusivity of KRAS and EGFR mutations is synthetically toxic in LUAD cells was based largely on experiments in which we used doxycycline (dox) to induce expression of mutant EGFR or KRAS alleles controlled by a tetracycline (tet)-responsive regulatory apparatus in LUAD cell lines containing endogenous mutations in the other gene (Unni et al., 2015). When we forced mutual expression of the pair of mutant proteins, the cells exhibited signs of RAS-induced toxicity, such as macropinocytosis and cell death. In addition, we observed increased phosphorylation of several proteins known to operate in the extensive signaling network downstream of RAS, implying that excessive signaling, driven by the conjunction of hyperactive EGFR and KRAS proteins, might be responsible for the observed toxicity.

Recognizing that such synthetic toxicities might be exploited for therapeutic purposes, we have extended our studies of signaling via the EGFR-RAS axis, with the goal of better understanding the biochemical events that are responsible for the previously observed toxicity in LUAD cell lines. In the work reported here, we have used a variety of genetic and pharmacological approaches to seek evidence that identifies critical mediators of the previously observed toxicities. Based on several concordant findings, we argue that activation of extracellular signal-regulated kinases (ERK1 and ERK2), serine/threonine kinases in the EGFR-RAS-RAF-MEK-ERK pathway, is a critical event in the generation of toxicity, and we show that at least one feedback inhibitor of the pathway, the dual specificity phosphatase, DUSP6, is a potential target for therapeutic inhibitors that could mimic the synthetic toxicity that we previously reported.

Results

Synthetic lethality induced by co-expression of mutant KRAS and EGFR is mediated through increased ERK signaling

In previous work, we established that mutant EGFR and mutant KRAS are not tolerated in the same cell (synthetic lethality), by placing one of these two oncogenes under the control of an inducible promoter in cell lines carrying a mutant allele of the other oncogene. These experiments provided a likely explanation for the pattern of mutual exclusivity in LUAD (Unni et al., 2015). While we documented several changes in cellular signaling upon induction of the second oncogene to produce toxicity, we did not establish if there is a node (or nodes) in the signaling network sensed by the cell as intolerable when both oncoproteins are produced. If such a node exists, we might be able to prevent toxicity by down-modulating the levels of activity; conversely, we might be able to exploit identification of that node to compromise or kill cancer cells.

To seek critical nodes in the RAS signaling pathway, we extended our previous study using the LUAD cell line we previously characterized (PC9, bearing the EGFR mutation, E746_A750del) and two additional LUAD lines, H358 and H1975. H358 cells express mutant KRAS (G12C), and H1975 cells express mutant EGFR (L858R/T790M). As in our earlier work, we introduced tet-regulated, mutant KRAS (G12V) into these lines to regulate mutant KRAS in an inducible manner and used the same vector encoding GFP rather than KRAS as a control. This single-vector system includes rtTA constitutively expressed from a ubiquitin promoter, allowing us to induce KRAS with the addition of dox (Meerbrey et al., 2011).

KRAS or GFP were appropriately induced after adding dox to the growth medium used for these cell lines (Figure 1A). To establish whether induction of a mutant KRAS transgene is detrimental to H358 cells producing endogenous mutant KRAS or H1975 cells producing mutant EGFR proteins, we cultured cell lines in dox for 7 days and measured the relative numbers of viable cells with Alamar blue. As we previously showed, the number of viable PC9 cells is reduced by inducing mutant KRAS (Figure 1A). Similarly, when mutant KRAS was induced in either H358 or H1975 cells for seven days, we observed fewer viable cells compared to cells grown without dox or to cells in which GFP was induced (Figure 1A). These results indicate that increased activity of the RAS pathway, either in LUAD cells with an endogenous KRAS mutation (H358 cells) or with an endogenous EGFR mutation (PC9 and H1975 cells) is toxic to these cell lines.

Figure 1 with 1 supplement see all
Induction of mutant KRAS reduces the numbers of viable lung cancer cells harboring KRAS or EGFR mutations, and the effects can be rescued by inhibiting ERK (A) Reduced numbers of viable LUAD cells after activation of KRAS.

Production of GFP or KRASG12V was induced by addition of 100 ng/mL dox in the indicated three cell lines as described in Methods. GFP and KRAS protein levels were measured by Western blotting 24 hr later. (top); tubulin served as a loading control. The numbers of viable cells, normalized to cells grown in the absence of dox (set to 1.0), were determined by measuring with Alamar blue six days later. Error bars represent standard deviations based on three replicates. (B) Induction of KRASG12V uniquely increases phosphorylation of ERK1/2 among several phosphoproteins. PC9-tetO-KRAS cells were treated with dox for 24 hr and cell lysates incubated on an array to detect phosphorylated proteins. Fold changes of phosphorylation compared with lysates from untreated cells (set to 1.0, dotted line) to treated cells is presented from a single antibody array. Error bars are derived from duplicate spots on antibody array. The detection of HSP60 and ß-catenin are of total protein, not phosphoprotein. (C) Phosphorylation of ERK occurs early after induction of mutant KRAS. Lysates prepared as described for panel (A) were probed for the indicated proteins by western blot. Loading control is the same as in A. (D) Drug-mediated inhibition of the MEK1/2 kinases ameliorates KRAS-induced loss of viable cells. Mutant KRAS was induced with dox in the three indicated cell lines in the absence and presence of trametinib at the indicated dose for 7 days. The relative number of viable cells was measured with Alamar blue. Error bars represent standard deviations determined from three samples grown under each set of conditions. Values are normalized to measurements of cells that received neither dox nor trametinib (bottom). Cells were treated with dox and with or without trametinib for 24 hr at the dose conferring rescue of numbers of viable cells. Lysates were probed for indicated proteins to confirm inhibition of MEK. (E) Reduction of ERK proteins with inhibitory small hairpin (sh) RNAs protects cells from loss of viability in response to induction of mutant KRAS. LUAD cell lines, transduced with the indicated shRNA targeted against ERK1 or ERK2, were assessed for levels of ERK proteins, p42 and p44, by Western blotting (top panels). The same lines were treated with dox for 7 days and the number of viable cells measured with Alamar blue. Values are normalized to numbers of viable cells of each type grown in the absence of dox (1.0), with error bars representing standard deviations among three replicates. Similar results were obtained from 2 or 3 independent experiments.

https://doi.org/10.7554/eLife.33718.002

We previously documented increases in phosphorylated forms of the stress kinases, phospho-JNK (P-JNK) and phospho-p38 (P-p38), as well as in phospho-ERK (P-ERK or P-p44/42), in one of these cell lines (PC9) 72 hr after treatment with dox (Unni et al., 2015; Varmus et al., 2016). We used a phospho-protein array to assess the status of protein activation more broadly after KRAS induction, using PC9-tetO-KRAS cells after 1 and 5 days of dox treatment (Figure 1B, Figure 1—figure supplement 1A). After 5 days, we again observed increases in P-JNK, P-p38, and P-ERK (Figure 1—figure supplement 1A), suggesting that three major branches of the MAPK pathway are activated after extended induction of mutant KRAS. In addition, several other proteins show enhanced phosphorylation at this time. At 24 hr after addition of dox, however, only P-ERK and P-AKT show a pronounced increase (Figure 1B). Specifically, the stress kinases, JNK and p38, were not detected as phosphorylated proteins with the protein array. A possible interpretation of these findings is that ERK may be phosphorylated relatively soon after induction of mutant KRAS, with subsequent phosphorylation (and activation) of stress kinases and several other proteins. We also observed increased phosphorylation of ERK 24 hr after induction of mutant KRAS by western blot in all three LUAD cell lines (Figure 1C). In H358 and in H1975-based cell systems we observed persistently increased levels of P-ERK and, ultimately, the presence of cleaved PARP (Figure 1—figure supplement 1B). We previously reported multiple mechanisms of RAS-induced toxicity in PC9-tetO-KRAS cells (Unni et al., 2015). Based on the cleavage of PARP in the studies shown here, apoptosis appears to be at least one of the mechanisms of reduced viability in H358 and H1975 cell lines.

The results shown in Figure 1 suggest that ERK itself could be the signaling node that causes a loss of viable cells when inappropriately activated. As one test of this hypothesis, we used trametinib (Gilmartin et al., 2011), an inhibitor of MEK, the kinase that phosphorylates ERK, to ask whether reduced levels of P-ERK would protect cells from the toxicity caused by induction of mutant KRAS. In all three LUAD cell lines, trametinib completely or partially rescued the loss of viable cells caused by induction of mutant KRAS by dox (Figure 1D, Figure 1—figure supplement 1C). We confirmed that doses of trametinib that protected cells from the toxic effects of seven days of treatment with dox were associated with reduced levels of P-ERK after 24 hr of induction of mutant KRAS (Figure 1D). A PI3K inhibitor, buparlisib, did not rescue mutant KRAS-induced lethality in H358-tetO-KRAS cells (Figure 1—figure supplement 1D), implying that the toxic effects of KRAS are not mediated by enhanced signaling via PI3K.

To extend these findings and further challenge the hypothesis that P-ERK is an important node in the cell signaling network downstream of KRAS that confers cell toxicity, we transduced LUAD cell lines with retroviral vectors encoding shRNAs that ‘knock down’ expression of ERK1 or ERK2. Using two different shRNAs for each gene, as well as a non-targeted shRNA vector as control, we stably reduced the levels of ERK1 or ERK2 in the three LUAD cell lines (Figure 1E). When PC9 and H358 lines were treated with dox to assess the effects of ERK1 or ERK2 knockdowns on the loss of viable cells, we found that depletion of ERK2, but not ERK1, rescued cells from KRAS toxicity after 7 days in dox (Figure 1E). In H1975 cells, however, neither knockdown of ERK1 nor of ERK2 prevented KRAS-induced cell toxicity. Since trametinib rescues the number of viable cells after induction of KRAS in H1975 cells (Figure 1D), it seemed possible that either ERK1 or ERK2 might be sufficient to mediate RAS-induced toxicity in this line. In that case, it would be necessary to reduce the levels or the activity of both ERK proteins to rescue H1975 cells from toxicity. We tested this idea by treating dox-induced H1975-tetO-KRAS cells with SCH772984 (Morris et al., 2013), a drug that inhibits the kinase activity of both ERK1 and ERK2 (Figure 1—figure supplement 1E). As we observed with the MEK inhibitor, trametinib, in other lines (Figure 1D, far right), the ERK inhibitor reduces KRAS-associated toxicity in H1975 cells with concomitant reductions of P-ERK1 and P-ERK2 (Figure 1—figure supplement 1E).

To examine this issue in a different way, we performed a genome-wide CRISPR-Cas9 screen to evaluate mechanisms of mutant KRAS-induced toxicity in an unbiased manner. After growing H358-tetO-KRAS cells for 7 days following introduction of the appropriate vectors carrying Cas9 and a library of DNA encoding gene-targeted RNAs (see Materials and methods), guide RNA (sgRNA) targeting ERK2 (MAPK1) was highly enriched in cells grown in the presence of doxycycline (Figure 1—figure supplement 1F, Supplementary file 1). Guide RNA targeting RAF1 (CRAF) was also significantly enriched. Data from this CRISPR-Cas9 genome-wide screen strongly suggests that depletion of critical proteins in the RTK-RAS pathway can mitigate the toxicity induced by excess RAS activation. Collectively, our data suggest that LUAD cell lines are sensitive to inappropriate hyperactivation of the ERK signaling node and that toxicity mediated by activation of the RAS pathway is ERK-dependent.

DUSP6 is a major regulator of negative feedback, expressed in LUAD cells, and associated with KRAS and EGFR mutations and with high P-ERK levels

The evidence that hyperactive ERK signaling has toxic effects on LUAD cells raises the possibility that cancers driven by mutations in the RAS pathway may have a mechanism to ‘buffer’ P-ERK levels and thereby avoid reaching a lethal signaling threshold. Genes encoding negative feedback regulators are typically activated at the transcriptional level by the EGFR-KRAS-ERK pathway to place a restraint on signaling (Avraham and Yarden, 2011). Such feedback regulators previously implicated in the control of EGFR-KRAS-ERK signaling include the six dual specificity phosphatases (DUSP1-6), the four sprouty proteins (SPRY1-4) and the three sprouty-related, EVH1 domain-containing proteins (SPRED1-3) (Avraham and Yarden, 2011; Lake et al., 2016). To begin a search for possible negative regulators of RAS-mediated signaling in LUAD cells driven by mutations in either KRAS or EGFR, we asked whether mutations in either proto-oncogene would up-regulate one or multiple members of these families of regulators, based on the assumption that such proteins might constrain P-ERK levels, leading to optimal growth without cytotoxic effects.

To search for potential negative regulators specifically involved in LUAD, we compared amounts of RNAs from DUSP, SPRY and SPRED gene families in tumors with and without mutations in either KRAS or EGFR, using RNA-seq data from The Cancer Genome Atlas (TCGA) (Cancer Genome Atlas Research Network, 2014) (Figure 2A,B and Figure 2—figure supplement 1A,B). DUSP6 was the only negative-feedback regulatory gene with significantly different levels of expression when we compared tumors with mutations in either KRAS or EGFR with tumors without such mutations (Bonferoni corrected p < 0.01, two-tailed t-test with Welch’s correction). Further, DUSP6 mRNA was significantly up-regulated in LUAD tumors with mutations in common RTK-RAS pathway components compared to those without, consistent with a role of DUSP6 in regulating EGFR-KRAS-ERK signaling (Figure 2—figure supplement 1C) (Avraham and Yarden, 2011; Muda et al., 1996a; Muda et al., 1996b; Groom et al., 1996; Kidger and Keyse, 2016; Zhang et al., 2010). DUSP6 RNA was also present at higher levels in LUADs with EGFR or KRAS mutations than in tumors without such mutations in an independent collection of 83 tumors collected at the British Columbia Cancer Agency (BCCA, p = 0.004), confirming the findings derived from the TCGA dataset (Figure 2C and Figure 2—figure supplement 1D). Furthermore, DUSP6 RNA was more abundant in EGFR/KRAS mutant LUADs than in normal lung tissue (p<0.0001) whereas no significant differences in DUSP6 levels were observed between normal lung tissue and tumors without mutations in either of these two genes (p = 0.64) (Figure 2C and Figure 2—figure supplement 1D).

Figure 2 with 1 supplement see all
DUSP6 is the only negative feedback regulator significantly up-regulated in LUAD tumors with KRAS or EGFR mutations.

(A) Negative feedback regulators differentially expressed between clinical LUADs with or without EGFR or KRAS mutations (as indicated in green or blue, respectively, in the third and second horizontal bars). Expression levels for the indicated genes as determined by RNA-seq were compared between LUAD tumors with (n = 107, red) and without (n = 123, black) KRAS or EGFR mutations. In the heatmap, red indicates high relative expression and blue, low expression. Significance, as determined by two-tailed unpaired t-test with Bonferroni multiple testing correction, is indicated as the –log2(p-value). The significance threshold was set at a p-value < 0.01 and is indicated by the dotted line. Only DUSP6 surpassed this threshold. (B) DUSP6 is the main negative feedback regulator upregulated in LUADs with EGFR or KRAS mutations. Box plots show levels of DUSP6 RNA from samples in A. LUADs with EGFR or KRAS mutations (n = 107) express DUSP6 at higher levels than do LUADs with wildtype KRAS and EGFR (n = 123) in the TCGA dataset. (C) Validation of increased DUSP6 expression in LUADs with mutated KRAS or EGFR. In an independent internal dataset from the BCCA, LUADs with EGFR or KRAS mutations (n = 54) demonstrated higher expression of DUSP6 compared to LUADs in which both EGFR and KRAS were wild-type (n = 29) and to normal lung tissues (n = 83). (D) Dusp6 is upregulated in the lungs of mice with tumors induced by mutant EGFR or Kras transgenes. Tumor-bearing lung tissues from mice expressing EGFR or Kras oncogenes produce higher levels of Dusp6 RNA than do normal lung controls or tumor-bearing lungs from mice with a MYC transgene. (E) Increased DUSP6 RNA is specific to cells with oncogenic signaling through RAS. Human primary epithelial cells expressing a HRAS oncogene (n = 10 biological replicates) express DUSP6 at higher levels than control cells producing GFP (n = 10 biological replicates) whereas cells expressing known oncogenes other than RAS genes (MYC, SRC, B-Catenin, and E2F-3) do not. (F) DUSP6 RNA levels increase in PC9, H358 and H1975 cells expressing mutant KRAS. Dox was added to induce either GFP or the KRASG12V oncogene for 24 hr; DUSP6 RNA was measured by qPCR. (G–I) DUSP6 expression is associated with P-ERK levels. (G) LUADs with EGFR or KRAS mutations (n = 107) have higher P-ERK levels, but not P-p38 or P-JNK levels, than LUADs with wildtype KRAS and EGFR (n = 123) in the TCGA dataset. (H) LUADs with the highest DUSP6 RNA levels (n = 46) demonstrated higher P-ERK levels, but not P-p38 or P-JNK levels, than LUADs with the lowest DUSP6 RNA levels (n = 46). (I) DUSP6 RNA levels correlate with the levels of P-ERK in LUADs (n = 182). Pearson correlation coefficient (r) and p-value are indicated. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, NS = Not Significant.

https://doi.org/10.7554/eLife.33718.004

To ascertain whether DUSP6 is up-regulated specifically in tumors driven by mutant KRAS or mutant EGFR signaling rather than in tumors associated with activation of other oncogenic pathways, we measured DUSP6 RNA in experimental systems driven by the activation of various oncogenes. In transgenic mouse models of lung cancer, Dusp6 RNA was present at significantly higher levels in the lungs of mice bearing tumors driven by mutant EGFR or KRAS transgenes than in normal mouse lung epithelium (Figure 2D) (Felsher and Bishop, 1999; Fisher et al., 2001; Politi et al., 2006). In contrast, Dusp6 RNA levels were not significantly different in lungs from mice with tumors driven by MYC and in normal mouse lung tissue (Figure 2D). Similarly, increased levels of DUSP6 RNA were observed in primary human epithelial cells only when the cells were also transduced with mutant RAS genes, but not with a variety of other oncogenes or with plasmids encoding GFP (p < 0.0001) (Figure 2E) (Bild et al., 2006). Lastly, our LUAD cell lines engineered to produce KRASG12V in response to dox showed an increase in DUSP6 RNA that correlated with augmented phosphorylation of ERK and cell toxicity (Figure 2F). It is unclear why increased levels of DUSP6 RNA are not sufficient to decrease P-ERK in these inducible systems; this may reflect the localization of P-ERK, which we have not explored here. Together, these findings suggest that DUSP6 is a critical negative feedback regulator activated in response to oncogenic signaling by mutant RAS or EGFR proteins in LUAD.

In our previous study (Unni et al., 2015) (see also Figure 1—figure supplement 1A), we found that co-induction of oncogenic KRAS and EGFR activated not only ERK, but also JNK and p38 MAPK pathways, albeit at later times. To investigate whether DUSP6 is up-regulated solely in response to phosphorylation of ERK or also in response to phosphorylation of JNK and p38, we assessed the relationship of amounts of DUSP6 RNA in tumors with levels of P-ERK, P-JNK and P-p38 proteins as determined for TCGA (Cancer Genome Atlas Research Network, 2014), using the Reverse Phase Protein Array (RPPA). LUADs with a KRAS or an EGFR mutation contained significantly higher levels of P-ERK – but not of P-JNK or P-p38 – than did tumors without those mutations, consistent with a role for these oncogenes in ERK activation (Figure 2G). Furthermore, tumors with high DUSP6 RNA have relatively high amounts of P-ERK but not of P-JNK or P-p38 (Figure 2H). Lastly, there is a positive correlation between P-ERK levels and DUSP6 RNA in LUAD (Figure 2I), whereas no such association was observed between DUSP6 RNA and P-JNK or P-p38 (Figure 2—figure supplement 1E,F). Together, these observations support the proposal that DUSP6 is expressed in response to activation of ERK and that it serves as a major negative feedback regulator of ERK signaling in LUAD, buffering the potentially toxic effects of ERK hyperactivation.

Knockdown of DUSP6 elevates P-ERK and reduces viability of LUAD cells with either KRAS or EGFR oncogenic mutations

If DUSP6 is a negative feedback regulator of RAS signaling through ERK, then inhibiting the function of DUSP6 in LUAD cell lines driven by oncogenic KRAS or EGFR should cause hyperphosphorylation and hyperactivity of ERK, possibly producing a signaling intensity that causes cell toxicity, as observed when we co-express mutant KRAS and EGFR. Consistent with this prediction, introduction of DUSP6-specific siRNA pools into PC9 cells decreased DUSP6 levels and reduced the number of viable cells to levels similar to those observed when mutant EGFR, the driver oncogene, was itself knocked down (Figure 3A). siRNA pools for either DUSP6 or EGFR decreased DUSP6 protein levels. A decrease in DUSP6 protein levels with siRNA against EGFR RNA can be explained by a reduction in EGFR protein levels causing a decrease in ERK activation (Figure 3A) and subsequently diminishing expression of DUSP6, a direct negative feedback regulator of ERK activity. Importantly, almost complete knockdown of DUSP6 was required to elicit toxic effects in PC9 cells.

Figure 3 with 1 supplement see all
Knockdown of DUSP6 increases P-ERK and selectively inhibits LUAD cell lines with KRAS or EGFR mutations.

(A) Interference with DUSP6 RNA induces toxicity in PC9 cells. Pooled siRNAs for DUSP6, EGFR or a non-gene targeting control (Non-T) were transfected into PC9 cells (carrying an EGFR mutation) on day 0 and day 3, and the numbers of viable cells in each condition was measured with Alamar blue at the indicated time points and scaled to the Non-T condition at day 1 to measure the relative changes in numbers of viable cells. Experiments were done in biological triplicate with the average values presented ±SEM. Western blots were performed at the endpoint of the assay (day 5) to confirm reduced amounts of DUSP6 protein and measure levels of ERK and P-ERK (p42/44 and P-p42/44, respectively). (B–C) A siRNA that targeted the 5’ region of DUSP6 mRNA coding sequence (siDUSP6-Qiagen; different from siDUSP6-8 that targets the 3’ mRNA coding region), reduces levels of DUSP6 protein and decreases the numbers of viable cells. The indicated siRNAs (DUSP6-pool, DUSP6-8, DUSP6-Qiagen, EGFR and Non-Target) were delivered to PC9 cells, the levels of DUSP6 protein measured and the numbers of viable cells was determined as described for panel A. Experiments were done at least three times, and the average ±SEM is indicated for cell viability. (D) Interference with DUSP6 RNA acutely increases P-ERK levels. DUSP6 was knocked down in PC9 and H1975 cells (EGFR mutants), A549 cells (KRAS mutant), and HCC95 cells (KRAS and EGFR wild-type); levels of ERK and P-ERK were measured by Western blot 24 hr later. Relative P-ERK levels (ratio of phosphorylated to total levels normalized to actin) were determined by dosimetry and compared to the non-targeting control (NT) to quantify the relative increase after DUSP6 knockdown. Three independent western blots were performed and the average ±SEM is plotted. (E) Interference with DUSP6 RNA inhibits LUAD cell lines with activating mutations in genes encoding components of the EGFR/KRAS signaling pathway. Numbers of viable cells 5 days after knockdown of DUSP6 or knockdown of positive controls (EGFR, KRAS or KIF11) were assessed with Alamar blue and compared to the non-targeting controls to determine relative changes. Experiments were done in biological triplicate with the average values presented ±SEM. Western blots to monitor knockdown of target genes at Day 5 are also displayed. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, NS = Not Significant.

https://doi.org/10.7554/eLife.33718.006

The pool of Dharmacon-synthesized siRNAs we used is composed of 4 individual siRNAs (labeled DUSP6-6,7,8 and 9, Figure 3 and Figure 3—figure supplement 1A,B). We tested the individual siRNAs to confirm knockdown of DUSP6 protein and assess cell viability after siRNA treatment (Figure 3—figure supplement 1A,B). Treatment of PC9 cells with any one of three particular siRNAs resulted in a significant decrease in DUSP6 levels (particularly DUSP6-6 and DUSP6-7), however, the number of viable cells on day 5 was greater than in cells treated with the non-targeting control siRNA (Figure 3—figure supplement 1A,B). This observation was in contrast to the loss of cell viability we documented with the siRNA pool against DUSP6 (Figure 3). However, treatment with one other siRNA in the pool, DUSP6-8, resulted in the greatest depletion in DUSP6 protein and also a striking loss of cell viability (Figure 3—figure supplement 1A,B), consistent with the results from the siRNA pool. This suggests that DUSP6 protein levels need to be substantially depleted to exert an effect in PC9 cells.

Because only one siRNA in the pool (DUSP6-8) had a deleterious effect on PC9 cells, we confirmed the effects of this siRNA by utilizing another siRNA that targets a different region of DUSP6 mRNA (A 5’ coding sequence is targeted by DUSP6-Qiagen, whereas a 3’ coding sequence is targeted by DUSP6-8). DUSP6-Qiagen suppresses DUSP6 protein to a level similar to what we observed with the siRNA pool (Figure 3B,C). We also observed a loss of cell viability in PC9s cells treated with DUSP6-Qiagen siRNA comparable to that of the siRNA pool, suggesting these effects are not off-target (Figure 3B,C).

While it was anticipated that knockdown of mutant EGFR would diminish the numbers of viable cells by reducing levels of P-ERK and its growth-promoting signal, cells in which DUSP6 was knocked down with siRNAs also displayed reduced P-ERK levels five days after transfection, not the expected increase in phosphorylation of ERK (Figure 3A). One way to reconcile this apparent discrepancy is to examine the kinetics of phosphorylation and dephosphorylation of ERK after manipulation of the abundance of DUSP6 and its resulting effects on RAS signaling. To determine whether an initial, transient increase in P-ERK occurred after nearly complete knockdown of DUSP6, preceding the observed reduction in viable cells, we measured P-ERK in two cell lines with mutations in EGFR (PC9 and H1975 cells), one cell line with a mutation in KRAS (A549 cells) and a lung squamous cell carcinoma with wildtype EGFR and KRAS (HCC95 cells) 24 hr after addition of DUSP6 siRNA. In the three cell lines assessed with mutant EGFR or KRAS, there was a small but consistent increase (~1.5 fold) in P-ERK 24 hr after receiving DUSP6 siRNA, compared to non-targeting siRNA controls (Figure 3D). Within 5 days, knockdown of DUSP6 reduced the numbers of viable cells in the LUAD lines with activating KRAS or EGFR mutations (PC9, H1975 and A549 cells), but not in a cell line with no known activating mutations affecting the EGFR-KRAS-ERK pathway (HCC95 cells) (Figure 3E).

Mirroring the decrease in viability, cleaved PARP was also induced five days after DUSP6 knockdown in EGFR/KRAS mutant, but not EGFR/KRAS wildtype cells (Figure 3—figure supplement 1C). While there was no correlation between sensitivity to DUSP6 knockdown and basal DUSP6 protein levels, KRAS or EGFR mutant cell lines demonstrate higher P-ERK levels and/or a high P-ERK to DUSP6 protein ratio that could contribute to P-ERK hyperactivity and the subsequent decrease in cell viability after inhibition of DUSP6 (Figure 3-figure supplement D,E,F). Lastly, as described above, reduction of ERK1 or ERK2 levels with shRNAs in EGFR-mutant PC9 cells partially rescued the decreased cell viability caused by DUSP6 knockdown, suggesting that ERK – at least in part - mediates the toxic effects of DUSP6 inhibition (Figure 3—figure supplement 1G,H,I). These data suggest that knockdown of DUSP6 or potentially other negative feedback regulators that can increase P-ERK would reduce cell viability in cells containing an oncogenic KRAS or EGFR mutation.

Pharmacological inhibition of DUSP6 reduces the number of viable LUAD cells bearing mutations that activate the ERK pathway

The results presented thus far suggest that LUAD cells with mutations in KRAS or EGFR depend on negative regulators like DUSP6 to attenuate P-ERK for survival, offering a potentially exploitable vulnerability that could be useful therapeutically. However, blocking synthesis of DUSP6 efficiently with siRNA is difficult, in part because reduced levels of DUSP6 lead to increased levels of phosphorylated ERK, stimulating a subsequent increase in DUSP6 mRNA. As DUSP6 mRNA rises, more siRNA may be required to sustain the reduction of DUSP6. Based on this negative feedback cycle, we reasoned that pharmacological inhibition of the enzymatic activity of DUSP6 would be more effective. A small molecule inhibitor of DUSP6, (E)−2-benzylidene-3-(cyclohexylamino)−2,3-dihydro-1H-inden-1-one (BCI), was identified through an in vivo chemical screen for activators of fibroblast growth factor signaling in zebrafish (Molina et al., 2009; Korotchenko et al., 2014). BCI inhibits DUSP6 allosterically, binding near the active site of the phosphatase, inhibiting activation of the catalytic site after binding to its substrate, ERK (Molina et al., 2009). BCI also selectively inhibits DUSP1, which, like DUSP6, has catalytic activity dependent on substrate binding. However, as demonstrated in Figure 2A, DUSP1 is not significantly up-regulated in LUADs with EGFR or KRAS mutations. Furthermore, siRNA-mediated knockdown of DUSP1, as opposed to knockdown of DUSP6, has no effect on viability of EGFR-mutant H1975 cells, suggesting that DUSP6 should be the main target of BCI (Figure 4—figure supplement 1A,B).

We tested 11 lung cancer cell lines - 8 with a KRAS or EGFR mutation and 3 with no known activating mutations in these genes – with a dosing strategy covering the previously determined active range of the drug (Shojaee et al., 2015). We predicted that cancer lines with mutations in KRAS or EGFR would be more sensitive to the potential effects of BCI treatment on numbers of viable cells, since DUSP6 would be required to restrain the toxic effects of P-ERK in these cells. Our findings are consistent with this prediction (Figure 4A,B). The cell lines fell into three categories of sensitivity: 1) the most sensitive lines, with IC50s between 1–3 uM and with > 90% loss of viable cells at 3.2 uM, all harbored KRAS or EGFR mutations; 2) the one line with intermediate sensitivity, H1437 (IC50 > 4 uM), contains an activating mutation in MEK (Q56P); and 3) the relatively insensitive lines (IC50s ≥ 5 uM) lack known mutations affecting the EGFR-KRAS-ERK signaling pathway. The insensitive cell lines did not demonstrate the marked (> 90%) reduction in numbers of viable cells observed with the sensitive cell lines and only sensitive cell lines showed induction of cleaved PARP after BCI treatment (Figure 4—figure supplement 1C). Together, these data suggest that pharmacological inhibition of DUSP6 specifically kills cells with EGFR or KRAS-mutations.

Figure 4 with 1 supplement see all
Treatment with the DUSP6 inhibitor BCI selectively kills LUAD cell lines with KRAS or EGFR mutation, implying a dependence on ERK-mediated signaling.

(A–B) BCI induces toxicity specifically in lung cancer cell lines with mutations in genes encoding components in the EGFR-KRAS-ERK pathway. (A) Eleven lung cancer cell lines were treated with increasing doses of BCI for 72 hr based on the reported effective activity of the drug (Shojaee et al., 2015). Cell lines could be assigned to three distinct groups: sensitive (red), intermediate (green) and insensitive (black). All sensitive cell lines contained either EGFR or KRAS mutations; the intermediate and insensitive cell lines were wild-type for genes encoding components of the EGFR-KRAS-ERK signaling pathway (as determined by the Sanger Cell Line Project and the Cancer Cell Line Encyclopedia [Barretina et al., 2012]). Experiments were done in biological duplicate with the average values presented ±SEM. (B) Crystal Violet stain of cells plated in the indicated doses of BCI or control (0 = 0.1% DMSO) for 72 hr. Sensitive cells with a KRAS mutation (H358 cells; denoted with red underlining) show a more pronounced decrease in cell number than do cells without oncogenic mutations in genes encoding components of the EGFR-KRAS-ERK pathway (H1648 cells; black underlining). Experiments were done in biological duplicate with a representative image shown. (C) BCI increases P-ERK levels specifically in BCI-sensitive cell lines. Sensitive lines (H358, PC9, H1975 and A549; red underlining) and insensitive lines (HCC95 and H1648; black underlining) were treated with the indicated doses of BCI or vehicle control (0.1% DMSO) for 30 min, and the levels of ERK (p44/p42) and P-ERK (P-p44/42 T202/Y204) assessed by Western blot. P-ERK appeared in the sensitive cells at low doses of BCI, but P-ERK levels did not increase in the insensitive cells at the tested doses of BCI. (D) Dosimetry plots from the experiment shown in panel. (C) (E–F) Cell lines sensitive to BCI are also dependent on P-ERK for survival. BCI-sensitive cells with oncogenic mutations in EGFR or KRAS (PC9 and H358, respectively; red underlining) and BCI-insensitive cells (H1648 and HCC95; black underlining) were treated with the indicated doses of the MEK inhibitor trametinib for 72 hr; viable cells were measured with Alamar blue and compared to cells receiving the vehicle control (0 = 0.1% DMSO). (E) Treatment with trametinib decreased P-ERK levels as determined by western blot. (F) The reduction in P-ERK corresponded to a greater decrease in viable cells in BCI-sensitive lines (red coloring), compared to BCI-insensitive cell lines (black coloring).

https://doi.org/10.7554/eLife.33718.008

P-ERK levels increase in LUAD cells after inhibition of DUSP6 by BCI, and P-ERK is required for BCI- mediated toxicity

Based on findings in the preceding section, we predicted that BCI-mediated inhibition of DUSP6 would increase P-ERK to toxic levels, similar to the effects of co-expressing mutant KRAS and EGFR. To test this proposal, we measured total ERK and P-ERK after BCI treatment in sensitive and insensitive cell lines. A subset of the most sensitive cell lines, H358 (KRAS mutant) and PC9 and H1975 (EGFR mutants), demonstrated a large, dose-dependent increase in P-ERK in response to BCI treatment, with appreciable increases observed even at the lowest doses tested (1 uM) (Figure 4C,D). This induction of P-ERK precedes the appearance of cleaved PARP and cell death, as indicated by a time course of observations after BCI treatment in KRAS-mutant H358 cells (Figure 4—figure supplement 1D). Likewise, another sensitive cell line, A549 (KRAS mutant), demonstrated an increase in P-ERK, albeit at higher BCI concentrations, consistent with a less acute BCI sensitivity (Figures 3C and 4C,D). Conversely, BCI did not induce increases in P-ERK in the insensitive cell lines HCC95 and H1648, even at the highest levels of BCI (10 uM) (Figure 4C,D). Importantly, cell lines sensitive to BCI were also dependent on sustained P-ERK signaling for survival, as the MEK inhibitor trametinib, while effectively reducing P-ERK in all cell lines, reduced cell viability to a greater degree in BCI- sensitive lines (H358 and PC9) compared to BCI-insensitive lines (H1648 and HCC95; Figure 4E,F). Thus, the oncogenic mutation profile and dependency on activation of the EGFR-RAS-ERK pathway correlates with dependence on DUSP6 activity. These correlations are likely to reflect the central significance of P-ERK as a determinant of cell growth and viability.

To confirm whether P-ERK is involved in regulation of BCI-mediated cell death, we treated KRAS mutant H358 cells with a combination of BCI and the ERK1/2 inhibitor VX-11E, predicting that simultaneous inhibition of DUSP6 and ERK would mitigate the toxic effects of BCI treatment. Unlike other ERK inhibitors such as SCH772984, VX-11E does not block ERK phosphorylation, but instead limits ERK activity following phosphorylation (Chaikuad et al., 2014). Consistent with this, while no difference in P-ERK induction was observed, VX-11E treatment limited BCI- induced phosphorylation of the downstream ERK target RSK (Figure 4—figure supplement 1F). In addition, treatment with VX-11E lead to a relative increase in the number of viable cells after BCI treatment in a dose-dependent manner, with higher VX-11E concentrations demonstrating less decline in viability in response to BCI compared to lower doses (Figure 4—figure supplement 1E). Together, these data suggest that ERK activation plays a vital role in mediating the inhibitory effects of BCI treatment in KRAS or EGFR mutant lung cancer cells.

To further understand BCI-mediated toxicity, we searched for potential resistance mechanisms through an unbiased, genome-wide CRISPR screen of the type described earlier (Figure 1—figure supplement 1F). If loss of genes targeted by guide RNA confers resistance, that can reveal the nature of the pathway being targeted, since inhibited expression of the gene mitigates the effects of the drug. We performed this screen in H460 cells that are mutant (Q61H) for KRAS and sensitive to BCI (Figure 4A). In the screen, we found that sgRNAs targeting KRAS were significantly enriched in KRAS-mutated H460 cells upon treatment with BCI compared to untreated controls (Figure 4—figure supplement 1G, Supplementary file 1). Guide RNA targeting KRAS were depleted in the absence of drug suggesting a dependence on mutant KRAS in this cell line. These results suggest that KRAS pathway activity is a major determinant of sensitivity to BCI (Figure 4—figure supplement 1G). To validate these results, we cloned two individual sgRNAs targeting KRAS and transduced H460 cells. After 7 days of puromycin selection, the polyclonal population was evaluated for KRAS depletion (Figure 4—figure supplement 1H). The KRAS-targeted and control H460 cells were treated at this time point with a dose response of BCI for 72 hr. Cells that contained sgRNAs against KRAS were less sensitive to BCI than cells containing control sgRNA and un-manipulated cells (Figure 4—figure supplement 1I).

We also generated two clones of DUSP6-deficient H358 cells using CRISPR-Cas9 and independent guide RNAs (Figure 4—figure supplement 1J). Unexpectedly, both clones remained responsive to BCI’s cell killing activity (Figure 4—figure supplement 1K). These results may be explained by the presence of DUSP1 (Figure 4—figure supplement 1J) and the reported activity of BCI against DUSP1 in addition to DUSP6. Further studies will be required to ascertain if these cells are still dependent on P-ERK for BCI-mediated sensitivity through DUSP1 or through another mechanism. While BCI sensitivity may not be solely due to DUSP6, our genome-wide screen for resistance to BCI suggests activation of the RAS pathway is at least partly required.

To further test RAS pathway dependency and its relation to BCI sensitivity, we predicted that stimulating the EGFR-RAS-ERK pathway in a BCI-insensitive cell line would make the cells more dependent on DUSP6 activity and more sensitive to BCI. Using HCC95 lung squamous carcinoma cells, which express relatively high levels of wild-type EGFR (Figure 5A), we showed that EGF increased the levels of both P-EGFR and P-ERK, confirming activation of the relevant signaling pathway (Figure 5A,B, Figure 5—figure supplement 1). In addition, BCI further enhanced the levels of P-ERK, especially in the EGF-treated cells, with dose-dependent increases; these findings are similar to those observed in cell lines with EGFR or KRAS mutations (Figure 4C,D). After pretreatment with EGF (100 ng/mL) for ten days and treating the cells with increasing doses of BCI to inhibit DUSP6, 3 uM BCI reduced the number of viable HCC95 cells by approximately 40% compared to the control culture that did not receive EGF (Figure 5C). This outcome implies that prolonged EGF treatment and subsequent activation of P-ERK signaling makes HCC95 cells dependent on DUSP6 activity, as also observed in cell lines with EGFR or KRAS mutations (Figure 4A). Taken together, these findings suggest that LUAD cells with KRAS or EGFR mutations are sensitive to BCI because the drug acutely increases P-ERK beyond a tolerable threshold in a manner analogous to the synthetic lethality we previously described in LUAD lines after co-expression of mutant KRAS and EGFR (Unni et al., 2015).

Figure 5 with 1 supplement see all
EGF-mediated activation of ERK signaling leads to dependence on DUSP6.

(A) EGF increases P-ERK in HCC95 cells. BCI- insensitive HCC95 cells were grown in the presence and absence of EGF (100 ng/mL) and increasing doses of BCI; levels of the indicated proteins were assessed in cell lysates by Western blotting. EGF increased the levels of P-EGFR and P-ERK, and levels of P-ERK were further increased by BCI. (B) Relative P-ERK levels (ratio of phosphorylated to total levels normalized to actin) were determined by dosimetry and compared to the vehicle controls (0 BCI = 0.1% DMSO) to quantify the relative increase after BCI treatment from the gels in A. (C) Increase of P-ERK promotes sensitivity of lung cancer cell lines without KRAS or EGFR mutations to BCI. BCI- insensitive HCC95 cells were treated with 100 ng/mL of EGF for 10 days and then grown in medium containing escalating doses on BCI with continued EGF. Viable cells were measured 72 hr later with Alamar blue and compared to the vehicle controls (in 0.1% DMSO) to assess the relative change in numbers of viable cells. Experiments were done in biological triplicate with the average values presented ±SEM. The EGF-treated cells (red line) showed increased sensitivity (decreased viable cells at lower BCI conditions) than those without EGF treatment (black line). (B–C).

https://doi.org/10.7554/eLife.33718.010

Discussion

The pattern of mutual exclusivity observed with mutant EGFR and mutant KRAS genes in LUAD is a consequence of synthetic lethality, not pathway redundancy; co-expression of these oncogenes is toxic, resulting in loss of viable cells (Unni et al., 2015; Varmus et al., 2016). There are reports of exceptions to this mutual exclusivity but these arise in conditions that include inhibition of EGFR (Blakely et al., 2017; Ramalingam et al., 2018). This is to be expected, as cells treated with kinase inhibitors are not experiencing the effects of both oncogenes (i.e. mutant EGFR and mutant KRAS). A cancer cell that has not been exposed to inhibitors (e.g. against mutant EGFR) could arise, particularly at an advanced stage of disease, with activating mutations in both EGFR and KRAS; but we would anticipate that other events—like decreased RAS-GTP levels---might prevent P-ERK from reaching toxic levels.

Despite the possible exceptions, it remains critical to understand why, based on the pattern of mutual exclusion, cells are generally unable to tolerate the combination of these two oncogenes more readily. And what are the biochemical mechanisms by which the toxicity is mediated, might be modulated to avoid lethality, or could be exploited therapeutically? To address these questions, we began by regulating the expression of mutant KRAS in LUAD cell lines carrying mutant RAS or EGFR alleles. The levels of RAS activation in these cells are not expected to mirror what is found in tumors; these levels presumably will exceed what tumors can tolerate. We suggest that tumor cells could experience this state during progression, particularly when co-mutations in the RAS pathway have occurred. Understanding how the toxicity arises provides insight into mutual exclusivity and how limits for RAS activation may be set and exploited in cancer cells.

Our efforts to answer these questions have led to the conclusions that the toxicity is mediated through the hyperactivity of phosphorylated ERK1/2 and that inhibition of DUSP6 may re-create the toxicity through the role of this phosphatase as a negative regulator of ERK1/2. Several results reported here support these conclusions: (i) the previously reported toxicity that results from co-expression of mutant EGFR and mutant KRAS is accompanied by an early increase in the phosphorylation of ERK1/2, and the effects can be attenuated by inhibiting MEK (which phosphorylates and activates ERK1/2) or by reducing ERK levels with inhibitory RNAs; (ii) DUSP6, a phosphatase known to be a feedback inhibitor of ERK activity, is present at relatively high levels in LUADs with EGFR and KRAS mutations; and (iii) inhibition of DUSP6, either by introduction of siRNAs or by treatment with the drug BCI, reduces the number of viable LUAD cells with EGFR or KRAS mutations or of BCI-resistant cells exposed to EGF.

Taken in concert, these findings support a general hypothesis about cell signaling. Activation of a biochemical signal from a critical node, such as ERK, in a signaling pathway must rise to a certain level to drive neoplastic changes in cell behavior; if signal intensity falls below that level, the cells may revert to a normal phenotype or initiate cell death as a manifestation of what is often called ‘oncogene addiction” (Nissan et al., 2013; Weinstein et al., 1997; Dow et al., 2015; Varmus et al., 2005; Sharma et al., 2006). Conversely, if the intensity of signaling rises to exceed a higher threshold, the cells may display a variety of toxic effects, including senescence, vacuolization, or apoptosis (Unni et al., 2015; Chi et al., 1999; Serrano et al., 1997; Joneson and Bar-Sagi, 1999; Overmeyer et al., 2008; Zhu et al., 1998). In this model, two approaches to cancer therapy can be envisioned: (i) blocks to signaling that reverse the oncogenic phenotype or induce the apoptosis associated with oncogene addiction, or (ii) enhancements of signaling that cause selective toxicity in cells with pre-existing oncogenic mutations, a form of synthetic lethality that depends on changes that produce a gain rather than a loss of function. The former is exemplified by using inhibitors of EGFR kinase activity to induce remissions in LUAD with EGFR mutations (Lynch et al., 2004; Paez et al., 2004; Pao et al., 2004). Based on the findings presented here, the latter strategy might be pursued by using inhibitors of DUSP6 or other negative feedback regulators to block its usual attenuation of signals emanating from activated ERK1/2.

Several factors are likely to determine the threshold for producing the cell toxicity driven by hyperactive signaling nodes, such as ERKs, in cancer cells. These factors are likely to include allele-specific attributes of oncogenic mutations in genes such as KRAS (Hunter et al., 2015) and BRAF (Hunter et al., 2015; Yao et al., 2017; Nieto et al., 2017); the cell lineage in which the cancer has arisen (Shojaee et al., 2015; Yao et al., 2017; Zhao et al., 2015); the levels of expression of mutant cancer genes (Zhu et al., 1998; Nieto et al., 2017; Cisowski et al., 2016; Ambrogio et al., 2017); the co-existence of certain additional mutations (Barretina et al., 2012); and the multiple proteins that negatively regulate oncogenic proteins through feedback loops, such as MIG6 on EGFR (Ambrogio et al., 2017; Maity et al., 2015; Anastasi et al., 2016), GAPs on RAS proteins (Courtois-Cox et al., 2006; Vigil et al., 2010), or SPROUTYs and DUSPs on kinases downstream of RAS (Kidger and Keyse, 2016; Shojaee et al., 2015; Zhao et al., 2015). All such factors would need to be considered in the design of therapeutic strategies to generate signal intensities that are intolerable specifically in cancer cells. DUSP6 is a well-established negative regulator of ERK activation in a normal cellular context (reviewed in Keyse, 2008, and Theodosiou and Ashworth, 2002), so it is perhaps not surprising that this protein appears to have a critical role in persistently limiting ERK activation, even in a pathological context such as cancer.

The findings presented here, as well as recent results from others (Shojaee et al., 2015; Leung et al., 2018; Wittig-Blaich et al., 2017), support several underlying features of a therapeutic strategy based on inordinate signaling activity involving RAS proteins: that the activity of ERK needs to be actively controlled in cancer cells of diverse tissue origins; that hyperactivation of ERK can be deleterious to cells; and that inhibition of negative regulators like DUSP6 can create a toxic cellular state. This leads to the hypothesis that cancer cells dependent on ERK signaling have an active RTK-RAS-RAF-MEK pathway that produces levels of activated (phosphorylated) ERK1/2 that require attenuation. In other words, ERK-dependent tumor cells, including cancers driven by mutant RTK, RAS, BRAF, or MEK proteins, will have a vulnerability to hyperactivated ERK and that vulnerability can potentially be exploited by inhibition of feedback regulators like DUSP6.

Relevant to this concept are recent studies that address ‘drug addiction’ whereby cells lose viability when the inhibitor (e.g. vemurafenib) is removed (Hong et al., 2018; Kong et al., 2017; Das Thakur et al., 2013; Moriceau et al., 2015; Sun et al., 2014). These scenarios, in which an additional mutation can arise in the RTK-RAS-RAF-MEK pathway, create conditions similar to those we have modeled, once the inhibitor is removed. Additionally, Hata et al. have shown that mutations can arise while cells are exposed to a drug; as mentioned above, such mutations might appear to violate patterns of mutual exclusivity but the pattern only arose because of pathway down-modulation (Hata et al., 2016) Recently, Leung et al. have found a similar dependency on ERK activation limits in mutant BRAF-driven melanoma (Leung et al., 2018).

The mechanisms of cell toxicity that arise from hyper-activation of ERK are likely to be diverse. We previously documented autophagy, apoptosis and macropinocytosis in cells expressing mutant EGFR and mutant KRAS, and others have described parthanatos and pseudosenescence as mechanisms for cell death from hyper-activation of ERK (Hong et al., 2018). ERK-dependent processes may differ from cell type to cell type based on mutation profiles and cellular state at the time of ERK activation. This same dependence on ERK (ERK2 specifically) has been documented for senescence when mutant RAS is introduced into normal cells (Shin et al., 2013).

The hypothesis that DUSP6 regulates ERK activity in the presence of signaling through the RAS pathway is particularly attractive in view of the frequency of RAS gene mutations in human cancers and the difficulties of targeting mutant RAS proteins (Simanshu et al., 2017; Papke and Der, 2017; Downward, 2015). Because DUSP6 directly controls the activities of ERK1 and ERK2, rather than proteins further upstream in the signaling pathway, it appears to be well-situated for controlling both the signal delivered to ERK through the activation of RAS and the signal emitted by phosphorylated ERK. Recently, Wittig-Blaich et al. have also found that inhibition of DUSP6 by siRNA was toxic in melanoma cells carrying mutant BRAF (Wittig-Blaich et al., 2017). Inhibition of other DUSPs, like DUSP5, that regulate ERK1 and ERK2 may create similar vulnerabilities and should be explored (Kidger and Keyse, 2016; Kidger et al., 2017). These ideas should provoke searches for inhibitors of DUSPs and other feedback inhibitors of this signaling pathway, as well as experiments that better define the downstream mediators and the consequences of non-attenuated ERK signaling.

Materials and methods

Cell lines and culture conditions

PC9 (PC-9), H358 (NCI-H358), H1975 (NCI-H1975), H1648 (NCI-H1648), A549, H460 (NCI-H460), H23 (NCI-H23), H2122 (NCI-H2122), H1650 (NCI-H1650), H2009 (NCI-H2009), H2030 (NCI-H2030), H1437 (NCI-H1437) and HCC95 cells were obtained from American Type Tissue Culture (ATCC) or were a kind gift from Dr. Adi Gazdar (UTSW) or Dr. Romel Somwar (MSKCC). Cell lines were periodically checked for mycoplasm contamination and found to be negative. Cells have been validated by STR profiling. For experiments involving doxycycline inducible constructs, cells were maintained in RPMI-1640 medium (Lonza) supplemented with 10% Tetracycline-free FBS (Clontech) or FBS that was tested to be Tet-free (VWR Life Science Seradigm), 10 mM HEPES (Gibco) and 1 mM Sodium pyruvate (Gibco). For other experiments, cells were grown in RPMI-1640 medium (Thermo Fisher) supplemented with 10% FBS (Sigma), 1% Glutamax (Thermo Fisher) and Pen/Strep (Thermo Fisher). Cells were cultured at 37°; air; 95%; CO2, 5%. Where indicated, doxycycline hyclate (Sigma-Aldrich) was added at the time of cell seeding at 100 ng/ml. Trametinib (Selleckchem), Buparlisib (Selleckchem), SCH772984 (Selleckchem), Dual Specificity protein phosphatase 1/6 inhibitor (BCI) (Calbiochem), and EGF recombinant human protein solution (Thermo Fisher) were added at the time of cell seeding at the indicated doses.

Plasmids and generation of stable cell lines

Plasmids used were identical to those described in a prior publication (Unni et al., 2015). In brief, DNAs encoding mutant KRAS or GFP were cloned into pInducer20, a vector that carries a tetracycline response element for dox-dependent gene control and encodes rtTA, driven from the UbC promoter (Meerbrey et al., 2011). Lentivirus was generated using 293 T cells (ATCC), psPAX2 #12260 (Addgene, Cambridge, MA) and pMD2.G (Addgene plasmid#12259). Polyclonal cell lines (H358-tetO-GFP, H358-tetO-KRASG12V, PC9-tetO-GFP, H1975-tetO-GFP) and single cell-derived clonal cell lines (PC9-tetO-KRASG12V, H1975-tetO-KRASG12V) were used. pLKO.1-based lentiviral vectors were used to establish cells stably expressing shRNAs for the indicated genes. Knockdown was achieved using two independent shRNAs targeting ERK1 (noted in text as A4 or ERK1-4 and A5 or ERK1-5) or ERK2 (noted in text as G6 or ERK2-6 and G7 or ERK2-7) RNAs. shRNA-GFP: GCAAGCTGACCCTGAAGTTCAT shRNA-ERK1 (A4): CGACCTTAAGATTTGTGATTT shRNA-ERK1 (A5): CTATACCAAGTCCATCGACAT shRNA-ERK2 (G6): TATTACGACCCGAGTGACGAG shRNA-ERK2 (G7): TGGAATTGGATGACTTGCCTA shRNAs targeting GFP or a scramble sequence were used as controls. shRNA constructs were kindly provided by J. Blenis, Weill Cornell Medicine. Lentivirus was generated using 293 T cells as above. After transduction, polyclonal cells were selected with puromycin and maintained as a stable cell line.

Measurements of protein levels

Cells were lysed in RIPA buffer (Boston Bioproducts) containing Halt protease and phosphatase inhibitor cocktail (Thermo Fisher). For experiments involving dox-inducible constructs, lysates were cleared by centrifugation, and protein concentration determined by Pierce BCA protein assay kit (Thermo Fisher). Samples were denatured by boiling in loading buffer (Cell Signaling). 20 μg of lysates were loaded on 10% MiniProtean TGX gels (Bio-Rad), transferred to Immun-Blot PVDF membranes (Bio-Rad), blocked in TBST (0.1% Tween-20) and 5% milk. For all other experiments, samples were denatured by boiling in loading buffer (BioRad) and 25 μg of lysates were loaded on 4–12% Bis-Tris gradient gels (Thermo Fisher), run using MOPS buffer, transferred to Immobilon-P PVDF membranes (Millipore) and blocked in TBST (0.1% Tween-20)/5% BSA (Sigma).

Primary incubation with antibodies was performed overnight at 4° in 5% BSA, followed by appropriate HRP-conjugated secondary antisera (Santa Cruz Biotechnology) and detected using ECL (Thermo Fisher). Antibodies were obtained from Cell Signaling and raised against the following proteins: phospho p-38 (4511), p38 (8690), p-p44/p42 (ERK1/2) (9101), p44/p42 (ERK1/2) (4695), p-SAPK/JNK (4668), SAPK/JNK (9252), P-EGFR (3777, 2234), EGFR (2232), KRAS (8955), PARP (9542), cleaved-PARP (5625), α-Tubulin (3873) and β-Actin (3700, 4970). Additionally, we used an antibody against GFP (A-21311, Thermo Fisher), DUSP1 (ab1351, abcam) and DUSP6 (ab76310, abcam and SC-377070, SC-137426, Santa Cruz)..

For 24 hr time course experiments, 100,000 cells (PC9, H1975) or 500,000 cells (H358) per well were seeded in a 6-well plate and stimulated with dox or dox and drug. For 5 day experiments, 25,000 cells were seeded in 6-well format. For 7 day time course experiments, 300,000 cells (H358) or 30,000 cells (H1975) were seeded into 10 cM plates and media was changed every day.

For proteome profiler array, 200 ug of total lysate was incubated on membranes in the A/B set (ARY003B, R and D Systems) and processed according to protocol (R and D Systems). Film exposures were scanned and spot density quantified using Image Studio Lite (Licor). Data were plotted in Microsoft Excel.

For western blots with BCI and Trametinib, cells were seeded to achieve 80% confluency 18 hr post seeding. Medium was aspirated and replaced with antibiotic-free medium containing drug at indicated concentrations and incubated for 30 min. Cells were lysed and protein levels assessed as stated above. Quantification of western blot images was performed using ImageJ software. Scanned files were saved in TIFF format, and background was subtracted from all images. Rectangle tool was used to fully encompass each separate band. Rectangles and bands were assigned lanes and histogram plots were generated based on each lane. Each histogram was enclosed using a straight line across the bottom and the ‘magic wand’ tool generated a value for area of histogram. These values were exported to and assessed using Excel and Graphpad Prism software.

Measurements of viable cells

For experiments with dox-inducible constructs, cells were seeded into media containing doxycycline (100 ng/ml) and/or drug (Trametinib, SCH772984). Media (with or without doxycycline or drug) were replenished every 3 days during the 7 days. At indicated time points, medium was aspirated and replaced with medium containing Alamar Blue (Thermo Fisher). Fluorescence intensities from each well were read in duplicate on a FLUOstar Omega instrument (BMG Labtech), and data plotted in Microsoft Excel. Cells were seeded in triplicate in 24-well format at 1,000 cells/well (PC9 or H1975 derivatives) or 5,000 cells/well (H358 derivatives). For other experiments, cells were grown in 6-well plates, Alamar Blue added, and intensities measured for each well in quadruplicate using a Cytation 3 Multi Modal Reader with Gen5 software (BioTek).

For crystal violet assays, cells were seeded to achieve 80–90% confluency at the end point in the absence of drug treatment. 18 hr later, medium was aspirated and replaced with medium containing drug. Cells were incubated for 72 hr, washed with PBS and Crystal Violet solution (Sigma) was added and incubated for 2 min before washing again with PBS and imaging.

Genomic datasets and analyses

RNA-Seq (RSEM) data for EGFR-KRAS-ERK pathway phosphatases (DUSP1-6, SPRED1-3, SPRY1-4) along with corresponding mutational data for EGFR, KRAS, MET, ERBB2, BRAF, NF1, NRAS and HRAS for 230 lung adenocarcinoma tumors from The Cancer Genome Atlas (Cancer Genome Atlas Research Network, 2014) were downloaded from cBioPortal (http://www.cbioportal.org/) (Cerami et al., 2012; Gao et al., 2013). Expression of each gene was compared between tumors with KRAS or EGFR mutations and those without, using an unpaired T-Test. Resulting p-values were adjusted for multiple comparisons using a Bonferroni correction and the –Log2 value plotted as an indication of significance. Normalized expression values (sample gene value – median gene expression across all samples/row median absolute deviation) for each gene were also plotted using MORPHEUS software (https://software.broadinstitute.org/morpheus, Broad Institute) as a heat map. Expression of DUSP6 was also individually compared for tumors with EGFR mutation only, KRAS mutation only, or any RTK-RAS-ERK pathway mutation (EGFR, KRAS, MET, BRAF, ERBB2, NRAS, HRAS or NF1) vs those wild-type for the in each instance using a two-tailed Mann-Whitney U-Test in Prism 7 (Graphpad).

Reverse phase protein array (RPPA) data (replicate-base normalized [Akbani et al., 2014]) for 182/230 tumors were downloaded from the UCSC Cancer Genomics Browser. Levels of MAPKPT202Y204, P38PT180Y18 and JNKPT183Y185 were compared between samples with a KRAS or EGFR mutation and those without, using the Mann-Whitney U-Test.. Likewise, samples were separated into groups with high and low DUSP6 expression levels, based on the highest and lowest DUSP6 expression quartiles; MAPKPT202Y204, P38PT180Y18 and JNKPT183Y185 levels were compared between the groups as above. Lastly, MAPKPT202Y204 levels from RPPA (RBN values) were correlated with DUSP6 expression (Log2 RSEM values), and the Pearson correlation coefficient and p-value determined. As phospho-protein levels were predicted to be higher in samples with KRAS or EGFR mutation or high DUSP6, one-tailed p-values were calculated.

DUSP6 expression was also compared between tumors with and without EGFR or KRAS mutations in 83 tumors and matched normal lung tissues from the BC Cancer Agency (BCCA) and deposited in the Gene Expression Omnibus (GSE75037) as described above. Similarly, DUSP6 expression was compared between human epithelial cells expressing various oncogenes or GFP control (GSE3151) (Bild et al., 2006). Lastly, Affymetrix Mouse Genome 430 2.0 Arrays were used to profile the lung from genetically engineered mouse models of lung cancer with and without the expression of different driver oncogenes (EGFR-DEL, EGFR-L858R, KRAS-G12D and MYC) (Fisher et al., 2001; Politi et al., 2006; Podsypanina et al., 2008) and levels of DUSP6 compared using a two-tailed Mann-Whitney U-Test in Prism seven software (Graphpad).

siRNA transfections

For the time course experiments, 50,000 cells (PC9) per well were seeded in a 6-well plate. For the endpoint experiments, 50,000 cells (PC9, PC9-shERK1-5, PC9-shERK2-7, PC9-shScramble) or 75,000 cells (1975, A549, HCC95) per well were seeded. Cells were then transfected with ON-TARGETplus siRNA pools (Dharmacon) against the following targets as previously described (Lockwood et al., 2012)--- EGFR (L-003114-00-0010), KIF11 (L-003317-00-0010), KRAS (L-005069-00-0010), DUSP6 (L-003964-00-0010)—as well as a non-targeting control (D-001810-10-20). In addition, to test specificity for DUSP6, siRNAs comprising the pool (J-003964-06-0005, J-003964-07-0005, J-003964-08-0005 and J-003964-09-0005) were also tested individually. An additional siRNA (Hs_DUSP6_6 FlexiTube siRNA SI03106404, Qiagen) targeting a different region of DUSP6 coding sequence than J-003964-08-0005 was tested to establish that the decreased viability was not due to off target effects.

DUSP6-8 (Dharmacon) Target Sequence: GGCATTAGCCGCTCAGTCA

DUSP6-Qiagen (Qiagen) Target Sequence: GTCGGAAATGGCGATCAGCAA

For consistent transfection efficiency across experiments, 10 uL of 20 uM siRNA pool was added in 190 uL of OptiMEM (Life Technologies) and 5 uL of Dharmafect was added in 195 uL of OptiMEM (Life Technologies) at room temperature. The siRNA and Dharmafect suspensions were mixed and incubated for 20 min prior to transfection. Media was changed 24 hr after transfection. For sustained knockdown of targets, transfections were conducted on Day 0 and again on Day 3. Viable cells were measured using Alamar Blue as described above. For the time course experiment, cell viability was determined on Day 1, Day 3 (prior to second transfection) and Day 5 or only on Day 5. Results were compared between each siRNA and non-targeting control using a one-sample t-test as previously described (Lockwood et al., 2012).

BCI dose-response treatments

Dose-response curves for BCI were established using a modified version of the protocol previously described (Lockwood et al., 2012). Briefly, cells were seeded in quadruplicate at optimal densities into 96-well plates containing media with and without BCI at indicated doses in 0.1% DMSO. Viable cells were measured 72 hr later with Alamar Blue as described above. All experiments were performed in at least biological duplicate and plotted ±SEM. For HCC95 sensitization assays, cells were cultured with or without 100 ng/mL of EGF Recombinant Human Protein Solution (Life Technologies) for 10 days prior to seeding in 96-well plates for BCI dose response assays with or without EGF. The cells were allowed to adhere for 24 hr before treatment with 17 different concentrations of BCI, ranging from 0 to 8 uM, with 0.5 uM increment doses at 0.1% DMSO concentration. Additionally, 100 uM of Etoposide (0.1% DMSO) was added as a positive control for cell death. Cell viability was determined after 72 hr of drug exposure using Alamar Blue. Graphpad Prism software was used to create dose response curves.

For BCI rescue experiments, 75,000 H358 cells were seeded in 6-well plates and adhered for 24 hr. After attachment, the cells were treated with varying combinations of VX-11e and BCI with the final DMSO concentration at 0.1% in each well. Cells were treated for 72 hr and then the media was switched with fresh media containing Alamar blue for viability assessment. Resulting values for each BCI + VX-11e containing well were normalized to well containing corresponding concentration of VX-11e only. Experiments were performed in biological triplicate and the average ±SEM plotted.

Quantitative RT-PCR

Cells were homogenized and RNA extracted using the RNeasy Mini kit (Qiagen) according to the manufacturer’s instructions. cDNA was prepared using the High-Capacity cDNA Reverse Transcription kit (Thermo Fisher). RT–PCR reactions were carried out using the TaqMan Gene Expression Master Mix (Thermo Fisher) and TaqMan Gene Expression Assays (Thermo Fischer) for DUSP6 (Hs00169257_m1) and GAPDH (Hs99999905_m1). Reactions were run on a QuantStudio6 Real Time PCR system (Thermo Fisher). The ΔΔCt method was used for relative expression quantification using the average cycle thresholds.

Genome-wide CRISPR screens

Genome-wide screens were performed with the Toronto Knockout version 3 (TKOv3) library (Hart et al., 2017). Lentivirus was generated from the TKOv3 library in low passage (<10) 293FT cells (Thermo Fisher) using Lipofectamine 3000 (Thermo Fisher). Approximately 120 million target cells were then infected with the TKOv3 library virus at an MOI of 0.3, in order to achieve an average 500-fold representation of the sgRNAs after selection. Cells were selected on puromycin for 7 days and then 35 million cells were seeded in culture. For the depletion screens, cells were passaged every 3 days, and after 14 population doublings, 35 million cells were harvested for genomic DNA extraction. For the enrichment screens, media (containing BCI or doxycycline) was changed every 3 days until cell death was no longer observed, at which point the remaining cells were harvested for genomic DNA extraction. sgRNA inserts were amplified with NEBNext High-Fidelity 2X PCR Master Mix (New England BioLabs). Samples were then purified and sequenced on a NextSeq 500 kit (Illumina).

For validation of the screen, two separate guides targeting KRAS were cloned into lentiCRISPR v275, lentivirus generated and H460 cells were transduced. Seven days after puromycin selection cells were harvested for protein analysis and seeded in the presence of BCI. A guide against LacZ was used as a control.

sgRNA_Lacz: GAGCGAACGCGTAACGCGAA sgRNA_KRAS-1: GGACCAGTACATGAGGACTG sgRNA_KRAS-2: GTAGTTGGAGCTGGTGGCGT

For targeting of DUSP6, two separate guides were cloned into lentiCRISPR v2, lentivirus generated, and H358 cells were transduced. A clonal population of cells were expanded and screened by western blotting and by DNA sequencing of the DUSP6 locus.

sgRNA_DUSP6-1: GTGCGCGCGCTCTTCACGCG sgRNA_DUSP6-2: ACTCGTATAGCTCCTGCGGC

Analysis of CRISPR screen

Sequencing reads were aligned to the reference library to determine the abundance of each sgRNA. sgRNAs with less than 30 raw read counts were excluded from further analysis. The read counts were then normalized to the total number of reads obtained from the respective sample. The log2 fold-change of each sgRNA was calculated by adding a pseudocount of 1 and comparing the abundance of the sgRNAs in the final cell population to their respective abundance in the TKOv3 plasmid library. Finally, genes were ranked according to the second-most enriched or second-most depleted sgRNA.

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Decision letter

  1. Jonathan A Cooper
    Senior and Reviewing Editor; Fred Hutchinson Cancer Research Center, United States

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

[Editors’ note: formal revisions were requested, following approval of the authors’ plan of action.]

Thank you for submitting your article "Hyperactivation of ERK by mutation-driven RAS signaling or by inhibition of DUSP6 is toxic to lung adenocarcinoma cells" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom (Thomas Look) is a member of our Board of Reviewing Editors, and Jonathan Cooper as the Senior Editor.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this letter to express the many issues that we feel must be addressed if this work is to advance to publication.

Summary:

In this manuscript Unni et al., describe their work on understanding the mechanism leading to cytotoxicity following forced overexpression of KRAS in LUAD cell lines harboring EGFR or KRAS mutations. They conclude that such toxicity owes to hyperactivation of pERK, which occurs through DUSP6. They show that MEK/ERK inhibitor treatment rescues the effect of forced overexpression while reducing the levels of pERK and that DUSP6 mRNA levels are increased in LUAD harboring EGFR or KRAS mutations relative to those with a wild type status of these proteins. Genetic or pharmacologic targeting of DUSP was found to induce pERK (transiently) and lead to diminished cell proliferation in EGFR/KRAS mutant cell lines but not in those with a wild type status. While overall the findings are intriguing, there are gaps in the experimental evidence provided which bias their conclusions. If the authors can address the issues noted below however this could be a very interesting article.

We have the following suggestions to improve the manuscript. For clarity, we address below the essential revisions related to the results presented in each figure.

1) Figure 1 a) Figure 1A: The expression level of tet-driven ectopic KRASG12V is very high in each of the three lung adenocarcinoma lines. The authors should demonstrate by western blotting whether these levels are comparable to endogenous KRAS levels found in lung adenocarcinoma lines. Studies from Tyler Jacks on mutant KRAS in knockin mice over 10 years ago emphasized the importance of expression levels of mutant KRAS to mediate transformation in lung adenocarcinoma. Massive overexpression of KRASG12V can induce senescence rather than transformation in most cell types.

b) Figure 1D: The trametinib/SCH984 experiments in Figure 1D require additional appropriate controls; the authors should show the effect of treatment in the absence of dox stimulation. Also, why are different concentrations of trametinib used?

c) In addition to the biochemistry and cell count data shown in each panel of Figure 1, straightforward studies need to be done to establish the cellular mechanism underlying the cell growth phenotype. Before and after induction of KRASG12V using dox, studies of cell cycle progression by DNA flow cytometry, for β-GAL expression assays should be done to assess senescence, and cleaved caspase 3, TUNEL and PARP cleavage assays should be done to assess apoptosis. The reduction of cell number 7-days after dox induction of KRASG12V of ~ 20-40 percent of control could be due to growth arrest, senescence or apoptosis. This will be important to establish with regard to the author's interpretation that over activation of ERK leads to synthetic lethality. The need for studies of cellular phenotype in the context of the experiments shown in Figure 1 apply broadly to experiments throughout the paper.

d) Does overexpression of KRASG12C in EGFR or KRAS WT cells also induce toxicity which can be mitigated by co-treatment with trametinib in cells with no activating mutations in EGFR-RAS-ERK pathway? The levels of overexpressed KRASG12C are so high that such levels could induce toxicity by exceeding the upper threshold of RAS-mediated signaling even in cells without hyperactive EGFR-KRAS-ERK signaling.

e) Since the main claim is that hyperactivation of ERK leads to toxicity, the authors ought to replicate their dox-inducible experiments with active ERK to show that these also lead to cytotoxicity. Also, just because inhibiting MEK/ERK reverses the some of the phenotype in plastic, this doesn't exclude that other RAS effectors are also involved (see induction of pAKT in addition to pERK in Figure 1B). The authors should thus carry out similar siRNA or inhibitor studies to demonstrate that the cytotoxic effects of KRAS overexpression are not due to pAKT.

2) Figure 2 a) Figure 2A: There should be symbols under the heat map denoting which tumors are KRAS mutant and which are EFGR mutant. Are there any tumors with ALK/ROS1/RET activation by translocation? Are there tumors with NF1, MET and BRAF mutations? These should be addressed since most of lung adenocarcinoma have activation of RTK/RAS/RAF pathway (TCGA, 2014) and increased dusp6 is among the five gene signatures to predict poor outcome (Chen et al., 2007).

b) After describing the emergence of DUSP6 as a key gene responding to activated ERK based on their own studies, the authors should put their findings of DUSP6 elevated expression in the context of previous work. It has been known for over 10 years that DUSP6 is transcriptionally regulated by ERK-responsive ETS transcription factors downstream of MAPK activation and that DUSP6 serves as a major negative feedback regulator of ERK signaling (Reffas et al., 2000; Kawakami et al., 2003; Eblaghie et al., 2003; Li et al., 2007; Ekerot et al., 2008; Furukawa et al., 2008; Jurek et al., 2009).

c) Figure 2B and C: For these panels, please show separate data categories for KRAS mutant and EGFR mutant tumors. The box plots shown do not really look statistically significantly different. The medians are close, and the quartiles are largely overlapping. Which statistical test was used to show significant differences? Has a biostatistician been consulted about whether parametric or non-parametric tests would be better for these comparisons? A detailed statistical section is needed in the Materials and methods section, outlining the statistical tests used for the data shown in each figure.

d) In Figure 2 A-C, the authors must also include the correlation between DUSP6 and P-p38 and p-JNK to show the readers that no correlation exists between them.

e) Figure 2D: Please provide information or citations about the mouse models used in this figure.

f) Figure 2E: The Material/Methods description about this experiment seems to be missing. Expression levels need to be shown of the transduced onco-proteins by Western blot to verify overexpression.

g) Figure 2G and H: Same comments as 2B and C.

3) Figure 3 a) Figure 3A: Only one siRNA was used for DUSP6 or EGFR and there is no rescue experiment to prove that the effect is due to knockdown of the intended target. DUSP6 de-phosphorylates ERK so ERK phosphorylation is expected to be increased with DUSP6 knockdown. Please explain why Figure 3A shows the opposite with reduced p-ERK after siDUSP6 knockdown.

b) Figure 3A: Can the toxicity mediated by DUSP6 knockdown in PC9 cells be reduced by co-treatment with trametinib (Figure 3A)? This would help confirm that toxicity caused by depletion of DUSP6 in these cells is due to increased pERK levels.

c) Figure 3B: PC9 cells in this panel show increased p-ERK after DUSP6 kd. Please explain why this is the opposite result compared to Panel A.

d) Figure 3B and C: Did the authors determine if the levels of DUSP6 in their EGFR and KRAS wild-type cell lines, HCC95 and H1648, are not as high as in the cell lines with EGFR or KRAS activating mutations? Lower levels of DUSP6 would indicate that these cells do not need to have similar buffering ability as the EGFR or KRAS mutant cell lines and would be consistent with their findings in Figure 2. In Figure 3B, it seems that DUSP6 is also buffering the pERK levels in HCC95 because knockdown of DUSP6 increases the levels of pERK in these cells by over 1.5 fold, similar to the cells with EGFR or KRAS activating mutations; but this increase in pERK has no impact on the cell survival (Figure 3C). This needs to be reconciled with the authors' main claim.

e) There seems to be a disconnect between the first part of the manuscript, where the authors describe the mechanism of toxicity caused by forced overexpression of KRAS and the second part, where they describe the effect of DUSP inhibition in cell lines with endogenous KRAS/EGFR mutations. To close this gap, the authors need to determine the levels of DUSP6 protein in their dox-inducible KRAS models and how they correlate with pERK. They should determine if the induction of pERK is transient, as that observed with DUSP6 siRNA, or sustained. Finally, they should use DUSP6 siRNA or BCI to determine if this reverses the effect of forced KRAS expression on pERK or proliferation. Another question that has not been addressed is why doesn't forced overexpression of KRAS induce sufficient DUSP6 to override the induction of pERK, if DUSP expression is under the control of EGFR/KRAS? Could there be other factors involved? If the authors can experimentally address these it would be a significant improvement.

f) More evidence is needed to show that the increase in DUSP mRNA is associated with an increased in DUSP6 protein levels or increased DUSP activity. The data in Figure 2I, where the authors compare the relationship between pERK (measured by RPPA) and DUSP6 mRNA is the only such evidence provided. This is underwhelming because the correlation is not great (r=0.1) and because the pERK does not seem to have been controlled for total ERK.

g) Finding that DUSP6 siRNA caused only a transient elevation in pERK (followed by inhibition of pERK at longer intervals), while mimicking the antiproliferative effect observed with forced overexpression of KRAS needs to be clarified with additional experiments. As it stands, it is difficult to agree with the authors conclusion that DUSP6 is the main mediator of the proliferative effect or that the effect of DUSP6 is through pERK. One consideration may be to use constitutively active ERK (i.e. DD phosphomimetic mutants) and attempt to reverse the effect of DUSP6. This is another point that, if addressed experimentally, could add value to the manuscript.

h) If indeed it is true that a transient induction in pERK leads to cytotoxicity several days later, then does EGF stimulation (which also causes a transient induction in pERK) have the same effect in EGFR WT/KRAS MT cells?

i) All three reviewers noted that HCC95 (RRID:CVCL_5137) is a squamous cell carcinoma line. This not comparable to lung adenocarcinoma because this tumor type has different pathway dependencies than LUAD (TCGA, Nature 2012). A wild type LUAD line should be tested instead.

j) Figure 3C: Same comments as 3A.

k) The investigators might consider inactivating DUSP6 with CRISPR-Cas9 in these cell lines to show genetic dependence.

4) Figure 4 a) Figure 4A: 11 lung cancer cell lines were treated with BCI and viable cells were measured after 72-hour treatment. Most of these cell lines are fast growing cells with doubling time around 20~30 hours. Reduction of viable cells by 72-hours does not necessarily mean cell killing. TUNEL or caspase-3/PARP western blot needs to be performed to detect the levels of apoptosis. Senescence and cell cycle arrest should be examined too.

b) Figure 4C and D: p-ERK levels at a single time point was measured in multiple cell lines (30 min). In order to explain the loss of viable cells at 72hours in Figure 4A, p-ERK should be measured at serial time points such as 1, 6, 12, 24, 48, 72 hours.

c) The data on BCI are very interesting but it's not clear how have the authors established that BCI is selective for DUSP? Sensitive and insensitive cell lines all have IC50s in the 1-5μM range (12/13 cells lines tested). What is the IC50 of the inhibitor in DUSP6 KD or KO cells (or in DUSP1/6 double KD/KO cells)? How do the authors know that the antiproliferative effect of BCI is due to its ability to induce pERK? These questions need to be addressed experimentally. The authors should also attempt to show that the inhibitor has an effect in vivo, given their claim that such an approach could be therapeutically beneficial in patients.

d) Figure 4E and F: Four cell lines were treated with 125nM trametinib for 72 hours. 125nM is a very high dose for trametinib-sensitive cell lines such as H358 (reported IC50 ~50nM). Apoptosis levels should be measured to document any cell death.

5) Figure 5.

See comments for Figure 3B. HCC95 is a SQCC cell line that is quite different from the LUAD cells used in the rest of this manuscript.

a) In figures where the authors make a comparison of protein levels under different conditions the uncut blot with all the lanes on the same blot must be shown. It is not ideal to make a comparison between levels of proteins on two different strips of blots. For example, in Figure 5B, authors claim that EGF increase levels of pEGFR and pERK in HCC95 cells when the pEGFR and pERK levels with and without EGF are on two different strips of blots. This is important to confirm that BCI treatment increases pERK levels in EGFR treated cells. Quantifications should be shown in addition.

Overall comment:

The authors should soften earlier claims that EGFR-mutations and KRAS-mutations are synthetically lethal in the adenocarcinoma subtype of NSCLC (Unni et al., 2015). Recent genetic studies of EGFR-mutant lung cancer (Blakely et al., 2017) have shown that 2.5%~4.7% EGFR-mutant lung cancer also harbor KRAS copy number gain or activating mutations. Tumor genomic analyses have indicated that bona fide driver mutations causing lung adenocarcinoma are not as mutually exclusive as previously thought (e.g. PMIDs: 25301630, 28498782, 28445112, 29106415, and other recent publications), particularly in metastatic lung adenocarcinoma instead of early-stage disease and/or during the evolution of treatment resistance in metastatic disease. Further, preclinical studies have shown acquired KRAS gain/activation in response to EGFRi in EGFR-mutant NSCLC, indicating that this can be a mechanism of drug resistance (Politi et al., 2000; Eberlein et al., 2015). The authors should acknowledge these recent works and temper their claim of absolute mutually exclusivity in this disease, at least under these more advanced-stage disease contexts and in the light of the emerging literature.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Hyperactivation of ERK by mutation-driven RAS signaling or by inhibition of DUSP6 is toxic to lung adenocarcinoma cells" for further consideration at eLife. First, let me apologize profusely for the very long time this has taken. The problem is basically that the reviewers are at an impasse and could not decide on a course of action.

Briefly, this is a follow up to a previous paper, that reported anti-proliferative effects of activation of Ras and EGFR in the same cancer cells. This new paper has provides evidence that the anti-proliferative effect of over-expressed, active Ras is due to ERK hyperactivation, and that DUSP6 is critical to prevent adverse effects of active ERK in lung cancer cells. In the revision, the authors have added results using ERK shRNA, ERKi, and a CRISPR screen that together provide convincing evidence that ERK mediates the antiproliferative effect of oncogene overexpression. The finding that sgKRAS are enriched in the BCI screen also indirectly supports that conclusion. The authors have also ruled out that the PI3K pathway is not involved by adding PI3K inhibitor experiments. These additions greatly strengthen the conclusion that hyperactivation of ERK is detrimental. However, the evidence that DUSP6 plays a key role is not convincing.

The DUSP6 knockdown was done with a single siRNA with no rescue experiment. (Other siRNAs did not effectively inhibit DUSP6 expression). Attempts to recapitulate the result with a DUSP6 CRISPR knockout were unsuccessful. Therefore, the conclusion that DUSP6 is necessary relies in large part on the specificity of the chemical BCI. The DUSP6 KO cells have the same IC50 to BCI, while DUSP1 siRNA did not affect proliferation in their system. Based on these results, the authors cannot claim that the BCI effect is DUSP6 specific nor that the BCI effect in DUSP6KO cells is driven by DUSP1 inhibition. It probably isn't, and by inference, the observed phenotype is not dependent on DUSP6 alone but on other ERK specific DUSPs as well.

The reviewers disagreed whether these weaknesses undermined the impact to the point where the paper was unsuitable for publication, or whether lengthy additional experiments would be needed. The eLife approach is not to ask for multiple rounds of revision. In this spirit, I suggest two possibilities:

Either

- Provide convincing evidence that validates DUSP6 as the key enzyme that downregulates ERK in lung cancer cells (e.g. try more siRNAs to find another that gives strong knockdown, and/or rescue DUSP6 siRNA with DUSP6 from mouse, or with silent mutations in the siRNA target sequence).

Or,

- Modify the title and abstract to allow for the possibility that other DUSPs are involved and be more open about the shortcomings of the results.

https://doi.org/10.7554/eLife.33718.021

Author response

[Editors’ notes: the authors’ response after being formally invited to submit a revised submission follows.]

Summary:

In this manuscript Unni et al., describe their work on understanding the mechanism leading to cytotoxicity following forced overexpression of KRAS in LUAD cell lines harboring EGFR or KRAS mutations. They conclude that such toxicity owes to hyperactivation of pERK, which occurs through DUSP6. They show that MEK/ERK inhibitor treatment rescues the effect of forced overexpression while reducing the levels of pERK and that DUSP6 mRNA levels are increased in LUAD harboring EGFR or KRAS mutations relative to those with a wild type status of these proteins. Genetic or pharmacologic targeting of DUSP was found to induce pERK (transiently) and lead to diminished cell proliferation in EGFR/KRAS mutant cell lines but not in those with a wild type status. While overall the findings are intriguing, there are gaps in the experimental evidence provided which bias their conclusions. If the authors can address the issues noted below however this could be a very interesting article.

The main message of our paper is that p-ERK hyperactivation is intolerable in cancer cells and that this property—the toxic consequences of exceeding a certain level of activated (phosphorylated) ERK—creates a therapeutic target in RAS pathway-mutated cancers: DUSP6, an ERK phosphatase that plays a major role in modulating the activity of ERK in lung cancer cells.

We arrived at these findings by studying the mutually exclusive pattern of EGFR and KRAS mutations in lung adenocarcinoma. As your review points out, there may be exceptions to this mutual exclusivity, but we do not believe they undermine our arguments. Nevertheless, we will make changes to the Discussion section to include the observations that the reviewers cite and also note their shortcomings (such as the difficulty of knowing whether normally excluded combinations of mutations have occurred in the same cell or separately in tumor subclones). Of particular relevance, p-ERK intolerance has also been documented in ‘drug addicted’ cells when inhibitors are removed (Kong et al., 2017; Hong et al., 2018, Das Thakur et al., 2013, Moriceau et al., 2015, Sun et al., 2014). Cells in these conditions appear to violate the mutual exclusivity pattern, however, we would argue that these mutations could have arisen while cells were on drug (Hata et al., 2016).

We have the following suggestions to improve the manuscript. For clarity, we address below the essential revisions related to the results presented in each figure.

1) Figure 1 a) Figure 1A: The expression level of tet-driven ectopic KRASG12V is very high in each of the three lung adenocarcinoma lines. The authors should demonstrate by western blotting whether these levels are comparable to endogenous KRAS levels found in lung adenocarcinoma lines. Studies from Tyler Jacks on mutant KRAS in knockin mice over 10 years ago emphasized the importance of expression levels of mutant KRAS to mediate transformation in lung adenocarcinoma. Massive overexpression of KRASG12V can induce senescence rather than transformation in most cell types.

Our intention was to force excess RAS pathway activation (beyond what is present in tumor cells) and determine if this is tolerated. The purpose of doing this was to model what might be happening when co-mutations arise in the RAS pathway. We recognize that these levels of RAS may not be commonly experienced by tumor cells and will state this explicitly in the text. Even though our system, like many others, is artificial, it provides an experimental platform for understanding why hyper activation of ERK occurs and allowed us to define a vulnerability (DUSP6 inhibition) that we could exploit.

We have now stated this in the text (Results section).

b) Figure 1D: The trametinib/SCH984 experiments in Figure 1D require additional appropriate controls; the authors should show the effect of treatment in the absence of dox stimulation. Also, why are different concentrations of trametinib used?

Different concentrations were required to rescue the phenotype in different cells. We will now provide a plot to show dose response (plus/minus dox and plus/minus drug). The degree to which p-ERK is induced in each cell line appeared to require different concentrations of a MEK inhibitor to reset p-ERK back to an acceptable level.

A dose response curve for doxycycline plus trametinib is now plotted and shown in Figure 1—figure supplement 1C.

c) In addition to the biochemistry and cell count data shown in each panel of Figure 1, straightforward studies need to be done to establish the cellular mechanism underlying the cell growth phenotype. Before and after induction of KRASG12V using dox, studies of cell cycle progression by DNA flow cytometry, for β-GAL expression assays should be done to assess senescence, and cleaved caspase 3, TUNEL and PARP cleavage assays should be done to assess apoptosis. The reduction of cell number 7-days after dox induction of KRASG12V of ~ 20-40 percent of control could be due to growth arrest, senescence or apoptosis. This will be important to establish with regard to the author's interpretation that over activation of ERK leads to synthetic lethality. The need for studies of cellular phenotype in the context of the experiments shown in Figure 1 apply broadly to experiments throughout the paper.

We have previously published some of the effects of co-induction of mutant EGFR and mutant KRAS. In that study, we documented apoptosis, autophagy, vacuolization and macropinocytosis in cell lines similar to those we now use (Unni et al., 2015). A recent study (Hong et al., 2018) found that cancer cells that were ‘drug addicted’ die by apoptosis, parthanatos and pseudosenescence when inhibitors were removed (similar p-ERK overload principle). For these reasons there are likely to be several distinct mechanisms that result in a loss of cell viability. Our goal here has been to focus on the factors that generate the cytotoxic signal, rather than on a cell’s response to the signal. Nevertheless, in response to the reasonable concerns raised by this comment, we will assess the extent of apoptosis by measuring cleaved PARP, CASP3 activity, or Annexin V levels to help clarify our statements about cell toxicity.

We have measured cleaved PARP in the H358 and H1975 experimental systems described in this manuscript and some assays are shown in Figure 1—figure supplement 1. We characterized mechanisms of cell toxicity in PC9 cells that express both mutant EGFR and mutant KRAS in our earlier paper in eLife.

d) Does overexpression of KRASG12C in EGFR or KRAS WT cells also induce toxicity which can be mitigated by co-treatment with trametinib in cells with no activating mutations in EGFR-RAS-ERK pathway? The levels of overexpressed KRASG12C are so high that such levels could induce toxicity by exceeding the upper threshold of RAS-mediated signaling even in cells without hyperactive EGFR-KRAS-ERK signaling.

Overexpression of KRAS G12V is likely to result in cell death or senescence in a variety of cell lines, as others have shown in the past. However, the motivation for experiments in Figure 1 was to test the limits of cancer cells to activation of the RAS pathway in a reproducible way that could allow us to study the mechanism by which the toxic signals arise.

We have added a comment on RAS-mediated senescence in the text (Discussion section).

e) Since the main claim is that hyperactivation of ERK leads to toxicity, the authors ought to replicate their dox-inducible experiments with active ERK to show that these also lead to cytotoxicity. Also, just because inhibiting MEK/ERK reverses the some of the phenotype in plastic, this doesn't exclude that other RAS effectors are also involved (see induction of pAKT in addition to pERK in Figure 1B). The authors should thus carry out similar siRNA or inhibitor studies to demonstrate that the cytotoxic effects of KRAS overexpression are not due to pAKT.

Including data that an inducible active ERK2 allele is toxic would be valuable. However, creating and characterizing these lines will take a significant amount of time. We have prioritized other experiments that the reviewers advise that will strengthen our paper. We did show increases in p-AKT at an early time point and it is possible that effectors of RAS other than RAF proteins can also be toxic to cells. To address this point, tetO KRAS G12V cells will be treated with a PI3K inhibitor (to inhibit AKT phosphorylation) and placed on dox. We will document the effects on cell viability, and on p-AKT and p-ERK signaling.

We have included data with a PI3K inhibitor (buparilisib) in H358-tetO-KRAS cells (Figure—figure supplement 1D). Using the same cell line, a genome wide CRISPR-Cas9 screen did not reveal an enrichment of guide RNA targeting PIK3CA (Figure 1—figure supplement 1F and Supplementary file 1).

2) Figure 2a) Figure 2A: There should be symbols under the heat map denoting which tumors are KRAS mutant and which are EFGR mutant. Are there any tumors with ALK/ROS1/RET activation by translocation? Are there tumors with NF1, MET and BRAF mutations? These should be addressed since most of lung adenocarcinoma have activation of RTK/RAS/RAF pathway (TCGA, Nature 2014) and increased dusp6 is among the five gene signatures to predict poor outcome (Chen et al., 2007).

Symbols will be added for mutant KRAS, EGFR, BRAF, NF1, MET, ERBB2 etc. Translocations were not assessed in this data set. The Chen et al., five gene signatures is interesting (DUSP6, MMD, STAT1, ERBB3 and LCK). Perhaps this signature is most common in KRAS mutant tumors, something Chen et al., do not address. We will comment on these observations in the revised manuscript.

We have now indicated which tumors are KRAS mutants and which are EGFR mutants in Figure 2A. In addition, we have added another heat map with NF1, BRAF, MET, ERBB2, NRAS and HRAS status indicated as Figure 2—figure supplement 1A. Further, we have compared levels of DUSP6 mRNA among all tumors with RTK-RAS-RAF pathway mutations vs those with only wild type components in this pathway; see Figure—figure supplement 1C.

b) After describing the emergence of DUSP6 as a key gene responding to activated ERK based on their own studies, the authors should put their findings of DUSP6 elevated expression in the context of previous work. It has been known for over 10 years that DUSP6 is transcriptionally regulated by ERK-responsive ETS transcription factors downstream of MAPK activation and that DUSP6 serves as a major negative feedback regulator of ERK signaling (Reffas et al., 2000; Kawakami et al., 2003; Eblaghie et al., 2003; Li et al., 2007; Ekerot et al., 2008; Furukawa et al., 2008; Jurek et al., 2009).

The reviewers correctly point to many papers that highlight the significance of DUSP6 in controlling ERK activity. Our main point in this analysis was to discover which of the prominent negative regulators (DUSPs, SPRYs and SPREDs) have been significantly modulated in lung adenocarcinoma. This revealed that lung adenocarcinoma with mutations in KRAS or EGFR appear to rely on DUSP6 to actively restrain the RTK-RAS-RAF-MEK-ERK pathway. Our work also emphasizes that tumor cells have a level of ERK activation that is still subject to negative feedback regulation and that this reliance is a vulnerability based on the data we show in Figure 1. We will mention several of the papers the reviewers cite to properly document the previous work with DUSP6.

The papers suggested by the reviewers are cited through two reviews in the text (Discussion section).

c) Figure 2B and C: For these panels, please show separate data categories for KRAS mutant and EGFR mutant tumors. The box plots shown do not really look statistically significantly different. The medians are close, and the quartiles are largely overlapping. Which statistical test was used to show significant differences? Has a biostatistician been consulted about whether parametric or non-parametric tests would be better for these comparisons? A detailed statistical section is needed in the Materials and methods section, outlining the statistical tests used for the data shown in each figure.

We will include a detailed analysis of the statistical tests used and the rationale. We will also separate KRAS and EGFR mutant cases. However, it should be noted that assessing KRAS and EGFR mutant tumors in separate groups will limit sample numbers. As a result, statistical power will be reduced, especially in RPPA assessment where the number of samples available is already limiting. It was for this reason that samples with KRAS and EGFR mutations were pooled. Of note, the box plots in Figure 2B and C are on a log scale, suggesting that the differences seen between the medians are quite large.

We have now included more details about the statistical tests used in the methods section. We have also separated EGFR and KRAS mutant tumors and compared each to KRAS/EGFR WT groups and included these data in Figure 2—figure supplement 1B,D).

d) In Figure 2 A-C, the authors must also include the correlation between DUSP6 and P-p38 and p-JNK to show the readers that no correlation exists between them.

These data are part of 2H. No correlations were observed. We will also provide plots similar to 2I for p-JNK and p-p38.

Correlation plots for P-p38 and P-JNK have been included as Figure 2—figure supplement 1E,F.

e) Figure 2D: Please provide information or citations about the mouse models used in this figure.

We will provide the proper citations of the mouse models used (Politi et al., 2006; Fisher et al., 2001; Felsher and Bishop, 1999).

The appropriate citations for the mouse models are now included (subsection “DUSP6 is a major regulator of negative feedback, expressed in LUAD cells, and associated with KRAS and EGFR mutations and with high P-ERK levels”).

f) Figure 2E: The Material/Methods description about this experiment seems to be missing. Expression levels need to be shown of the transduced onco-proteins by Western blot to verify overexpression.

These data were retrieved from a previous publication and not adequately cited (GSE3151, Bild et al., 2006; Kim et al., 2010). We will correct this in the text to clearly state that it is from publicly available data.

This citation has been added, and the origin of the data is now clearly stated in the text (subsection “DUSP6 is a major regulator of negative feedback, expressed in LUAD cells, and associated with KRAS and EGFR mutations and with high P-ERK levels”).

g) Figure 2G and H: Same comments as 2B and C

EGFR and KRAS mutant tumors will be assessed separately. However, as mentioned above, combining these genotypes provides greater statistical power.

Addressed above and in Figure 2—figure supplement 1.

3) Figure 3 a) Figure 3A: Only one siRNA was used for DUSP6 or EGFR and there is no rescue experiment to prove that the effect is due to knockdown of the intended target. DUSP6 de-phosphorylates ERK so ERK phosphorylation is expected to be increased with DUSP6 knockdown. Please explain why Figure 3A shows the opposite with reduced p-ERK after siDUSP6 knockdown.

We have used pooled siRNA in the knockdown experiments. We now have PC9 cells expressing wildtype or catalytically inactive DUSP6. These cells will be used to verify that our DUSP6 siRNA is on-target (using siRNA against the 3’UTR of the endogenous DUSP6 which is not represented in the transgenes).

Unfortunately, despite repeated efforts, no siRNAs targeting the 3’UTR proved to be effective at knocking down DUSP6. In addition to using the original siRNA pool, we have now transfected PC9 cells with each individual siRNA comprising the pool, four in total, all of which target the coding region. This revealed a dose-dependent effect of knockdown on growth inhibition: suppression but incomplete knockdown stimulated cell growth, whereas more complete inhibition was toxic to cells (Figure 3—figure supplement 1A,B). This conforms with our hypothesis and suggests the siRNAs for DUSP6 are on target.

The challenging aspect of this study was that knockdown of DUSP6 will result in increased p-ERK leading to increased DUSP6 mRNA, which is being targeted by the siRNA (‘technical’ feedback loop). p-ERK is reduced in this figure probably because the measurement was made on day 5 (see 3B) when the cells are dying. We will include a measure of apoptosis (cleaved PARP) at this time point. We will also provide a longer exposure of the western blot showing the efficiency of DUSP6 knockdown as there could be remaining DUSP6 protein. This may contribute to the decreased p-ERK on day 5.

We have assessed cleaved PARP on day 5 after DUSP6 knockdown and shown that it is indeed induced in EGFR mutant H1975 cells but not EGFR/KRAS wild-type HCC95 cells (Figure 3—figure supplement 1C). We conclude that P-ERK levels are low at day 5 after DUSP6 knockdown because cells with increased P-ERK have already become non-viable by this time. This point was further investigated in BCI experiments below.

b) Figure 3A: Can the toxicity mediated by DUSP6 knockdown in PC9 cells be reduced by co-treatment with trametinib (Figure 3A)? This would help confirm that toxicity caused by depletion of DUSP6 in these cells is due to increased pERK levels.

This experiment was tried several times, but we could not find a dose of Trametinib that rescues lethality. MEK and ERK inhibitors are lethal in this line (PC9) and this presents a technical problem: both ERK inhibition and ERK hyperactivation are not tolerated. However, H1975 cells are much more tolerant to ERK inhibition using SCH772984. Experiments are underway to treat H1975 cells that have received siRNA against DUSP6 with an ERK inhibitor like SCH772984 to try and rescue the loss of cell viability.

Addition of drug (SCH772984) to cells transfected with siRNA against DUSP6 led to indiscriminate toxicity; cells could not withstand the stress of transfection coupled with an ERK inhibitor. As an alternative strategy, we knocked down DUSP6 with siRNA in PC9 cells co-transduced with shRNAs targeting either ERK1 or ERK2 as used in Figure 1. Stable, viable cells were established with reduced ERK levels. These cells displayed increased relative viability after DUSP6 knockdown compared to shScramble control cells, further suggesting that ERK plays a role in mediating the toxic effects of DUSP6 inhibition (now shown in Figure 3—figure supplement 1G,H,I).

c) Figure 3B: PC9 cells in this panel show increased p-ERK after DUSP6 kd. Please explain why this is the opposite result compared to Panel A.

These data are from 24hr samples, not 5 day samples (Figure 3A). We expect that acute loss of DUSP6 should increase levels of p-ERK that will then be part of a feedback loop of DUSP6 activation, followed by de-phosphorylation of ERK.

As mentioned above, 24 hours after DUSP6 knockdown, cells are still viable and P-ERK is induced whereas, at day 5, cells have induced cleaved PARP and demonstrate substantially decreased viability. We postulate that cells transfected with siRNA for DUSP6 develop high levels of P-ERK and subsequent cell death, leaving only cells with lower P-ERK at day 5.

d) Figure 3B and C: Did the authors determine if the levels of DUSP6 in their EGFR and KRAS wild-type cell lines, HCC95 and H1648, are not as high as in the cell lines with EGFR or KRAS activating mutations? Lower levels of DUSP6 would indicate that these cells do not need to have similar buffering ability as the EGFR or KRAS mutant cell lines and would be consistent with their findings in Figure 2. In Figure 3B, it seems that DUSP6 is also buffering the pERK levels in HCC95 because knockdown of DUSP6 increases the levels of pERK in these cells by over 1.5 fold, similar to the cells with EGFR or KRAS activating mutations; but this increase in pERK has no impact on the cell survival (Figure 3C). This needs to be reconciled with the authors' main claim.

We will provide the basal levels of DUSP6 across the lines in one figure. Additionally, we will include the quantitation of p-ERK changes from our independent experiments to help establish the fold changes.

We have included immunoblots indicating the basal levels of DUSP6 and P-ERK across the panel of cell lines (Figure 3—figure supplement 1D). Due to the variability associated with transfection-based experiments, we have now compiled dosimetry for three independent western blots in Figure 3B and plotted the results. This revealed that EGFR or KRAS mutant, but not wild type, cells consistently demonstrate increased P-ERK upon DUSP6 knockdown. All these results and their potential implications are now described in the text (subsection “Knockdown of DUSP6 elevates P-ERK and reduces viability of LUAD cells with either KRAS or EGFR oncogenic mutations”).

e) There seems to be a disconnect between the first part of the manuscript, where the authors describe the mechanism of toxicity caused by forced overexpression of KRAS and the second part, where they describe the effect of DUSP inhibition in cell lines with endogenous KRAS/EGFR mutations. To close this gap, the authors need to determine the levels of DUSP6 protein in their dox-inducible KRAS models and how they correlate with pERK. They should determine if the induction of pERK is transient, as that observed with DUSP6 siRNA, or sustained. Finally, they should use DUSP6 siRNA or BCI to determine if this reverses the effect of forced KRAS expression on pERK or proliferation. Another question that has not been addressed is why doesn't forced overexpression of KRAS induce sufficient DUSP6 to override the induction of pERK, if DUSP expression is under the control of EGFR/KRAS? Could there be other factors involved? If the authors can experimentally address these it would be a significant improvement.

We don’t understand why the reviewers believe there is a “disconnect” between the early and late phases of the manuscript. In fact, we believe that there is a logical flow from identification of p-ERK as the locus that transmits a toxic signal to the implication of DUSP6 as a critical regulator of the activity of ERK. So the notion of an informational gap is not clear to us. Nevertheless, we agree that the situation is complicated by the kinetics of activation and de-activation of the components of the signaling system, and we will follow the request to obtain more kinetic data. We will perform time course experiments in tetO-RAS lines, measuring p-ERK induction and DUSP6 protein levels at 1,3,5 and 7 days. Contrary to the reviewers’ speculation, we would not anticipate that DUSP6 siRNA or BCI would reverse the effects of forced KRAS expression; they should potentiate the effects of KRAS. On the other hand, it is unclear why DUSP6 cannot ‘override’ the induction of p-ERK. It is possible that p-ERK has fully localized to the nucleus and is no longer accessible to DUSP6. We will consider these possibilities in the revised manuscript.

The kinetics of p-ERK induction have been provided for H358 (days 1, 3, 5 and 7) and H1975 (day 7) cells in Figure 1—figure supplement 1B). The time course of induction of p-ERK upon treatment of H358 cells with BCI (at 1, 6, 12, 24, 48, 72 hours) is provided in Figure 4—figure supplement 1D. Experiments with BCI provide initial assessment of the kinetics of induction of p-ERK upon DUSP6 inactivation. The kinetics suggest that p-ERK induction for at least 24 hours is required before markers of apoptosis (PARP cleavage) are detected. Similar kinetics of p-ERK induction (at least 24-48 hours) before PARP cleavage detection were observed for H358-tetO-KRAS cells (subsection “Synthetic lethality induced by co-expression of mutant KRAS and EGFR is mediated through increased ERK Signalling”, subsection “P-ERK levels increase in LUAD cells after inhibition of DUSP6 by BCI, and P-ERK is required for BCI-mediated

toxicity.”).

f) More evidence is needed to show that the increase in DUSP mRNA is associated with an increased in DUSP6 protein levels or increased DUSP activity. The data in Figure 2I, where the authors compare the relationship between pERK (measured by RPPA) and DUSP6 mRNA is the only such evidence provided. This is underwhelming because the correlation is not great (r=0.1) and because the pERK does not seem to have been controlled for total ERK.

The RPPA assays (from TCGA) are controlled for total protein. The time course studies in tetO lines and BCI-treated cell lines may help address the issue of ‘sufficient’ levels of DUSP6.

We have performed and included in the manuscript time course experiments for both dox treatment in TetO cell lines and BCI treated cells as described above.

g) Finding that DUSP6 siRNA caused only a transient elevation in pERK (followed by inhibition of pERK at longer intervals), while mimicking the antiproliferative effect observed with forced overexpression of KRAS needs to be clarified with additional experiments. As it stands, it is difficult to agree with the authors conclusion that DUSP6 is the main mediator of the proliferative effect or that the effect of DUSP6 is through pERK. One consideration may be to use constitutively active ERK (i.e. DD phosphomimetic mutants) and attempt to reverse the effect of DUSP6. This is another point that, if addressed experimentally, could add value to the manuscript.

The ‘transient elevation’ in p-ERK with siRNA against DUSP6 may be a technical limitation of this assay as previously described. The time course studies in tetO lines and with BCI will help establish this. We will try and rescue the effects of siRNA against DUSP6 and BCI in H1975 cells—a cell line that is tolerant to ERK inhibition and provides an experimental system to ‘dial’ back appropriate p-ERK levels. A constitutively active ERK mutant is likely to be lethal in the presence of tet-induced mutant KRAS; for instance, ERK mutants have been documented to have a lethal effect in melanoma cells (Goetz et al., 2014). We will focus our attention on H1975 cells to rescue the effects of DUSP6 siRNA and BCI w/ MEK or ERK inhibition.

As mentioned above, we have used shRNA to inhibit ERK1 or ERK2 in PC9 cells and inhibition of ERK1 or ERK2 limited the toxic effects of knocking down DUSP6 (Figure 3—figure supplement 1G,H,I). In addition, we observed similar reductions in the toxic effects of BCI when H358 cells were co-treated with an ERK inhibitor (Figure 4—figure supplement 1E). These experiments further reinforce the conclusion that inhibition of DUSP6 (genetically or pharmacologically) decreases viability of EGFR or KRAS mutant cells – at least partially – through ERK induction.

h). If indeed it is true that a transient induction in pERK leads to cytotoxicity several days later, then does EGF stimulation (which also causes a transient induction in pERK) have the same effect in EGFR WT/KRAS MT cells?

As previously mentioned, the effects of transient vs. prolonged p-ERK will be addressed by studying the time course of response to BCI in cells and to mutant KRAS induced by dox. Transient treatment of cells with EGF is not expected to cause cytotoxicity based on our earlier experiments. In fact, transient administration of EGF to HCC95 cells failed to shift the IC50 for BCI; only prolonged exposure to EGF did that (Figure 5A). We will consider inclusion of this information during revision of the manuscript.

We have provided time course experiments of dox-mediated induction in TetO-KRAS cells (Figure 1—figure supplement 1B) and of BCI treatment in H358 cells (Figure 4—figure supplement 1D). Both approaches caused an initial increase in P-ERK levels coupled with later induction of cleaved-PARP and subsequent decrease in P-ERK (Figure 4—figure supplement 1D).

i) All three reviewers noted that HCC95 (RRID:CVCL_5137) is a squamous cell carcinoma line. This not comparable to lung adenocarcinoma because this tumor type has different pathway dependencies than LUAD (TCGA, 2012). A wild type LUAD line should be tested instead.

HCC95 cells were used because they are a cancer cell line (lung) that does not have mutations in EGFR or other examined components of the RAS pathway. We will state in the text that this is a squamous lung cancer cell line. Based on our data, cells with a mutation in the RAS pathway are likely be vulnerable to DUSP6 inhibition, regardless of cell lineage. Cells without these mutations (like HCC95) illustrate cancers (of any origin) that we would predict to be un-responsive to DUSP6 inhibition.

We have noted the nature of HCC95 cells in the text (subsection “Knockdown of DUSP6 elevates P-ERK and reduces viability of LUAD cells with either KRAS or EGFR oncogenic mutation”).

j) Figure 3C: Same comments as 3A.

Addressed above.

k) The investigators might consider inactivating DUSP6 with CRISPR-Cas9 in these cell lines to show genetic dependence.

We have now created PC9 and H358 cells in which DUSP6 has been deleted or damaged using CRISPR-Cas9. We anticipate that the cells selected for this loss may have developed other mechanisms to maintain p-ERK or may have other pathways activated to bypass the need for p-ERK to mediate survival. Thus, they may or may not be uniquely vulnerable to inhibition of MEK or ERK. We will analyze the recently identified mutant cells for p-ERK levels, growth rates, and sensitivities to BCI and to inhibition of MEK and ERK.

We created H358 cells deficient in DUSP6 (Figure 4—figure supplement 1J,K). These cells were equally sensitive to BCI as cells that were targeted with a control (lacZ) sgRNA. We suspect that DUSP1 may be controlling p-ERK levels in the absence of DUSP6, and BCI has known specificity towards DUSP1 in addition to DUSP6. Additionally, these cell lines were derived from clones, so it is possible that new mutations or pathway re-wirings have taken place and that they continue to control p-ERK.

4) Figure 4 a) Figure 4A: 11 lung cancer cell lines were treated with BCI and viable cells were measured after 72-hour treatment. Most of these cell lines are fast growing cells with doubling time around 20~30 hours. Reduction of viable cells by 72-hours does not necessarily mean cell killing. TUNEL or caspase-3/PARP western blot needs to be performed to detect the levels of apoptosis. Senescence and cell cycle arrest should be examined too.

We agree that the reduction in numbers of viable cells does not reveal the mechanism by which the numbers were reduced, and we have been careful to avoid any suggestion that it does (e.g. by labeling our charts “number of viable cells”). As explained earlier, our focus has been on the generation of the toxic signal, not the response to it. Nevertheless, in response to the reviewers’ concerns on this point, we will examine cells for apoptosis by measuring PARP cleavage.

We have assessed cleaved-PARP after BCI treatment in a panel of seven sensitive and insensitive cell lines and in a time course experiment in H358s (Figure 4—figure supplement 1). Only sensitive cell lines induced cleaved PARP after treatment.

b) Figure 4C and D: p-ERK levels at a single time point was measured in multiple cell lines (30 min). In order to explain the loss of viable cells at 72hours in Figure 4A, p-ERK should be measured at serial time points such as 1, 6, 12, 24, 48, 72 hours.

We will provide a time course of our measurements of p-ERK and DUSP6 in H1975 and H358 cells during treatment with BCI.

We provide a time course for H358 cells treated with BCI at the time points suggested by the reviewer in Figure 4—figure supplement 1.

c) The data on BCI are very interesting but it's not clear how have the authors established that BCI is selective for DUSP? Sensitive and insensitive cell lines all have IC50s in the 1-5μM range (12/13 cells lines tested). What is the IC50 of the inhibitor in DUSP6 KD or KO cells (or in DUSP1/6 double KD/KO cells)? How do the authors know that the antiproliferative effect of BCI is due to its ability to induce pERK? These questions need to be addressed experimentally. The authors should also attempt to show that the inhibitor has an effect in vivo, given their claim that such an approach could be therapeutically beneficial in patients.

A potential target of BCI is DUSP1, but we have data showing that siRNA against DUSP1 is not lethal in H1975 cells while siRNA to DUSP6 is. We will now also try to rescue the effects of BCI in H1975 cells by inhibiting ERK, using this cell line for the reasons described above (3b,g). In addition to PC9 CRISPR-Cas9 DUSP6 knockout cells described above (Figure 3, comment k), we have generated PC9 cells expressing wild type and catalytically inactive DUSP6. We will use these cell models to determine if there is a shift in the BCI IC50 with manipulation of DUSP6 to further evaluate its role as the biological target of BCI.

Importantly, we have now completed a genome-wide CRISPR screen in H460 cells (an KRAS mutant cell line sensitive to BCI), looking for loss of function mutations that confer resistance to BCI. The most highly enriched guide RNA in this screen was specific for KRAS, suggesting that BCI is ‘on-target’ with respect to its proposed role in causing excessive activation of the RAS pathway. We will confirm these findings by measuring BCI sensitivity in H460 cells treated with siRNA against KRAS and expect to include a version of the results in the revised paper to further support our interpretation of our findings with BCI.

We have included data showing that DUSP1 knockdown, as opposed to DUSP6 knockdown, is not lethal in H1975 cells (Figure 4—figure supplement 1A,B). Further, we have demonstrated that co-treatment with an ERK inhibitor decreases the toxic effects of BCI in H358 cells (Figure 4—figure supplement 1E,F). Lastly, we added the genome-wide CRISPR screen data in H460 cells showing that sgRNAs for KRAS are enriched upon BCI treatment, which we have subsequently confirmed using individual sgRNAs and BCI dose response experiments. Together, these results confirm that BCI works mainly through DUSP6 in the context described and mediates its toxic effects through ERK.

d) Figure 4E and F: Four cell lines were treated with 125nM trametinib for 72 hours. 125nM is a very high dose for trametinib-sensitive cell lines such as H358 (reported IC50 ~50nM). Apoptosis levels should be measured to document any cell death.

The purpose of these experiments was to address whether there was a correlation between the sensitivity of cells to ERK inhibition and their sensitivity to ERK hyperactivation. This correlation appears to hold (PC9 and H358 vs. HCC95 and H1648).

5) Figure 5.

See comments for Figure 3B. HCC95 is a SQCC cell line that is quite different from the LUAD cells used in the rest of this manuscript.

a) In figures where the authors make a comparison of protein levels under different conditions the uncut blot with all the lanes on the same blot must be shown. It is not ideal to make a comparison between levels of proteins on two different strips of blots. For example, in Figure 5B, authors claim that EGF increase levels of pEGFR and pERK in HCC95 cells when the pEGFR and pERK levels with and without EGF are on two different strips of blots. This is important to confirm that BCI treatment increases pERK levels in EGFR treated cells. Quantifications should be shown in addition.

Data in the western blots are normalized to total ERK and actin to make the values comparable. This will be explicitly stated in methods. Additionally, samples grown with and without EGF will be run in the same gel for the highest dose of BCI to provide a visual comparison.

We have included a western blot using extracts of cells treated and not treated with EGF, run on the same gel in Figure 5—figure supplement 1.

Overall comment:

The authors should soften earlier claims that EGFR-mutations and KRAS-mutations are synthetically lethal in the adenocarcinoma subtype of NSCLC (Unni et al., 2015). Recent genetic studies of EGFR-mutant lung cancer (Blakely et al., Nature Genetics 2017) have shown that 2.5%~4.7% EGFR-mutant lung cancer also harbor KRAS copy number gain or activating mutations. Tumor genomic analyses have indicated that bona fide driver mutations causing lung adenocarcinoma are not as mutually exclusive as previously thought (e.g. PMIDs: 25301630, 28498782, 28445112, 29106415, and other recent publications), particularly in metastatic lung adenocarcinoma instead of early-stage disease and/or during the evolution of treatment resistance in metastatic disease. Further, preclinical studies have shown acquired KRAS gain/activation in response to EGFRi in EGFR-mutant NSCLC, indicating that this can be a mechanism of drug resistance (Politi et al., 2000; Eberlein et al., 2015). The authors should acknowledge these recent works and temper their claim of absolute mutually exclusivity in this disease, at least under these more advanced-stage disease contexts and in the light of the emerging literature.

As noted earlier, we will provide a more thorough discussion of these points in the manuscript.

The additional discussion of these issues has been added to the text (Discussion section). We hope that with these changes and additions to the manuscript, the revised version will suitable for re-submission and consideration for publication at eLife.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Hyperactivation of ERK by mutation-driven RAS signaling or by inhibition of DUSP6 is toxic to lung adenocarcinoma cells" for further consideration at eLife. First, let me apologize profusely for the very long time this has taken. The problem is basically that the reviewers are at an impasse and could not decide on a course of action.

Briefly, this is a follow up to a previous paper, that reported anti-proliferative effects of activation of Ras and EGFR in the same cancer cells. This new paper has provides evidence that the anti-proliferative effect of over-expressed, active Ras is due to ERK hyperactivation, and that DUSP6 is critical to prevent adverse effects of active ERK in lung cancer cells. In the revision, the authors have added results using ERK shRNA, ERKi, and a CRISPR screen that together provide convincing evidence that ERK mediates the antiproliferative effect of oncogene overexpression. The finding that sgKRAS are enriched in the BCI screen also indirectly supports that conclusion. The authors have also ruled out that the PI3K pathway is not involved by adding PI3K inhibitor experiments. These additions greatly strengthen the conclusion that hyperactivation of ERK is detrimental. However, the evidence that DUSP6 plays a key role is not convincing.

The DUSP6 knockdown was done with a single siRNA with no rescue experiment. (Other siRNAs did not effectively inhibit DUSP6 expression). Attempts to recapitulate the result with a DUSP6 CRISPR knockout were unsuccessful. Therefore, the conclusion that DUSP6 is necessary relies in large part on the specificity of the chemical BCI. The DUSP6 KO cells have the same IC50 to BCI, while DUSP1 siRNA did not affect proliferation in their system. Based on these results, the authors cannot claim that the BCI effect is DUSP6 specific nor that the BCI effect in DUSP6KO cells is driven by DUSP1 inhibition. It probably isn't, and by inference, the observed phenotype is not dependent on DUSP6 alone but on other ERK specific DUSPs as well.

The reviewers disagreed whether these weaknesses undermined the impact to the point where the paper was unsuitable for publication, or whether lengthy additional experiments would be needed. The eLife approach is not to ask for multiple rounds of revision. In this spirit, I suggest two possibilities:

Either

- Provide convincing evidence that validates DUSP6 as the key enzyme that downregulates ERK in lung cancer cells (e.g. try more siRNAs to find another that gives strong knockdown, and/or rescue DUSP6 siRNA with DUSP6 from mouse, or with silent mutations in the siRNA target sequence).

Or,

- Modify the title and abstract to allow for the possibility that other DUSPs are involved and be more open about the shortcomings of the results.

1) To test additional DUSP6 siRNAs for their effects on protein abundance and cell fitness, we obtained a DUSP6-specific siRNA from Qiagen (the previous siRNAs were prepared by Dharmacon). In contrast to the DUSP6-8 siRNA that targeted a sequence in the 3’ domain of DUSP6 mRNA, the new species (called DUSP6-Qiagen in Figure 3B,C) targeted a sequence in the 5’ coding region of DUSP6 mRNA and reduced levels of DUSP6 protein in PC9 cells to levels similar to those achieved with one of the previously tested Dharmacon siRNAs (DUSP6-8 in Figure 3B and Figure 3—figure supplement 1A) and with the pool of four Dharmacon siRNAs (DUSP6-pool in Figure 3B and Figure 3—figure supplement 1A). Furthermore, DUSP6-Qiagen reduced the number of viable PC9 cells to a level similar to that observed with the pooled Dharmacon siRNAs (Figure 3C). We have described the effects of this second effective inhibitory RNA in the text and conclude that it strengthens the case for a central role of DUSP6 in regulation of ERK activity in RTK-RAS-driven LUAD. We also point out that this conclusion is supported by the correlation between the effects of one Dharmacon siRNA (DUSP6-8) on both DUSP6 protein levels and cell fitness (Figure 3—figure supplement 1A,B).

2) We also attempted, unsuccessfully, to rescue the effects of DUSP6 siRNA by generating a plasmid encoding DUSP6 mRNA with several synonymous mutations in the coding sequence to render the mRNA target sequence resistant to the siRNA without changing the protein sequence. For a variety of technical reasons related to transfection procedures, we have not been able to perform these experiments in a reproducible manner. We are convinced that the work required to carry out a satisfying rescue experiment would take an unreasonable amount of time and inappropriately delay publication, when we have provided the requested data with a second effective siRNA.

3) Despite our positive findings with the Qiagen siRNA, we recognize that our conclusions about the role of DUSP6 in regulation of the activity of ERK kinases should be cautious. (DUSP6 may not be the only important regulator and we cannot fully exclude some off-target effects of our siRNAs.) We have therefore removed specific mention of DUSP6 in the title of the manuscript, and we have modulated the description of the results in the abstract, along the lines suggested in your letter.

One other relevant item: two recent papers confirm the significance of the level of ERK kinase activity in another cancer type, melanoma, and address the possible role of DUSP6. Leung et al., over-express ERK2 in melanoma cell lines and show that high levels of ERK2 protein are toxic specifically in lines that carry BRAF V600E. Wittig-Blaich et al., use a complex screening method to identify genes that produce a synthetic lethality when disrupted in melanoma cell lines carrying the BRAF V600E mutation; one of the five implicated genes is DUSP6, allowing the authors to draw conclusions similar to our own. We mention and cite these papers (Leung et al., 2018 and Wittig-Blaich et al., 2017) in the Discussion section.

In addition to the changes that address your main concerns, we have found a few places in the text that lacked clarity upon careful re-reading of our previously submitted revision.

https://doi.org/10.7554/eLife.33718.022

Article and author information

Author details

  1. Arun M Unni

    Meyer Cancer Center, Weill Cornell Medicine, New York, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Investigation, Methodology, Writing—original draft, Project administration, Writing—review and editing
    For correspondence
    aru2001@med.cornell.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0530-1470
  2. Bryant Harbourne

    Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, Canada
    Contribution
    Data curation, Formal analysis, Investigation, Methodology
    Contributed equally with
    Min Hee Oh
    Competing interests
    No competing interests declared
  3. Min Hee Oh

    Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, Canada
    Contribution
    Data curation, Formal analysis, Investigation, Methodology
    Contributed equally with
    Bryant Harbourne
    Competing interests
    No competing interests declared
  4. Sophia Wild

    Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, Canada
    Contribution
    Data curation, Formal analysis
    Competing interests
    No competing interests declared
  5. John R Ferrarone

    Meyer Cancer Center, Weill Cornell Medicine, New York, United States
    Contribution
    Resources, Data curation, Formal analysis, Investigation
    Competing interests
    No competing interests declared
  6. William W Lockwood

    1. Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, Canada
    2. Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Investigation, Methodology, Writing—original draft, Project administration, Writing—review and editing
    Contributed equally with
    Harold Varmus
    For correspondence
    wlockwood@bccrc.ca
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9831-3408
  7. Harold Varmus

    Meyer Cancer Center, Weill Cornell Medicine, New York, United States
    Contribution
    Conceptualization, Supervision, Writing—original draft, Project administration, Writing—review and editing
    Contributed equally with
    William W Lockwood
    For correspondence
    varmus@med.cornell.edu
    Competing interests
    No competing interests declared

Funding

Canadian Institutes of Health Research (PJT-148725)

  • William W Lockwood

Terry Fox Research Institute

  • William W Lockwood

Michael Smith Foundation for Health Research (Scholar Award)

  • William W Lockwood

National Institutes of Health

  • Harold Varmus

Meyer Cancer Center at Weill Cornell Medicine

  • Harold Varmus

BC Cancer Foundation

  • William W Lockwood

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

Acknowledgements

We would like to thank Katerina Politi (Yale University) for providing gene expression data from her transgenic mice. We would like to thank members of the Varmus lab for useful discussions and Oksana Mashadova, in particular, for experimental help.

Senior and Reviewing Editor

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

Publication history

  1. Received: November 21, 2017
  2. Accepted: November 26, 2018
  3. Accepted Manuscript published: November 26, 2018 (version 1)
  4. Version of Record published: December 18, 2018 (version 2)

Copyright

© 2018, Unni 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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