De Novo Versus Secondary Metastatic EGFR-Mutated Non-Small-Cell Lung Cancer

Background: Metastatic epidermal growth factor receptor-mutated (EGFR⁺) non-small-cell lung cancer (NSCLC) can present de novo or following previous nonmetastatic disease (secondary). Potential differences between these two patient subsets are unclear at present.

Methods: We retrospectively analyzed characteristics of tyrosine kinase inhibitor (TKI)-treated patients with de novo vs. secondary metastatic EGFR⁺ NSCLC until December 2019 (n = 401).

Results: De novo metastatic disease was 4× more frequent than secondary (n = 83/401), but no significant differences were noted regarding age (median 66 vs. 70 years), sex (65% vs. 65% females), smoking history (67% vs. 62% never/light-smokers), and histology (both >95% adenocarcinoma). Patients with secondary metastatic disease showed a better ECOG performance status (PS 0–1 67%–32% vs. 46%–52%, p = 0.003), fewer metastatic sites (mean 1.3 vs. 2.0, p < 0.001), and less frequent brain involvement (16% vs. 28%, p = 0.022) at the time of stage IV diagnosis. Progression-free survival (PFS) under TKI (median 17 for secondary vs. 12 months for de novo, p = 0.26) and overall survival (OS, 29 vs. 25 months, respectively, p = 0.47) were comparable. EGFR alterations (55% vs. 60% exon 19 deletions), TP53 mutation rate at baseline (47% vs. 43%, n = 262), and T790M positivity at the time of TKI failure (51% vs. 56%, n = 193) were also similar. OS according to differing characteristics, e.g., presence or absence of brain metastases (19–20 or 30–31 months, respectively, p = 0.001), and ECOG PS 0 or 1 or 2 (32–34 or 20–23 or 5–7 months, respectively, p < 0.001), were almost identical for de novo and secondary metastatic disease.

Conclusions: Despite the survival advantage reported in the pre-TKI era for relapsed NSCLC, molecular features and outcome of TKI-treated metastatic EGFR⁺ tumors are currently independent of preceding nonmetastatic disease. This simplifies design of outcome studies and can assist prognostic considerations in everyday management of patients with secondary metastatic EGFR⁺ tumors.

Introduction

Epidermal growth factor receptor-mutated non-small-cell lung cancer (EGFR⁺ NSCLC) comprises about 10%–15% of lung adenocarcinomas (1). According to the current guidelines, the preferred therapy for metastatic disease are tyrosine kinase inhibitors (TKI), which have consistently shown superior efficacy and better tolerability than chemotherapy (2). In contrast, treatment of earlier-stage tumors relies on other modalities, such as surgery, radiotherapy, chemotherapy, and/or immunotherapy, the use of which does not depend on the results of molecular tumor work-up (2). Consequently, testing for EGFR mutations is currently standard practice only for stage IV or otherwise incurable NSCLC (3), which results in two distinct subpopulations of these patients: “de novo” cases that directly present with stage IV disease, and “secondary” metastatic EGFR⁺ NSCLC cases that are initially diagnosed with stage I-III disease and develop stage IV NSCLC through subsequent relapse or progression, upon which molecular analysis is performed and EGFR mutations are detected. From a practical standpoint, both patient subsets are currently being treated according to the same principles (2), but potential clinical and biologic differences remain unclear. In addition, several factors, such as the metastatic pattern, histological subtype, EGFR variant, presence of TP53 mutations, ECOG performance (PS) and smoking status have been shown to correlate with survival of stage IV EGFR⁺ lung cancer patients (4–9), but it is unknown whether the distribution and the prognostic importance of these parameters are similar between de novo and secondary metastatic cases. The current study was performed to address these topics and is presented in accordance with the STROBE reporting checklist.

Material and Methods

Patient Selection and Clinical Data

This retrospective study was approved by the ethics committee of Heidelberg University (S-145/2017) and included all 401 stage IV NSCLC patients with sensitizing mutations of EGFR exons 18–21 treated with TKI at the Thoraxklinik Heidelberg and its regional network hospitals (Löwenstein, Esslingen) between 2010 and 2019. Patients with EGFR exon 20 insertions (n = 39) were excluded, since they respond poorly to currently approved targeted compounds and are mainly managed with other treatments (10). Histological diagnosis of early, as well as histological diagnosis and molecular profiling of metastatic NSCLC were performed at the Institute of Pathology Heidelberg using next-generation sequencing (NGS) after September 2014 (n = 262), and Sanger sequencing previously, as described (1, 11, 12). For NGS, a semiconductor-based platform (ThermoFisher Scientific, Waltham, MA, USA) was used with a custom panel covering 38–42 genes considered relevant for lung cancer biology, which included all EGFR exons, TP53 exons 4–10, CDKN2A exons 1–2, PIK3CA exons 2, 5, 8 10, 14, 21, and CTTNB1 exon 3 (Table 1), as published (1). Clinical data were collected through a systematic review of patient records with a cut-off on December 31 2019. Overall survival (OS) was calculated from the start of systemic treatment for stage IV disease. Progression-free survival (PFS) was calculated from the first dose of TKI or chemotherapy administered for metastatic disease until radiologic disease progression or death, whichever occurred first. Cross-sectional imaging studies, i.e., chest and abdomen CT/brain MRI were routinely performed at baseline and every 6 to 12 weeks thereafter, or earlier in case of clinically suspected progression. The progression date was verified through review of radiologic images by the investigators without formal RECIST reassessment, since progression based on real-world data has been shown to correlate reasonably well with RECIST-defined progression in recent studies (13, 14). Patients initially diagnosed with early tumors that preceded development of secondary metastatic EGFR⁺ NSCLC, had undergone regular follow-up including imaging studies every 3 months during the first 2 years, every 6 months in years 3–5, and yearly thereafter as per our institutional standard, which was taken into account in the interpretation of results.

TABLE 1

Table 1 Patient characteristics.

Statistical Analysis

The effect of categorical and continuous parameters on survival was analyzed according to Kaplan-Meier with logrank tests and Cox regression analysis. Duration of follow-up was calculated using the reverse Kaplan-Meier method. Numerical data were compared among two groups with the Student’s t-test, while for categorical data the chi-square test was used. All statistical calculations were performed with SPSS version 24 (IBM, Armonk, NY, USA), while plots were generated with GraphPad Prism version 7 (La Jolla, CA, USA).

Results

Patient Baseline Characteristics

Among the entire population of 401 study patients, 318 were diagnosed with primary stage IV disease (79%, “de novo” stage IV EGFR⁺ NSCLC, Table 1), while 83 had initially presented with nonmetastatic disease, were treated as shown in Table 2, and developed stage IV EGFR⁺ NSCLC after subsequent tumor relapse or progression (21%, “secondary” stage IV). Demographics of both patient groups were very similar. The median age at diagnosis was 66 years [interquartile range (IQR) 18] for de novo, and 70 years (IQR 16) for secondary metastatic disease (Table 1). About two-thirds of the patients in each group were females (65% and 66%) and never/light-smokers (i.e., had tobacco exposure <10 pack-years, 67% and 62%, Table 1). The vast majority were diagnosed with adenocarcinoma (>95% in both groups, Table 1). EGFR variants showed similar distributions in the two groups (60% vs. 55% exon 19 deletions [del19], 28% vs. 30% L858R, and 12% vs. 14% rare mutations, Table 1). Within the subset of patients with available NGS profiling at baseline (262/401, i.e., patients tested after implementation of NGS in 2014, see Material and Methods), the two patient groups showed a similar frequency of co-mutations in TP53 (43% vs. 47%) and other genes included in our panel (39 vs. 40%, Table 1).

TABLE 2

Table 2 Treatment of nonmetastatic EGFR⁺ tumors preceding secondary stage IV disease.

One first difference was the higher total number of metastatic sites at the time of stage IV diagnosis in de novo compared to secondary cases (mean 2.0 vs. 1.3, p < 0.001, Figure 1A and Supplementary Table 1). Both intra- and extrathoracic metastases tended to be increased in de novo stage IV cases to a similar extent, with significant differences in the frequency of brain (28% vs. 16%, p = 0.022), bone (46% vs. 33%, p = 0.032) and adrenal lesions (13% vs. 5%, p = 0.038, Figure 1A and Supplementary Table 1). In addition, at the time of stage IV diagnosis, patients with de novo metastatic disease had a worse ECOG performance status (PS 0-1-2 rates 46%-52%-3% vs. 67%–32%, respectively, p = 0.003), i.e., presentation with initially nonmetastatic disease was linked to a better ECOG PS at the time of subsequent stage IV relapse compared to patients with de novo stage IV (Figure 1B and Table 1). Basic laboratory parameters, such as the blood neutrophil-to-lymphocyte ratio (NLR), blood hemoglobin, blood platelet counts, serum C-reactive protein (CRP), serum creatinine, and serum GPT were similar among the two groups, with the notable exception of serum lactate dehydrogenase (LDH), which was increased in patients with de novo compared to secondary metastatic disease (mean 295 vs. 228 U/l, p = 0.006, Figure 1C and Supplementary Table 2). Both the ECOG PS and the level of serum LDH were significantly associated with the number of metastatic sites at diagnosis of stage IV disease (Figure 1D).

FIGURE 1

Figure 1 Metastatic spread, ECOG performance status (PS), and basic laboratory values at diagnosis of de novo vs. secondary metastatic EGFR⁺ NSCLC. (A) The average number of metastatic sites (lung, pleura, brain, liver, bone, adrenals, other) and the percentage of cases with metastases for each localization in de novo vs. metastatic stage IV EGFR⁺ NSCLC. Statistical comparisons were performed with the Student’s t-test for numerical (left part), and with the chi-square test for categorical data (right part). Details are shown in Supplementary Table 1. (B) The distribution of ECOG PS among patients diagnosed with de novo vs. secondary stage IV EGFR⁺ NSCLC, compared with a chi-square test. Details are shown in Table 1. (C) Results of basic laboratory tests at diagnosis of de novo vs. secondary stage IV EGFR⁺ NSCLC, compared with the Student’s t-test. Boxes and error bars show mean values and standard errors. Details are given in Supplementary Table 2. (D) Relationship between serum LDH and the number of metastatic sites at diagnosis of stage IV EGFR⁺ NSCLC (p = 0.006 with the Student’s t-test). Boxes and error bars show mean values and standard errors. Details are given in Supplementary Table 2. Relationship between the ECOG PS and the number of metastatic sites at diagnosis of stage IV EGFR⁺ NSCLC (p = 0.028 with the Student’s t-test). Boxes and error bars show mean values and standard errors, respectively. Details are given in Table 1.

Patient Treatment and Survival

Treatment characteristics for the two groups of patients with metastatic EGFR⁺ NSCLC were very similar (Table 1). All cases received EGFR TKI, mostly first/second-generation compounds (87% vs. 89% for de novo vs. secondary), which were administered as the first palliative treatment line in over two-thirds of patients (73% and 86%, respectively). For patients with molecular reanalysis in a tissue or liquid rebiopsy at the time of TKI failure, rates of T790M positivity were also similar (56% vs. 51%, Table 1). Moreover, the frequencies of palliative radiotherapy (51% vs. 43%), platinum doublets (31% vs. 55%), or mono-chemotherapy (8% vs. 6%) did not show significant differences (Table 1).

Patient survival was also comparable for de novo vs. secondary metastatic cases: OS from the start of treatment for stage IV disease (25 vs. 29 months in median, p = 0.47), PFS for the first TKI treatment line (12 vs. 17 months in median, p = 0.26), and PFS for the first chemotherapy treatment line (6 vs. 4 months in median, p = 0.74) did not differ substantially between the two groups (Table 1). For the subset of patients with secondary tumors after surgery and adjuvant chemotherapy (n = 33), the molecular profile and survival were also comparable to these of patients with de novo stage IV tumors (Supplementary Table 3).

Influence of De Novo vs. Secondary Setting on the Impact of Prognostic Factors in Metastatic EGFR⁺ Non-Small-Cell Lung Cancer

The previous comparisons revealed two main differences in the basic clinical characteristics of patients with de novo vs. secondary metastatic EGFR⁺ NSCLC: frequency of brain and other extrathoracic metastases, as well as ECOG PS at diagnosis of stage IV disease (Table 1 and Supplementary Table 1). Since these factors have been reported to correlate with survival of stage IV EGFR⁺ NSCLC patients, we examined whether this association might be affected by the setting of metastatic disease, i.e., de novo vs. secondary. The presence of brain metastases was associated with almost identical OS regardless of whether the metastatic disease was de novo or secondary (31 or 30 months in median, respectively, for cases without brain metastases, and 20 or 19 months for cases with brain metastases, Figure 2A). A bivariable Cox regression was additionally performed in order to obtain a quantitative measure for the effect of brain involvement on OS (hazard ratio (HR) = 1.65, p = 0.001) relative to that of the metastatic disease setting (HR = 1.06, p = 0.75, Table 3). Likewise, OS was strongly associated with the presence of extrathoracic metastases (HR = 1.79 with p < 0.001, vs. HR = 1.09 with p = 0.62, Figure 2B and Table 3) and ECOG PS at the time of stage IV diagnosis (HR = 1.66 with p < 0.001 for PS 1, and HR = 4.65 with p < 0.001 for PS 2, vs. HR = 1.02 with p = 0.91, Figure 3 and Table 3) regardless of whether the metastatic disease was de novo or secondary.

FIGURE 2

Figure 2 Overall survival of TKI-treated EGFR⁺ NSCLC patients with de novo vs. secondary metastatic disease by the presence of brain and extrathoracic metastases. (A) Median overall survival (OS) from the diagnosis of metastatic disease for TKI-treated EGFR⁺ NSCLC was 30 months (standard error [SE] 2.5) for patients with secondary stage IV disease without brain metastases (BM, n = 70), 31 months (SE 3.3) for patients with de novo stage IV disease without BM (n = 229), 19 months (SE 5.0) for patients with secondary stage IV disease and BM (n = 13), and 20 months (SE 1.5) for patients with de novo stage IV disease and BM (n = 89, logrank p = 0.008). In a bivariable Cox regression, only presence of brain metastases at diagnosis of stage IV disease (hazard ratio [HR] = 1.65, p = 0.001), but not presence of de novo vs. secondary metastatic disease (HR 1.06, p = 0.75) was a significant predictor for OS in our entire cohort (n = 401). (B) Median OS from the diagnosis of metastatic disease for TKI-treated EGFR⁺ NSCLC was 43 months (SE 12) for patients with secondary stage IV disease without extrathoracic metastases (EM, n = 37), 35 months (SE 4.4) for patients with de novo stage IV disease without EM (n = 109), 22 months (SE 4) for patients with secondary stage IV disease and EM (n = 46), and 23 months (SE 1.5) for patients with de novo stage IV disease with EM (n = 89, logrank p < 0.001). In a bivariable Cox regression, only presence of extrathoracic metastases at diagnosis of stage IV disease (HR = 1.79, p < 0.001), but not presence of de novo vs. secondary metastatic disease (HR = 1.09, p = 0.62) was a significant predictor for OS in our entire cohort (n = 401).

TABLE 3

Table 3 Relative effect of the de novo vs. secondary setting, compared to the effect of metastatic pattern and ECOG performance status on overall survival of EGFR⁺ lung cancer patients.

FIGURE 3

Figure 3 Overall survival of TKI-treated EGFR⁺ NSCLC patients with de novo vs. secondary metastatic disease by the ECOG performance status. Median overall survival (OS) from the diagnosis of metastatic disease for TKI-treated EGFR⁺ NSCLC was 32 months (standard error [SE] 3.0) for patients with secondary stage IV disease and ECOG performance status 0 (PS 0, n = 53), and 34 months (SE 4.3) for patients with de novo stage IV disease and ECOG PS 0 (n = 135); 23 months (SE 7.2) for patients with secondary stage IV disease and ECOG PS 1 (n = 25), and 20 months (SE 1.5) for patients with de novo stage IV disease with EM (n = 154); 5 months for the single patient with secondary stage IV disease and ECOG PS 2 (n = 1), and 6.7 months (SE 2.4) for patients with de novo stage IV disease and ECOG PS 2 (n = 8, logrank p < 0.0001). In a bivariable Cox regression, only the ECOG PS at diagnosis of stage IV disease (HR = 1.66, p < 0.0001 for ECOG PS 1; HR = 4.65, p < 0.0001 for ECOG PS 2), but not presence of de novo vs. secondary metastatic disease (HR = 1.02, p = 0.91) was a significant predictor for OS in our entire cohort (n = 401).

Discussion

Metastatic EGFR⁺ NSCLC is a model disease for the efficacy of targeted therapies in thoracic oncology. Upfront administration of increasingly potent TKI, meanwhile spanning three generations, has considerably improved prognosis with the median overall survival currently approaching 3 years (5, 15–17). However, clinical courses of individual patients can vary widely in association with several clinical and pathological parameters (4–9). The present study analyzed the potential impact that a prior diagnosis with stage I-III disease might have on the clinical course of stage IV EGFR⁺ NSCLC patients.

A first important finding is that the setting of stage IV disease, de novo vs. secondary, itself is not associated with survival of EGFR⁺ NSCLC patients from the time of stage IV diagnosis: PFS under TKI or chemotherapy, and OS were similar among the two patient groups (Table 1). Furthermore, most other parameters known to be associated with OS of stage IV EGFR⁺ NSCLC, such as the histological subtype, type of EGFR mutation, TP53 status, presence of co-mutations, especially in TP53, frequency of T790M development (5–7, 9), were equally distributed among de novo and secondary cases (Table 1). Along the same lines, a previous study observed a similar distribution of EGFR mutations among early-stage and metastatic EGFR⁺ lung cancers (18), which is also consistent with the notion that EGFR alterations represent “early events” during lung carcinogenesis (19). Moreover, other investigators have noted that the tumor mutational burden of NSCLC does not change after relapse of resected early-stage disease (20), or after chemotherapy and radiotherapy (21). The only significant differences seen in our study were: i) the extent of metastatic spread, with more frequent involvement of brain and other extrathoracic sites, as well as higher serum LDH values among de novo vs. secondary cases (Figure 1, Supplementary Tables 1 and 2); and ii) the ECOG performance status, which was also worse among de novo cases (Table 1). Interestingly, even though both the metastatic pattern and ECOG PS have been described as predictors of survival in metastatic EGFR⁺ NSCLC (5, 9, 22), our results show clearly that their associations with OS are not affected by the de novo vs. secondary metastatic setting (Figures 2 and 3). Therefore, a first conclusion is that de novo and secondary metastatic cases can be considered together when analyzing the effect of all currently known prognostic factors in TKI-treated EGFR⁺ NSCLC.

A second important conclusion is that the “left-shift” toward more limited metastatic spread within stage IV, evident as fewer metastatic sites, lower serum LDH and a better ECOG PS for “secondary” compared to de novo cases (Figure 1D), does not have a significant impact on the outcome of TKI-treated EGFR⁺ NSCLC (Table 1). In keeping with this, an earlier study had found no relationship between initial tumor volume and OS of TKI-treated EGFR⁺ NSCLC patients (23). This contrasts the results of several previous investigations including all-comer and/or non-TKI-treated NSCLC cohorts [(24) and (25) both published in 2019, but analyzing patients diagnosed until 2012 and 2013, respectively; (26) analyzing EGFR⁺ patients diagnosed until 2011], which have observed a slight, but significant OS advantage in the “secondary” setting. In our cohort this advantage is absent, presumably neutralized by the much higher efficacy of TKI, which all our stage IV patients per inclusion criteria received, compared to the chemotherapy-only treatment in the aforementioned previous studies. Thus, our findings aid correct interpretation of the published literature by extending and updating older results in the context of contemporary treatment for EGFR⁺ lung cancer.

The similar benefit (PFS) from TKI and chemotherapy, the comparable OS, and the absence of other clinical, laboratory or molecular disparities between secondary and de novo metastatic EGFR⁺ NSCLC (Table 1) argue against true biologic differences among them. Instead, the observed lower tumor burden of secondary cases (Figure 1) is probably simply due to an earlier diagnosis, because patients treated for early-stage disease undergo regular imaging follow-up, which can detect subsequent relapse or progression even if asymptomatic. Along the same lines, a more limited metastatic spread with less extrapulmonary metastatic sites, as well as a better ECOG PS for secondary (relapsed) vs. de novo metastatic tumors have also been noted by other investigators, who analyzed unselected NSCLC patients regardless of EGFR mutation status (24, 25). One limitation of our study is the lack of detailed data about patient symptoms at the time of diagnosis. However, the better ECOG PS of secondary metastatic cases at baseline (Figure 1 and Table 1) suggests that secondary tumors were indeed detected despite being less symptomatic than their de novo counterparts. Of note, the ratio of secondary to de novo metastatic EGFR⁺ NSCLC, approximately 1:4 in our study (Table 1), itself is not a purely biological characteristic either, but also influenced by the efficacy of lung cancer detection strategies. For example, the upcoming implementation of volume CT-based lung cancer screening according to the NELSON findings, is expected to increase this ratio, since many tumors previously detected as de novo metastatic NSCLC will then be diagnosed already in earlier stages, and also proportionally contribute more to the pool of “secondary” stage IV after relapse (27). Nevertheless, according to the results of the current study, across the entire population of patients ultimately developing stage IV EGFR⁺ NSCLC, the prognosis is not expected to change significantly.

The apparent lack of a specific biologic basis for the higher metastatic burden of de novo vs. secondary metastatic EGFR⁺ NSCLC contrasts a similar constellation in the closely related ALK⁺ NSCLC: here, an increased number of metastatic sites at initial diagnosis is also associated with a worse baseline ECOG PS (28), but linked to the special biologic properties of EML4-ALK variant 3 (V3) that enhance cancer dissemination (28–31). Consequently, several well-controlled retrospective analyses (32–35) and the prospective phase 3 clinical trial ALTA-1L (36) have demonstrated a more aggressive clinical course and shorter survival for EML4-ALK V3⁺ patients, while metastatic EGFR⁺ NSCLC appears to be prognostically homogenous regardless of the metastatic disparities between the de novo and secondary setting. At the same time, this similarity of secondary cases to their de novo counterparts, suggests that paired analysis of secondary stage IV tumors comparative to their earlier stage ancestors represents a promising approach to decipher the molecular pathogenesis of metastatic EGFR⁺ lung cancer in general. The particular molecular features of early EGFR⁺ lung cancers and their potential impact on TKI efficacy now acquire direct clinical relevance due to the recent promising results of the ADAURA study, which might lead to routine adjuvant administration of osimertinib in the near future (37).

From a practical standpoint, an important consequence of the results presented in this study is that patients with de novo and secondary TKI-treated metastatic EGFR⁺ NSCLC can be safely considered together in various analyses, in contrast to concerns regarding non-TKI-treated NSCLC based on earlier investigations (24–26). For example, one potential application is the development of risk stratification schemes for EGFR⁺ NSCLC, for which the data of both patient subsets could be merged together in order to derive an algorithm that will then be equally applicable to both. A second relevant issue are decisions about patient stratification in clinical trials: for example, when faced with the dilemma of whether to stratify newly diagnosed stage IV EGFR⁺ NSCLC patients according to the presence or absence of prior early-stage disease, or according to their current brain or ECOG PS status, our results show that stratification according to the baseline characteristics of the current stage IV disease is more important, and actually sufficient (Figures 2 and 3, Table 3). Main limitation of our work is its retrospective character, which cannot guarantee the absence of potential confounders. However, the relatively large size, homogeneity and typical characteristics of our cohort, the simple study design, the long follow-up, and the clear results add to the quality of the evidence presented by this study and suggest generalizability.

In summary, the present study shows that clinical and molecular features of metastatic EGFR⁺ NSCLC are largely independent of preceding nonmetastatic disease. This insight aids interpretation of older findings by updating them in the contemporary therapeutic context, simplifies the design of prospective or retrospective outcome studies, and can support prognostic considerations in everyday management of patients with secondary metastatic disease.

Data Availability Statement

The datasets generated and analyzed in this study are available from the corresponding author upon reasonable request.

Ethics Statement

This study was reviewed and approved by the ethics committee of the Heidelberg University (approval S-145/2017). Since this was a non-interventional, retrospective study, informed consent was obtained whenever possible, but its need for every participant was waived by the ethics committee.

Author Contributions

FB and PC conceptualized and designed the study. IC, AS, MT, and PC provided administrative support. FB, NM, LK, JF, MF, MT, and PC provided the study materials or patients. FB, DK, IC, MKi, NM, MKr, MA, TM, RE, JF, MF, MT, and PC collected and assembled the data. FB, DK, AS, MT, and PC analyzed and interpreted the data. All authors contributed to the article and approved the submitted version.

Funding

This study was supported by the German Center for Lung Research (DZL). The funding source did not have any influence on the design, conduction, and report of the results for this study.

Conflict of Interest

FB reports honoraria from Novartis, MSD, ChugaiPharma, Roche, AstraZeneca and research grants from AstraZeneca, BMS, and Roche. DK reports personal fees from AstraZeneca, personal fees from Bristol-Myers Squibb GmbH, and personal fees from Pfizer Pharma GmbH. TM reports research funding from Roche and patents with Roche. JF reports advisory board honoraria from Boehringer, Roche, Celgene, and AstraZeneca. AS reports advisory board honoraria and/or speaker fees: Astra Zeneca, Bayer, Eli Lilly, Roche, BMS, Illumina, MSD, Novartis, Pfizer, Seattle Genetics, Takeda, Thermo Fisher, and research grants from BMS, Bayer, and Chugai. MT reports advisory board honoraria from Novartis, Lilly, BMS, MSD, Roche, Celgene, Takeda, AbbVie, Boehringer, speaker’s honoraria from Lilly, MSD, Takeda, research funding from AstraZeneca, BMS, Celgene, Novartis, Roche, and travel grants from BMS, MSD, Novartis, Boehringer. PC reports lecture/advisory board fees from AstraZeneca, Boehringer, Chugai, Novartis, Pfizer, Roche, and Takeda, as well as research funding from AstraZeneca, Novartis, Roche, and Takeda.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank Petra Kettenring of the Clinical Trial Unit, Thoracic Oncology, Thoraxklinik Heidelberg, for assistance with the collection of patient data.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2021.640048/full#supplementary-material

References

1. Volckmar AL, Leichsenring J, Kirchner M, Christopoulos P, Neumann O, Budczies J, et al. Combined targeted DNA and RNA sequencing of advanced NSCLC in routine molecular diagnostics: Analysis of the first 3,000 Heidelberg cases. Int J Cancer (2019) 145:649–61. doi: 10.1002/ijc.32133

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Planchard D, Popat S, Kerr K, Novello S, Smit EF, Faivre-Finn C, et al. Metastatic non-small cell lung cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol (2019) 30:863–70. doi: 10.1093/annonc/mdy474

PubMed Abstract | CrossRef Full Text | Google Scholar

3. Kalemkerian GP, Narula N, Kennedy EB, Biermann WA, Donington J, Leighl NB, et al. Molecular Testing Guideline for the Selection of Patients With Lung Cancer for Treatment With Targeted Tyrosine Kinase Inhibitors: American Society of Clinical Oncology Endorsement of the College of American Pathologists/International Association for the Study of Lung Cancer/Association for Molecular Pathology Clinical Practice Guideline Update. J Clin Oncol (2018) 36:911–9. doi: 10.1200/jco.2017.76.7293

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Aggarwal C, Davis CW, Mick R, Thompson JC, Ahmed S, Jeffries S, et al. Influence of TP53 Mutation on Survival in Patients With Advanced EGFR-Mutant Non-Small-Cell Lung Cancer. JCO Precis Oncol (2018) 2018 2:1–29. doi: 10.1200/PO.18.00107

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Lin JJ, Cardarella S, Lydon CA, Dahlberg SE, Jackman DM, Janne PA, et al. Five-Year Survival in EGFR-Mutant Metastatic Lung Adenocarcinoma Treated with EGFR-TKIs. J Thorac Oncol (2016) 11:556–65. doi: 10.1016/j.jtho.2015.12.103

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Canale M, Petracci E, Delmonte A, Chiadini E, Dazzi C, Papi M, et al. Impact of TP53 Mutations on Outcome in EGFR-Mutated Patients Treated with First-Line Tyrosine Kinase Inhibitors. Clin Cancer Res (2017) 23:2195–202. doi: 10.1158/1078-0432.CCR-16-0966

PubMed Abstract | CrossRef Full Text | Google Scholar

7. Joshi A, Zanwar S, Noronha V, Patil VM, Chougule A, Kumar R, et al. EGFR mutation in squamous cell carcinoma of the lung: does it carry the same connotation as in adenocarcinomas? Onco Targets Ther (2017) 10:1859–63. doi: 10.2147/OTT.S125397

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Yu HA, Suzawa K, Jordan E, Zehir A, Ni A, Kim R, et al. Concurrent Alterations in EGFR-Mutant Lung Cancers Associated with Resistance to EGFR Kinase Inhibitors and Characterization of MTOR as a Mediator of Resistance. Clin Cancer Res (2018) 24:3108–18. doi: 10.1158/1078-0432.CCR-17-2961

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Christopoulos P, Kirchner M, Roeper J, Saalfeld F, Janning M, Bozorgmehr F, et al. Risk stratification of EGFR+ lung cancer diagnosed with panel-based next-generation sequencing. Lung Cancer (2020) 148:105–12. doi: 10.1016/j.lungcan.2020.08.007

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Vyse S, Huang PH. Targeting EGFR exon 20 insertion mutations in non-small cell lung cancer. Signal Transduct Target Ther (2019) 4:5. doi: 10.1038/s41392-019-0038-9

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Penzel R, Sers C, Chen Y, Lehmann-Muhlenhoff U, Merkelbach-Bruse S, Jung A, et al. EGFR mutation detection in NSCLC–assessment of diagnostic application and recommendations of the German Panel for Mutation Testing in NSCLC. Virchows Arch (2011) 458:95–8. doi: 10.1007/s00428-010-1000-y

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Warth A, Penzel R, Lindenmaier H, Brandt R, Stenzinger A, Herpel E, et al. EGFR, KRAS, BRAF and ALK gene alterations in lung adenocarcinomas: patient outcome, interplay with morphology and immunophenotype. Eur Respir J (2014) 43:872–83. doi: 10.1183/09031936.00018013

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Bartlett CH, Mardekian J, Cotter M, Huang X, Zhang Z, Parrinello CM, et al. Concordance of real world progression free survival (PFS) on endocrine therapy as first line treatment for metastatic breast cancer using electronic health record with proper quality control versus conventional PFS from a phase 3 trial. Cancer Res (2018) 78:P3–17-03. doi: 10.1158/1538-7445.Sabcs17-p3-17-03

CrossRef Full Text | Google Scholar

14. Ma X, Nussbaum NC, Magee K, Bourla AB, Tucker M, Bellomo L, et al. Comparison of real-world response rate (rwRR) to RECIST-based response rate in patients with advanced non-small cell lung cancer (aNSCLC). Ann Oncol (2019) 30:1581P. doi: 10.1093/annonc/mdz260.103

CrossRef Full Text | Google Scholar

15. Wu YL, Cheng Y, Zhou X, Lee KH, Nakagawa K, Niho S, et al. Dacomitinib versus gefitinib as first-line treatment for patients with EGFR-mutation-positive non-small-cell lung cancer (ARCHER 1050): a randomised, open-label, phase 3 trial. Lancet Oncol (2017) 18:1454–66. doi: 10.1016/S1470-2045(17)30608-3

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Soria JC, Ohe Y, Vansteenkiste J, Reungwetwattana T, Chewaskulyong B, Lee KH, et al. Osimertinib in Untreated EGFR-Mutated Advanced Non-Small-Cell Lung Cancer. N Engl J Med (2018) 378:113–25. doi: 10.1056/NEJMoa1713137

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Park K, Tan E-H, O’Byrne K, Zhang L, Boyer M, Mok T, et al. Afatinib versus gefitinib as first-line treatment of patients with EGFR mutation-positive non-small-cell lung cancer (LUX-Lung 7): a phase 2B, open-label, randomised controlled trial. Lancet Oncol (2016) 17:577–89. doi: 10.1016/S1470-2045(16)30033-X

PubMed Abstract | CrossRef Full Text | Google Scholar

18. Pi C, Xu C-R, Zhang M-F, Peng X-X, Wei X-W, Gao X, et al. EGFR mutations in early-stage and advanced-stage lung adenocarcinoma: Analysis based on large-scale data from China. Thorac Cancer (2018) 9:814–9. doi: 10.1111/1759-7714.12651

PubMed Abstract | CrossRef Full Text | Google Scholar

19. McGranahan N, Swanton C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell (2015) 27:15–26. doi: 10.1016/j.ccell.2014.12.001

PubMed Abstract | CrossRef Full Text | Google Scholar

20. Kazdal D, Endris V, Allgäuer M, Kriegsmann M, Leichsenring J, Volckmar A-L, et al. Spatial and Temporal Heterogeneity of Panel-Based Tumor Mutational Burden in Pulmonary Adenocarcinoma: Separating Biology From Technical Artifacts. J Thor Oncol (2019) 14:1935–47. doi: 10.1016/j.jtho.2019.07.006

CrossRef Full Text | Google Scholar

21. Jonna S, Vanderwalde AM, Nieva JJ, Poorman KA, Saul M, von Buttlar X, et al. Impact of prior chemotherapy or radiation therapy on tumor mutation burden in NSCLC. J Clin Oncol (2019) 37:2627. doi: 10.1200/JCO.2019.37.15_suppl.2627

CrossRef Full Text | Google Scholar

22. Lin J-H, Lin D, Xu L, Wang Q, Hu H-H, Xu H-P, et al. The association between clinical prognostic factors and epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) efficacy in advanced non-small-cell lung cancer patients: a retrospective assessment of 94 cases with EGFR mutations. Oncotarget (2017) 8:3412–21. doi: 10.18632/oncotarget.13787

PubMed Abstract | CrossRef Full Text | Google Scholar

23. Leduc C, Moussa N, Faivre L, Caramella C, Soria J-C, Besse B. Impact of tumor burden on tyrosine kinase inhibitors (TKI) efficacy in advanced non-small cell lung cancer (NSCLC) patients with EGFR-sensitizing mutations (EGFRm) and ALK rearrangement (ALK+). J Clin Oncol (2014) 32:e19021–1. doi: 10.1200/jco.2014.32.15_suppl.e19021

CrossRef Full Text | Google Scholar

24. Moore S, Leung B, Wu J, Ho C. Survival Implications of De Novo Versus Recurrent Metastatic Non-Small Cell Lung Cancer. Am J Clin Oncol (2019) 42:292–7. doi: 10.1097/COC.0000000000000513

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Gibson AJ, Li H, D’Silva A, Tudor RA, Elegbede AA, Otsuka S, et al. Comparison of Clinical Characteristics and Outcomes in Relapsed Versus De Novo Metastatic Non-Small Cell Lung Cancer. Am J Clin Onc (2019) 42:75–81. doi: 10.1097/COC.0000000000000483

CrossRef Full Text | Google Scholar

26. Yu HA, Sima CS, Hellmann MD, Naidoo J, Busby N, Rodriguez K, et al. Differences in the survival of patients with recurrent versus de novo metastatic KRAS-mutant and EGFR-mutant lung adenocarcinomas. Cancer (2015) 121:2078–82. doi: 10.1002/cncr.29313

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Koning HJ de, van der Aalst CM, Jong PA de, Scholten ET, Nackaerts K, Heuvelmans MA, et al. Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial. N Engl J Med (2020) 382:503–13. doi: 10.1056/NEJMoa1911793

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Christopoulos P, Budczies J, Kirchner M, Dietz S, Sultmann H, Thomas M, et al. Defining molecular risk in ALK(+) NSCLC. Oncotarget (2019) 10:3093–103. doi: 10.18632/oncotarget.26886

PubMed Abstract | CrossRef Full Text | Google Scholar

29. O’Regan L, Barone G, Adib R, Woo CG, Jeong HJ, Richardson EL, et al. EML4-ALK V3 oncogenic fusion proteins promote microtubule stabilization and accelerated migration through NEK9 and NEK7. J Cell Sci (2020) 133:jcs241505. doi: 10.1242/jcs.241505

PubMed Abstract | CrossRef Full Text | Google Scholar

30. Noh KW, Lee MS, Lee SE, Song JY, Shin HT, Kim YJ, et al. Molecular breakdown: a comprehensive view of anaplastic lymphoma kinase (ALK)-rearranged non-small cell lung cancer. J Pathol (2017) 243:307–19. doi: 10.1002/path.4950

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Christopoulos P, Kirchner M, Bozorgmehr F, Endris V, Elsayed M, Budczies J, et al. Identification of a highly lethal V3⁺TP53⁺ subset in ALK⁺ lung adenocarcinoma. Int J Cancer (2019) 144:190–9. doi: 10.1002/ijc.31893

PubMed Abstract | CrossRef Full Text | Google Scholar

32. Woo CG, Seo S, Kim SW, Jang SJ, Park KS, Song JY, et al. Differential protein stability and clinical responses of EML4-ALK fusion variants to various ALK inhibitors in advanced ALK-rearranged non-small cell lung cancer. Ann Oncol (2017) 28:791–7. doi: 10.1093/annonc/mdw693

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Christopoulos P, Endris V, Bozorgmehr F, Elsayed M, Kirchner M, Ristau J, et al. EML4-ALK fusion variant V3 is a high-risk feature conferring accelerated metastatic spread, early treatment failure and worse overall survival in ALK⁺ non-small cell lung cancer. Int J Cancer (2018) 142:2589–98. doi: 10.1002/ijc.31275

PubMed Abstract | CrossRef Full Text | Google Scholar

34. Chang G-C, Yang T-Y, Chen K-C, Hsu K-H, Huang Y-H, Su K-Y, et al. ALK variants, PD-L1 expression, and their association with outcomes in ALK-positive NSCLC patients. Sci Rep (2020) 10:21063. doi: 10.1038/s41598-020-78152-1

PubMed Abstract | CrossRef Full Text | Google Scholar

35. Yang C-Y, Liao W-Y, Ho C-C, Chen K-Y, Tsai T-H, Hsu C-L, et al. Association of Programmed Death-Ligand 1 Expression with Fusion Variants and Clinical Outcomes in Patients with Anaplastic Lymphoma Kinase-Positive Lung Adenocarcinoma Receiving Crizotinib. Oncologist (2020) 25:702–11. doi: 10.1634/theoncologist.2020-0088

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Camidge DR, Niu H, Kim HR, Yang JC-H, Ahn M-J, Li JY-C, et al. Correlation of baseline molecular and clinical variables with ALK inhibitor efficacy in ALTA-1L. J Clin Oncol (2020) 38:9517. doi: 10.1200/JCO.2020.38.15_suppl.9517

CrossRef Full Text | Google Scholar

37. Wu Y-L, Tsuboi M, He J, John T, Grohe C, Majem M, et al. Osimertinib in Resected EGFR -Mutated Non–Small-Cell Lung Cancer. N Engl J Med (2020) 383:1711–23. doi: 10.1056/NEJMoa2027071

PubMed Abstract | CrossRef Full Text | Google Scholar