<table><caption>Table 1. Clinical and Histologic Data Pertaining to NSCLC Patients Harboring *MET* Exon 14 Mutations (N = 30)</caption><tbody><tr><td>Age, mean, y (range)</td><td>73 (45-91)</td></tr><tr><td>Sex, n (%)</td><td></td></tr><tr><td>Male</td><td>13</td><td>(43)</td></tr><tr><td>Female</td><td>17</td><td>(57)</td></tr><tr><td>Smoking status</td><td></td></tr><tr><td>Current</td><td>4</td><td>(13)</td></tr><tr><td>Former</td><td>12</td><td>(40)</td></tr><tr><td>Never</td><td>14</td><td>(47)</td></tr><tr><td>Histology</td><td></td></tr><tr><td>Adenocarcinoma</td><td>24</td><td>(80)</td></tr><tr><td>PSC</td><td>3</td><td>(10)</td></tr><tr><td>NSCLC NOS</td><td>3</td><td>(10)</td></tr><tr><td>Stage</td><td></td></tr><tr><td>I to III</td><td>12</td><td>(40)</td></tr><tr><td>IV</td><td>16</td><td>(53)</td></tr><tr><td>Unknown</td><td>2</td><td>(7)</td></tr><tr><td>Type of MET exon 14 splice site mutations</td><td></td></tr><tr><td>Point mutations</td><td>9</td><td>(30)</td></tr><tr><td>Insertions, deletions or indels</td><td>21</td><td>(70)</td></tr></tbody></table>

Values are presented as n (%) unless otherwise specified.

ADC, adenocarcinoma; NSCLC NOS, not otherwise specified; PSC, pulmonary sarcomatoid carcinoma.

increase. In this sample, however, the read count displayed a high background, preventing accurate data interpretation (data not shown). Tumor samples from five patients with no tissue available for FISH analysis were subjected to read count analysis, and two were found to harbor an increased *MET* copy number (patients 10 and 16). Accordingly, these two tumor samples displayed high *MET* expression (IHC 3+). Raw data are shown for samples 10, 16, 20, and 22, which displayed an increased copy number, and for sample 1, which did not (Supplemental Fig. 4). Taken together, the FISH and NGS data analyses revealed six *MET* gene amplifications or copy number increases among 30 patients (20%).

Discussion

*MET* exon 14 splice site mutations are different from most receptor tyrosine kinase mutations amenable to targeted therapies. Firstly, they occur either within the introns flanking exon 14 or at the junction between intron and exon 14. Secondly, *MET* exon 14 splice site mutations are molecularly diverse, including small and large deletions, point mutations, and indels. Consequently, detection of *MET* exon 14 splice site mutations requires a specific approach. Here we show that combining fragment-length analysis with adapted targeted NGS allows detection of *MET* exon 14 splice site mutations in 2.2% of patients in routine practice, as compared to the 0.3% detection rate obtained with nonoptimized targeted NGS alone.

*MET* exon 14 mutations were first reported on large retrospective cohorts. Various methods were used to

detect them, including mRNA and whole-exome sequencing, large-scale targeted NGS based on hybrid capture (including 4557 exons of 287 genes), and Sanger sequencing of *MET* regions known to harbor such alterations.14,15,28-30 These approaches are not suitable for molecular testing in routine practice, as they are expensive, time consuming, or require both large quantities of genomic DNA and in-depth bioinformatic analysis. Targeted NGS panels used in routine practice usually cover hotspots known to harbor genomic alterations. These panels, however, have not been specifically designed to cover intronic mutations such as *MET* exon 14 splice site mutations. It has recently been reported that none of the eight amplicon-based NGS panels commercially available is able to detect more than 63% of *MET* exon 14 mutations.31 For instance, the ability of the Colon&LungV2 panel to detect *MET* exon 14 splice site mutations has been estimated in silico at 24%. Accordingly, we found this panel to detect only 4 *MET* exon 14 splice site mutations among 1514 NSCLC patients. This is only 0.3%, far below the expected rate. In contrast, the optimized CLAPv1 panel detected *MET* exon 14 mutations (half point mutations and half deletions) in 2.2% of NSCLC patients. In addition, the CLAPv1 panel accurately covered most of the other targeted genes, yielding rates of EGFR, KRAS, BRAF, or ERBB2 mutations similar to those reported so far.40 As the CLAPv1 panel allows accurate identification of *MET* exon 14 mutated patients liable to benefit from MET TKI treatment, we provide the details of this panel in Supplementary Table 3.

Although amplicon-based NGS assays such as the CLAPv1 panel are suitable for routine molecular screening, some well-known intrinsic limitations remain.41 For instance, the usual bioinformatic workflows might fail to detect some deletions or insertions, or primers might fail to hybridize to the regions affected by such modifications. As approximately half of all *MET* exon 14 mutations are deletions or insertions, we have avoided this drawback by developing another molecular assay based on fragment length analysis. We show that two large deletions undetected by the CLAPv1 panel for lack of primer hybridization to the deleted sequence were successfully detected by fragment length analysis. Yet fragment length analysis also has potential drawbacks. First, its sensitivity is lower than that of amplicon-based NGS, as shown by the case of patient 21, whose deletion was detected with the CLAPv1 panel but not by fragment-length analysis. Second, fragment-length analysis does not provide the sequence of the mutant allele and has to be combined with sequencing of the amplified fragment. Another approach to detecting *MET* exon 14 alterations is mRNA analysis. We show here that melting curve analysis of fluorescent reverse transcriptase
(RT)-PCR products allows effective discrimination of mRNAs with and without *MET* exon 14 skipping. This method is sensitive, specific, and can be applied to FFPE samples where the RNA quality is not optimal, thanks to the small size of the amplicons. This method could thus be useful, for instance, in further characterizing *MET* genomic mutations not initially identified as splice site mutations. Indeed, it is accepted that mutations affecting splice sites lead to exon 14 skipping, but it could be difficult to predict effect of mutations located deeper in intron 13 or within exon 14. Exon 14 mutations are highly diverse and their effect on RNA is published only for a few of them.<sup>19,21,23</sup> Overall, we identified 30 NSCLC patients harboring *MET* exon 14 splice site mutations. In line with previous reports, this group of patients was characterized by an advanced age (median age, 73 years), a high proportion of women (57%), and a high proportion of never-smokers (47%).

*MET* exon 14 skipping leads to in-frame deletion of the juxtamembrane domain. This regulatory domain contains the phosphorylated tyrosine residue 1003 involved in recruiting the E3 ubiquitin ligase CBL.<sup>42</sup> Mutation of this residue prevents degradation of the receptor and causes its aberrant activation.<sup>43</sup> Juxta-membrane deletion has been proposed to cause similar effects.<sup>19</sup> Patients with *MET* exon 14 mutations might thus display increased *MET* expression. Here we found 64% of the patients displaying *MET* exon 14 splice site mutations to show high expression of *MET* (IHC 2+ and 3+), as compared to approximately 50% of unselected NSCLC patients.<sup>33</sup> Two patients, however, had tumors with *MET* exon 14 splice site mutations but no *MET* expression. Whether such patients can still benefit from *MET* TKI treatment must be investigated.

*MET* gene amplification is a rare event in NSCLC. It can be viewed as an oncogenic driver and has been associated with *MET* TKI efficacy.<sup>44</sup> In NSCLC patients harboring *MET* exon 14 splice site mutations, *MET* gene amplification appears more frequent (15% to 20% of tumor samples) than in other patients, but its impact on patient clinicopathologic characteristics and disease outcomes remains unclear.<sup>29</sup> FISH analysis of 25 tumor samples of our cohort showed the presence of increased GCN (due to gene amplification, chromosome 7 polysomy, or both) in several patients. In parallel, we set up a bioinformatic analysis to evaluate GCN on the basis of the CLAPv1 NGS data. This analysis confirmed the *MET* GCN increases observed by FISH and allowed, when FISH was not possible, identifying additional patients potentially harboring such alterations. Because NGS data analysis does not unambiguously identify gene amplification (which relies on observation of gene clustering or on calculating the ratio of the number of gene copies to the number of chromosome

centromeres) this method remains indicative and cannot substitute for FISH analysis. Constitution of a larger cohort of *MET* exon 14 splice site mutations might be needed to assess whether FISH and bio-informatic analysis of NGS data are in total agreement. Taken together, both our FISH analysis and our NGS data analysis revealed probable *MET* gene amplification and *MET* GCN increases in approximately 20% of tested patients, all of whom displayed *MET* overexpression as determined by IHC. Analysis of *MET* mutations and *MET* amplification raises the question of the mutant allele specific imbalance phenomenon which could have an impact on prognosis or response to treatment.<sup>45,46</sup> Based on analysis of mutant allele frequency, we observed mutant allele specific imbalance in four samples from our series. Further characterization of this phenomenon in *MET*-mutated samples is warranted.

In conclusion, optimized targeted NGS and fragment analysis allow better routine identification of NSCLC patients harboring *MET* exon 14 splice site mutations. This shows that these technologies can be rapidly adapted to the routine diagnosis of recently discovered molecular alterations.

## Acknowledgments

This work was supported by the CNRS, the Institut Pasteur de Lille, and INSERM, and by grants from the Cancéropôle Nord-Ouest, the Agence Nationale de la Recherche; Metropolis project, the Ligue Contre le Cancer, Comité Nord, the Institut National du Cancer, Ecole Doctorale Biologie Santé, and the Site de Recherche Intégrée sur le Cancer, SIRIC ONCOLille.

## Supplementary Data

Note: To access the supplementary material accompanying this article, visit the online version of the *Journal of Thoracic Oncology* at www.jto.org and at https://doi.org/10.1016/j.jtho.2018.08.2023.

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