EGFR mutation-positive patients with non–small cell lung cancer (NSCLC) respond well to treatment with EGFR–tyrosine kinase inhibitors (EGFR–TKI); however, treatment with EGFR–TKIs is not curative, owing to the presence of residual cancer cells with intrinsic or acquired resistance to this class of drugs. Additional treatment targets that may enhance the efficacy of EGFR–TKIs remain elusive. Using a CRISPR/Cas9-based screen, we identified the leucine-rich repeat scaffold protein SHOC2 as a key modulator of sensitivity to EGFR–TKI treatment. On the basis of in vitro assays, we demonstrated that SHOC2 expression levels strongly correlate with the sensitivity to EGFR–TKIs and that SHOC2 affects the sensitivity to EGFR–TKIs in NSCLC cells via SHOC2/MRAS/PP1c and SHOC2/SCRIB signaling. The potential SHOC2 inhibitor celastrol phenocopied SHOC2 depletion. In addition, we confirmed that SHOC2 expression levels were important for the sensitivity to EGFR–TKIs in vivo. Furthermore, IHC showed the accumulation of cancer cells that express high levels of SHOC2 in lung cancer tissues obtained from patients with NSCLC who experienced acquired resistance to EGFR–TKIs. These data indicate that SHOC2 may be a therapeutic target for patients with NSCLC or a biomarker to predict sensitivity to EGFR–TKI therapy in EGFR mutation-positive patients with NSCLC. Our findings may help improve treatment strategies for patients with NSCLC harboring EGFR mutations.

Implications:

This study showed that SHOC2 works as a modulator of sensitivity to EGFR–TKIs and the expression levels of SHOC2 can be used as a biomarker for sensitivity to EGFR–TKIs.

Non–small cell lung cancer (NSCLC) is a dominant subtype of lung cancer and one of the leading causes of death worldwide (1). Recent advancements in genomic sequencing have revealed that a substantial fraction of patients with NSCLC have mutated oncogenic drivers, such as the EGFR, Kirsten rat sarcoma viral oncogene (KRAS), and anaplastic lymphoma kinase (ALK; ref. 2). Among these oncogenes, gain-of-function mutations in the kinase domain of EGFR are promising targets of tyrosine kinase inhibitors (TKI) in patients with lung cancer (3). Multiple clinical trials have shown that TKIs are less toxic and more effective than traditional cytotoxic chemotherapeutics. EGFR–TKIs are the first-line treatment for patients with lung cancer, including those with mutated EGFR (4, 5); however, EGFR–TKI monotherapy cannot cure EGFR mutation-positive patients with lung cancer, owing to drug resistance (6, 7). Although there is a dramatic reduction in the tumor size in most patients undergoing EGFR–TKI treatment, therapeutic resistance develops within 1–2 years (8, 9). The expansion of rare, pre-existing, TKI-resistant clones, and/or small numbers of drug-tolerant persister cells (DTP) promotes resistance to EGFR–TKIs. Studies have elucidated the mechanisms involved in acquired resistance to EGFR–TKIs (10–12), but little is known about the survival of DTPs during the initial phase of drug exposure and how they rapidly adapt to EGFR–TKIs. A combination of EGFR–TKI and MEK inhibitors prevents the emergence of DTPs in a preclinical model (13), but the toxicity of this combination limits its application in patients (14, 15). To date, only a handful of drugs have been reported to improve the efficiency of EGFR–TKIs in clinical trials, such as bevacizumab and ramucirumab (12, 16, 17). Using a genome-wide CRISPR/Cas9 screen, we demonstrated that DTPs use endoplasmic reticulum stress to survive EGFR–TKI exposure. Multiple genes can affect the initial response to EGFR–TKIs, including the scaffold protein encoded by SHOC2 (18).

In this study, we characterized SHOC2 and demonstrated its role as a modulator of response to EGFR–TKIs in lung cancer cells in vitro and in vivo. Furthermore, we designed a putative drug combination to eliminate DTPs by targeting SHOC2. Finally, using lung cancer tissues from patients who experienced acquired resistance to EGFR–TKIs, we identified a population of cells that express high levels of SHOC2. Our findings offer a novel strategy for the diagnosis and treatment of patients with NSCLC with mutant EGFR and could improve the prognosis of patients with NSCLC.

Cell lines, culture conditions, and drugs

PC9 [EGFR exon 19 deletion (delE746-A750)] cells were obtained from collaborating laboratories and authenticated using a short tandem repeat analysis. H1975 (EGFR L858R + T790M) and H3122 cells (EML4–ALK fusion) were obtained from the ATCC. KOLK43 cells were derived from the tumor of a patient with NSCLC who acquired resistance to osimertinib (19). All cell lines were cultured in RPMI-1640 (Life Technologies) medium supplemented with 10% FBS and 1% penicillin/streptomycin at 37°C in a humidified 5% CO2 incubator. All cell lines were negative for Mycoplasma. Erlotinib, afatinib, and trametinib were purchased from LC Laboratories. Osimertinib and selumetinib were purchased from Selleck Chemicals. Celastrol was purchased from AdipoGen. Cisplatin and docetaxel were purchased from Wako Pure Chemical Industries, Ltd.

Cell proliferation assay

Cell density was measured after 120 hours of drug treatment with an MTS assay using CellTiter 96 Aqueous One Solution Assay (Promega) and a microplate reader (Model 680, Bio-Rad) following the manufacturer's protocol. Of note, SHOC2 depletion or overexpression alone did not impact cell proliferation. Data were normalized to the DMSO control. All samples were assayed in triplicate. The plotted data represent the mean ± standard deviation of technical triplicates and a representative experiment from at least two independent experiments.

Crystal violet staining

A total of 1 × 105 cells were seeded in triplicates in 6-well plates, allowed to attach overnight, and incubated with media containing drugs for 18 days. Media supplemented with the drugs were replaced every 4 days unless otherwise mentioned. After 18 days in culture, cells were fixed with 1% paraformaldehyde and stained with 0.1% w/v of crystal violet as previously described (18).

Western blotting

Proteins were extracted from cells using Cell Lysis Buffer (Cell Signaling Technology) following the manufacturer's protocol. Proteins were quantified using a BCA protein assay (Thermo Fisher Scientific), and equal amounts of protein were separated using SDS-PAGE and transferred to polyvinylidene fluoride membranes. The membranes were then incubated overnight with primary antibodies at 4°C followed by incubation with secondary antibodies for 1 hour. Immunoreactive proteins were incubated with LumiGLO reagent and peroxide (Cell Signaling Technology) and exposed to X-ray films. Antibodies targeting EGFR (#2232), ERK, MAPK (#9102), phospho-ERK (T202/204; #9101), and SHOC2 (#53600) were purchased from Cell Signaling Technology. Antibody against phospho-EGFR (Y1068; 44788G) was purchased from Invitrogen/Life Technologies. Antibodies targeting phospho-SHC1 (Y427; ab68166) and SHC1 (ab24787) were purchased from Abcam. Antibody against actin (#A5441) was purchased from Sigma-Aldrich.

Phosphopeptide enrichment and nanoscale liquid chromatography coupled to tandem mass spectrometry

Proteins were extracted using 100 mmol/L Tris-HCl (pH 9.0) containing 12 mmol/L sodium deoxycholate (SDC) and 12 mmol/L sodium lauroylsarcosinate (SLS) and were digested with Lys-C and trypsin. SDC and SLS were removed from the samples by phase transfer as previously described (20). Phosphorylated peptides were enriched using aliphatic hydroxy acid-modified metal oxide chromatography (21) and the Titansphere Phos-TiO Kit (GL Sciences). Peptides were purified using SDC-XC StageTip as previously described (22). TripleTOF 5600 (SCIEX) equipped with a Dionex Ultimate 3000 RSLS (Thermo Fisher Scientific Inc.) was used for nanoscale liquid chromatography coupled to tandem mass spectrometry. The injection volume was 5 μL and the flow rate was 300 nL/min. For peptide identification, data were acquired in the data-dependent acquisition mode and analyzed using ProteinPilot 4.5 (SCIEX) connected to the UniProt human reference proteome database (release 2017_09). Phosphorylation was set as the “Special Factors” in the sample description. The protein identification confidence for the dataset was evaluated on the basis of the FDR. For protein quantification, data were acquired in the data-independent acquisition mode (SWATH-MS) with a variable window for the precursor ions. The acquired data were analyzed using PeakView Software version 2.1 (SCIEX).

Constructing stable cell lines

To knockout SHOC2 from the cancer cell lines, we used sgRNA for SHOC2 (#1: 5′-CTCCAGTGCTGCCCAACCAG-3′, #2: 5′-GAGCTACATCCAGCGTAATG-3′, and #3: 5′-TAACATTTCTACTTTACCAG-3′) and control (dummy 5′- ATCGTTTCCGCTTAACGGCG-3′) to integrate into the lenti-CRISPR v2 (Addgene #52961) vector. To overexpress SHOC2, the insert from pENTR223-SHOC2 (#HsCD00513961, obtained from DNASU; refs. 23–26) was transferred to the pLEX_307 (Addgene #41392) and pLX304 (Addgene #25890) vectors using the Gateway cloning system (27). Each mutant of SHOC2 was generated using the following primers using QuikChange II Site-Directed Mutagenesis Kit (Agilent technologies): PAM-F, 5′-GCTGAAATTGGTGAATTATGTAATCTCATTACGCTGGATGTAGC-3′; PAM-R, 5′-GCTACATCCAGCGTAATGAGATTACATAATTCACCAATTTCAGC-3′; S2G-F, 5′-CTTTGTACAAAAAAGTTGGCATGGGTAGTAGTTTAGGAAAAG-3′; S2G-R, 5′-CTTTTCCTAAACTACTACCCATGCCAACTTTTTTGTACAAAG-3′; M173I-F, 5′-GAAGAAGCTGCGGATCCTTGATTTACGGCATAATAAAC-3′; M173I-R, 5′-GTTTATTATGCCGTAAATCAAGGATCCGCAGCTTCTTC-3′; D175N-F, 5′- GAAGAAGCTGCGGATGCTTAATTTACGGCATAATAAACTG-3′; D175N-R, 5′- CAGTTTATTATGCCGTAAATTAAGCATCCGCAGCTTCTTC-3′; E457K-F, 5′- GTTAAGAGAGTTGGATCTAGAAAAGAACAAATTGGAATCCTTGCC-3′; and E457K-R, 5′-GGCAAGGATTCCAATTTGTTCTTTTCTAGATCCAACTCTCTTAAC-3′. The expression plasmids were co-transfected with packaging plasmids (psPAX2, Addgene #12260 and pMD2.G, Addgene #12259) into HEK293T-17 cells to generate the lentivirus that was used to infect the PC9 and H1975 cell lines.

Mouse xenograft model

All animal experiments were approved by the Laboratory Animal Center, Keio University School of Medicine (approval no. 12115). Female BALB/c nude mice were purchased from Japan Charles River Laboratories. Mice were anesthetized with ketamine and Matrigel (Corning) suspensions containing sgDummy PC9 or sgSHOC2 PC9 cells were subcutaneously injected. Tumor volumes were measured using calipers. Randomly chosen mice were administered the vehicle control (1% DMSO, 30% PEG300) or osimertinib (5 mg/kg, 5 days per week, orally) once average tumor volumes reached 150 mm3.

IHC of clinical biopsy specimens

We selected patients who were administered EGFR–TKIs and had acquired resistance to them. This study was approved by the Institutional Review Board at Keio University School of Medicine (approval no. 20110171). All biopsy specimens were collected after patients provided written informed consent. Sections were stained using the anti-SHOC2 antibody (Proteintech #17561–1-AP, 1:100) and staining intensity was determined (0, no; 1, weak; 2, moderate; and 3, strong expression). Subsequently, the distribution of tumor cells with various staining intensities was evaluated for each sample. H score was calculated using the following formula: 1 × (% of tumor cells with weak intensity) + 2 × (% of tumor cells with moderate intensity)+3 × (% of tumor cells with strong intensity). The range was between 0 and 300 (28).

Statistical analysis

Statistical analysis was performed using GraphPad Prism 8.0 (GraphPad Software, Inc.). The student t test was used for all experiments. A P value of <0.05 was considered statistically significant.

Identification of SHOC2 as the top candidate gene that modulates the initial response to EGFR–TKIs

We reanalyzed the data from our CRISPR/Cas9 screen using EGFR mutation-positive NSCLC PC9 cells treated with the first-generation EGFR–TKI erlotinib (18). In our previous study, we conducted a genome-wide CRISPR/Cas9 screen using the Avana sgRNA library (29). Subsequently, we performed a follow-up validation screen using a small-scale custom library comprising sgRNAs targeting approximately 1,000 genes regulating the sensitivity to erlotinib (identified by the initial screen; Supplementary Table S1). To identify genes affecting the initial response to EGFR–TKIs, we used the STARS algorithm to create a list of genes that enhanced cellular lethality induced in patients who received 100 nmol/L erlotinib compared with those who received DMSO (Supplementary Fig. S1; ref. 29). We identified several candidate genes that strongly enhanced sensitivity to EGFR–TKI treatment upon ablation during the initial phase of therapy (Supplementary Table S2). These candidates had been previously classified as genes that confer resistance to EGFR–TKIs, such as AXL (12), FGFR1 (30), and BRAF (31), confirming the validity of the analysis. We selected SHOC2 because it was ranked second by the STARS algorithm and its depletion exerted a negligible effect on normal cells (Fig. 1A and B).

SHOC2 regulates the sensitivity of EGFR mutation-positive lung cancer cells to EGFR–TKIs

To confirm the data from the screen and understand the role(s) of SHOC2 in EGFR–TKI-sensitive cell lines, we used a lentiviral CRISPR/Cas9 system to generate SHOC2-depleted PC9 cells (32). Sensitivity to erlotinib significantly increased in SHOC2-depleted PC9 cells compared with the non-targeting dummy sgRNA-transduced PC9 cells (Fig. 2AC). We then determined that the effect of second- and third-generation EGFR–TKIs (afatinib and osimertinib, respectively) was enhanced in SHOC2-depleted PC9 cells (Fig. 2D). Furthermore, depleting SHOC2 in H1975 another lung cancer cell line with the EGFR L858R+T790M mutation, revealed that SHOC2 also regulates sensitivity to afatinib and osimertinib (Fig. 2D and E). This effect was not observed in cells incubated with CDDP or docetaxel, which are cytotoxic drugs used in the clinic (Supplementary Fig. S2A). Furthermore, SHOC2 depletion did not affect sensitivity to the ALK inhibitors, ceritinib, crizotinib, and alectinib in EML4–ALK-dependent H3122 lung cancer cells (Supplementary Fig. S2B), indicating that SHOC2 specifically affects sensitivity to EGFR–TKIs. Consistent with these findings, overexpression of SHOC2 in PC9 or H1975 cells renders them resistant to EGFR–TKIs (Fig. 2F and G). These results suggest that SHOC2 expression strongly correlates with sensitivity to EGFR–TKIs.

Domain analysis using mutagenesis reveals the effect of SHOC2 on sensitivity to EGFR–TKIs is through the regulation of PP1, MRAS, and SCRIB

Because SHOC2 is a scaffold protein (33), identifying its binding partners is important for understanding its function. The heterotrimeric holoenzyme formed by SHOC2, MRAS, and PP1c plays a key role in dephosphorylation of the RAF protein conserved inhibitory site (S259 in CRAF; ref. 34). On the other hand, the MRAS–SHOC2–SCRIB complex has been reported to play a role in the ERK pathway in the context of cell polarity (35). First, we determined whether the overexpression of SHOC2, with mutations in the protospacer adjacent motif (PAM) sequence that did not alter the codons, conferred resistance to targeting by CRISPR/Cas9-SHOC2 and rescued the effect seen by wild-type SHOC2 in SHOC2-depleted cells (Supplementary Fig. S3A). As expected, overexpressing PAM-mutant SHOC2 reduced sensitivity to EGFR–TKIs in the SHOC2-depleted PC9 cells (Supplementary Fig. S3B). We then selected four SHOC2 mutants based on previous reports (34) to characterize the domain(s) responsible for regulating sensitivity to EGFR–TKIs (Supplementary Fig. S3C). The D175N and E457K mutations enhanced sensitivity to EGFR–TKIs (Fig. 3A). On the basis of previous reports (34), compared with wild-type SHOC2, the D175N mutant was defective in interacting with PP1c and MRAS, and the E457K mutant was defective in binding SCRIB. On the other hand, the S2G and M173I mutants showed lower sensitivity to EGFR–TKIs, similar to that of the PAM mutant (Fig. 3A). In prior studies, both these mutants strongly activated the MAPK–ERK pathway, which is consistent with their causative role in RASopathy (Noonan syndrome; refs. 34, 36–38). These results and published reports suggest that the regulation of EGFR–TKI activity by SHOC2 may be mediated by the MRAS–PP1–ERK pathways, and to some extent, by the SCRIB pathway. The M173I and E457K mutants increased the phosphorylation of ERK; meanwhile, the D175N mutant decreased ERK phosphorylation, and the S2G SHOC2 mutant did not strongly enhance the phosphorylation of ERK (Fig. 3B). Moreover, the SHOC2 E457K mutant failed to protect cells against EGFR-TKI, even though it preserved pERK signaling, suggesting the potential function of SHOC2–SCRIB binding in the context of EGFR–TKI sensitivity. Conversely, according to a previous study, SHOC2 S2G enhances MAPK signaling by localizing to the inner plasma membrane and post-translationally modifying the N-terminus (N-myristoylation) of SHOC2 via ERK phosphorylation; however, this was not strongly increased by the SHOC2 S2G mutant in our model (38, 39). To understand the subcellular distribution of SHOC2, we performed immunofluorescence using a V5 antibody in PC9 cells expressing V5-tagged SHOC2 mutants; all SHOC2 mutants except S2G localized to the cytoplasm (Supplementary Fig. S3D). Consistent with previous reports (38, 39), the SHOC2 S2G mutant localized to the transmembrane, where it could interact with the MRAS/PP1c complex to activate MAPK signaling.

Phosphoproteomic analysis identified the downstream effectors of SHOC2

To identify the upstream and downstream effectors of SHOC2, we determined the levels of phosphorylated proteins by phosphoproteomic analysis using cell lysates from sgSHOC2- and sgDummy-transduced PC9 cells in the presence or absence of erlotinib for 24 hours (Fig. 3C; Supplementary Fig. S4A). The threonine/serine phosphorylation sites affected by SHOC2 depletion are shown in Supplementary Fig. S4B and S4C. We observed a strong reduction in SHC1 phosphorylation in both sgSHOC2- and sgDummy-transduced PC9 cells treated with erlotinib (Supplementary Fig. S4D). We examined the level of phosphorylation of these proteins using immunoblotting; there was a reduction in SHC1 phosphorylation at Y427 in SHOC2-depleted cells after osimertinib or erlotinib treatment (Fig. 3D). SHC1 is a temporal regulator of EGF signaling (40); thus, dephosphorylation of SHC1 would reflect the downregulation of EGF signaling in SHOC2-depleted cells. A previous study demonstrated that RAF dephosphorylation is mediated by the SHOC2 phosphatase complex consisting of SHOC2, MRAS, and PP1c (41), and dephosphorylation of the conserved inhibitory site of the RAF protein (ARAF S214, BRAF S365, CRAF S259) leads to its dimerization and activation (42, 43). Thus, we examined the phosphorylation status of ARAF S214, BRAF S365, and CRAF S259 in PC9-sgSHOC2 and PC9-sgDummy cells. There was increased phosphorylation of BRAF S365 in sgSHOC2 PC9 cells, whereas the phosphorylation of ARAF S214 and CRAF S259 was undetectable (Supplementary Fig. S4D). These results suggest that the SHOC2 complex mediates the phosphorylation of BRAF 365 in our model. Furthermore, these data are consistent with the CRISPR/Cas9 screen analysis, as BRAF ranked 4th using the STARS algorithm (Fig. 1A and B; Supplementary Table S2).

Potential strategy to improve the efficacy of EGFR–TKIs

Celastrol is a pharmacologically active triterpenoid extracted from the Chinese herb Tripterygium wilfordii. Celastrol has various physiological activities against cancer, autoimmune diseases, and neurodegenerative diseases (44). Celastrol can inhibit the growth of multiple cancers, including prostate cancer, glioma, osteosarcoma, liver cancer, and colorectal cancer (45). Celastrol binds SHOC2 and inhibits its function (44). Thus, we investigated the effects of celastrol on SHOC2 in PC9 cells. Consistent with SHOC2 depletion, concentrations of celastrol that were found to be ineffective as a single therapy, acted synergistically with osimertinib in PC9 and H1975 cells (Fig. 4A; Supplementary Fig. S5A). We confirmed the synergistic effect of the combination treatment at multiple concentrations, according to scores given by the Bliss Independence model (Supplementary Table S3). Moreover, combined incubation with celastrol and the EGFR–TKI osimertinib decreased the phosphorylation of ERK compared with that induced by treatment with either drug alone (Fig. 4B).

SHOC2 deletion selectively sensitizes KRAS- and EGFR-mutant NSCLC cells to MEK inhibitors (41). This prompted us to analyze the efficacy of MEK inhibitors in combination with EGFR–TKIs and SHOC2 depletion. Treatment with the MEK inhibitors, trametinib, or selumetinib, synergistically inhibited cell proliferation when combined with osimertinib in SHOC2-depleted PC9 cells (Fig. 4C). The MEK inhibitors enhanced the effects of the combination of osimertinib and celastrol. In fact, this triple therapy eliminated DTPs completely (Fig. 4D). Moreover, we observed a reduction in the phosphorylated forms of ERK and SHC1 (Fig. 4E and F).

SHOC2 depletion regulates EGFR–TKI sensitivity in vivo

To determine whether SHOC2 affects sensitivity to EGFR–TKIs in vivo, we subcutaneously injected SHOC2-depleted and control PC9 cells into nude mice to induce xenografted tumors and then treated the mice with osimertinib (Fig. 5A). During treatment, we did not observe any changes in body weight (Supplementary Fig. S6A). Consistent with a recent report that SHOC2 is essential for growth in non-adherent leukemia cell lines (46), sgSHOC2 PC9-induced tumors proliferated slightly slower than sgDummy PC9-induced tumors. Osimertinib strongly inhibited the growth of sgSHOC2 PC9-induced tumors compared with sgDummy PC9 xenografts (Fig. 5B and C). We used immunoblotting to identify the downstream effectors of SHOC2 in vivo; however, clear signals in the xenograft tumor lysates were not detected (Supplementary Fig. S6B). Because we did not clone the sgDummy or sgSHOC2#2 PC9 cell lines before inoculation, the differences in SHOC2/actin expression between mice may have been due to cell heterogeneity.

Expression of SHOC2 after EGFR–TKI treatment in clinical biopsy specimens

To confirm the clinical relevance of SHOC2 in patients with lung cancer with mutant EGFR, we collected biopsy specimens pre- and post-EGFR–TKI treatment and performed IHC. We defined weak, moderate, and strong SHOC2 expression according to staining intensity (Fig. 6A). There was no significant difference in the maximum SHOC2 expression between the pre- and post-treatment biopsy specimens; however, there was an increase in localized areas of SHOC2 staining in post-treatment biopsies. To understand this result, we evaluated the H score (28) to clarify significant increases in the biopsy specimens treated with EGFR–TKI (Fig. 6B). Patient characteristics and H scores are summarized in Table 1. Figure 6C shows representative images of pre- and post-treatment biopsies stained with SHOC2. All post-treatment biopsies obtained from patients met the established clinical definition of acquired resistance to EGFR–TKI. In addition, we identified the major EGFR T790M resistance mutation in 7 out of 11 patients. However, we did not observe any correlation between the T790M EGFR second mutation and SHOC2 expression level. Finally, we established a cell line, KOLK43, from the tumor biopsy of patient 4 post-EGFR–TKI treatment (19) and found that depletion of SHOC2 in these cells conferred sensitivity to osimertinib (Fig. 6D), suggesting that SHOC2 expression renders the cells resistant to EGFR–TKI.

Several clinical reports have shown the importance of the initial response to combination treatments that include EGFR–TKIs to achieve long-term, progression-free survival (47, 48). These findings suggest that eliminating DTPs from NSCLC tumors is necessary to maintain the effectiveness of EGFR–TKIs and devise combinatorial therapeutic strategies; however, inhibiting multiple targets or using cytotoxic chemotherapy in therapeutic combinations may increase the probability of side effects. In this study, we demonstrated that SHOC2 is critical for modulating the response of EGFR-mutant lung cancer cells to EGFR–TKIs. To the best of our knowledge, this is the first report to show the effect of SHOC2 in lung cancer cells treated with EGFR–TKI in vitro and in vivo.

Recent publications have characterized SHOC2 as a key modulator of the MEK pathway (34, 41, 43). Thus, we confirmed that the expression of SHOC2 affects sensitivity to EGFR–TKI therapies and EGFR–TKI/MEK inhibitor combination therapies. SHOC2 did not affect sensitivity to classical cytotoxic agents or ALK–TKIs in NSCLC cells with ALK translocations, suggesting that SHOC2 affects EGFR and MEK signaling pathways.

To characterize the molecular mechanisms responsible for the effects of SHOC2 on EGFR–TKI sensitivity, we evaluated the interaction between SHOC2 and its binding partners, PP1c and SCRIB (34). SHOC2 modulated the effect of EGFR–TKIs mainly via MAPK signaling when it bound to PP1c, and to some extent, via its binding with SCRIB, although there are no reports implicating the SCRIB pathway in modulating sensitivity to EGFR–TKI therapy. SCRIB was originally reported as a tumor-suppressor gene in Drosophila (49). Moreover, the complex formed by MRAS, SHOC2, and SCRIB was previously reported as a regulator of the ERK pathway (35). SCRIB has also been reported as a potential oncogene, and of note, its mutant form has been shown to activate the PI3K pathway in a mammalian cancer model (50). At least as a representative marker of MAPK activation, p-ERK was increased in PC9 cells carrying the SHOC2 E457K mutant; however, this was not enough to reduce the sensitivity to EGFR–TKIs. It is possible that the SHOC2–SCRIB complex would impact both PI3K pathway–mediated and MAPK pathway–mediated signaling, but this could not be concluded with certainty in our study. Further research is needed to understand how the interaction between SHOC2 and SCRIB affects the sensitivity of NSCLC cells to EGFR–TKIs.

Although the research and development of TKIs have progressed, advances in phosphatase inhibitors have been lagging. Several recent reports have explored dephosphorylation inhibition, such as targeted therapy against PTPN11, as a therapeutic strategy (51). SHOC2 mediates RAF dephosphorylation (41). Consistent with these findings, in our phosphoproteomic analyses, we found that BRAF phosphorylation increased in SHOC2-depleted cell lines. As a phosphatase, PP1c has a broad target spectrum, and while targeting the SHOC2 complex (which includes PP1c) may inhibit dephosphorylation in a more specific manner, there have been no reports of drugs that specifically inhibit the function of SHOC2. Since a recent publication characterized celastrol as a potential SHOC2 inhibitor, we explored its efficacy in combination with EGFR–TKIs and MEK inhibitors in NSCLC cells (44). Combining celastrol with EGFR–TKIs or EGFR–TKI/MEK inhibitors phenocopied the effects of those treatments in SHOC2-depleted cells. Phosphorylating T507 of SHOC2 induces its ubiquitylation and degradation, so increased kinase activity targeted to this site may be an alternative way to reduce SHOC2 levels (52). In addition, Sulahian and colleagues (53) demonstrated that SHOC2 depletion combined with MEK inhibitors were effective in a xenograft mouse model of ductal pancreatic adenocarcinoma. These data indicate that targeting SHOC2 may be a promising therapeutic strategy when combined with TKIs to enhance its effects.

In addition, we found that the number of SHOC2-expressing cancer cells in NSCLC biopsies increased in patients who had acquired resistance to EGFR–TKIs; therefore, we speculate that cells that express higher levels of SHOC2 are more likely to survive EGFR–TKI treatment. Although we used pre- and post-EGFR–TKI treatment tissue samples in the current study to demonstrate multiple mechanisms and magnitudes of EGFR–TKI resistance, future studies with multiple patient biopsy specimens from multiple time points would elucidate the precise mechanism of SHOC2 in EGFR-mutant–positive patients with lung cancer. There are many types of EGFR mutants detected in clinical NSCLC; therefore, evaluating the SHOC2 effects in context of these mutations would be important. Because SHOC2-derived modulation of the EGFR pathway is mediated by its binding partners PP1c, MRAS, and SCRIB, it is also important to investigate whether different mutations impact any of these proteins. In the present study, we evaluated the roles of SHOC2 in PC9 [EGFR exon 19 deletion (delE746-A750)] and H1975 (EGFR L858R + T790M) cell lines. Of note, the EGFR alterations in the IHC-evaluated patients included EGFR exon 19 deletion, exon 19 deletion + T790M, L858R, L858R + T790M, and G719C. Although multiple groups have reported the combined efficacy of SHOC2 and MEK inhibitors (43, 52, 53), they did not evaluate SHOC2 expression levels in clinical samples. Thus, this study is the first to show the clinical relevance of SHOC2 as a modulator of TKI sensitivity. We propose that SHOC2 levels may be used as a biomarker for the efficacy of EGFR–TKI therapy alone or in combination with MEK inhibitors. The combination of osimertinib and the MEK inhibitor, trametinib, is currently being evaluated in a clinical trial (NCT03392246).

However, this study has some limitations. For example, the mechanisms by which SHOC2 exerts and modulates its functions need to be elucidated using domain analysis or subcellular localization. Moreover, a larger number of NSCLC biopsies need to be evaluated to conclusively demonstrate the clinical relevance of targeting SHOC2. Even with these limitations, our study begins to clarify the mechanisms responsible for the initial response to EGFR–TKIs and suggests a new treatment strategy for EGFR mutation–positive NSCLC, which may improve the prognosis of patients with NSCLC.

K. Soejima reports grants from AstraZeneca, Nippon Boehringer Ingelheim, and Taiho Pharmaceutical, as well as personal fees from AstraZeneca, Chugai Pharmaceutical, Ono Pharmaceutical, Bristol-Myers Squibb Japan, MSD Oncology, Lily Japan, Taiho Pharmaceutical, Nippon Kayaku, and Novartis Pharma outside the submitted work. No disclosures were reported by the other authors.

H. Terai: Conceptualization, data curation, funding acquisition, methodology, writing–original draft, writing–review and editing. J. Hamamoto: Validation, methodology, writing–original draft, project administration. K. Emoto: Resources, methodology. T. Masuda: Resources, methodology, writing–review and editing. T. Manabe: Resources, methodology. S. Kuronuma: Resources, methodology. K. Kobayashi: Resources, methodology. K. Masuzawa: Resources, methodology. S. Ikemura: Conceptualization, writing–review and editing. S. Nakayama: Data curation, writing–review and editing. I. Kawada: Supervision, writing–review and editing. Y. Suzuki: Supervision, writing–review and editing. O. Takeuchi: Resources, supervision, writing–review and editing. Y. Suzuki: Supervision. S. Ohtsuki: Resources, supervision. H. Yasuda: Resources, supervision, funding acquisition. K. Soejima: Supervision, funding acquisition, writing–review and editing. K. Fukunaga: Supervision, funding acquisition.

This work was supported in part by the Japan Society for the Promotion of Science (grant #18K08184; to H. Terai) and (grant #17K09667; to H. Yasuda). This work was also supported in part by grants awarded by the Takeda Science Foundation (to H. Yasuda and H. Terai). We thank Dr. David Barbie (Dana Farber Cancer Institute, Boston, MA) and Peter Hammerman (Novartis Institutes of Biomedical Research, Cambridge, MA) for their advice. The authors thank Chinatsu Yonekawa, Mikiko Shibuya, Miho Takeoka, Yui Kakishima, and Nodoka Adegawa for their technical assistance. We would like to thank Editage (www.editage.com) for English language editing.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Siegel
RL
,
Miller
KD
,
Jemal
A
. 
Cancer statistics, 2016
.
CA Cancer J Clin
2016
;
66
:
7
30
.
2.
Campbell
JD
,
Alexandrov
A
,
Kim
J
,
Wala
J
,
Berger
AH
,
Pedamallu
CS
, et al
Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas
.
Nat Genet
2016
;
48
:
607
16
.
3.
Paez
JG
,
Janne
PA
,
Lee
JC
,
Tracy
S
,
Greulich
H
,
Gabriel
S
, et al
EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy
.
Science
2004
;
304
:
1497
500
.
4.
Mok
TS
,
Wu
YL
,
Thongprasert
S
,
Yang
CH
,
Chu
DT
,
Saijo
N
, et al
Gefitinib or carboplatin-paclitaxel in pulmonary adenocarcinoma
.
N Engl J Med
2009
;
361
:
947
57
.
5.
Sequist
LV
,
Yang
JC
,
Yamamoto
N
,
O'Byrne
K
,
Hirsh
V
,
Mok
T
, et al
Phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations
.
J Clin Oncol
2013
;
31
:
3327
34
.
6.
Maemondo
M
,
Inoue
A
,
Kobayashi
K
,
Sugawara
S
,
Oizumi
S
,
Isobe
H
, et al
Gefitinib or chemotherapy for non–small cell lung cancer with mutated EGFR
.
N Engl J Med
2010
;
362
:
2380
8
.
7.
Miller
VA
,
Hirsh
V
,
Cadranel
J
,
Chen
YM
,
Park
K
,
Kim
SW
, et al
Afatinib versus placebo for patients with advanced, metastatic non–small cell lung cancer after failure of erlotinib, gefitinib, or both, and one or two lines of chemotherapy (LUX-Lung 1): a phase 2b/3 randomised trial
.
Lancet Oncol
2012
;
13
:
528
38
.
8.
Hata
AN
,
Niederst
MJ
,
Archibald
HL
,
Gomez-Caraballo
M
,
Siddiqui
FM
,
Mulvey
HE
, et al
Tumor cells can follow distinct evolutionary paths to become resistant to epidermal growth factor receptor inhibition
.
Nat Med
2016
;
22
:
262
9
.
9.
Sharma
SV
,
Lee
DY
,
Li
B
,
Quinlan
MP
,
Takahashi
F
,
Maheswaran
S
, et al
A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations
.
Cell
2010
;
141
:
69
80
.
10.
Holohan
C
,
Van Schaeybroeck
S
,
Longley
DB
,
Johnston
PG
. 
Cancer drug resistance: an evolving paradigm
.
Nat Rev Cancer
2013
;
13
:
714
26
.
11.
Soucheray
M
,
Capelletti
M
,
Pulido
I
,
Kuang
Y
,
Paweletz
CP
,
Becker
JH
, et al
Intratumoral heterogeneity in EGFR-mutant NSCLC results in divergent resistance mechanisms in response to EGFR tyrosine kinase inhibition
.
Cancer Res
2015
;
75
:
4372
83
.
12.
Morgillo
F
,
Della Corte
CM
,
Fasano
M
,
Ciardiello
F
. 
Mechanisms of resistance to EGFR-targeted drugs: lung cancer
.
ESMO Open
2016
;
1
:
e000060
.
13.
Tricker
EM
,
Xu
C
,
Uddin
S
,
Capelletti
M
,
Ercan
D
,
Ogino
A
, et al
Combined EGFR/MEK inhibition prevents the emergence of resistance in egfr-mutant lung cancer
.
Cancer Discov
2015
;
5
:
960
71
.
14.
Corcoran
RB
,
Andre
T
,
Atreya
CE
,
Schellens
JHM
,
Yoshino
T
,
Bendell
JC
, et al
Combined BRAF, EGFR, and MEK inhibition in patients with BRAF(V600E)-mutant colorectal cancer
.
Cancer Discov
2018
;
8
:
428
43
.
15.
Daud
A
,
Tsai
K
. 
Management of treatment-related adverse events with agents targeting the MAPK pathway in patients with metastatic melanoma
.
Oncologist
2017
;
22
:
823
33
.
16.
Herbst
RS
,
Ansari
R
,
Bustin
F
,
Flynn
P
,
Hart
L
,
Otterson
GA
, et al
Efficacy of bevacizumab plus erlotinib versus erlotinib alone in advanced non–small cell lung cancer after failure of standard first-line chemotherapy (BeTa): a double-blind, placebo-controlled, phase 3 trial
.
Lancet
2011
;
377
:
1846
54
.
17.
Alexander
M
,
Halmos
B
. 
VEGF inhibitors in EGFR-mutated lung cancer: a never-ending story?
Ann Transl Med
2018
;
6
:
446
.
18.
Terai
H
,
Kitajima
S
,
Potter
DS
,
Matsui
Y
,
Quiceno
LG
,
Chen
T
, et al
ER stress signaling promotes the survival of cancer "persister cells" tolerant to EGFR tyrosine kinase inhibitors
.
Cancer Res
2018
;
78
:
1044
57
.
19.
Manabe
T
,
Yasuda
H
,
Terai
H
,
Kagiwada
H
,
Hamamoto
J
,
Ebisudani
T
, et al
IGF2 autocrine-mediated IGF1R activation is a clinically relevant mechanism of osimertinib resistance in lung cancer
.
Mol Cancer Res
2020
;
18
:
549
59
.
20.
Masuda
T
,
Tomita
M
,
Ishihama
Y
. 
Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis
.
J Proteome Res
2008
;
7
:
731
40
.
21.
Sugiyama
N
,
Masuda
T
,
Shinoda
K
,
Nakamura
A
,
Tomita
M
,
Ishihama
Y
. 
Phosphopeptide enrichment by aliphatic hydroxy acid-modified metal oxide chromatography for nano-LC-MS/MS in proteomics applications
.
Mol Cell Proteomics
2007
;
6
:
1103
9
.
22.
Rappsilber
J
,
Mann
M
,
Ishihama
Y
. 
Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using stagetips
.
Nat Protoc
2007
;
2
:
1896
906
.
23.
Seiler
CY
,
Park
JG
,
Sharma
A
,
Hunter
P
,
Surapaneni
P
,
Sedillo
C
, et al
DNASU plasmid and PSI:biology-materials repositories: resources to accelerate biological research
.
Nucleic Acids Res
2014
;
42
:
D1253
60
.
24.
Cormier
CY
,
Mohr
SE
,
Zuo
D
,
Hu
Y
,
Rolfs
A
,
Kramer
J
, et al
Protein structure initiative material repository: an open shared public resource of structural genomics plasmids for the biological community
.
Nucleic Acids Res
2010
;
38
:
D743
9
.
25.
Cormier
CY
,
Park
JG
,
Fiacco
M
,
Steel
J
,
Hunter
P
,
Kramer
J
, et al
PSI:Biology-materials repository: a biologist's resource for protein expression plasmids
.
J Struct Funct Genomics
2011
;
12
:
55
62
.
26.
Rual
JF
,
Hirozane-Kishikawa
T
,
Hao
T
,
Bertin
N
,
Li
S
,
Dricot
A
, et al
Human ORFeome version 1.1: a platform for reverse proteomics
.
Genome Res
2004
;
14
:
2128
35
.
27.
Katzen
F
. 
Gateway((R)) recombinational cloning: a biological operating system
.
Expert Opin Drug Discov
2007
;
2
:
571
89
.
28.
McCarty
KS
,
Szabo
E
,
Flowers
JL
,
Cox
EB
,
Leight
GS
,
Miller
L
, et al
Use of a monoclonal anti-estrogen receptor antibody in the immunohistochemical evaluation of human tumors
.
Cancer Res
1986
;
46
:
4244s
8s
.
29.
Doench
JG
,
Fusi
N
,
Sullender
M
,
Hegde
M
,
Vaimberg
EW
,
Donovan
KF
, et al
Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9
.
Nat Biotechnol
2016
;
34
:
184
91
.
30.
Terai
H
,
Soejima
K
,
Yasuda
H
,
Nakayama
S
,
Hamamoto
J
,
Arai
D
, et al
Activation of the FGF2–FGFR1 autocrine pathway: a novel mechanism of acquired resistance to gefitinib in NSCLC
.
Mol Cancer Res
2013
;
11
:
759
67
.
31.
Yu
HA
,
Arcila
ME
,
Rekhtman
N
,
Sima
CS
,
Zakowski
MF
,
Pao
W
, et al
Analysis of tumor specimens at the time of acquired resistance to EGFR–TKI therapy in 155 patients with EGFR-mutant lung cancers
.
Clin Cancer Res
2013
;
19
:
2240
7
.
32.
Shalem
O
,
Sanjana
NE
,
Hartenian
E
,
Shi
X
,
Scott
DA
,
Mikkelsen
TS
, et al
Genome-scale CRISPR-Cas9 knockout screening in human cells
.
Science
2014
;
343
:
84
7
.
33.
Matsunaga-Udagawa
R
,
Fujita
Y
,
Yoshiki
S
,
Terai
K
,
Kamioka
Y
,
Kiyokawa
E
, et al
The scaffold protein Shoc2/SUR-8 accelerates the interaction of Ras and Raf
.
J Biol Chem
2010
;
285
:
7818
26
.
34.
Young
LC
,
Hartig
N
,
Boned Del Rio
I
,
Sari
S
,
Ringham-Terry
B
,
Wainwright
JR
, et al
SHOC2–MRAS–PP1 complex positively regulates RAF activity and contributes to Noonan syndrome pathogenesis
.
Proc Natl Acad Sci U S A
2018
;
115
:
E10576
85
.
35.
Young
LC
,
Hartig
N
,
Munoz-Alegre
M
,
Oses-Prieto
JA
,
Durdu
S
,
Bender
S
, et al
An MRAS, SHOC2, and SCRIB complex coordinates ERK pathway activation with polarity and tumorigenic growth
.
Mol Cell
2013
;
52
:
679
92
.
36.
Hannig
V
,
Jeoung
M
,
Jang
ER
,
Phillips
JA
 III
,
Galperin
E
. 
A novel SHOC2 variant in rasopathy
.
Hum Mutat
2014
;
35
:
1290
4
.
37.
Komatsuzaki
S
,
Aoki
Y
,
Niihori
T
,
Okamoto
N
,
Hennekam
RC
,
Hopman
S
, et al
Mutation analysis of the SHOC2 gene in Noonan-like syndrome and in hematologic malignancies
.
J Hum Genet
2010
;
55
:
801
9
.
38.
Cordeddu
V
,
Di Schiavi
E
,
Pennacchio
LA
,
Ma'ayan
A
,
Sarkozy
A
,
Fodale
V
, et al
Mutation of SHOC2 promotes aberrant protein N-myristoylation and causes Noonan-like syndrome with loose anagen hair
.
Nat Genet
2009
;
41
:
1022
6
.
39.
Motta
M
,
Chillemi
G
,
Fodale
V
,
Cecchetti
S
,
Coppola
S
,
Stipo
S
, et al
SHOC2 subcellular shuttling requires the KEKE motif-rich region and N-terminal leucine-rich repeat domain and impacts on ERK signalling
.
Hum Mol Genet
2016
;
25
:
3824
35
.
40.
Zheng
Y
,
Zhang
C
,
Croucher
DR
,
Soliman
MA
,
St-Denis
N
,
Pasculescu
A
, et al
Temporal regulation of EGF signalling networks by the scaffold protein Shc1
.
Nature
2013
;
499
:
166
71
.
41.
Jones
GG
,
Del Rio
IB
,
Sari
S
,
Sekerim
A
,
Young
LC
,
Hartig
N
, et al
SHOC2 phosphatase-dependent RAF dimerization mediates resistance to MEK inhibition in RAS-mutant cancers
.
Nat Commun
2019
;
10
:
2532
.
42.
Kaplan
FM
,
Kugel
CH
 III
,
Dadpey
N
,
Shao
Y
,
Abel
EV
,
Aplin
AE
. 
SHOC2 and CRAF mediate ERK1/2 reactivation in mutant NRAS-mediated resistance to RAF inhibitor
.
J Biol Chem
2012
;
287
:
41797
807
.
43.
Boned Del Rio
I
,
Young
LC
,
Sari
S
,
Jones
GG
,
Ringham-Terry
B
,
Hartig
N
, et al
SHOC2 complex-driven RAF dimerization selectively contributes to ERK pathway dynamics
.
Proc Natl Acad Sci U S A
2019
;
116
:
13330
9
.
44.
Xiao-Pei
H
,
Ji-Kuai
C
,
Xue
W
,
Dong
YF
,
Yan
L
,
Xiao-Fang
Z
, et al
Systematic identification of Celastrol-binding proteins reveals that Shoc2 is inhibited by Celastrol
.
Biosci Rep
2018
;
38
:
BSR20181233
.
45.
Cascao
R
,
Fonseca
JE
,
Moita
LF
. 
Celastrol: a spectrum of treatment opportunities in chronic diseases
.
Front Med
2017
;
4
:
69
.
46.
Wang
T
,
Yu
H
,
Hughes
NW
,
Liu
B
,
Kendirli
A
,
Klein
K
, et al
Gene essentiality profiling reveals gene networks and synthetic lethal interactions with oncogenic ras
.
Cell
2017
;
168
:
890
903 e15
.
47.
Noronha
V
,
Patil
VM
,
Joshi
A
,
Menon
N
,
Chougule
A
,
Mahajan
A
, et al
Gefitinib versus gefitinib plus pemetrexed and carboplatin chemotherapy in EGFR-mutated lung cancer
.
J Clin Oncol
2019
:
JCO1901154
.
48.
Kuczynski
EA
,
Sargent
DJ
,
Grothey
A
,
Kerbel
RS
. 
Drug rechallenge and treatment beyond progression—implications for drug resistance
.
Nat Rev Clin Oncol
2013
;
10
:
571
87
.
49.
Bilder
D
,
Perrimon
N
. 
Localization of apical epithelial determinants by the basolateral PDZ protein scribble
.
Nature
2000
;
403
:
676
80
.
50.
Michaelis
UR
,
Chavakis
E
,
Kruse
C
,
Jungblut
B
,
Kaluza
D
,
Wandzioch
K
, et al
The polarity protein Scrib is essential for directed endothelial cell migration
.
Circ Res
2013
;
112
:
924
34
.
51.
Ruess
DA
,
Heynen
GJ
,
Ciecielski
KJ
,
Ai
J
,
Berninger
A
,
Kabacaoglu
D
, et al
Mutant KRAS-driven cancers depend on PTPN11/SHP2 phosphatase
.
Nat Med
2018
;
24
:
954
60
.
52.
Xie
CM
,
Tan
M
,
Lin
XT
,
Wu
D
,
Jiang
Y
,
Tan
Y
, et al
The FBXW7–SHOC2-raptor axis controls the cross-talks between the RAS–ERK and mTORC1 signaling pathways
.
Cell Rep
2019
;
26
:
3037
50 e4
.
53.
Sulahian
R
,
Kwon
JJ
,
Walsh
KH
,
Pailler
E
,
Bosse
TL
,
Thaker
M
, et al
Synthetic lethal interaction of SHOC2 depletion with MEK inhibition in RAS-driven cancers
.
Cell Rep
2019
;
29
:
118
34 e8
.