Next Article in Journal
A Novel Methylation Marker NRN1 plus TERT and FGFR3 Mutation Using Urine Sediment Enables the Detection of Urothelial Bladder Carcinoma
Next Article in Special Issue
The Role of cMET in Gastric Cancer—A Review of the Literature
Previous Article in Journal
Salvage Perioperative Interstitial High-Dose-Rate Interventional Radiotherapy (Brachytherapy) for Local Recurrences of the Chest Wall Following Mastectomy and Previous External Irradiation
Previous Article in Special Issue
Rilotumumab Resistance Acquired by Intracrine Hepatocyte Growth Factor Signaling
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

MET Amplification as a Resistance Driver to TKI Therapies in Lung Cancer: Clinical Challenges and Opportunities

1
Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
2
Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
*
Author to whom correspondence should be addressed.
Cancers 2023, 15(3), 612; https://doi.org/10.3390/cancers15030612
Submission received: 7 December 2022 / Revised: 13 January 2023 / Accepted: 14 January 2023 / Published: 18 January 2023
(This article belongs to the Special Issue Roles of MET in Cancer Development and Treatment)

Abstract

:

Simple Summary

Secondary amplifications/copy number changes of the gene MET (MET protocol oncogene) play a significant role in the development of resistance to targeted drugs in advanced non-small cell lung cancer (NSCLC). In this review, we aim to clarify the biological mechanisms of MET amplification-mediated resistance to tyrosine kinase inhibitors, discuss the challenges of commonly used assays for the identification of MET amplifications. We also summarize the latest findings on combined strategies to overcome acquired MET amplification-mediated resistance, especially the combinatory regimens with EGFR-TKIs and MET-TKIs.

Abstract

Targeted therapy has emerged as an important pillar for the standard of care in oncogene-driven non-small cell lung cancer (NSCLC), which significantly improved outcomes of patients whose tumors harbor oncogenic driver mutations. However, tumors eventually develop resistance to targeted drugs, and mechanisms of resistance can be diverse. MET amplification has been proven to be a driver of resistance to tyrosine kinase inhibitor (TKI)-treated advanced NSCLC with its activation of EGFR, ALK, RET, and ROS-1 alterations. The combined therapy of MET-TKIs and EGFR-TKIs has shown outstanding clinical efficacy in EGFR-mutated NSCLC with secondary MET amplification-mediated resistance in a series of clinical trials. In this review, we aimed to clarify the underlying mechanisms of MET amplification-mediated resistance to tyrosine kinase inhibitors, discuss the ways and challenges in the detection and diagnosis of MET amplifications in patients with metastatic NSCLC, and summarize the recently published clinical data as well as ongoing trials of new combination strategies to overcome MET amplification-mediated TKI resistance.

1. Introduction

Non-small cell lung cancer (NSCLC) constitutes around 85% of lung cancer, which has been the leading cause of cancer-related deaths worldwide [1]. In the past decade, groundbreaking progress in personalized therapy and targeted agents has led to unprecedented clinical improvements in the subgroup of patients with advanced or metastatic NSCLC carrying active oncogenic driver alterations. Molecular profiling to identify actionable oncogenic drivers is now recommended as part of the initial clinical work-up for patients with metastatic NSCLC. Currently, In NSCLC, especially of the non-squamous histology, predictive biomarkers recommended for testing by the NCCN profiling panel are EGFR, KRAS, and BRAF mutations; ALK, RET, and ROS1 gene rearrangements; MET alterations including MET exon 14 skipping mutations and MET amplifications; ERBB2 (HER2) mutations; and NTRK 1/2/3 gene fusions [2]. Although the well-established targeted drugs show outstanding efficacy in initial disease control, drug resistance always inevitably develops. Clarifying and overcoming the resistance to targeted drugs with novel strategies is one of the major challenges in the era of personalized therapy.
The MET proto-oncogene (hereafter referred to as MET) encodes the receptor tyrosine kinase or hepatocyte growth factor (HGF) receptor, which, along with its ligand HGF (HGF/MET axis), functions as an essential regulator of cell survival, proliferation, motility and migration. Dysregulation of MET signaling has been found in a variety of cancers through different mechanisms, such as activating point mutations of the MET gene, overexpression of the ligand HGF, MET gene copy number gain (MET-CNG)/amplification, and MET gene fusions [3,4].
MET amplification occurs in 1–6% of NSCLC cases and was considered as a negative prognostic factor [5,6,7]. In recent years, increasing evidence has implicated that MET amplification was a key driver of acquired resistance to these aforementioned targeted therapies such as EGFR-TKIs and ALK-TKIs. Although an increasing number of drugs acting on MET signaling is currently achievable, for example, the MET/ALK/ROS tyrosine-kinase inhibitor crizotinib or selective MET-TKIs (capmatinib, savolitinib, tepotinib) [7], more strategies are needed to overcome MET amplification-mediated acquired resistance to TKIs. Therefore, it is important and necessary to clarify the underlying molecular mechanisms of MET amplification-mediated resistance, and to find out appropriate ways to identify MET copy number gains and amplifications, so that researchers can develop effective therapeutic strategies to overcome this resistance and prolong the life of NSCLC patients. Our review focuses on the molecular mechanisms of acquired resistance to targeted therapies mediated by MET amplifications, and the ways and challenges in detection and diagnosis of MET amplifications in NSCLC. We also summarize the recently published clinical data as well as the ongoing trials focusing on new combination strategies to overcome MET amplification-mediated TKI resistance.

2. MET Biology, Structure, Function, and Pathways

The receptor tyrosine kinases (RTKs) are encoded by a family of proto-oncogenes with more than 75 members that regulate cellular growth, oncogenesis, tumor metastasis, and progression through downstream signaling pathways such as the RAS-RAF-MEK-ERK and PI3K-AKT-mTOR pathways [8]. MET, together with EGFR, ALK, BRAF, etc. are all members of this family, which were found to be frequently mutated in advanced NSCLC [9]. Tyrosine kinase inhibitors bind and act on these RTKs, and lead to the inhibition of downstream signaling pathways which would otherwise induce tumor cell growth and proliferation [10]. In patients with advanced NSCLC undergoing TKI treatments, acquired resistance always develops and limits the long-term application of these targeted agents. Bypassing the activation of MET-related pathways has proven to be one of the underlying reasons [11].
The human MET gene is a 120 kb proto-oncogene that is located on chromosome 7 band 7q21–q31. Hepatocyte growth factor receptor (HGFR) or MET protein is the product of the MET proto-oncogene, and its ligand HGF is a disulfide-linked a-b heterodimeric molecule, also known as plasminogen-related growth factor-1(PRGF-1) [12]. MET protein is normally expressed in various epithelial and mesenchymal cell types. Upon HGF binding, the HGF/MET signaling pathway is activated, then MET undergoes homodimerization and autophosphorylation of a series of tyrosine residues within the intracellular region, including Y1230, Y1234, Y1235, Y1313, Y1349, and Y1356, etc., which lead to the activation of multiple intracellular signaling pathways including the RAS-RAF-MAPK, JAK-STAT and PI3K-AKT/mTOR, and phospholipase C pathways [13] (Figure 1). The signalings have been shown to trigger a variety of cellular responses, including cell proliferation, tissue regeneration, angiogenesis, and cellular invasion, etc. [14]. Oncogenic MET alterations, including the overexpression of MET protein or MET gene alterations, such as mutations, amplifications, or fusions, cause dysregulation of the HGF/MET signaling pathway, and lead to a wide range of human cancers, including papillary renal cell carcinoma, gastric cancer, and non-small cell lung cancer, etc. [3,15].

3. MET Amplification as a Mediator of Resistance to Targeted Agents in NSCLC

Increased gene copy numbers (GCN) of the MET gene could be observed in approximately 1–3% of NSCLC, either due to de novo amplification or as a secondary resistance mechanism in response to targeted therapies [4]. Acquired resistance to EGFR-TKIs can develop via both EGFR-dependent and EGFR-independent mechanisms. Acquisition of the Exon20 T790M mutation has been proven to be the most common EGFR-dependent cause, with MET signaling dysregulation as the most common EGFR-independent cause [16,17]. MET amplification-mediated resistance has a prevalence of 5–21% after first/second generation EGFR-TKI treatment, 7–15% after first-line osimertinib therapy, and 5–50% of osimertinib resistance after secondary and/or further-line osimertinib treatment [18,19,20].
The underlying mechanism by which MET amplification leads to EGFR-TKI resistance may be associated with phosphorylation of ErbB3 (HER3), which functions as a key activator of the PI3K/AKT and MEK/MAPK pathways, providing bypass signaling in the presence of EGFR-TKIs [17,21,22]. A study by Y.Yarden and colleagues showed that a combination of mAb33 (an anti-HER3 antibody) with cetuximab and third-generation EGFR-TKI osimertinib markedly reduced HER3, and also downregulated MET expression [21]. In another study, inhibition of MET through an inhibitor or knockdown of the MET gene restored the effects of osimertinib on ErbB3 inactivation and ErbB3 phosphorylation suppression [22]. Taken together, these findings suggested that phosphorylation of ErbB3 was involved in MET amplification-mediated acquired resistance to EGFR-TKIs in advanced NSCLC. In addition, an upregulation of mTOR and Wnt signaling proteins was observed in MET-TKIs/EGFR-TKI-resistant NSCLC cell lines, implying the role of alternative cell signaling pathways in TKI resistance [23]. Furthermore, MET-TKIs and EGFR-TKIs showed a synergistic inhibitory effect on cell proliferation and downstream activation of signal transduction. Therefore, a combination of HGF and EGF tyrosine kinase inhibitors could potentially be targeted in a synergistic fashion to overcome MET amplification-mediated resistance to EGFR-TKIs [24,25].
ALK-rearranged NSCLC is another major subtype of lung cancer, which occurs in around 3–5% of lung adenocarcinomas [26]. As a member of the RTKs family, ALK also regulates cellular proliferation and survival through pathways such as the PI3K-AKT-mTOR, RAS-RAF-MEK-ERK, and JAK-STAT pathways [27,28]. Around 50% of resistance to second-generation ALK-TKIs (ceritinib, alectinib, and brigatinib, etc.) is caused by ALK-independent resistance mechanisms, most often due to activation of bypass signaling pathways, including activation of MET, EGFR, and IGF-1R (insulin-like growth factor 1 receptor), etc. [29,30]. MET overactivation was shown to be involved in the development of acquired resistance to alectinib, but not to crizotinib in NSCLC cell lines [31,32,33]. MET activation-mediated resistance was found to be overcome by crizotinib, which was initially developed as a MET receptor TKI [32,33,34]. However, more evidence is needed to fully clarify the mechanism and functions of MET amplification in ALK downstream signaling and ALK-TKI resistance development.
KRAS is the most frequently mutated cancer-related driver in non-small cell lung cancer, which could be observed in over 30% of NSCLC patients. KRAS G12C variants are the most commonly found subtype of oncogenic KRAS alterations, which have been identified in around 10% of NSCLC cases [35]. Acquired focal MET amplification in a patient with KRAS G12C-mutant lung adenocarcinoma treated with sotorasib was also documented [36].
A preclinical study reported that constitutive activation of KRAS could lead to the persistent stimulation of downstream signaling pathways, for example, the PI3K/AKT/mTOR cascade and the overexpression of MET protein [37], which indicated that MET amplification was one of the acquired bypass mechanisms of resistance to KRAS inhibitors. Lito et al. demonstrated that the inhibition of SHP2, which functions as a valuable co-inhibitory target in KRAS G12C signaling and is also a central node in RTK and RAS inhibition signaling, was able to overcome KRAS G12C inhibitor resistance in vitro [38,39].
MET amplification is also a known resistance mechanism in RET-rearranged NSCLC. Data on acquired resistance to RET-specific inhibitors, such as selpercatinib and pralsetinib, have suggested that on-target mutations at non-gatekeeper sites or the emergence of off-target alterations such as MET amplification or NTRK fusion are potential mechanisms of acquired resistance [40,41,42]. Furthermore, combinational therapy with crizotinib, which is a MET/ALK/ROS1 TKI, with selpercatinib in patients who had RET fusion-positive and MET-amplified NSCLC showed clinical efficacy in selpercatinib-resistant tumors [40].
Although there have been many studies that investigated and identified the underlying mechanism of acquired resistance to the targeted agents mediated by MET amplification, this issue requires further elucidation through more preclinical and clinical studies.

4. Detection of MET Amplification and Overexpression

Since MET amplification is a common resistance mechanism to different TKI resistances in lung cancer and inhibitors are available to be used, it is then critical to detect MET amplification with appropriate methods and cut-offs so that patients can be identified to be offered potential anti-MET treatment. MET copy number gains can occur either as polysomy (multiple copies of chromosome 7) or true amplification (regional or focal copy number gains without chromosome 7 duplication) [43]. True amplification is more likely to lead to oncogene addiction [44]. Various assays have been developed for the detection of MET copy number changes. Fluorescence in situ hybridization (FISH) is the gold standard method for MET amplification detection. Next-generation sequencing (NGS) is becoming more popular clinically, as the results cover multiple oncogenes, and NGS profiling can be utilized for tissue or liquid biopsy/circulating tumor DNA, either DNA- or RNA-based. Immunochemistry (IHC) is mainly used for the identification of MET overexpression. Quantitative real-time polymerase chain reaction (qRT-PCR) is less commonly used. Each assay has its advantages and disadvantages.

4.1. Fluorescence In Situ Hybridization (FISH)

Fluorescence in situ hybridization (FISH) is the standard method, and is also the way that is mostly used clinically for identification of MET amplification. MET amplification can be defined by FISH, either by determining gene copy number or by taking the ratio of MET to CEP7 (centromere 7 enumeration probe). MET amplification is defined as MET GCN ≥ 5 with the Cappuzzo criteria, which means five or more copies of MET are detected per tumor cell [45,46,47]. Cut-off points such as a MET GCN of ≥6 or 10 or 15 are also used in some studies [48,49,50,51,52]. However, GCN itself cannot distinguish true amplification from polysomy. MET amplification can also be determined by the MET/CEP7 ratio, and a cut-off value of MET/CEP7 ratio round 2 is commonly used to define MET amplification [46,47,53,54,55,56,57].
In some studies, MET amplification was categorized into three degrees using the MET/CEP7 ratio: low amplification 1.8 ≤ MET/CEP7 ≤ 2.2; intermediate amplification 2.2 < MET/CEP7 < 5; and high amplification MET/CEP7 ≥ 5 [44]. Compared with GCN, the MET/CEP7 ratio identifies MET amplification more accurately when there is no concurrent chromosome 7 polysomy [58]. However, there is no consensus on a single definition cut-off value with the FISH assay; other cut-off values may also be used. For instance, in a study by Buckingham et al., tumor cells with CEN7 signals on average ≥3.6 were categorized as polysomic MET amplification [59].
Tumors harboring de novo MET amplifications (high level, i.e., MET to CEP7 ratio ≥ 5) are thought to be primarily dependent on the MET signaling pathway for growth, as there are often no other concurrent oncogenic drivers. These amplifications are identified in <1–5% of NSCLCs, and indicate a poor prognosis [60,61,62,63].
Furthermore, the literature suggests that, compared with other assays, FISH is unique in that it can capture the various levels of MET gene amplification, including “true” high-level MET gene amplified cases characterized by a high MET GCN (≥6 per cell) without concomitant polysomy (i.e., a high MET/CEN7 ratio) [64]. However, FISH only detects tissue samples, and it is inapplicable when tissue samples are not available, which limits its clinical use [65].

4.2. Next-Generation Sequencing (NGS)

Simultaneous targeted DNA- and RNA-based next-generation sequencing (NGS) offers the most straightforward and comprehensive profiling for not only MET amplifications, but for all treatment relevant genetic alterations, including the MET14-skipping aberrations, which cannot be identified by FISH but are of high clinical significance; therefore, NGS has also been widely applied in clinical practice for detection of MET copy number gains [66].
Two methods are commonly used for NGS-targeted approaches: capture hybridization-based sequencing and amplicon-based sequencing, and each has its own advantages and disadvantages. A head-to-head study compared these two types of methods, and indicated that amplicon-based approaches have a much-simplified workflow, and require smaller amounts of DNA for assessment. By contrast, hybridization-based NGS profiling was less likely to miss mutations, and performed better with respect to sequencing complexity and uniformity of coverage [67,68,69,70].
However, MET amplification detected via NGS is reported as continuous variables, and there is a lack of consensus on a single cut-off value. Normally, the cut-off value ranges from GCN 2.3–10. For example, in the TATTON study, MET amplification used a cut-off value as GCN ≥ 5 [71]; in the INC280 study [72], MET amplification was determined with a GCN ≥ 2.3; in the ongoing phase 2 INSIGHT 2 (NCT03940703) study, MET amplification was defined as GCN ≥ 6 [73].
Now that NGS is increasingly used to optimize precision oncology therapy in NSCLC, the question is whether NGS assays can replace the FISH method regarding the classification of MET copy number status. Copious studies have investigated this question. Heydt C. et al. [74] compared 35 MET-amplified NSCLC samples (including 5 samples showing a low-level MET amplification, 10 samples with an intermediate-level MET amplification, and 10 samples with a high-level MET amplification), and found that MET-IHC had the best agreement with MET-FISH. Furthermore, only high-level MET-amplified cases (GCN ≥ 6), showed better concordance between NGS and FISH detections than those in intermediate- or low-level MET-amplified patients. This was confirmed through a study by Schubart C. et al., which compared detection results of 205 consecutive NSCLC cases with MET alterations, using either an amplicon-based, 15-gene NGS panel, or the standard FISH method. Among the 205 patients detected, 9 cases were classified as MET-amplified by NGS, and 16 cases were classified as high-level MET-amplification by FISH, yielding a discrepancy of 43.7% (7/16); only cases harboring a MET GCN > 10 showed the best concordance when comparing FISH versus NGS (80%, 4/5) [64]. In a study by Peng et al. [75], the concordance rate among FISH and NGS was only 62.5% (25/40). In addition, amplification identified by NGS was found to be an ineffective predictive biomarker, and failed to distinguish significant clinical outcomes. The PR rate was 60.0% (6/10, with MET GCN ≥ 5) vs. 40.0% (12/30, with MET GCN < 5); the median PFS was 4.8 months vs. 2.2 months (p = 0.357). A study by Lai et al. also demonstrated a low concordance between the FISH assay and NGS profiling; among samples with FISH-positive results with GCN ≥ 8, only one-third were identified as MET amplification with NGS [76]. Of the 18/39 patients identified as MET-high (two amplifications and 16 polysomies), only 8/18 were deemed to have MET CNG by NGS. Of the two MET-amplified tumors (3.4 and 2 by ratio), the latter was reported as non-MET- amplified on NGS. In addition, only 1/3 tumors with a MET CNG greater than 8 by FISH were identified as MET-amplified with NGS. The result of the TATTON study also showed low consistency between NGS and FISH for MET amplification; among all 47 FISH-positive patients, only 12 had MET amplification by NGS [71]. Taken together, FISH is the standard method for the detection of various levels of MET amplifications during routine diagnostics; NGS is widely used, but is not yet able to replace FISH for the detection of MET gene copy number gains.
In recent years, the use of liquid biopsy for genomic profiling has made multi-gene sequencing more easily accessible to patients. NGS of circulating cell-free DNA (cfDNA) has also been used to detect MET alterations in clinical studies, including the VISION study [77] and the INSIGHT 2 study [73]. Both studies used liquid biopsy to prospectively screen patients for enrollment and establish the role of liquid biopsy as a tissue-sparing, less-invasive and more easily accessible method for the detection of MET alterations.

4.3. Immunohistochemistry (IHC)

MET can be transcriptionally induced in cancer cells in the setting of hypoxia/inflammation to activate proliferation, decrease apoptosis, and promote migration. Thus, tumors can rely on MET signaling, even in the absence of a genomic driver such as MET amplification, mutation, or fusion [78]. MET can also be overexpressed in cancers that harbor an activating genomic signature, including those with primary/secondary MET amplification, or MET exon 14 alterations. Therefore, MET protein overexpression detected by IHC is also commonly used for screening of MET gene amplification. Various scoring systems are currently in clinical use to define MET protein expression and overexpression. The most common way is categorizing the MET expression based on a 0–3+ scale into four degrees: negative (0), weak (1+), moderate (2+), or strong (3+). By the MetMab criteria, the cut-off for MET overexpression should be 2+ in at least 50% of the cells [79].
The H-score system multiplies the percentage of cells with 1+, 2+, or 3+ staining by the SI (staining intensity) score [80]. H-scores range from 0–300, and over 200 usually defines MET overexpression. However, cut points vary as well [81,82]. Investigators also used a median H-score (of the range of H-scores obtained from samples exclusively within a given study) as a cut point for overexpression; this approach makes standardization across studies difficult [50,83]. The H-scoring system multiplies the percentage of cells with 1+, 2+, or 3+ staining by the staining intensity score [80]. H-scores range from 0–300; ≥200 usually denotes overexpression, but cut points vary [82,84].
Whether IHC screening for MET overexpression can be used for MET amplification detection remains controversial, and attempts to take MET IHC as a marker of MET dependency have largely been unsuccessful [63,82,84]. MET IHC demonstrated poor correlation with the MET/CEP7 ratio in sarcomatoid lung cancer, regardless of the stage [82]. In a tri-institutional cohort of patients with metastatic lung adenocarcinoma, more than 30% of cases were MET IHC-positive, but only 2% were MET-amplified. MET IHC even failed to detect MET in two of the three MET-amplified patients [63]. MET IHC was not an effective predictive marker for MET-directed therapies in some clinical trials [85,86]. For example, in a study by Spigel D.R. et al. [85], the HR of PFS in patients with MET IHC 3+ status was 0.86 (95% CI, 0.58 to 1.29), compared with 1.06 (95% CI, 0.85 to 1.32) in patients with MET IHC 2+ status. Moreover, no statistically significant differences in OS, PFS, or ORR between the onartuzumab and placebo arms were observed when analyzed using MET FISH status. Coupling the reports from the growing literature, there is a strong challenge in taking MET IHC as an effective way of screening for MET dependency. Therefore, MET IHC is not viewed as an effective way of screening for MET dependency, and it is less commonly used for clinical MET amplification detection.

4.4. Reverse-Transcription Polymerase Chain Reaction—qRT-PCR

Real-time PCR(RT-PCR), also known as quantitative PCR (qPCR), is the gold-standard for sensitive, specific detection and quantification of nucleic acid targets, and is a valid method for MET exon 14-skipping mutation detection [87]. However, unlike gene point mutation, MET amplification is difficult to test with qPCR or qRT-PCR; therefore, it is less commonly used in clinical settings for MET amplification detection compared to FISH/NGS [16,88,89,90,91].
Although seldomly used, the detection of MET amplification using ddPCR shows very high concordance rates with FISH, either in tissue samples only (100%, 102/102) or among both peripheral blood and tissue samples (94.17%, 97/103). This indicates that ddPCR is an optional non-invasive method for detecting of MET CNG in blood samples as compared with the FISH method in tissue samples; thus, it may be an alternative method for MET amplification detection when FISH is not applicable, especially when tumor tissue is not available [65]. Again, cut-off values vary, and consensus on the standard definition for MET amplification by PCR remains to be proposed.

5. Drug Combination Strategies to Overcome Secondary MET Amplification Resistance

Since acquired MET amplification can bypass the initial oncogene driver to mediate resistance, it is reasonable to hypothesize that inhibition of MET signaling, together with continued inhibition of the initial oncogene driver, can overcome resistance. In the last a few years, there has also been much progression in the development of new agents that act on the HGF/MET pathways. MET-targeting drugs that are currently used in clinics and trials can be divided into three general categories: small molecule inhibitors (e.g., crizotinib, savolitinib, tepotinib, and foretinib), antibodies against the MET receptor (e.g., onartuzumab or amivantamab), and antibody-drug conjugates (e.g., telisotuzumab, vedotin) [92]. In some of the preclinical studies, it has been shown that adding a MET inhibitor to MET-amplified EGFR-mutant-resistant NSCLC cells can overcome resistance [93].
Therefore, numerous clinical studies have shown preliminary efficacy using this approach. In patients with EGFR-mutant NSCLC and MET amplification with disease progression on EGFR TKI treatment, subsequent treatment with an MET inhibitor and EGFR-TKI combination rendered clinical benefits in a series of phase I/II studies (Table 1) [71,72,73,94,95,96,97,98,99,100,101].
The TATTON trial [71] demonstrated the clinical benefits of osimertinib plus savolitinib in patients with previously treated EGFR-mutant MET-amplified NSCLC, with an objective response rate (ORR) of 44%. Among patients progressed on a third-generation EGFR-TKI, the ORR was 30%. Notably, an ORR of 64% was observed among 23 patients with EGFR-mutant T790M-negative NSCLC without prior third-generation EGFR-TKI treatments. Another study confirmed that the combination of capmatinib with geftinib demonstrated a PFS of 3.3 months, and an ORR up to 47% in patients with EGFR mutation and MET amplification (defined by CGN ≥ 6) [5]. In the INSIGHT study, the combination of tepotinib and gefitinib showed significantly a better PFS (16.6 months vs. 4.2 months) and OS (37.3 months vs. 17.9 months, respectively) than chemotherapy in patients with resistant EGFR-mutant NSCLC, especially in patients with high MET over-expression [96]. The ongoing ORCHARD study (NCT03944772) included 20 patients with MET amplification who progressed on first-line osimertininb monotherapy, and received second-line combinatory treatment with osimertinib and savolitinib [99]. Initial benefits for the patients were presented with good tolerance: among 17 patients who were evaluable for confirmed response analysis at data cut-off (DCO), 7 patients had confirmed partial response (ORR 41%, 7/17) and 7 patients had stable disease (DCR 41%, 7/17). The ORCHARD study is still ongoing, and more results are expected to be released in the future.
With those successes, pivotal trials were designed to further evaluate this combination approach to overcome MET amplification-medicated resistance in EGFR-mutant NSCLC. The data in the INSIGHT study led to the investigation of tepotinib plus osimertinib in the INSIGHT 2 trial [73]. Preliminary data from the INSIGHT 2 study suggested that the combination of tepotinib and osimertinib has activity in patients with EGFR-mutated advanced NSCLC with MET amplification who progressed on first-line osimertinib. In the first 48 patients who had over 3 months follow up, the ORR was 45.8% [95% CI, 31–61%], with duration of response not reached [73]. Similarly, results of the TATTON trial led to further development of the savolitnib plus osimertinib combination in the SAVANNAH trial [101]. SAVANNAH is a global, randomized, single-arm phase II trial that is studying the efficacy of savolitinib with osimertinib in patients with EGFR-mutant, locally advanced or metastatic NSCLC with MET overexpression and/or amplification, who progressed following treatment with osmiertinib. Patients were treated with savolitinib with osimertinib. Preliminary results demonstrated an ORR of 32% in the total population. In patients with high levels of MET overexpression and/or MET amplification (defined as IHC90+ and/or FISH10+), the ORR was high at 49% [95% CI, 39–59%] [101].
Other studies investigating the clinical evidence of dual inhibition of EGFR and MET with small molecule inhibitors or monoclonal antibodies, such as capmatinib plus geftinib, telisotuzumab plus erlotinib, savolitinib plus geftinib, onartuzumab plus erlotinib, capmatinib plus erlotinib, and emibetuzumab plus erlotinib within patients with NSCLC with EGFR-mutant and MET alterations, are summarized in Table 1 [71,72,73,94,95,96,97,98,99,100,101].

6. Conclusions

Acquired MET amplification functions as a mechanism of resistance to targeted therapies in NSCLC, and now has been proven to be a pharmaceutical target to overcome this resistance. Although evidence was most abundant and convincing for MET amplification mediated resistance to EGFR TKIs, its role in mediating resistance to other targeted therapies, such as ALK, ROS1, or RET TKIs, is being recognized. Case reports and case series have indicated that dual inhibition of MET and the initial oncogene driver pathway may be a valid clinical approach to overcome resistance. With MET amplification serving as a general resistance mechanism to targeted therapies in lung cancer, it is crucial to be able to detect MET amplification in a reliable manner, in order to identify the appropriate patients who can benefit from MET-targeting therapy.
MET amplification or MET overexpression could be detected by multiple clinical pathology laboratory tests, including FISH, NGS, and IHC. However, clinically meaningful cut-offs need to be standardized for continuous variables, including the copy number gain of MET amplification and MET overexpression. As clinical diagnostic methods migrate towards more comprehensive and technically sophisticated NGS assays, further understanding of NGS assays for the detection of MET amplification is needed, both in tumors and plasma, and ideally both in DNA and RNA. The effective detection of MET-dependent cancers is critical, given that MET-directed targeted therapy is active in many of these cancers. Importantly, the level of activity of MET-targeted therapies is associated with the degree of oncogenic addiction to MET pathway signaling.
To overcome MET amplification-mediated acquired resistance to TKIs, combination therapies to inhibit both MET and the primary driver oncogene are necessary. EGFR-MET TKI combination therapy has shown promising clinical efficacy in this setting. While awaiting the maturation of the large clinical trial results and regulatory approval of this approach, further studies are necessary that aim to standardize the MET amplification detection assay and the cut-off values.

Author Contributions

Conceptualization, K.Q. and X.L.; methodology, K.Q.; software, K.Q. and L.H.; data curation, K.Q.; writing—original draft preparation, K.Q.; writing—review and editing, K.Q., J.Z. and X.L.; visualization, L.H.; supervision, X.L.; All authors have read and agreed to the published version of the manuscript.

Funding

X.L. is supported by Damon Runyon Cancer Research Foundation, V Foundation for Cancer Research, and Lung Cancer Research Foundation.

Conflicts of Interest

There is no conflict of interest related to this work. Outside of this work, X.L. receives consulting/advisory fees from EMD Serono (Merck KGaA), AstraZeneca, Spectrum Pharmaceutics, Novartis, Eli Lilly, Boehringer Ingelheim, Hengrui Therapeutics, Janssen, Blueprint Medicines, Sensei Biotherapeutics, and Abbvie, and Research Funding from Eli Lilly, EMD Serono, Teligene, ArriVent, Regeneron, and Boehringer Ingelheim. Outside of this work, J.Z. reports grants from Merck, grants and personal fees from Johnson and Johnson and Novartis, personal fees from Bristol Myers Squibb, AstraZeneca, GenePlus, Innovent and Hengrui.

Abbreviations

NSCLCnon-small cell lung cancer
RTKsreceptor tyrosine kinases
METmesenchymal-epithelial transition factor
EGFRepidermal growth factor receptor
ALKanaplastic lymphoma kinase

References

  1. Jemal, A.; Siegel, R.; Ward, E.; Murray, T.; Xu, J.; Thun, M.J. Cancer statistics, 2007. CA Cancer J. Clin. 2007, 57, 43–66. [Google Scholar] [CrossRef] [PubMed]
  2. Ettinger, D.S.; Wood, D.E.; Aisner, D.L.; Akerley, W.; Bauman, J.R.; Bharat, A.; Shapiro, T.A.; Singh, A.P.; Stevenson, J.; Hughes, M.; et al. NCCN Guidelines Insights: Non-Small Cell Lung Cancer, Version 2.2021. J. Natl. Compr. Cancer Netw. 2021, 19, 254–266. [Google Scholar] [CrossRef] [PubMed]
  3. Comoglio, P.M.; Trusolino, L.; Boccaccio, C. Known and novel roles of the MET oncogene in cancer: A coherent approach to targeted therapy. Nat. Rev. Cancer 2018, 18, 341–358. [Google Scholar] [CrossRef] [PubMed]
  4. Lee, M.; Jain, P.; Wang, F.; Ma, P.C.; Borczuk, A.; Halmos, B. MET alterations and their impact on the future of non-small cell lung cancer (NSCLC) targeted therapies. Expert Opin. Ther. Targets 2021, 25, 249–268. [Google Scholar] [CrossRef]
  5. Miranda, O.; Farooqui, M.; Siegfried, J.M. Status of Agents Targeting the HGF/c-Met Axis in Lung Cancer. Cancers 2018, 10, 280. [Google Scholar] [CrossRef] [Green Version]
  6. Planchard, D. Have We Really MET a New Target? J. Clin. Oncol. 2018, 36, JCO2018793455. [Google Scholar] [CrossRef]
  7. Garon, E.B.; Brodrick, P. Targeted Therapy Approaches for MET Abnormalities in Non-Small Cell Lung Cancer. Drugs 2021, 81, 547–554. [Google Scholar] [CrossRef]
  8. Ciuffreda, L.; Incani, U.; Steelman, L.; Abrams, S.; Falcone, I.; DEL Curatolo, A.; Chappell, W.; Franklin, R.A.; Vari, S.; Cognetti, F.; et al. Signaling Intermediates (MAPK and PI3K) as Therapeutic Targets in NSCLC. Curr. Pharm. Des. 2014, 20, 3944–3957. [Google Scholar] [CrossRef]
  9. Cardarella, S.; Ogino, A.; Nishino, M.; Butaney, M.; Shen, J.; Lydon, C.; Yeap, B.Y.; Sholl, L.M.; Johnson, B.E.; Jänne, P.A. Clinical, pathologic, and biologic features associated with BRAF mutations in non-small cell lung cancer. Clin. Cancer Res. 2013, 19, 4532–4540. [Google Scholar] [CrossRef] [Green Version]
  10. Domvri, K.; Zarogoulidis, P.; Darwiche, K.; Browning, R.F.; Li, Q.; Turner, J.F.; Kioumis, I.; Spyratos, D.; Porpodis, K.; Papaiwannou, A.; et al. Molecular Targeted Drugs and Biomarkers in NSCLC, the Evolving Role of Individualized Therapy. J. Cancer 2013, 4, 736–754. [Google Scholar] [CrossRef]
  11. Soucheray, M.; Capelletti, M.; Pulido, I.; Kuang, Y.; Paweletz, C.P.; Becker, J.H.; Kikuchi, E.; Xu, C.; Patel, T.B.; Al-Shahrour, F.; et al. Intratumoral Heterogeneity in EGFR-Mutant NSCLC Results in Divergent Resistance Mechanisms in Response to EGFR Tyrosine Kinase Inhibition. Cancer Res. 2015, 75, 4372–4383. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Seid, T.; Hagiya, M.; Shimonishi, M.; Nakamura, T.; Shimizu, S. Organization of the human hepatocyte growth factor-encoding gene. Gene 1991, 102, 213–219. [Google Scholar] [CrossRef] [PubMed]
  13. Mars, W.M.; Zarnegar, R.; Michalopoulos, G.K. Activation of hepatocyte growth factor by the plasminogen activators uPA and tPA. Am. J. Pathol. 1993, 143, 949–958. [Google Scholar]
  14. Ma, P.C.; Maulik, G.; Christensen, J.; Salgia, R. c-Met: Structure, functions and potential for therapeutic inhibition. Cancer Metastasis Rev. 2003, 22, 309–325. [Google Scholar] [CrossRef] [PubMed]
  15. Dong, Y.; Xu, J.; Sun, B.; Wang, J.; Wang, Z. MET-Targeted Therapies and Clinical Outcomes: A Systematic Literature Review. Mol. Diagn. Ther. 2022, 26, 203–227. [Google Scholar] [CrossRef] [PubMed]
  16. Bean, J.; Brennan, C.; Shih, J.-Y.; Riely, G.; Viale, A.; Wang, L.; Chitale, D.; Motoi, N.; Szoke, J.; Broderick, S.; et al. MET amplification occurs with or without T790M mutations in EGFR mutant lung tumors with acquired resistance to gefitinib or erlotinib. Proc. Natl. Acad. Sci. USA 2007, 104, 20932–20937. [Google Scholar] [CrossRef] [Green Version]
  17. Engelman, J.A.; Zejnullahu, K.; Mitsudomi, T.; Song, Y.; Hyland, C.; Park, J.O.; Lindeman, N.; Gale, C.-M.; Zhao, X.; Christensen, J.; et al. MET Amplification Leads to Gefitinib Resistance in Lung Cancer by Activating ERBB3 Signaling. Science 2007, 316, 1039–1043. [Google Scholar] [CrossRef]
  18. Wu, Y.-L.; Soo, R.A.; Locatelli, G.; Stammberger, U.; Scagliotti, G.; Park, K. Does c-Met remain a rational target for therapy in patients with EGFR TKI-resistant non-small cell lung cancer? Cancer Treat. Rev. 2017, 61, 70–81. [Google Scholar] [CrossRef]
  19. Ramalingam, S.S.; Cheng, Y.; Zhou, C.; Ohe, Y.; Imamura, F.; Cho, B.C.; Lin, M.-C.; Majem, M.; Shah, R.; Gray, J.; et al. Mechanisms of acquired resistance to first-line osimertinib: Preliminary data from the phase III FLAURA study. Ann. Oncol. 2018, 29 (Suppl. S8), LBA50. [Google Scholar] [CrossRef]
  20. Papadimitrakopoulou, V.A.; Wu, Y.L.; Han, J.Y.; Ahn, M.J.; Ramalingam, S.S.; John, T.; Okamoto, I.; Yang, J.H.; Bulusu, K.C.; Laus, G.; et al. Analysis of resistance mechanisms to osimertinib in patients with EGFR T790M advanced NSCLC from the AURA3 study. Ann. Oncol. 2018, 29, viii741. [Google Scholar] [CrossRef]
  21. Romaniello, D.; Marrocco, I.; Nataraj, N.B.; Ferrer, I.; Drago-Garcia, D.; Vaknin, I.; Oren, R.; Lindzen, M.; Ghosh, S.; Kreitman, M.; et al. Targeting HER3, a Catalytically Defective Receptor Tyrosine Kinase, Prevents Resistance of Lung Cancer to a Third-Generation EGFR Kinase Inhibitor. Cancers 2020, 12, 2394. [Google Scholar] [CrossRef] [PubMed]
  22. Shi, P.; Oh, Y.-T.; Zhang, G.; Yao, W.; Yue, P.; Li, Y.; Kanteti, R.; Riehm, J.; Salgia, R.; Owonikoko, T.K.; et al. Met gene amplification and protein hyperactivation is a mechanism of resistance to both first and third generation EGFR inhibitors in lung cancer treatment. Cancer Lett. 2016, 380, 494–504. [Google Scholar] [CrossRef] [PubMed]
  23. Fong, J.T.; Jacobs, R.J.; Moravec, D.N.; Uppada, S.B.; Botting, G.M.; Nlend, M.; Puri, N. Alternative Signaling Pathways as Potential Therapeutic Targets for Overcoming EGFR and c-Met Inhibitor Resistance in Non-Small Cell Lung Cancer. PLoS ONE 2013, 8, e78398. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Puri, N.; Salgia, R. Synergism of EGFR and c-Met pathways, cross-talk and inhibition, in non-small cell lung cancer. J. Carcinog. 2008, 7, 9. [Google Scholar] [CrossRef] [PubMed]
  25. Nakagawa, T.; Takeuchi, S.; Yamada, T.; Nanjo, S.; Ishikawa, D.; Sano, T.; Kita, K.; Nakamura, T.; Matsumoto, K.; Suda, K.; et al. Combined Therapy with Mutant-Selective EGFR Inhibitor and Met Kinase Inhibitor for Overcoming Erlotinib Resistance in EGFR-Mutant Lung Cancer. Mol. Cancer Ther. 2012, 11, 2149–2157. [Google Scholar] [CrossRef] [Green Version]
  26. Proietti, A.; Alì, G.; Pelliccioni, S.; Lupi, C.; Sensi, E.; Boldrini, L.; Servadio, A.; Chella, A.; Ribechini, A.; Cappuzzo, F.; et al. Anaplastic lymphoma kinase gene rearrangements in cytological samples of non-small cell lung cancer: Comparison with histological assessment. Cancer Cytopathol. 2014, 122, 445–453. [Google Scholar] [CrossRef]
  27. Morales La Madrid, A.; Campbell, N.; Smith, S.; Cohn, S.L.; Salgia, R. Targeting ALK: A promising strategy for the treatment of non-small cell lung cancer, non-Hodgkin’s lymphoma, and neuroblastoma. Target Oncol. 2012, 7, 199–210, Erratum in Target Oncol. 2013, 8, 301. [Google Scholar] [CrossRef]
  28. Shaw, A.T.; Solomon, B. Targeting Anaplastic Lymphoma Kinase in Lung Cancer. Clin. Cancer Res. 2011, 17, 2081–2086. [Google Scholar] [CrossRef] [Green Version]
  29. Katayama, R. Drug resistance in anaplastic lymphoma kinase-rearranged lung cancer. Cancer Sci. 2018, 109, 572–580. [Google Scholar] [CrossRef] [Green Version]
  30. Choi, S.H.; Kim, D.H.; Choi, Y.J.; Kim, S.Y.; Lee, J.-E.; Sung, K.J.; Kim, W.S.; Choi, C.-M.; Rho, J.K.; Lee, J.C. Multiple receptor tyrosine kinase activation related to ALK inhibitor resistance in lung cancer cells with ALK rearrangement. Oncotarget 2017, 8, 58771–58780. [Google Scholar] [CrossRef] [Green Version]
  31. Gouji, T.; Takashi, S.; Mitsuhiro, T.; Yukito, I. Crizotinib Can Overcome Acquired Resistance to CH5424802: Is Amplification of the MET Gene a Key Factor? J. Thorac. Oncol. 2014, 9, e27–e28. [Google Scholar] [CrossRef] [PubMed]
  32. Kogita, A.; Togashi, Y.; Hayashi, H.; Banno, E.; Terashima, M.; DE Velasco, M.A.; Sakai, K.; Fujita, Y.; Tomida, S.; Takeyama, Y.; et al. Activated MET acts as a salvage signal after treatment with alectinib, a selective ALK inhibitor, in ALK-positive non-small cell lung cancer. Int. J. Oncol. 2015, 46, 1025–1030. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Tanimoto, A.; Yamada, T.; Nanjo, S.; Takeuchi, S.; Ebi, H.; Kita, K.; Matsumoto, K.; Yano, S. Receptor ligand-triggered resistance to alectinib and its circumvention by Hsp90 inhibition in EML4-ALK lung cancer cells. Oncotarget 2014, 5, 4920–4928. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Isozaki, H.; Ichihara, E.; Takigawa, N.; Ohashi, K.; Ochi, N.; Yasugi, M.; Ninomiya, T.; Yamane, H.; Hotta, K.; Sakai, K.; et al. Non–Small Cell Lung Cancer Cells Acquire Resistance to the ALK Inhibitor Alectinib by Activating Alternative Receptor Tyrosine Kinases. Cancer Res. 2016, 76, 1506–1516. [Google Scholar] [CrossRef] [Green Version]
  35. Hong, D.S.; Fakih, M.G.; Strickler, J.H.; Desai, J.; Durm, G.A.; Shapiro, G.I.; Falchook, G.S.; Price, T.J.; Sacher, A.; Li, B.T.; et al. KRAS G12C Inhibition with Sotorasib in Advanced Solid Tumors. N. Engl. J. Med. 2020, 383, 1207–1217. [Google Scholar] [CrossRef]
  36. Awad, M.; Liu, S.; Arbour, K.; Zhu, V.; Johnson, M.; Heist, R.; Patil, T.; Riely, G.; Jacobson, J.; Dilly, J.; et al. Abstract LB002: Mechanisms of acquired resistance to KRAS G12C inhibition in cancer. Cancer Res. 2021, 81, LB002. [Google Scholar] [CrossRef]
  37. Zhao, Y.; Murciano-Goroff, Y.R.; Xue, J.Y.; Ang, A.; Lucas, J.; Mai, T.T.; Da Cruz Paula, A.F.; Saiki, A.Y.; Mohn, D.; Achanta, P.; et al. Diverse alterations associated with resistance to KRAS(G12C) inhibition. Nature 2021, 599, 679–683. [Google Scholar] [CrossRef]
  38. Lito, P.; Solomon, M.; Li, L.-S.; Hansen, R.; Rosen, N. Allele-specific inhibitors inactivate mutant KRAS G12C by a trapping mechanism. Science 2016, 351, 604–608. [Google Scholar] [CrossRef] [Green Version]
  39. Ahmed, T.A.; Adamopoulos, C.; Karoulia, Z.; Wu, X.; Sachidanandam, R.; Aaronson, S.A.; Poulikakos, P.I. SHP2 Drives Adaptive Resistance to ERK Signaling Inhibition in Molecularly Defined Subsets of ERK-Dependent Tumors. Cell Rep. 2019, 26, 65–78.e5. [Google Scholar] [CrossRef] [Green Version]
  40. Rosen, E.Y.; Johnson, M.L.; Clifford, S.E.; Somwar, R.; Kherani, J.F.; Son, J.; Bertram, A.A.; Davare, M.A.; Gladstone, E.G.; Ivanova, E.V.; et al. Overcoming MET-Dependent Resistance to Selective RET Inhibition in Patients with RET Fusion–Positive Lung Cancer by Combining Selpercatinib with Crizotinib. Clin. Cancer Res. 2021, 27, 34–42. [Google Scholar] [CrossRef]
  41. Subbiah, V.; Hu, M.I.-N.; Gainor, J.F.; Mansfield, A.S.; Alonso, G.; Taylor, M.H.; Zhu, V.W.; Lopez, P.G.; Amatu, A.; Doebele, R.C.; et al. Clinical activity of the RET inhibitor pralsetinib (BLU-667) in patients with RET fusion+ solid tumors. J. Clin. Oncol. 2020, 38, 109. [Google Scholar] [CrossRef]
  42. Lin, J.; Liu, S.; McCoach, C.; Zhu, V.; Tan, A.; Yoda, S.; Peterson, J.; Do, A.; Prutisto-Chang, K.; Dagogo-Jack, I.; et al. Mechanisms of resistance to selective RET tyrosine kinase inhibitors in RET fusion-positive non-small-cell lung cancer. Ann. Oncol. 2020, 31, 1725–1733. [Google Scholar] [CrossRef] [PubMed]
  43. Hellman, A.; Zlotorynski, E.; Scherer, S.W.; Cheung, J.; Vincent, J.B.; Smith, D.I.; Trakhtenbrot, L.; Kerem, B. A role for common fragile site induction in amplification of human oncogenes. Cancer Cell 2002, 1, 89–97. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Noonan, S.A.; Berry, L.; Lu, X.; Gao, D.; Barón, A.E.; Chesnut, P.; Sheren, J.; Aisner, D.L.; Merrick, D.; Doebele, R.C.; et al. Identifying the Appropriate FISH Criteria for Defining MET Copy Number–Driven Lung Adenocarcinoma through Oncogene Overlap Analysis. J. Thorac. Oncol. 2016, 11, 1293–1304. [Google Scholar] [CrossRef] [Green Version]
  45. Cappuzzo, F.; Marchetti, A.; Skokan, M.; Rossi, E.; Gajapathy, S.; Felicioni, L.; del Grammastro, M.; Sciarrotta, M.G.; Buttitta, F.; Incarbone, M.; et al. Increased MET Gene Copy Number Negatively Affects Survival of Surgically Resected Non–Small-Cell Lung Cancer Patients. J. Clin. Oncol. 2009, 27, 1667–1674. [Google Scholar] [CrossRef] [Green Version]
  46. Kato, H.; Arao, T.; Matsumoto, K.; Fujita, Y.; Kimura, H.; Hayashi, H.; Nishiki, K.; Iwama, M.; Shiraishi, O.; Yasuda, A.; et al. Gene amplification of EGFR, HER2, FGFR2 and MET in esophageal squamous cell carcinoma. Int. J. Oncol. 2013, 42, 1151–1158. [Google Scholar] [CrossRef] [Green Version]
  47. Graziano, F.; Galluccio, N.; Lorenzini, P.; Ruzzo, A.; Canestrari, E.; D’Emidio, S.; Catalano, V.; Sisti, V.; Ligorio, C.; Magnani, M.; et al. Genetic activation of the MET pathway and prognosis of patients with high-risk, radically resected gastric cancer. J. Clin. Oncol. 2011, 29, 4789–4795. [Google Scholar] [CrossRef]
  48. Yin, X.; Zhang, T.; Su, X.; Ji, Y.; Ye, P.; Fu, H.; Fan, S.; Shen, Y.; Gavine, P.R.; Gu, Y. Relationships between Chromosome 7 Gain, MET Gene Copy Number Increase and MET Protein Overexpression in Chinese Papillary Renal Cell Carcinoma Patients. PLoS ONE 2015, 10, e0143468. [Google Scholar] [CrossRef] [Green Version]
  49. Lee, H.E.; A Kim, M.; Jung, E.-J.; Yang, H.-K.; Lee, B.L.; Bang, Y.-J.; Kim, W.H. MET in gastric carcinomas: Comparison between protein expression and gene copy number and impact on clinical outcome. Br. J. Cancer 2012, 107, 325–333. [Google Scholar] [CrossRef] [Green Version]
  50. Nagatsuma, A.K.; Aizawa, M.; Kuwata, T.; Doi, T.; Ohtsu, A.; Fujii, H.; Ochiai, A. Expression profiles of HER2, EGFR, MET and FGFR2 in a large cohort of patients with gastric adenocarcinoma. Gastric Cancer 2015, 18, 227–238. [Google Scholar] [CrossRef] [Green Version]
  51. Tanaka, A.; Sueoka-Aragane, N.; Nakamura, T.; Takeda, Y.; Mitsuoka, M.; Yamasaki, F.; Hayashi, S.; Sueoka, E.; Kimura, S. Co-existence of positive MET FISH status with EGFR mutations signifies poor prognosis in lung adenocarcinoma patients. Lung Cancer 2012, 75, 89–94. [Google Scholar] [CrossRef] [PubMed]
  52. Wolf, J.; Seto, T.; Han, J.Y.; Reguart, N.; Garon, E.B.; Groen, H.J.; Tan, D.S.; Hida, T.; de Jonge, M.; Heist, R.S.; et al. Capmatinib in MET Exon 14-Mutated or MET-Amplified Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2020, 383, 944–957. [Google Scholar] [CrossRef] [PubMed]
  53. An, X.; Wang, F.; Shao, Q.; Wang, F.-H.; Wang, Z.-Q.; Chen, C.; Li, C.; Luo, H.-Y.; Zhang, D.-S.; Xu, R.H.; et al. MET amplification is not rare and predicts unfavorable clinical outcomes in patients with recurrent/metastatic gastric cancer after chemotherapy. Cancer 2014, 120, 675–682. [Google Scholar] [CrossRef]
  54. Kondo, S.; Ojima, H.; Tsuda, H.; Hashimoto, J.; Morizane, C.; Ikeda, M.; Ueno, H.; Tamura, K.; Shimada, K.; Kanai, Y.; et al. Clinical impact of c-Met expression and its gene amplification in hepatocellular carcinoma. Int. J. Clin. Oncol. 2013, 18, 207–213. [Google Scholar] [CrossRef] [PubMed]
  55. Go, H.; Jeon, Y.K.; Park, H.J.; Sung, S.-W.; Seo, J.-W.; Chung, D.H. High MET Gene Copy Number Leads to Shorter Survival in Patients with Non-small Cell Lung Cancer. J. Thorac. Oncol. 2010, 5, 305–313. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Lennerz, J.K.; Kwak, E.L.; Ackerman, A.; Michael, M.; Fox, S.B.; Bergethon, K.; Lauwers, G.Y.; Christensen, J.G.; Wilner, K.D.; Haber, D.A.; et al. MET Amplification Identifies a Small and Aggressive Subgroup of Esophagogastric Adenocarcinoma With Evidence of Responsiveness to Crizotinib. J. Clin. Oncol. 2011, 29, 4803–4810. [Google Scholar] [CrossRef] [Green Version]
  57. Jardim, D.L.; Tang, C.; Gagliato, D.D.M.; Falchook, G.S.; Hess, K.; Janku, F.; Fu, S.; Wheler, J.J.; Zinner, R.G.; Naing, A.; et al. Analysis of 1,115 Patients Tested for MET Amplification and Therapy Response in the MD Anderson Phase I Clinic. Clin. Cancer Res. 2014, 20, 6336–6345. [Google Scholar] [CrossRef] [Green Version]
  58. Reams, A.B.; Roth, J.R. Mechanisms of gene duplication and amplification. Cold Spring Harb. Perspect. Biol. 2015, 7, a016592. [Google Scholar] [CrossRef] [Green Version]
  59. Buckingham, L.E.; Coon, J.S.; Morrison, L.E.; Jacobson, K.K.; Jewell, S.S.; Kaiser, K.A.; Mauer, A.M.; Muzzafar, T.; Polowy, C.; Basu, S.; et al. The Prognostic Value of Chromosome 7 Polysomy in Non-small Cell Lung Cancer Patients Treated with Gefitinib. J. Thorac. Oncol. 2007, 2, 414–422. [Google Scholar] [CrossRef] [Green Version]
  60. Tong, J.H.; Yeung, S.F.; Chan, A.W.H.; Chung, L.Y.; Chau, S.L.; Lung, R.W.M.; Tong, C.Y.; Chow, C.; Tin, E.K.Y.; Yu, Y.H.; et al. MET Amplification and Exon 14 Splice Site Mutation Define Unique Molecular Subgroups of Non–Small Cell Lung Carcinoma with Poor Prognosis. Clin. Cancer Res. 2016, 22, 3048–3056. [Google Scholar] [CrossRef] [Green Version]
  61. Le, X. Heterogeneity in MET-Aberrant NSCLC. J. Thorac. Oncol. 2021, 16, 504–506. [Google Scholar] [CrossRef]
  62. Kron, A.; Scheffler, M.; Heydt, C.; Ruge, L.; Schaepers, C.; Eisert, A.-K.; Merkelbach-Bruse, S.; Riedel, R.; Nogova, L.; Fischer, R.N.; et al. Genetic Heterogeneity of MET-Aberrant NSCLC and Its Impact on the Outcome of Immunotherapy. J. Thorac. Oncol. 2021, 16, 572–582. [Google Scholar] [CrossRef] [PubMed]
  63. Guo, R.; Luo, J.; Chang, J.; Rekhtman, N.; Arcila, M.; Drilon, A. MET-dependent solid tumours—Molecular diagnosis and targeted therapy. Nat. Rev. Clin. Oncol. 2020, 17, 569–587. [Google Scholar] [CrossRef] [PubMed]
  64. Schubart, C.; Stöhr, R.; Tögel, L.; Fuchs, F.; Sirbu, H.; Seitz, G.; Seggewiss-Bernhardt, R.; Leistner, R.; Sterlacci, W.; Vieth, M.; et al. MET Amplification in Non-Small Cell Lung Cancer (NSCLC)—A Consecutive Evaluation Using Next-Generation Sequencing (NGS) in a Real-World Setting. Cancers 2021, 13, 5023. [Google Scholar] [CrossRef] [PubMed]
  65. Fan, Y.; Sun, R.; Wang, Z.; Zhang, Y.; Xiao, X.; Liu, Y.; Xin, B.; Xiong, H.; Lu, D.; Ma, J. Detection of MET amplification by droplet digital PCR in peripheral blood samples of non-small cell lung cancer. J. Cancer Res. Clin. Oncol. 2022, 148, 1–11. [Google Scholar] [CrossRef] [PubMed]
  66. Hu, T.; Chitnis, N.; Monos, D.; Dinh, A. Next-generation sequencing technologies: An overview. Hum. Immunol. 2021, 82, 801–811. [Google Scholar] [CrossRef] [PubMed]
  67. Hung, S.S.; Meissner, B.; Chavez, E.A.; Ben-Neriah, S.; Ennishi, D.; Jones, M.R.; Shulha, H.P.; Chan, F.C.; Boyle, M.; Kridel, R.; et al. Assessment of Capture and Amplicon-Based Approaches for the Development of a Targeted Next-Generation Sequencing Pipeline to Personalize Lymphoma Management. J. Mol. Diagn. 2018, 20, 203–214. [Google Scholar] [CrossRef] [Green Version]
  68. Samorodnitsky, E.; Jewell, B.M.; Hagopian, R.; Miya, J.; Wing, M.R.; Lyon, E.; Damodaran, S.; Bhatt, D.; Reeser, J.W.; Datta, J.; et al. Evaluation of Hybridization Capture Versus Amplicon-Based Methods for Whole-Exome Sequencing. Hum. Mutat. 2015, 36, 903–914. [Google Scholar] [CrossRef] [Green Version]
  69. Wang, J.; Yu, H.; Zhang, V.W.; Tian, X.; Feng, Y.; Wang, G.; Gorman, E.; Wang, H.; Lutz, R.E.; Schmitt, E.S.; et al. Capture-based high-coverage NGS: A powerful tool to uncover a wide spectrum of mutation types. Genet. Med. 2016, 18, 513–521. [Google Scholar] [CrossRef] [Green Version]
  70. Wong, S.Q.; Li, J.; Salemi, R.; Sheppard, K.E.; Do, H.; Tothill, R.W.; McArthur, G.A.; Dobrovic, A. Targeted-capture massively-parallel sequencing enables robust detection of clinically informative mutations from formalin-fixed tumours. Sci. Rep. 2013, 3, 3494. [Google Scholar] [CrossRef] [Green Version]
  71. Hartmaier, R.J.; Markovets, A.A.; Ahn, M.J.; Sequist, L.V.; Han, J.Y.; Cho, B.C.; Yu, H.A.; Kim, S.W.; Yang, J.C.; Janne, P.A.; et al. Osimertinib + Savolitinib to Overcome Acquired MET-Mediated Resistance in Epidermal Growth Factor Receptor Mutated MET-Amplified Non-Small Cell Lung Cancer: TATTON. Cancer Discov. 2023, 13, 98–113. [Google Scholar] [CrossRef]
  72. Wu, Y.L.; Zhang, L.; Kim, D.W.; Liu, X.; Lee, D.H.; Yang, J.C.; Ahn, M.-J.; Vansteenkiste, J.F.; Su, W.-C.; Tan, D.S.; et al. Phase Ib/II Study of Capmatinib (INC280) Plus Gefitinib After Failure of Epidermal Growth Factor Receptor (EGFR) Inhibitor Therapy in Patients With EGFR-Mutated, MET Factor-Dysregulated Non-Small-Cell Lung Cancer. J. Clin. Oncol. 2018, 36, 3101–3109, Erratum in J. Clin. Oncol. 2019, 37, 261. [Google Scholar] [CrossRef] [PubMed]
  73. Smit, E.F.; Dooms, C.; Raskin, J.; Nadal, E.; Tho, L.M.; Le, X.; Mazieres, J.; Hin, H.; Morise, M.; Wu, Y.L.; et al. INSIGHT 2: A phase II study of tepotinib plus osimertinib in MET-amplified NSCLC and first-line osimertinib resistance. Future Oncol. 2022, 18, 1039–1054. [Google Scholar] [CrossRef] [PubMed]
  74. Heydt, C.; Becher, A.-K.; Wagener-Ryczek, S.; Ball, M.; Schultheis, A.M.; Schallenberg, S.; Rüsseler, V.; Büttner, R.; Merkelbach-Bruse, S. Comparison of in situ and extraction-based methods for the detection of MET amplifications in solid tumors. Comput. Struct. Biotechnol. J. 2019, 17, 1339–1347. [Google Scholar] [CrossRef] [PubMed]
  75. Peng, L.-X.; Jie, G.-L.; Li, A.-N.; Liu, S.-Y.; Sun, H.; Zheng, M.-M.; Zhou, J.-Y.; Zhang, J.-T.; Zhang, X.-C.; Zhou, Q.; et al. MET amplification identified by next-generation sequencing and its clinical relevance for MET inhibitors. Exp. Hematol. Oncol. 2021, 10, 52. [Google Scholar] [CrossRef]
  76. Lai, G.G.Y.; Lim, T.H.; Lim, J.; Liew, P.J.R.; Kwang, X.L.; Nahar, R.; Aung, Z.W.; Takano, A.; Lee, Y.Y.; Lau, D.P.X.; et al. Clonal MET Amplification as a Determinant of Tyrosine Kinase Inhibitor Resistance in Epidermal Growth Factor Receptor–Mutant Non&ndash;Small-Cell Lung Cancer. J. Clin. Oncol. 2019, 37, 876–884. [Google Scholar] [CrossRef]
  77. Sakai, H.; Morise, M.; Kato, T.; Matsumoto, S.; Sakamoto, T.; Kumagai, T.; Tokito, T.; Atagi, S.; Kozuki, T.; Tanaka, H.; et al. Tepotinib in patients with NSCLC harbouring MET exon 14 skipping: Japanese subset analysis from the Phase II VISION study. Jpn. J. Clin. Oncol. 2021, 51, 1261–1268. [Google Scholar] [CrossRef]
  78. Drilon, A.; Cappuzzo, F.; Ou, S.-H.I.; Camidge, D.R. Targeting MET in Lung Cancer: Will Expectations Finally Be MET? J. Thorac. Oncol. 2017, 12, 15–26. [Google Scholar] [CrossRef] [Green Version]
  79. Spigel, D.R.; Ervin, T.J.; Ramlau, R.A.; Daniel, D.B.; Goldschmidt, J.H., Jr.; Blumenschein, G.R., Jr.; Krzakowski, M.J.; Robinet, G.; Godbert, B.; Barlesi, F.; et al. Randomized Phase II Trial of Onartuzumab in Combination With Erlotinib in Patients With Advanced Non–Small-Cell Lung Cancer. J. Clin. Oncol. 2013, 31, 4105–4114. [Google Scholar] [CrossRef] [Green Version]
  80. Stenger, M. Calculating H-Score. 2015. Available online: https://ascopost.com/issues/april-102015/calculating-h-score/ (accessed on 8 August 2022).
  81. Aisner, D.L.; Sholl, L.M.; Berry, L.D.; Rossi, M.R.; Chen, H.; Fujimoto, J.; Moreira, A.L.; Ramalingam, S.S.; Villaruz, L.C.; Otterson, G.A.; et al. The Impact of Smoking and TP53 Mutations in Lung Adenocarcinoma Patients with Targetable Mutations—The Lung Cancer Mutation Consortium (LCMC2). Clin. Cancer Res. 2018, 24, 1038–1047. [Google Scholar] [CrossRef] [Green Version]
  82. Mignard, X.; Ruppert, A.-M.; Antoine, M.; Vasseur, J.; Girard, N.; Mazières, J.; Moro-Sibilot, D.; Fallet, V.; Rabbe, N.; Thivolet-Bejui, F.; et al. c-MET Overexpression as a Poor Predictor of MET Amplifications or Exon 14 Mutations in Lung Sarcomatoid Carcinomas. J. Thorac. Oncol. 2018, 13, 1962–1967. [Google Scholar] [CrossRef] [PubMed]
  83. Camidge, D.R.; Otterson, G.A.; Clark, J.W.; Ou, S.-H.I.; Weiss, J.; Ades, S.; Shapiro, G.I.; Socinski, M.A.; Murphy, D.A.; Conte, U.; et al. Crizotinib in Patients with MET-Amplified NSCLC. J. Thorac. Oncol. 2021, 16, 1017–1029. [Google Scholar] [CrossRef] [PubMed]
  84. Sterlacci, W.; Fiegl, M.; Gugger, M.; Bubendorf, L.; Savic, S.; Tzankov, A. MET overexpression and gene amplification: Prevalence, clinico-pathological characteristics and prognostic significance in a large cohort of patients with surgically resected NSCLC. Virchows Arch. 2017, 471, 49–55. [Google Scholar] [CrossRef] [PubMed]
  85. Spigel, D.R.; Edelman, M.; O’Byrne, K.; Paz-Ares, L.; Mocci, S.; Phan, S.; Shames, D.S.; Smith, D.; Yu, W.; Paton, V.E.; et al. Results From the Phase III Randomized Trial of Onartuzumab Plus Erlotinib Versus Erlotinib in Previously Treated Stage IIIB or IV Non–Small-Cell Lung Cancer: METLung. J. Clin. Oncol. 2017, 35, 412–420. [Google Scholar] [CrossRef] [Green Version]
  86. Neal, J.W.; E Dahlberg, S.; A Wakelee, H.; Aisner, S.C.; Bowden, M.; Huang, Y.; Carbone, D.P.; Gerstner, G.J.; Lerner, R.E.; Rubin, J.L.; et al. Erlotinib, cabozantinib, or erlotinib plus cabozantinib as second-line or third-line treatment of patients with EGFR wild-type advanced non-small-cell lung cancer (ECOG-ACRIN 1512): A randomised, controlled, open-label, multicentre, phase 2 trial. Lancet Oncol. 2016, 17, 1661–1671. [Google Scholar] [CrossRef] [Green Version]
  87. Cai, Y.-R.; Zhang, H.-Q.; Zhang, Z.-D.; Mu, J.; Li, Z.-H. Detection of MET and SOX2 amplification by quantitative real-time PCR in non-small cell lung carcinoma. Oncol. Lett. 2011, 2, 257–264. [Google Scholar] [CrossRef] [Green Version]
  88. Zhang, Y.; Tang, E.-T.; Du, Z. Detection of MET Gene Copy Number in Cancer Samples Using the Droplet Digital PCR Method. PLoS ONE 2016, 11, e0146784. [Google Scholar] [CrossRef]
  89. Xu, C.-W.; Wang, W.-X.; Wu, M.-J.; Zhu, Y.-C.; Zhuang, W.; Lin, G.; Du, K.-Q.; Huang, Y.-J.; Chen, Y.-P.; Chen, G.; et al. Comparison of the c-MET gene amplification between primary tumor and metastatic lymph nodes in non-small cell lung cancer. Thorac. Cancer 2017, 8, 417–422. [Google Scholar] [CrossRef]
  90. Bardelli, A.; Corso, S.; Bertotti, A.; Hobor, S.; Valtorta, E.; Siravegna, G.; Sartore-Bianchi, A.; Scala, E.; Cassingena, A.; Zecchin, D.; et al. Amplification of the MET Receptor Drives Resistance to Anti-EGFR Therapies in Colorectal Cancer. Cancer Discov. 2013, 3, 658–673. [Google Scholar] [CrossRef] [Green Version]
  91. Galimi, F.; Torti, D.; Sassi, F.; Isella, C.; Corà, D.; Gastaldi, S.; Ribero, D.; Muratore, A.; Massucco, P.; Siatis, D.; et al. Genetic and Expression Analysis of MET, MACC1, and HGF in Metastatic Colorectal Cancer: Response to Met Inhibition in Patient Xenografts and Pathologic Correlations. Clin. Cancer Res. 2011, 17, 3146–3156. [Google Scholar] [CrossRef] [Green Version]
  92. Pasquini, G.; Giaccone, G. C-MET inhibitors for advanced non-small cell lung cancer. Expert Opin. Investig. Drugs 2018, 27, 363–375. [Google Scholar] [CrossRef] [PubMed]
  93. Le, X.; Puri, S.; Negrao, M.V.; Nilsson, M.B.; Robichaux, J.; Boyle, T.; Hicks, J.K.; Lovinger, K.L.; Roarty, E.; Rinsurongkawong, W.; et al. Landscape of EGFR-Dependent and -Independent Resistance Mechanisms to Osimertinib and Continuation Therapy Beyond Progression in EGFR-Mutant NSCLC. Clin. Cancer Res. 2018, 24, 6195–6203. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  94. Yang, J.-J.; Fang, J.; Shu, Y.-Q.; Chang, J.-H.; Chen, G.-Y.; He, J.X.; Li, W.; Liu, X.-Q.; Yang, N.; Zhou, C.; et al. A phase Ib study of the highly selective MET-TKI savolitinib plus gefitinib in patients with EGFR-mutated, MET-amplified advanced non-small-cell lung cancer. Investig. New Drugs 2021, 39, 477–487. [Google Scholar] [CrossRef] [PubMed]
  95. McCoach, C.E.; Yu, A.; Gandara, D.R.; Riess, J.W.; Vang, D.P.; Li, T.; Lara, P.N.; Gubens, M.; Lara, F.; Mack, P.C.; et al. Phase I/II Study of Capmatinib Plus Erlotinib in Patients With MET-Positive Non–Small-Cell Lung Cancer. JCO Precis. Oncol. 2021, 1, 177–190. [Google Scholar] [CrossRef] [PubMed]
  96. Wu, Y.-L.; Cheng, Y.; Zhou, J.; Lu, S.; Zhang, Y.; Zhao, J.; Kim, D.-W.; Soo, R.A.; Kim, S.-W.; Pan, H.; et al. Tepotinib plus gefitinib in patients with EGFR-mutant non-small-cell lung cancer with MET overexpression or MET amplification and acquired resistance to previous EGFR inhibitor (INSIGHT study): An open-label, phase 1b/2, multicentre, randomised trial. Lancet Respir. Med. 2020, 8, 1132–1143. [Google Scholar] [CrossRef]
  97. Camidge, D.R.; Barlesi, F.; Goldman, J.W.; Morgensztern, D.; Heist, R.; Vokes, E.; Spira, A.; Angevin, E.; Su, W.-C.; Kelly, K.; et al. Phase Ib Study of Telisotuzumab Vedotin in Combination With Erlotinib in Patients With c-Met Protein-Expressing Non-Small-Cell Lung Cancer. J. Clin. Oncol. 2022, 3, JCO2200739. [Google Scholar] [CrossRef]
  98. Camidge, D.R.; Moran, T.; Demedts, I.; Grosch, H.; Mileham, K.; Molina, J.; Juan-Vidal, O.; Bepler, G.; Goldman, J.W.; Park, K.; et al. A Randomized, Open-Label Phase II Study Evaluating Emibetuzumab Plus Erlotinib and Emibetuzumab Monotherapy in MET Immunohistochemistry Positive NSCLC Patients with Acquired Resistance to Erlotinib. Clin. Lung Cancer 2022, 23, 300–310. [Google Scholar] [CrossRef]
  99. Available online: https://oncologypro.esmo.org/meeting-resources/esmo-congress-2021/orchard-osimertinib-savolitinib-interim-analysis-a-biomarker-directed-phase-ii-platform-study-in-patients-pts-with-advanced-non-small-cell-lun (accessed on 16 September 2021).
  100. Felip, E.; Minotti, V.; Soo, R.; Wolf, J.; Solomon, B.; Tan, D.; Ardizzoni, A.; Lee, D.; Sequist, L.; Barlesi, F.; et al. 1284P MET inhibitor capmatinib plus EGFR tyrosine kinase inhibitor nazartinib for EGFR-mutant non-small cell lung cancer. Ann. Oncol. 2020, 31, S829–S830. [Google Scholar] [CrossRef]
  101. Available online: https://www.astrazeneca.com/media-centre/press-releases/2022/tagrisso-plus-savolitinib-demonstrated-49-objective-response-rate-in-lung-cancer-patients-in-savannah-phase-ii-trial.html (accessed on 8 August 2022).
Figure 1. Mechanisms of MET amplification-mediated resistance to molecularly targeted therapies in non-small cell lung cancer (NSCLC). EGFR mutation or ALK-rearrangement as the primary driver oncogene shown. MET, EGFR, and ALK are all members of the RTK family, which regulates cellular proliferation and survival through common downstream pathways such as the PI3K-AKT-mTOR and RAS-RAF-MEK-ERK pathways.
Figure 1. Mechanisms of MET amplification-mediated resistance to molecularly targeted therapies in non-small cell lung cancer (NSCLC). EGFR mutation or ALK-rearrangement as the primary driver oncogene shown. MET, EGFR, and ALK are all members of the RTK family, which regulates cellular proliferation and survival through common downstream pathways such as the PI3K-AKT-mTOR and RAS-RAF-MEK-ERK pathways.
Cancers 15 00612 g001
Table 1. Summary of key clinical studies on combined therapies to overcome acquired MET-amplification-mediated resistance to EGFR-TKIs in EGFR-mutated NSCLC.
Table 1. Summary of key clinical studies on combined therapies to overcome acquired MET-amplification-mediated resistance to EGFR-TKIs in EGFR-mutated NSCLC.
Study (Author, Year, NCT ID)TreatmentPhase of Study (Number of Patients)MET Diagnostic Assays and CriteriaConcurrent EGFR Mutations and Prior EGFR-TKIsLines of Therapies
(Prior EGFR TKIs)
mPFS, MonthsmOS, MonthsORR%
Combined therapies with first-generation EGFR-TKIs and MET inhibitors
Yang et al. (2021) NCT02374645 [94]Savolitinib plus
Gefitinib
phase Ib n = 64 safety run-in n = 13 (savolitinib +
gefitinib n = 6; savolitinib +
gefitinib n = 7);
expansion savolitinib+ gefitinib n = 51
MET GCN ≥5 or MET/CEP7 ratio ≥2 by FISHEGFR-mutated advanced NSCLC≥1 (A prior EGFR-TKI)4.2 (95% CI: 3.5, 8.5)NRNR; In EGFR T790M-negative: ORR: 52% (12/23)
McCoach CE, et al. (2021) NCT01911507 [95]Capmatinib + ErlotinibPhase I/II n = 17 Cohort A (EGFR
mutant n = 12)
cohort B (EGFR
wildtype, n = 5)
CNG or MET/CEN7 ratio outside of
normal range by FISH; MET IHC 2-3+;
Cohort A: EGFR
Mutant;
cohort B: EGFR
wildtype
≥1 prior EGFR TKINRNRCohort A: 50%;
Cohort B: 75%
Wu et al. (2020).
INSIGHT study NCT01982955 [96]
Tepotinib + Gefitinib vs. Chemotherapy (pemetrexed + cisplatin or
carboplatin);
Phase Ib (18)/Phase II (55)MET OE (IHC 2+ or IHC3+) or MET
amp (FISH, mean GCN ≥ 5, and/or MET/CEP7 ratio of ≥2)
EGFR-mutant, T790M-negative≥2Overall: 4.9 (90% CI: 3.9–6.9) vs. 4.4 (90% CI: 4.2–6.8)HR 0.67 (90% CI:0.35–1.28)
In the high MET subgroup (IHC3+): mPFS:
8.3 (90% CI: 4.1–16.6) vs. 4.4 (90% CI: 4.1–6.8), HR 0.35, 90% CI: 0.17–0.74
In the MET amplification subgroup:16.6 (90% CI: 8.3–not estimable) vs. 4.2 (90% CI: 1.4–7.0); HR 0.13, 90% CI: 0.04–0.43
Phase II Overall: 17.3 (90% CI: 12.1–37.3) vs. 18.7 (90% CI:15.9–20.7); HR 0.69, (90% CI: 0.34–1.41)
In the high (IHC3+) MET subgroup: 37.3 (90% CI 24·2–37·3) vs. 17·9 (12.0–20.7); HR 0.33, 90% CI: 0.14–0.76.
In the MET amplification subgroup
37.3 months (90% CI not estimable) vs. 13.1 [3.25–not estimable]; HR 0.08, 90% CI: 0.01–0.51)
Phase II Overall:
45% (29.7–61.3) vs. 33%
(17.8–52.1)
In the high (IHC3+) MET subgroup:
68% (47.0–85.3) vs. 33%
(14.2–57.7)
In the MET amplification subgroup:
67% (39.1–87.7) vs.
43% (12.9–77.5)
Camidge et al. (2022) [97]Telisotuzumab
Vedotin + erlotinib
phase 1b
42 NSCLC pts received T + E; 37 were c-MET+ (36 evaluable; 35 H-score ≥ 150, 1 MET amplified)
c-Met+ (central lab IHC H-score ≥150 or local lab MET amplification) ≥1NR 95%CI: 2.8–NE5.9 m 95CI: 1.2–NEEGFR mut+:
34.5 (95%CI: 17.9–54.3)
EGFR wildtype:
28.6% (95%CI: 3.7–71.0)
Wu et al. (2018).
NCT01610336 [72]
Capmatinib (INC280) + GefitinibPhase Ib(61)/phaseII(100)(GCN < 4: n = 41
4 ≤ GCN < 6:
N = 18;
GCN ≥ 6: n = 36)
IHC, MET OE 2+ or 3+; FISH, MET
Amp GCN ≥ 5, MET/(CEP7) ratio of
≥2:1
50% of tumor cells with IHC 3+ or MET GCN < 4)
EGFR-mutated advanced
NSCLC
≥2 (≥1 prior EGFR-TKI)Overall: 5.5 (95% CI, 3.8 to 5.6;
mPFS in GCN ≥ 6 subgroup: 5.49 (95% CI, 4.21 to 7.29),
mPFS in the
4 ≤ GCN < 6 subgroup: 5.39 (95% CI, 3.65 to 7.46);
mPFS in the GCN < 4 subgroup:
3.91(95% CI, 3.65 to 5.55)
mPFS in the IHC2+/GCN ≥ 5 subgroup:
7.29 (95%CI, 1.81 to 9.07)
mPFS in the IHC3+ subgroup: 5.45 (95% CI, 3.71 to 7.10)
NRPhase Ib/II overall: 43%;
Phase II overall: 29%;
GCN ≥ 6: 47%;
4 ≤ GCN < 6:
22%; GCN < 4:
12%;
IHC 3+: 32%
Camidge et al. (2022)
NCT01900652 [98]
emibetuzumab + erlotinib vs. emibetuzumab monotherapyPhase II
emibetuzumab + erlotinib (n = 83);
emibetuzumab monotherapy (n = 28)
≥10% of cells expressing MET at ≥2+ by IHCEGFR-mt
NSCLC
≥13.3 vs. 1.6NR3.0 for emibetuzumab + erlotinib (95% CI: 0.4, 10.5) vs. 4.3% for emibetuzumab (95% CI: 0.1, 21.9)
Combined therapies with third-generation EGFR-TKIs and MET-TKIs
Yu et al. (2021) ORCHARD Study [99]Osimertinib + Savolitinibphase II (n = 17)NGS (criteria NR; GCN ranged from 7 to 68)EGFRm2 (progressed after prior first-line Osimertinib)NRNRORR: 41% (7/17)
Sequist et al. (2020)
TATTON study
NCT02143466 [71]
Osimertinib + Savolitinibphase 1B; Part B n = 138 (osimertinib 80 mg psavolitinib 600 mg or 300 mg):
(Part B1: previously received third generation EGFR TKI n = 69; part B2: no previous third-generation EGFR TKI, Thr790Met negative, n = 51; Part B3: no previous
third-generation
EGFR TKI,
Thr790Met positive n = 18);
Part D n = 42 (osimertinib plus savolitinib; no
previous third-generation
EGFR TKI, Thr790Met
negative)
MET gene copy number gain ≥ 5 or MET/CEP7 ratio ≥ 2 by FISH; MET + 3 expression in ≥50% of tumor cells by IHC; ≥20% tumor cells, coverage of ≥200× sequencing depth and ≥5 copies of MET over tumor ploidy by NGSEGFR
mutation-positive(with or without T790M mutation)
≥2 (≥1 prior EGFR-TKI)
Part B overall: 5.5–11.1;
Part D: 9.0 (95%CI: 5.4–12.9)
NRpart B: 33–67%;
part D: 62%
E. Felip et al. (2019)
NCT02335944 [100]
Capmatinib + Nazartinib n = 68 (66 had known MET status: 23
MET+, 43 METȡ)
Phase 1b/II studyMET+: IHC 3+ and/or GCN ≥4EGFR-mutant
stage IIIB/IV NSCLC
≥17.7 (95% CI: 5.4–12.2)18.8 (95% CI:14.0–21.3)43.5 (95% CI:23.2–65.5)
NCT03940703
INSIGHT 2 study [73]
Tepotinib plus
Osimertinib vs. chemotherapy
Phase II (n = 425)METamp by FISH testing (GCN ≥ 5 and/or MET/CEP7 ratio ≥ 2) or METamp determined by using NGS (GCN ≥ 2.3)EGFR-mutated NSCLC2NRNR54.5% among the 22 patients with FISH detected MET amplification and at least 9 months of follow-up; 45.8% among the 48 participants with follow-up of 3 months or more; 50.0% for the 16 patients who were followed up for 9 months or more and 56.5% for the 23 followed up for 3 months or more
NCT03778229
SAVANNAH Study [101]
Osimertinib + SavolitinibPhase II (n = 193)High levels of MET overexpression and/or amplification, defined as IHC90+ and/or FISH10+,
(IHC50+ and/or FISH5+; n = 193)
EGFRm+, MET+,
progressed on prior Osimertinib
≥2All patients (IHC50+ and/or FISH5+; n = 193): 5.3 (4.2, 5.8);
Patients with high levels of MET
(IHC90+ and/or FISH10+):
(n = 108)
7.1 (5.3, 8.0)
Patients with high levels of MET
(IHC90+ and/or FISH10+)
No prior chemo (n = 87):
7.2 (4.7, 9.2)
Patients with lower levels of MET (n = 77):
2.8 (2.6, 4.3)
NROverall:
All patients (IHC50+ and/or FISH5+; n = 193):
5.3 (4.2, 5.8)
Patients with high levels of MET (IHC90+ and/or FISH10+) (n = 108):
7.1 (5.3, 8.0)
Patients with high levels of MET (IHC90+ and/or FISH10+)
No prior chemo (n = 87):
7.2 (4.7, 9.2)
Patients with lower levels of MET (n = 77):
9 (4, 18)
Abbreviations: NSCLC, non-small cell lung cancer; ORR, objective response rate; mPFS, median progression-free survival; OS, median overall survival; MET, mesenchymal-epithelial transition factor; amp, amplification; EGFR, epidermal growth factor receptor; IHC, immunohistochemistry; FISH, fluorescence in situ hybridization; GCN, gene copy number; Pem, pemetrexed; Dox, docetaxel; Gem, gemcitabine; LBx, liquid biopsy; TBx, tissue biopsy; [CI], confidence interval; NR, not reported.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Qin, K.; Hong, L.; Zhang, J.; Le, X. MET Amplification as a Resistance Driver to TKI Therapies in Lung Cancer: Clinical Challenges and Opportunities. Cancers 2023, 15, 612. https://doi.org/10.3390/cancers15030612

AMA Style

Qin K, Hong L, Zhang J, Le X. MET Amplification as a Resistance Driver to TKI Therapies in Lung Cancer: Clinical Challenges and Opportunities. Cancers. 2023; 15(3):612. https://doi.org/10.3390/cancers15030612

Chicago/Turabian Style

Qin, Kang, Lingzhi Hong, Jianjun Zhang, and Xiuning Le. 2023. "MET Amplification as a Resistance Driver to TKI Therapies in Lung Cancer: Clinical Challenges and Opportunities" Cancers 15, no. 3: 612. https://doi.org/10.3390/cancers15030612

APA Style

Qin, K., Hong, L., Zhang, J., & Le, X. (2023). MET Amplification as a Resistance Driver to TKI Therapies in Lung Cancer: Clinical Challenges and Opportunities. Cancers, 15(3), 612. https://doi.org/10.3390/cancers15030612

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop