Detection of epidermal growth factor receptor (EGFR) mutations from preoperative circulating tumor DNA (ctDNA) as a prognostic predictor for stage I–III non-small cell lung cancer (NSCLC) patients with baseline tissue EGFR mutations

Introduction

Lung cancer is the most commonly diagnosed cancer and leading cause of death globally (1). Non-small cell lung cancer (NSCLC) accounts for approximately 85–90% of lung cancer cases (2). Although the conventional therapeutic strategies including surgical resection, chemotherapy, and radiotherapy contribute to clinical benefits for NSCLC patients, the 5-year survival rate is still unsatisfactory. This poor prognosis is partly due to the insidious onset and easy metastasis of the disease, with more than half of all cases being diagnosed at advanced stages (3). Therefore, to improve long-term survival, it is essential to perform imaging techniques for screening of NSCLC at early stages and to develop more sensitive approaches of early metastasis detection.

Epidermal growth factor receptor (EGFR) mutations occur in 10–30% of NSCLC patients. Previous clinical trials have confirmed that advanced-stage NSCLC patients with EGFR mutations have better progression-free survival (PFS) and overall survival (OS) after tyrosine kinase inhibitor (TKI) therapy compared with chemotherapy (4-9).Thus, EGFR mutation detection may be a crucial part in the therapeutic decision of administering TKI drugs. At present, tissue biopsy is the primary means to obtaining the genetic information of NSCLC patients. However, its invasive nature and difficulty in acquiring tissue hamper the frequent sampling, which is needed for dynamic monitoring of EGFR mutations and treatment response. Moreover, local tumor sampling may not only cause inevitable bias because of heterogeneous characteristics of NSCLC but also fail to detect potential micrometastases in the early stages (10,11). On the other hand, liquid biopsy, as a noninvasive and easily repeated modality, is increasingly becoming an alternative approach to tissue-based EGFR detection. This has facilitated comprehensive monitoring of the real-time dynamics and of tumors genetic information via circulating biomarkers, such as circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs).

It is currently believed that the DNA fragments derived from passive release by apoptosis and necrosis and active release of tumor cells are essential component of plasma ctDNA, which makes it a promising biomarker in solid tumors (12-15). In addition, a series of previous studies have also demonstrated the feasibility and reliability of ctDNA EGFR mutation detection. Using denaturing high-performance liquid chromatography (DHPLC), Bai et al. reported the consistency, sensitivity, and specificity of plasma EGFR detection to be 87%, 82%, 90% respectively in stage IIIB–IV NSCLC patients (16). In contrast, another study reported a consistency, sensitivity and, specificity of 58%, 66%, 63% of direct sequencing (17). Kim et al. applied peptide nucleic acid (PNA)-mediated polymerase chain reaction (PCR) clamping to detect plasma EGFR mutations, which yielded a sensitivity of only 17.1% (18). The significant discrepancies between these studies can be explained by the variability in detection techniques used. Scorpion amplification refractory mutation system (Scorpion-ARMS) is the most widely accepted and commonly used method in the identification of known EGFR mutations. The results of the IPASS study, as reported by Goto et al., showed a sensitivity of 43.1% and a specificity of 100%, which is basically consistent with our previous results (19,20). Another first-line, single-arm study of gefitinib using the Scorpion-ARMS method yielded a consistency of 94.3%, a sensitivity of 65.7%, and a specificity of 99.8% (21). The relatively higher sensitivity and lower false-positive rate make Scorpion-ARMS a reliable and efficient approach for clinical plasma-based EGFR mutation detection.

Because of the potential value to the accurate timing of therapeutic interventions and treatment efficacy assessment, research into the correlation between blood biopsy and NSCLC prognosis has intensified in recent years. Sawabata et al. suggested that CTCs, detected from blood samples immediately after NSCLC surgery may be a predictor of tumor recurrence. For instance, the 2-year recurrence-free survival (RFS) rates of CTC-negative patients were found to be significantly higher than those of patients with single CTC or cluster CTCs (22). In an analysis of the dynamic changes of postoperative ctDNA, Chen et al. reported that patients being ctDNA positive on the third day after lung cancer surgery was predictive of poor PFS (23). Using the cobas blood test, the FASTACT-2 study detected the circulating cell-free DNA (cfDNA) at baseline, cycle 3, and progression, respectively. No significant difference in PFS was observed between baseline EGFR mutation-positive (mut⁺) cfDNA and EGFR mutation-negative (mut⁻) cfDNA (6.2 versus 6.1 months) (24). However, few studies have addressed the predictive value of preoperative ctDNA EGFR mutations for NSCLC prognosis. Hence, further studies are necessary to clarify this uncertainty.

In this single-center, prospective study, blood-based EGFR mutations of stage I–III NSCLC patients who had tissue EGFR mutations were investigated. Through analyzing at least 5 years of follow-up data, we demonstrated, for the first time, that the preoperative plasma EGFR mutation status can be a significant prognostic biomarker for both early and locally advanced stage NSCLC patients. For stage III NSCLC patients with tissue and plasma EGFR mutations, adjuvant TKI therapy may potentially be more effective than chemotherapy. All these results may offer new insights into the prognostic significance of preoperative plasma-based EGFR testing and provide an innovative strategy for future clinical practice. We present the following article in accordance with the STROBE reporting checklist (available at https://dx.doi.org/10.21037/tlcr-21-530).

Methods

Study design and patient population

In the present study of a real-life clinical setting, the primary objective was to determine the correlation between preoperative plasma EGFR mutations and long-term prognosis or tumor metastasis in the stage I–III NSCLC patients confirmed with tumor EGFR mutations. We also preliminarily investigated the impacts of adjuvant treatment on OS and DFS in stage III patients. Thus, this study represents the first of its kind to examine the prognostic predictive values of preoperative plasma-based EGFR detection.

The patients who had not received any preoperative treatment and who had been pathologically diagnosed as stage I–III NSCLC were deemed eligible for this study. The staging system used was the American Joint Committee on Cancer (AJCC) 7th edition. All patients had undergone standard pulmonary lobectomy and lymph node dissection at the Department of Thoracic Surgery of Tangdu Hospital of the Air Force Medical University (Xi’an, China) between February 2014 and June 2015. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethics Committee of the Air Force Medical University (TDLL-KY-202106-09). Written informed consents, which included agreement to use personal clinical data and the collection of tissue and plasma samples, were signed by all patients before any study-related procedures began. Experimental data were collected and recorded independently by investigators blinded to clinical data until analyses were completed by statisticians.

Sample collection

One day before operation, blood samples of patients were collected into 10 ml EDTA-containing tubes and then centrifuged at 4 °C and 1500 rpm for 15 minutes within 4 hours. The supernatants were transferred to 1.5 mL RNase-free tubes and stored at –80 °C until further use in subsequent experiments. All tissue samples were acquired through surgical resections and underwent pathological diagnosis by professional pathologists to confirm histological differentiations and pathological stages. Tumor specimens were excised and transferred to a −80 °C refrigerator within half an hour after NSCLC resection.

EGFR mutation analysis in tissue and plasma samples

EGFR mutation detection in tissue samples were subsequently performed using real-time PCR in our laboratory. For those patients with tissue EGFR mutations, their paired preoperative plasma samples were selected, and the presence of EGFR mutations was confirmed. ctDNA extraction and real-time PCR analysis for EGFR mutations were performed as described in our previous study (20). During method implementation, the procedures were strictly followed by manufacturer’s protocol (Amoy Diagnostics Corporation, Xiamen, China). The real-time PCR data of tissue and plasma EGFR detections were analyzed by 2 professional research fellows. In the event of any discrepancies, a third fellow would be present to conduct discussion until consensus was achieved. To be identified as EGFR-positive, at least 1 mutation, such as exon 19 deletion (19del), L858R, G719X, 20Ins, or L861Q, needed to be detected in a sample.

Postoperative follow-up

After primary tumor resection, all patients were followed up every 2–3 months for the first 2 years and every 3–6 monthsthereafter via telephone interviews and clinic visits by specially trained personnel. All patients were required to be followed up for at least 5 years until the occurrence of cancer-related death, tumor metastasis, or the last follow-up.The main endpoint in the study was OS. The clinical and histopathological data of all patients, including sex, age, smoking history, date of surgery, tumor size, local invasion, tumor differentiation, and tumor-node-metastasis (TNM) stages, and postoperative protocol, were extracted from their electronic medical records. The contents of the follow-up mainly contained the patients’ basic clinic features and other information including laboratory tests, regular imaging tests.

Statistical analysis

SPSS 23.0 software (IBM Corp., NY, Armonk, USA) was used to analyze the data. χ²-test and Fisher’s exact test were used to assess the relationship between EGFR mutation status and clinicopathologic parameters. The OS and DFS rates were analyzed using Kaplan-Meier method and log-rank test. The univariate or multivariate analysis was performed using the Cox proportional hazards model. Statistical significance was set at a P value <0.05.

Results

The correlation between baseline characteristics and plasma EGFR mutation

Previously, we reported the plasma-based EGFR detection in stage I–IV NSCLC patients (20). In the current study, 186 stage I–III NSCLC patients were re-enrolled. They had all been initially diagnosed with EGFR mut⁺ as assessed by surgically resected NSCLC specimens. Their matched preoperative plasma samples were subsequently investigated, and regular follow-up ensued. Of these patients, 12 (6.5%) were lost to follow-up, while 174 (93.5%) completed at least 5 years of follow-up evaluation and were ultimately included in the analysis. The baseline clinical characteristics stratified by plasma EGFR mutation status are summarized in Table 1.

Table 1 The baseline clinical characteristics stratified by ctDNA mutation status
Full table

Of the final enrolled patients, 78 (44.8%) were older than 60 years, 58.0% were females, and 75.3% had never smoked. In addition, 117 patients (67.2%) were identified as stage I to II, with adenocarcinoma and high/moderate tumor differentiation accounting for 92.5% and 82.8% of the patients, respectively. Moreover, a positive plasma EGFR mutation was observed in 27 patients (15.5%), and their mutation types were fully concordant with the results detected through tissues samples. Specifically, 19del (21/27, 77.8%) and exon 21 L858R point mutation (L858R) (4/27, 14.8%) were the predominant plasma mutation types. The other 2 mutations were rare types, and included 1 case each of L861Q mutation and exon 20 insertion. Further analysis suggested that the plasma-based EGFR-positive rate was closely associated with N stages, TNM stages, and tumor differentiation. The patients with N1–N3, stage III, or poor differentiation had a higher plasma-positive rate (P<0.001).

The predictive power of preoperative plasma EGFR mutations to OS and DFS of NSCLC patients

Initially, our evaluation of the 2-year follow-up data indicated discrepancies in OS and DFS were present between plasma ctDNA EGFR mut⁺ and mut⁻ subgroups, which spurred our interest in examining the predictive power of preoperative plasma EGFR detection for NSCLC patients.

The analysis of our complete 5-year follow-up data showed that the ctDNA EGFR mut⁺ NSCLC patients had a median OS of 29.00±2.55 months; meanwhile, in ctDNA EGFR mut⁻ patients, the median OS time was not reached within the follow-up period [hazard ratio (HR) 5.552, 95% CI, 3.284–9.387, P=0.000]. Moreover, the OS was also significantly associated with tumor invasion, lymph node metastasis, TNM stage, and tumor differentiation (P<0.05). The NSCLC patients with T3–T4, N1–N3, stage III, or poor differentiation had significantly shorter OS. In addition, the results of multivariate Cox proportional hazards analysis suggested that both ctDNA EGFR mutation and TNM stages were independent prognostic risk factors for OS of NSCLC patients (HR, 3.289, 95% CI, 1.816–5.956, P=0.000; HR, 3.433, 95% CI, 1.997–5.900, P=0.000; Table 2).

Table 2 Univariate analysis of the correlation between clinicopathological variables and overall survival of NSCLC patients
Full table

The Kaplan-Meier curve indicated that ctDNA EGFR mut⁺ patients suffered poorer OS (P<0.001; Figure 1A). A stratified analysis was further implemented to explore the prognostic impact of ctDNA EGFR status for early and locally advanced stage NSCLC patients. As shown in Figure 1B, both ctDNA EGFR mut⁻ subgroups also had comparatively better prognosis (P<0.01). In stage I–II, the median OS of the ctDNA EGFR mut⁻ subgroup was not reached, while the median OS of the ctDNA EGFR mut⁺ subgroup was 40.00±14.40 months. The median OS of the corresponding stage III subgroups was 63.00±12.01 and 25.00±4.47 months, respectively. From this it is clear that ctDNA EGFR detection might be a significant predictive factor for OS of NSCLC patients.

Figure 1 The predictive power of preoperative plasma EGFR mutations to NSCLC patients. (A,B) OS of all enrolled patients (A) and stage I–II or III patients (B) stratified by preoperative ctDNA EGFR mutation status. (C,D) DFS of all enrolled patients (C) and stage I–II or III patients (D) stratified by preoperative ctDNA EGFR mutation status. OS, overall survival; DFS, disease-free survival; ctDNA, circulating tumor DNA; EGFR, epidermal growth factor receptor; NSCLC, non-small cell lung cancer.

Tumor metastasis is one of crucial factor affecting postoperative survival of NSCLC patients. Thus, the DFS data were collected and analyzed to further unveil the potential links between clinicopathological variables and NSCLC postoperative metastasis risks. Interestingly, similar findings were observed in the DFS-related analyses. The univariate analysis demonstrated that the DFS of NSCLC patients was closely associated with ctDNA EGFR mutation, TNM stage, lymph node metastasis, and tumor differentiation (P<0.005). The further multivariate analysis showed that ctDNA EGFR mutation and TNM stage were also the independent risk factors affecting DFS (HR, 4.860, 95% CI, 2.660–8.880, P=0.000; HR, 4.803, 95% CI, 2.692–8.567, P=0.000; Table 3). Moreover, ctDNA EGFR mut⁺ patients demonstrated a remarkably shorter DFS than did ctDNA EGFR mut⁻ patients, with the median DFS of ctDNA EGFR mut⁺ patients being only 19.00±2.50 months. Furthermore, the NSCLC patients with ctDNA EGFR mut⁺ suffered a higher probability of developing distant metastasis than did those with ctDNA EGFR mut⁻ (P<0.001). However, the patients with different tumor local invasions showed similar DFS outcomes (P=0.838).

Table 3 Univariate analysis of the correlation between clinicopathological variables and disease-free survival of NSCLC patients
Full table

The Kaplan-Meier analysis suggested that ctDNA EGFR mut⁺ patients had dramatically reduced DFS (P<0.001, Figure 1C). Through stratified analysis, we further investigated the effects of ctDNA EGFR status on DFS of early or locally advanced stage NSCLC patients. Of note, the ctDNA EGFR mut⁺ patients in stage I–II or III subgroups both had significantly worse DFS (P<0.01; Figure 1D). For stage I–II, the median DFS of the ctDNA EGFR mut⁻ was not reached, while the median DFS of ctDNA EGFR mut⁺ subgroup was 20.00±1.31 months. For stage III, the median DFS of these subgroups was 41.00±4.16 and 15.00±4.24 months, respectively. Thus, it can be seen that ctDNA EGFR detection also might be a key predictor for postoperative metastasis of NSCLC patients.

The effect of adjuvant therapy on OS and DFS of stage III NSCLC patients

As adjuvant therapies may substantially affect NSCLC prognosis, we further assessed OS and DFS under different treatment interventions based on our clinical data. Among the 57 stage III patients, 6 patients (10.5%) did not receive any treatment, 22 patients (38.6%) received adjuvant chemotherapy, 13 patients (22.8%) underwent first-line TKI treatment, and another 16 patients (28.1%) received TKI plus chemotherapy treatment.

The survival analysis showed that the stage III patients who underwent adjuvant treatments exhibited markedly different OS. Specifically, the median OS of nontreated and chemotherapy subgroups was 5.00±1.84 and 29.00±2.31, respectively, whereas the median OS of the TKI-alone subgroup was 49.00±14.60 months. Compared with chemotherapy patients, TKI-alone or TKI-plus-chemotherapy patients all achieved significantly better OS (P<0.05; Figure 2A). Meanwhile, similar analysis was conducted to assess the impact of adjuvant therapies on DFS of the above patient groups. As shown in Figure 2B,a prolonged DFS was seen in both the TKI-alone or TKI-plus-chemotherapy patients compared with the nontreated subgroup (P<0.05). However, the chemotherapy subgroup did not exhibit superior DFS as compared to the nontreated subgroup (P=0.071). More notably, no statistical differences were found between the TKI-alone and TKI-plus-chemotherapy subgroups in terms of DFS (P=0.724), but these 2 subgroups did show better DFS than the chemotherapy subgroup (P<0.05).

Figure 2 The effect of adjuvant therapy on the prognosis of stage III NSCLC patients. (A,B) The effect of different adjuvant therapies on OS (A) and DFS (B) of stage III NSCLC patients with tissue EGFR mutations. (C,D) The effect of different adjuvant therapies on OS (C) and DFS (D) of stage III NSCLC patients with 19del or L858R mutations in tissue and plasma samples. OS, overall survival; DFS, disease-free survival; EGFR, epidermal growth factor receptor; NSCLC, non-small cell lung cancer.

Because the most common mutation types in plasma EGFR detection were 19del and L858R, we further explored the association between adjuvant treatments and OS or DFS in stage III patients who were identified as having plasma 19del or L858R mutations. A total of 18 individuals were included: 14 with plasma 19del and 4 with plasma L858R. Even though the sample size was small, the survival curve showed a significantly prolonged OS in the TKI-alone-subgroup compared with the chemotherapy subgroup (P=0.025; Figure 2C). The TKI-alone subgroup also seemed to have a better DFS than did the chemotherapy subgroup, but this difference did not reach statistical significance (P=0.060, Figure 2D). In addition to this, the OS and DFS were not significantly different between the TKI-plus-chemotherapy and chemotherapy subgroups.

Discussion

In the single-center prospective study in a real-life clinical setting, a long-term follow-up (at least of 5 years) was implemented in stage I–III NSCLC patients with EGFR mutations through detection in surgically resected tumor tissues. By combining their preoperative plasma EGFR detection results and other clinical parameters, we confirmed the strong predictive power of preoperative ctDNA EGFR detection for survival and postoperative metastasis. In addition, we also observed that TKI therapy had a significantly better therapeutic effect than did chemotherapy on both tissue and plasma EGFR-positive NSCLC patients. These findings may be instructive for developing new clinical strategies in the future.

It is now widely acknowledged that driver gene mutations play a pivotal role in NSCLC initiation and progression. With the universal application of next-generation sequencing (NGS) testing, multiple driver genes, including EGFR, ALK, and KRAS, have been identified. As one of most important driver genetic alterations, EGFR mutations have long been of substantial clinical importance for TKI treatment of NSCLC patients. However, tissue biopsy, a gold standard for EGFR detection at present, faces a number of challenges. In addition to its invasive nature and risk, tissue biopsy often fails to reflect the genetic heterogeneity of tumor cells and is not conducive to dynamic monitoring for treatment response (25). Thus, a more comprehensive evaluation of NSCLC genotypic information and therapy response is valuable and will ultimately aid in providing patients more suitable treatment strategies.

Blood-based EGFR detection is a vital component of liquid biopsy and has the most potential clinical application value. A number of previous studies have explored the use of plasma ctDNA for assessment of EGFR mutations but have revealed discrepant results. Zhao et al. reported an 45.9% EGFR sensitivity in plasma analysis of stage IA–IIIA patients using mutant-enriched PCR (26). Another study showed a 100% sensitivity in IIIB–IV patients (27). In our previous study, in which the ARMS method was used, the sensitivity in stage IA–IIIA and IIIB–IV patients was 14.8% and 46.7%, respectively (20). In the present analysis, we demonstrated that the presence of plasma EGFR mutations were positively correlated with N stages, TNM stages, and tumor differentiation. Therefore, the difference in detection efficiency of these methods highlights the need for a sensitive and standardized method for blood-based EGFR testing. It should also be emphasized that ctDNA EGFR detection might be a feasible and reliable approach for NSCLC patients with tumors unsuitable for biopsy, those at advanced stages, or those who are only able to contribute blood samples.

A series of prior studies has indicated that blood-based detection could possess potential value in predicting lung cancer prognosis. By screening CTCs immediately after operation, Sawabata et al. found differences in the OS and RFS between CTC-negative and CTC-positive NSCLC patients. The 2-year OS and RFS rates were 96.5% and 94.6% respectively, for the CTC-negative group, versus 80% and 62.5%, respectively, for the CTC-positive group (22). The DYNAMIC trial demonstrated that the lung cancer patients who were ctDNA positive on the third day after R0 resection suffered a poorer prognosis (23).In addition, posttreatment ctDNA could also precede radiographic progression in 72% of patients by a median of 5.2 months (28). However, the definite prognostic value of preoperative blood-based detection for NSCLC remains unclear. In the present study, our data showed that preoperative ctDNA EGFR mutation status was an independent prognostic factor for tissue EGFR-positive NSCLC patients. The early or locally advanced stage NSCLC patients who were both tissue and plasma EGFR-positive suffered significantly poorer OS and DFS than did those who were only tissue EGFR-positive. This finding implies that the EGFR detection using preoperative blood may warrant further attention in future clinical practice. Moreover, the NSCLC patients with both plasma and tissue EGFR mutations may need to be more closely monitored.

Postoperative metastasis and recurrence are the key factors affecting the long-term survival prognosis of NSCLC patients. However, the current imaging-based diagnosis involves considerable hysteresis, which is not conductive to early detection. A growing body of recent evidence suggests minimum residual disease (MRD) to be positively correlated with tumor metastasis and recurrence (29).In addition, it has also been confirmed that ctDNA monitoring is a practical approach for MRD detection of solid tumors, such as those of NSCLC, pancreatic cancer, and breast cancer (28,30,31). Furthermore, positive ctDNA status often implies a higher risk of tumor relapse and metastasis (32). Therefore, ctDNA might be a potential biomarker of the early detection of NSCLC postoperative metastasis and may provide new opportunities for early clinical interventions. In our study, a higher frequency of distant metastasis was observed in NSCLC patients who were EGFR-positive in tissue and plasma than in patients who were tissue EGFR-positive and plasma EGFR negative (81.5% versus 25.2%). Moreover, the former group of patients suffered significantly decreased DFS. The possible reason for these results is that the EGFR mutations identified in preoperative plasma samples may indicate a high ctDNA load. This could also reflect the high-risk factors of NSCLC, including high tumor burden, poor differentiation, high-risk pathological types, and short tumor doubling time. Thus, these patients may have a higher chance of having postoperative ctDNA, and a higher likelihood of having MRD in turn. In the future, in-depth studies of the association between blood-based EGFR detection and MRD dynamic monitoring could provide further support for the early detection of NSCLC metastasis, targeted postoperative management, and individualized treatments.

Several previous clinical studies have confirmed that TKI therapy is significantly superior to platinum-based chemotherapy for EGFR-positive patients (4,6). Consistent with these results, our current data also showed that TKI-alone or TKI-plus-chemotherapy patients all achieved significantly better OS and DFS than did chemotherapy subgroup. Moreover, we further analyzed the impacts of different adjuvant therapies on the prognosis of locally advanced stage NSCLC patients who were identified with 19del or L858R mutations in both tissue and plasma samples. Although a significantly prolonged OS was observed in the TKI-alone subgroup compared with the chemotherapy subgroup, the DFS analysis did not result in a statistically significant difference. Furthermore, our current data did not produce a significant difference in OS and DFS between the TKI-plus-chemotherapy and chemotherapy subgroups. One reason for this may be the sample size limitations of the NSCLC patients in this study. Considering that only a few previous studies have conducted prognostic analyses on the relationship between preoperative plasma EGFR mutation and postsurgical adjuvant therapy, our findings still have relevance for current clinical practice.

Due to extensive research on liquid biopsy of EGFR mutations for NSCLC, there seems to be no shortage of higher sensitivity detection methods, such as DHPLC, multiplex PCR, and digital droplet PCR (ddPCR), than the Scorpion-ARMS used in this study. However, the relationship between these methods and prognostic evaluation capacity has not been extensively reported. One possible reason is that Scorpion-ARMS has an appropriate sensitivity for mutated ctDNA of blood samples, while an excessive sensitivity may instead affect the prognostic evaluation of NSCLC patients. Therefore, further follow-upinvestigations are needed in future trials.

One limitation of our study that should be noted is that the dynamic monitoring of plasma EGFR mutation and specific therapeutic interventions was not included in our analysis. More prospective clinical studies with large sample sizes and specifically defined treatment regimens are necessary to further investigate the prognostic impacts of different adjuvant therapies on plasma EGFR-positive patients. It should also be noted that different mutation types were all classified as EGFR-positive and it did not involve all rare EGFR mutations. Thus, determining the detection efficacy and treatment response of specific plasma EGFR mutations in future studies may produce more refined conclusions.

In summary, we proposed, for the first time, that EGFR mutations detection in preoperative plasma have a powerful capacity to predict long-term survival and postoperative metastasis in NSCLC patients with tissue EGFR mutations. Our data also indicate that postoperative adjuvant TKI therapy has better efficacy than does chemotherapy for locally advanced stage NSCLC patients with tissue and plasma EGFR mutations. Thus, our findings may offer new insights into plasma-based EGFR testing and may provide an innovative strategy for future clinical practice.

Acknowledgments

The authors appreciate the academic support from AME Lung Cancer Collaborative Group.

Funding: Our study received funding from the National Natural Science Foundation of China (No. 81871866), the Natural Science Foundation of Shaanxi Province (No. 2019SF-033), and the Scientific Research Project of Xi’an Health Commission (No. 2020qn01).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://dx.doi.org/10.21037/tlcr-21-530

Data Sharing Statement: Available at https://dx.doi.org/10.21037/tlcr-21-530

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/tlcr-21-530). XY serves as an unpaid editorial board member of Translational Lung Cancer Research from Jun 2019 to Jun 2021. All authors declare that the Amoy Diagnostics Corporation (Xiamen, China) supports study materials. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethics Committee of the Air Force Medical University (TDLL-KY-202106-09). Written informed consents, which included agreement to use personal clinical data and the collection of tissue and plasma samples, were signed by all patients before any study-related procedures began.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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