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Introduction
Patients diagnosed with advanced non-small cell lung cancer (NSCLC) generally have a very poor prognosis. The median overall survival of patients with unresectable disease is 10–13 months when treated with standard platinum-doublet chemotherapeutic regimens, and 22 months when immune checkpoint inhibitor is combined with cytotoxic chemotherapy [1–4]. Nevertheless, NSCLC treatment has been revolutionized by the discovery of oncogenic driver mutations and the development of matched selective and targeted inhibitors. For epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor therapy, survival outcomes have been significantly improved, and anaplastic lymphoma kinase (ALK) inhibitors demonstrate even better results in metastatic lung cancer patients harboring these targetable oncogenic molecular alterations [5,6]. Therefore, identifying driver mutations and developing matching selective inhibitors is a key strategy in the treatment of these specific subsets of lung cancer.
Mesenchymal-epithelial transition factor (MET) is a receptor tyrosine kinase that initiates multiple signaling cascades upon activation through binding of hepatocyte growth factor. Pathways activated by MET activation include mitogen-activated protein kinase, phosphoinositide 3-kinase/AKT-axis, signal transducer and activator of transcription, and nuclear factor-κB complex, which are all key signaling pathways in tumorigenesis [7]. Accordingly, MET dysregulation has been validated as an oncogenic driver in many types of malignancies, including NSCLC [8,9].
MET dysregulation is known to be caused by various mechanisms, including overexpression or genetic alteration. However, gene amplification or mutations that lead to functional activation of kinase activity are widely accepted indices for clinically defining MET dysregulations in patients with these molecular alterations, and have been associated with poor clinical prognosis and response to selective MET inhibition [10–13].
Previous studies have assessed MET amplification by utilizing gene copy number (GCN) in surgically resected NSCLC samples, and found that high GCN levels are associated with worse survival [10,11,14]. In addition, positive responses to MET inhibitors have been reported in patients with de novo MET amplification [15,16]. Mutations causing skipping of exon 14 (METex14) are another well-known mechanism of MET dysregulation. Exon 14 encodes the binding site for casitas B-lineage lymphoma, the E3 ubiquitin ligase that degrades MET [17]. Thus, mutations that result in deletion of exon 14 invariably enhance MET stability, causing signaling dysregulation. Exon 14-skipping mutations are also reported to be associated with poor clinical outcome in NSCLC [10,18]. Importantly, small molecule MET inhibitors have been shown to be effective in patients harboring these genetic mutations [12,13,19–22]. And recently, crizotinib has been demonstrated to be a potent therapeutic option in lung cancer patients with METex14 in a prospective clinical trial [23]. The incidence of MET dysregulation is relatively rare in newly diagnosed NSCLC, with MET amplification reportedly occurring in 2%–3% of newly diagnosed cases [11,24,25], and mutations leading to exon 14 skipping occurring in 3%–4% of NSCLCs [12,22,25,26]. Nevertheless, identifying lung cancer patients with MET dysregulation is a priority as novel therapeutic agents become available.
Capmatinib (INC280) is a highly potent MET inhibitor that has been validated in preclinical research [27]. We participated in the phase 2 trial of capmatinib (GEOMETRY mono-1, NCT02414139) and screened locally advanced/metastatic NSCLC patients for eligibility [28]. The study was designed to evaluate the efficacy of MET inhibition in six different cohorts based on MET GCN levels or the presence of METex14. We tested these two profiles in addition to performing immunohistochemical (IHC) staining of MET for patients who participated in the screening.
In this retrospective study, we aimed to delineate the clinical characteristics and prognostic effect of MET dysregulation in advanced NSCLC by utilizing clinical data from patients who were screened for eligibility in the capmatinib trial. We also determined whether capmatinib affects the survival of patients with MET dysregulation, defined as either the presence of METex14 or GCN of at least 10 copies per cell.
Materials and Methods
1. Patients
Patients who were screened for eligibility for a phase 2 trial of capmatinib (INC280) at the National Cancer Center Hospital (Goyang, Korea) from December 2015 to January 2019 were included in this retrospective analysis (NCT02414139). All the patients were diagnosed with locally advanced (stage IIIB) or metastatic (stage IV) NSCLC, with no documented molecular alteration of EGFR or ALK genes. Data were mainly collected by review of electronic medical records. For patients enrolled in the trial, capmatinib was given at the dose of 400 mg twice a day in tablet formulation. Response to capmatinib was assessed by the Response Evaluation Criteria in Solid Tumors ver. 1.1.
2. Gene copy number
MET GCN was analyzed by fluorescence in situ hybridization (FISH) using the Vysis MET FISH kit (Abbott Molecular, Des Plaines, IL). In brief, 4-μm thick sections prepared from formalin-fixed paraffin-embedded (FFPE) tissue samples were deparaffinized, hybridized with probes targeting MET, and counterstained with 4′,6-diamidino-2-phenylindole (DAPI). At least 50 non-overlapping nuclei of tumor cells were selected using DAPI, and the average count of MET signals was determined for each specimen.
3. Detection of MET exon 14-skipping mutation
MET exon 14-skipping mutation was assessed by real-time quantitative polymerase chain reaction (RT-qPCR). RNA was extracted from FFPE samples, and cDNA was synthesized for use as the template. TaqMan probes spanning the exon 13 and 15 junction (Applied Biosystems, Foster City, CA) were used to detect exon 14 skipping in RT-qPCR.
4. IHC staining
All pathology slides were examined and reviewed by a board-certified pathologist with expertise in thoracic malignancies. IHC staining for MET (CONFIRM anti-Total c-MET (SP44), Ventana Medical Systems, Tucson, AZ) was performed on FFPE tissue sections using the Benchmark XT instrument (Ventana Medical Systems). Results were scored based on the intensity and proportion of the staining. Intensity was scored in a semiquantitative manner from 0 (absent) to 3 (strong). A proportion of the stained area was scored as either < 25%, 25%–50%, or ≥ 50%. By combining the intensity and proportion scales, IHC results were classified into three groups, modifying the previously reported scoring system [29,30]. High expression was defined as an intensity score greater than 3 and proportion ≥ 50%. An intermediate expression was defined as an intensity score of 2 and a proportion ≥ 50%, or an intensity score of 3 and a proportion between 25 and 50%. All other cases were classified as low expression.
5. Statistical analyses
Statistical analyses were performed using R (ver. 3.5.1, R Foundation for Statistical Computing, Vienna, Austria). Descriptive statistics were reported as numbers and percentages of patients. Continuous variables were compared using a t test, or analysis of variance (ANOVA) test. Categorical variables were analyzed using the chi-square test or Fisher exact test. Overall survival (OS) was determined from the date the patient was diagnosed of locally advanced or metastatic NSCLC to the date of death or last follow-up. Survival was analyzed with the Kaplan-Meier method and compared using a log-rank test, and multivariable analysis was performed with the Cox regression method. Statistical significance was defined as a two-sided p-value < 0.05.
Results
1. Clinical characteristics
A total of 72 patients who participated in the screening for a phase 2 capmatinib trial were enrolled in this study. Data cutoff was August 19, 2019, and the median follow-up period was 10.0 months (with a range of 1.0–68.6 months). In the phase 2 trial, participants were enrolled through various cohorts based on different GCN cutoff values and the presence of METex14. Nevertheless, to scrutinize the clinical impact of MET dysregulation, study participants were divided into two groups based on the GCN cutoff level of 10 and the presence of METex14. Fourteen patients were classified as group A (GCN ≥ 10, or METex14), and the other 58 patients as group B (Table 1, S1 Fig.). The majority of patients were male and had a history of adenocarcinoma histology and smoking. Patients in group A were significantly older than group B, with a mean age of 67.7 and 60.8 years, respectively (p=0.014). Although the difference was not statistically significant, all the patients in group A were male (Table 1).
Table 1
Clinical characteristics of patients
2. Correlation of MET assessments
We analyzed MET status using GCN, METex14, and IHC. These data were available in 72, 64, and 66 patients, respectively (Table 2). Among patients in group A, 10 had high GCN levels (GCN ≥ 10), and five had METex14. These two alterations occurred simultaneously in one patient (S2 Fig.).
Table 2
Assessments of the MET status
| Total | Group A (GCN ≥ 10 or METex14) | Group B (others) | |
|---|---|---|---|
| GCN | 72 | 14 | 58 |
| Mean (range) | 5.9 (1.8–22.8) | 11.9 (4.1–22.8) | 4.5 (1.8–8.5) |
| GCN ≥ 10 | 10 (13.9) | 10 (71.4) | 0 |
| GCN < 10 | 62 (86.1) | 4 (28.6) | 58 (100) |
| Exon 14 skipping mutation | 64 | 12 | 52 |
| Present | 5 (7.8) | 5 (41.7) | 0 |
| Absent | 59 (92.2) | 7 (58.3) | 52 (100) |
| Immunohistochemistrya) | 66 | 13 | 53 |
| High | 32 (48.5) | 8 (61.5) | 24 (45.3) |
| Intermediate | 17 (25.8) | 1 (7.7) | 16 (30.2) |
| Low | 17 (25.8) | 4 (30.8) | 13 (24.5) |
IHC for MET protein expression is a feasible assay that might reflect the level of MET amplification. Therefore, we sought whether MET IHC results have correlation with GCN values or METex14 mutations. Patients with high protein expression had significantly higher GCN values (ANOVA, p=0.015), and were also enriched for MET-amplified subjects (GCN ≥ 10). However, METex14 did not show a correlation with IHC. Among the five patients with METex14, two showed low expression, one showed intermediate, and two showed high expression results in IHC (Fig. 1).
Fig. 1
Correlation of MET immunohistochemistry and gene copy numbers. Scatter plot of MET gene copy number values classified by immunohistochemistry staining results. A dotted line indicates the gene copy number threshold value of 10 copies per cell. Statistical analyses were performed using an ANOVA test. METex14, MET exon 14 skipping mutation.
3. Responses to capmatinib
For the capmatinib clinical trial (NCT02414139), patients were enrolled through six cohorts with varying degrees of MET GCN levels and treatment histories. Thirteen patients in our study population were enrolled in the trial, and of these, eight patients were classified as group A and five were group B (S3 Table, S1 Fig.). All 13 patients were male. Three patients had stage 3B cancer, and 10 patients had stage 4. Among the patients in group A, five patients had high GCN, two had METex14, and one patient had alterations in both GCN and METex14.
Capmatinib responses were different between the two groups. For patients in group A, the objective response rate (ORR) was 50%, with four partial responses (PR), one stable disease (SD), and three progressive diseases. Median duration of response was 16.1 months (range, 5.3 to 36.4 months). However, there was no PR in group B. Only one patient showed SD (Table 3).
Table 3
Best overall response to capmatinib
4. Prognostic impact of MET dysregulation
In order to assess the prognostic impact of MET dysregulation in advanced NSCLC, we compared OS between the two groups of our study population. The median OS was 20.2 months (95% confidence interval [CI], 6.9 to not applicable [NA]) for patients in group A, and 11.3 months (95% CI, 8.2 to 20.3) for group B. Although survival time was greater in group A, this difference was not statistically significant (log-rank test, p=0.457) (Fig. 2A). Because eight out of 14 patients in group A were enrolled in the capmatinib trial, we compared the OS according to capmatinib treatment among group A patients. The clinical characteristics of these patients, including histologic subtype, smoking history, clinical stage, and Eastern Cooperative Oncology Group performance status, were similar between the two subgroups (Table 4). Capmatinib was given as first-line therapy in one patient, and second-line therapy in seven patients. Patients who were not enrolled in the trial were treated with standard cytotoxic chemotherapy regimens. The median OS was 21.5 months (95% CI, 20.8 to NA) for patients treated with capmatinib, and 7.5 months (95% CI, 3.2 to NA) for patients without capmatinib (log-rank test, p=0.025) (Fig. 2B).
Fig. 2
Kaplan-Meier plots for overall survival. Kaplan-Meier plots for overall survival in all study patients (n=72) stratified by study groups (log-rank test, p=0.457) (A), patients with MET gene copy number (GCN) ≥ 10 or MET exon 14 skipping mutation (METex14) (n=14) stratified by capmatinib treatment (log-rank test, p=0.025) (B), and patients untreated with capmatinib (n=59) stratified by MET GCN levels (GCN > 10) and the presence of MET- ex14 (log-rank test, p=0.123) (C). mOS, median overall survival.
Table 4
Clinical characteristics of patients with c-MET GCN ≥ 10 or METex14
| Total (n=14) | Capmatinib (−) (n=6, 42.9%) | Capmatinib (+) (n=8, 57.1%) | p-value | |
|---|---|---|---|---|
| Age (yr) | 69.5 (57–79) | 68.0 (57–74) | 70.0 (57–79) | 0.559 |
| Sex | ||||
| Male | 14 (100) | 6 (100) | 8 (100) | > 0.99 |
| Female | 0 | 0 | 0 | |
| Histology | ||||
| Adenocarcinoma | 13 (92.9) | 6 (100) | 7 (87.5) | > 0.99 |
| Squamous cell carcinoma | 1 (7.1) | 0 | 1 (12.5) | |
| Other | 0 | 0 | 0 | |
| Smoking history | ||||
| Current or former | 12 (85.7) | 5 (83.3) | 7 (87.5) | > 0.99 |
| Never | 2 (14.3) | 1 (16.7) | 1 (12.5) | |
| Stage | ||||
| III | 3 (21.4) | 1 (16.7) | 2 (25.0) | > 0.99 |
| IV | 11 (78.6) | 5 (83.3) | 6 (75.0) | |
| ECOG PS | ||||
| 0 | 4 (28.6) | 2 (33.3) | 2 (25.0) | > 0.99 |
| 1 | 10 (71.4) | 4 (66.7) | 6 (75.0) | |
| First-line treatment | ||||
| Platinum-doubleta) | 13 (92.9) | 6 (100) | 7 (87.5) | |
| Capmatinib | 1 (7.1) | 0 | 1 (12.5) | |
| Second-line treatment | ||||
| Platinum-doubleta) | 3 (21.4) | 2 (33.3) | 1 (12.5) | |
| Pemetrexed | 1 (7.1) | 1 (16.7) | 0 | |
| Capmatinib | 7 (50.0) | 0 | 7 (87.5) | |
As capmatinib was beneficial to patients with GCN ≥ 10 and METex14, we investigated whether it would have led to a survival benefit in patients with lower GCN values. However, capmatinib treatment did not significantly prolong the OS of patients in subgroups with GCN values higher than 4 or 6 (S4A and S4B Fig.). Likewise, we also attempted to see whether IHC high expression could be a predictive biomarker for capmatinib treatment, but the OS also did not significantly differ within this subgroup (S4C Fig.).
To corroborate whether capmatinib treatment is a predictive biomarker for better clinical outcome in NSCLC patients with GCN ≥ 10 or METex14, we analyzed various clinical characteristics that are known to be associated with survival. In multivariable analyses, capmatinib treatment was the only factor associated with better clinical outcome (hazard ratio, 0.09; 95% CI, 0.01 to 0.73) (S5 Table).
Next, we compared OS among patients untreated with capmatinib (n=59) to determine whether MET dysregulation, defined as GCN ≥ 10 or METex14, was indeed associated with poor clinical outcome. The median OS for patients in group B and untreated with capmatinib (n=53) was 11.3 months (95% CI, 7.9 to 29.4), similar to the result for all patients in the whole group B patients. Since the median OS for group A patients untreated with capmatinib was 7.5 months (Fig. 2B), we observed a tendency towards poorer clinical outcome in advanced NSCLC patients harboring MET amplification or activating mutation (log-rank test, p=0.123) (Fig. 2C).
Discussion
In this study, we retrospectively analyzed the clinical characteristics and prognosis of advanced NSCLC patients screened for enrollment in a phase 2 trial of capmatinib, a potent and selective MET inhibitor [28]. These patients had no EGFR or ALK mutations, reflecting the population treated with platinum-doublets as standard therapy. The median OS of patients without METex14 and GCN < 10 was 11.3 months, which is consistent with results of previous landmark studies [1,2]. OS of all patients in group A (GCN ≥ 10 or METex14) was comparable to group B (GCN < 10 without METex14). However, considering that ORR of capmatinib was 50% among group A patients, we subdivided this group based on capmatinib treatment. In group A patients untreated with capmatinib, the median OS was 7.5 months, indicating that MET dysregulation defined by GCN ≥ 10 or the presence of METex14 may cause worse clinical outcome in locally advanced or metastatic NSCLC. However, the median OS was significantly longer in patients treated with capmatinib, and was independent of other clinical factors that could affect survival. These results imply that MET inhibition could be a compelling treatment option for appropriately selected patients. The definition of MET dysregulation is still controversial, and there is no established consensus. This is largely due to a lack of studies examining subgroups of patients that best respond to selective MET inhibition. Although defining METex14 is relatively clear using RT-qPCR or next generation sequencing, the definition MET amplification varies according to the study. Many researchers have used GCN values with a threshold of 3 or 5 copies per cell [31]. These previous studies used a cutoff value that split the prognosis of their study cohort, rather than a robust, scientifically determined value that would assure true activation of MET signaling [28]. However, in order to scrutinize the clinical impact of MET dysregulation in advanced NSCLC, we applied the highest cutoff value (GCN 10) to enrich for patients with the strongest MET activity [22].
In the phase 2 trial of capmatinib, study subjects were recruited into various cohorts based on GCN and METex14. The cutoff values of GCN for cohort entry were 4, 6, or 10. A recent biomarker analysis from the phase 1 trial of capmatinib showed that patients with MET GCN ≥ 6 showed a high response rate (ORR 47%, 7 out of 15) [32]. Yet, in the phase 2 GEOMETRY mono-1 trial, capmatinib showed substantial antitumor activity in patients with METex14 or GCN ≥ 10 [28]. Overall response for patients with METex14 was 41% for second- or third-line therapy, and 68% for first-line therapy. And in patients with GCN ≥ 10, overall response was 29% for second- or third-line therapy, and 40% for first-line therapy. In this study, only one patient was treated with capmatinib as first-line; thus, it is difficult to compare the efficacy according to the presence of prior therapy. Response rates were lower in patients with MET GCN levels below 10, and these cohorts were closed at the interim analysis. Results from our analyses are in line with these data which supports that capmatinib should be indicated for patients with MET-ex14 or GCN ≥ 10.
Of note, high MET GCN and METex14 activity was concurrently observed in one patient (1 out of 5 with MET-ex14). This observation is in line with a previous study that detected concurrent MET amplification in 15%–20% of patients with METex14 [22,26]. Since the majority of patients with MET amplification or activating mutations had only one of these alterations, both GCN levels and mutational status of MET should be tested to determine whether patients would benefit from selective MET inhibition.
Immunohistochemical staining was not considered for enrollment in this study, but is widely used in clinics due to its feasibility. In addition, protein expression levels reflected in IHC results may be correlated with amount of gene amplification. Hence, we examined whether IHC was correlated with GCN levels, and found that MET-amplified patients were enriched in patients with positive IHC results. This finding was consistent with previous reports demonstrating that high IHC scores correlated with MET gene amplification measured by the FISH technique [24,32,33]. However, IHC did not seem to correlate with METex14, as only two out of five patients with the mutation had positive IHC results. Additionally, IHC was not a good predictive biomarker for response to capmatinib in our data (S4C Fig.), and also in the analysis of the phase 1 trial [32]. Therefore, IHC alone cannot be employed as a single screening tool for MET dysregulation, and additional gene amplification or mutational profiles must be performed for accurate molecular assessment.
Notably, METex14 mutations are reported to be relatively frequent in pulmonary sarcomatoid carcinoma (PSC) which is a rare but highly aggressive subtype of NSCLC. Sequencing results have revealed that it ranges from 13.6% to 31.8% in PSC, varying from study to study, but still higher than adenocarcinoma or squamous cell carcinoma [10,34,35]. None of our patients with METex14 were PSC, but this may be because there were only five patients in our cohort. Since METex14 is a druggable oncogenic mutation, efforts to search potential candidates are especially required in these patients.
This study has several limitations such as the retrospective nature and the small number of patients. Nevertheless, our key findings are in line with the results from the prospective multi-cohort phase 2 trial (GEOMETRY mono-1), and strengthens its conclusion [28]. Also, this is the first report demonstrating that in patients with MET GCN ≥ 10 and METex14, treatment with capmatinib led to an improved OS compared to those that were treated only with standard chemotherapy.
In conclusion, in this study, we showed that patients with MET GCN ≥ 10 or METex14 tend to show worse clinical outcome in locally advanced or metastatic NSCLC. Nevertheless, MET inhibitors could be a compelling treatment option for carefully selected patients. Although the definition of MET dysregulation is still controversial, stringent criteria could be used to refine the target population that would benefit the most from selective MET inhibition.
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