Efficacy of third-generation EGFR-TKIs in advanced NSCLC with different T790M statuses tested via ddPCR and NGS

doi:10.21203/rs.3.rs-2486337/v1

Objective

Third-generation epidermal growth factor receptor (EGFR)-tyrosine kinase inhibiors (TKIs) is the standard strategy for T790M-positive non-small cell lung cancer (NSCLC). We hypothesize that ddPCR, with a higher sensitivity than NGS, would optimize the treatment strategies in EGFR-TKIs relapsed patients. In this study, we compared the efficacy of third-generation TKIs with various T790M statuses via these two assays.

Methods

NGS was performed on blood samples of patients progressed from previous EGFR-TKIs treatment for resistance mechanism. T790M-negative patients received a further liquid biopsy using ddPCR for T790M status detection. The analysis of efficacy and survival for subsequent third-generation EGFR-TKIs was carried out.

Results

A cohort of 40 patients were enrolled from Sept, 2020 to Dec, 2021, with 30.0% (12/40) tested T790M-positive via NGS (Group A). In another 28 T790M-negative patients by NGS, 11 (39.3%) were T790M-positive (Group B) and 17 (60.7%) were T790M-negative (Group C) via ddPCR. After a median follow-up period of 13.7 months, a relatively longer progression-free survival (PFS) was observed in group A (not reached) and group B (10.0 months, 95% CI 7.040-12.889) than in group C (7.0 months, 95%CI 0.000-15.219), with no significant difference across all three groups (P = 0.196), or between group B and Group C (P = 0.412). The detection of EGFR-sensitive comutations correlated with an inferior mPFS (P = 0.041) and objective response rate (p = 0.326), and a significantly lower disease control rate (P = 0.033) in T790M-negative patients via NGS (n = 28).

Conclusion

This study indicates that ddPCR may contribute as a supplement to NGS in liquid biopsies for T790M detection in EGFR-TKIs relapsed patients and help to optimize the treatment strategies, especially for those without EGFR-sensitive comutations.

NSCLC

ddPCR

NGS

T790M mutation

EGFR-TKIs

The majority of patients with non-small cell lung cancer (NSCLC) eventually develop resistance to epidermal growth factor receptor (EGFR)-tyrosine kinase inhibiors (TKIs), and approximately 50% of acquired resistance accounts for the threonine-to-methionine mutation at codon 790 (T790M) of the EGFR gene¹. Osimertinib is a third-generation EGFR-TKI that targets both EGFR-sensitive mutations and EGFR T790M resistance mutations². In the AURA3 study, osimertinib significantly prolonged progression-free survival (PFS) in advanced NSCLC patients harboring the T790M mutation after progression of first-line EGFR-TKIs compared to platinum-based chemotherapy (10.1 months vs. 4.4 months, P < 0.001) and provided a higher objective response rate (ORR; 71% vs. 31%)³. Other third-generation TKIs have also been proven to be effective in targeting the T790M mutation, with a response rate of 68.9–74.0%^4,5.

Liquid biopsy has become an essential tool in tumor monitoring and a potential alternative and a supplement to tissue biopsy for genetic characteristics, especially in relapsed or metastatic diseases⁶. T790M detection using liquid biopsy in ctDNA can be qualitative or quantitative, including amplification refractory mutation system PCR (ARMS-PCR), digital droplet polymerase chain reaction (ddPCR), and next-generation sequencing (NGS)-based methods. Previous studies have compared multiple detecting platforms for EGFR mutations in plasma samples to determine the most feasible assay in clinical practice, and have revealed that ddPCR has a higher sensitivity than the ARMS-PCR assay, and both methods have a high specificity for EGFR detection in cell-free (cfDNA)⁷. Since the ddPCR assay provides a high sensitivity to detect EGFR T790M in ctDNA, it may serve as a more practical assay to support the application of osimertinib⁸. Previous studies have also validated that ddPCR had high concordance with NGS in determining ctDNA EGFR mutations⁹ and a higher sensitivity than Cobas¹⁰, and also showed a 42.7–46.7% positive rate for T790M in cases with acquired resistance to EGFR-TKIs^9,11. NGS has shown potential to detect EGFR-dependent or EGFR-independent mechanisms of resistance to targeted therapy, which helps to determine the following treatment strategy¹². In addition, NGS may identify any genetic changes in the entire target regions screened, even chromosomal rearrangement and fusion genes¹³. Compared to NGS, ddPCR assay for EGFR mutations has a higher sensitivity down to 0.04%¹⁴, with a faster turn-around time, a lower cost, and less complex informatics support required for data analysis. Patients without EGFR T790M mutations may still benefit from third-generation inhibitors with a durable response reported in our previous study¹⁵, probably due to the false-negative rate of NGS in ctDNA.

Therefore, it is hypothesized that the application of ddPCR in addition to NGS would help to optimize the treatment strategies in NSCLC patients progressed from prior first- or second-generation TKIs. In this study, we investigated the feasibility of ddPCR for detecting EGFR T790M mutation in patients without T790M resistance mutation via NGS in ctDNA, and compared the utility of ddPCR and NGS for guiding decisions regarding third-generation TKI in NSCLC patients who had developed resistance to first- or second-generation EGFR-TKIs, by analyzing the efficacy of third-generation EGFR-TKIs with various T790M statuses via these two assays (ClinicalTrials.gov number, NCT05458726).

2.1 Study design

The patients included in this study were EGFR-mutated NSCLC patients progressed from prior TKI therapy at Cancer Hospital, Chinese Academy of Medical Sciences between September, 2020 and December, 2021. The inclusion criteria are listed as follows: 1) histologically/cytologically confirmed stage IV NSCLC patients harboring sensitizing EGFR mutations; 2) having progressed from first- or second-generation EGFR-TKIs, confirmed by radiographic imaging. Exclusion criteria were as follows: 1) having progressed from first- or second-generation EGFR-TKIs in the adjuvant setting; and 2) having received third-generation EGFR-TKIs prior to the liquid biopsy; 3) no available medical records or complete follow-up data. Blood samples were collected for T790M detection, and T790M-negative patients via NGS received further gene tests via ddPCR. The demographic characteristics have been collected from their medical records, including their gender, age, smoking status, EGFR mutation status at diagnosis, duration and the metastatic pattern of prior TKIs. Treatment information including the EGFR-TKI initiation and progression date, and the best overall response (BOR) to previous TKIs were also reviewed.

2.2 Clinical assessment

Progression-free survival (PFS) was defined as the period from initiation of third-generation TKI treatment to progression or death from any cause. Complete (CR) and partial responses (PR), stable disease (SD), and progression disease (PD) were defined as per RECIST criteria version 1.1¹⁶. ORR was defined as the proportion of patients with CR or PR, and disease control rate (DCR) was defined as the proportion of patients with CR, PR, or SD. Age, gender, smoking status, EGFR status at diagnosis, EGFR-sensitive comutations at progression, presence of brain metastases, prior TKI regimens, and lines of previous systemic treatments were included in the analysis of prognostic factors to efficacy of third-generation EGFR-TKIs.

2.3 ctDNA extraction and next-generation sequencing (NGS)

Ten milliliters of whole blood at 4℃ was centrifuged at 2000× g for 10 minutes. Then the supernatant was centrifuged at 16000× g for another 10 minutes at 4℃ for plasma collection. About 4ml plasma was transferred to a new tube for DNA extraction. Plasma ctDNAs were extracted using the Plasma Circulating Nucleic Acid Preparation Kit (Qiagen, Duesseldorf, Germany), following the manufacturer’s instructions. Qubit 2.0 Fluorometer (Thermo Fisher Scientific, Carlsbad, CA, USA) was used for DNA quantity determination. A capture-based panel was used for targeted NGS that covers 168 cancer-related genes as previously reported¹⁷. Available indexed samples were sequenced on NextSeq (Illumina, San Diego, CA) with pair-end reads. The minimal median sequencing depth was 10000×; and the minimal effective sequencing depth was 2000×.

2.4 Droplet digital polymerase chain reaction (ddPCR)

QX200 Droplet Digital PCR system (Bio-Rad Laboratories, Inc., Hercules, CA, USA) was used for ddPCR according to the manufacturer’s instructions. The T790M Mutation Detection Assay Kit was purchased from Righton Gene (Shanghai, China) and applied according to the manufacturer’s instructions. The results was analyzed using QuantaSoft Software version 1.0.596.0525 (Bio-Rad Laboratories, Inc., Hercules, CA, USA).

2.5 Statistical analysis

All statistical analyses were performed by SPSS version 26.0 (Chicago, IL, USA). Clinical characteristics were presented with descriptive statistics. The categorical variables were analyzed by χ2 tests. Median PFS was estimated by the Kaplan-Meier method, and differences in survival were assessed by log-rank test. A P value < 0.05 was considered statistically significant. The univariate Cox proportional hazards regression model was conducted for the investigation of predictive factor for PFS, with the covariates that have been listed above.

3.1 Characteristics of patients

In total, 89 patients who were diagnosed with advanced or metastatic NSCLC with activating EGFR mutations, and who had progressed from prior first- or second-generation EGFR-TKIs were screened for inclusion. Forty-nine patients were excluded for the following reasons: 10 patients received targeted therapy as adjuvant therapy instead of first-line therapy, 10 patients having received third-generation TKIs before T790M detection, and other 29 patients had incomplete medical records or loss of follow-up data. Therefore, 40 patients met the inclusion criteria for analysis. A proportion of patients without T790M mutations who were reluctant or intolerant to cytotoxic agents and consented to the administration of third-generation TKIs were also included for analysis in this study. The demographic features of all enrolled patients are listed in Table 1. The median age was 63 years old (IQR 54–71). A total of 60.0% of the patients were female, and 72.5% of the patients were non-smokers. The majority of patients had common EGFR-sensitizing mutations at diagnosis (20/40, 50.0% with EGFR exon 19 deletion mutation, and 17/40, 42.5% with EGFR exon 21 L858R mutation).

3.2 Previous treatment

All included patients had received first- or second-generation EGFR-TKIs as first-line treatment (65.0% and 35.0%, respectively). The efficacy of previous TKI treatment as well as the metastatic mode were reviewed and are shown in Table 1.

The median duration of prior TKI therapy was 16.3 months (ranging from 3.8 to 77.2 months), and the ORR was 70.0% (0 CR and 20 PR) in 29 patients with at least one target lesion before first-line EGFR-TKIs. A total of 72.5% of the patients (29/40) had extracranial progression only, and another 27.5% of patients had intracranial progression only.

3.3 T790M status at progression via NGS and ddPCR

The efficacy of third-generation TKIs was compared among patients with different T790M statuses. In total, 30.0% of included patients (12/40) were T790M-positive tested via NGS using peripheral blood (Group A), and the other 70.0% (28/40) were negative via NGS, among whom 39.3% (11/28) were T790M-positive (Group B) and another 60.7% (17/28) were T790M-negative (Group C) in further testing via ddPCR. The grouping of included patients is shown in Fig. 1. According to the results of NGS, EGFR-sensitive mutations remained in 25 patients (62.5%). The genetic characteristics of patients at progression to previous TKI treatment are shown in Table 1. The abundance of T790M mutations measured by ddPCR ranged from 0.03–0.70% in patients tested T790M-negative via NGS.

3.4 Clinical efficacy

By September 2022, 55.0% of patients had progressed from third-generation TKIs (22/40), with a median follow-up period of 13.7 months. The median PFS (mPFS) for third-generation EGFR-TKI was 10.2 months (HR = 2.794, 95% CI 4.734–15.686), and the mPFS of third-generation TKI for T790M-positive patients via NGS through peripheral blood was numerically longer than others (not reached, NR vs. 8.3 months, P = 0.123).

We further compared the mPFS in patients with different T790M statuses via NGS and ddPCR, and found a relatively longer survival in Group A (NR) and Group B (10.0 months, 95% CI 7.040-12.889) than in Group C (7.0 months, 95% CI 0.000-15.219), shown in Fig. 2. However, there was no significant difference across all three groups (P = 0.196) or between Group B and Group C (P = 0.412). Among patients who had a negative status of T790M mutation via NGS (Group B and Group C, n = 28), EGFR-sensitive comutations at progression of previous TKI correlated with an inferior mPFS of third-generation EGFR-TKI (P = 0.041). The mPFS was 15.9 months (95%CI 1.775–29.945) in patients without EGFR-sensitive comutations compared to 6.3 months (95%CI 0.000-13.495) in those with EGFR sensitive comutations (Fig. 3A). In Group B (n = 11), the patients harboring EGFR-sensitive comutations also tended to have a shorter mPFS than those without (8.3 months vs. NR), with no significant difference (P = 0.214, probably due to the limited sample size), as shown in Fig. 3B. A typical case of a patient in Group B who was successfully treated with osimertinib as third-line therapy is shown in Fig. 4.

In addition, the patients who had only intracranial progression from prior TKI tended to have a longer PFS than those who had only extracranial progression (mPFS = 15.9 months, 95% CI 0.000-32.425, vs. 10.5 months, 95% CI 8.093–12.907; P = 0.934), as shown in Supplementary Fig. 1. A similar trend was observed in those without the T790M mutation (mPFS = 15.9 months, 95% CI 3.891–27.829, vs. 8.0 months, 95%CI 5.708–10.372; P = 0.439), as shown in Supplementary Fig. 2.

The best response to third-generation TKIs among all included patients as well as patients with different T790M statuses is shown in Table 2. In 32 patients with at least 1 target lesion, the ORR was 25.0% (with 0 CR and 8 PR), and the DCR was 78.1% (with 0 CR, 8 PR, and 17 SD). The ORRs in patients with T790M positive and negative via NGS were 36.4% and 19.0%, respectively (P = 0.519), and the DCRs were 100.0% and 66.7%, respectively (P = 0.086). When comparing the response rates in Group B to Group C, no significant difference was observed in either ORR (P = 0.844) or DCR (P = 0.413), although both the ORR and the DCR were numerically higher in Group B (28.6% vs. 14.3%, and 85.7% vs. 57.1%, respectively). Among T790M-negative patients via NGS, those without EGFR-sensitive comutations at progression of previous TKIs showed a stronger correlation with a promoted response rate from third-generation EGFR-TKIs in comparison to those detected with EGFR-sensitive comutations. The ORRs were 0.0% and 28.6% in patients with and without EGFR-sensitive comutations, respectively (P = 0.326), and the DCRs were 28.6% and 71.4% in patients with and without EGFR-sensitive comutations, respectively (P = 0.033). The best response in this subset of patients is shown in Table 3.

3.5 Progression events and risk factors

Among 22 patients who have progressed from third-generation TKIs, 9.1% (2/22) had intracranial progression only, 68.2% (15/22) had extracranial progression only, and 13.6% (3/22) had intra- and extracranial progression. There were 2 patients (9.1%) who had death events without disease progression.

In all included patients with different ages, sex, smoking status, EGFR status at baseline, kinds of prior TKI regimens, metastatic pattern of prior TKI, or lines of third-generation TKIs had no significant difference in PFS (Supplementary Fig. 3). In patients without the T790M mutation via NGS in ctDNA, EGFR-sensitizing comutations had a negative effect on PFS (P = 0.05). Other factors showed no significant impact (Supplementary Fig. 4).

Despite an initial response to first- and second-generation TKIs in advanced NSCLC patients harboring EGFR-sensitive mutations, a majority of patients develop resistance within 1–2 years^18,19. Various mechanisms may lead to resistance, including the T790M substitution accounting for approximately half these patients¹. Patients with proven T790M resistance mutations can be treated with third-generation EGFR-TKIs, including osimertinib³, furmonertinib⁴, and aumolertinib⁵. Therefore, it is of great importance for T790M detection in clinical practice. As rebiopsy can be difficult in most patients after previous antitumor therapy, due to the location of primary lesions or the insufficient sample for genetic analysis, ctDNA via liquid biopsy is being applied increasingly, with its high accordance to tissue testing in determining EGFR status²⁰. The application of NGS helps to reveal other resistance mechanisms that are less frequent than T790M mutations, such as amplification in MET and EGFR²¹, while ddPCR has a high sensitivity¹⁴ in detecting mutations such as the resistance T790M mutations. In this study, we analyzed the efficacy of third-generation EGFR-TKIs with various T790M statuses via ddPCR and NGS to explore whether the detection of T790M mutation using ddPCR in ctDNA would be helpful in guiding decisions regarding third-generation TKIs in NSCLC patients progressed from first- or second-generation EGFR-TKIs, as a supplement to NGS assay.

The mPFS in T790M-positive patients was not reached until the last follow-up in our study, which was relatively longer than that in T790M-negative patients (P = 0.123). Our results regarding survival were parallel to previous studies, such that the effect of third-generation TKIs in T790M-negative patients was inferior, although no significant difference was observed due to the small sample size. Multiple studies have revealed the efficacy of third-generation TKIs in patients without the T790M mutation after failure of first-line TKI treatment. For example, the mPFS of T790M-negative patients was 2.8 months in the AURA1 study²². This study may underestimate the efficacy of standard-dose osimertinib in T790M-negative patients, as a proportion of patients in the dose-escalation cohorts were included in the analysis. In the TREM study, the mPFS and mOS of osimertinib for T790M-negative patients were 5.1 months and 13.4 months, respectively, superior to those of T790M-positive patients²³. Moreover, T790M-negative patients with brain metastases and EGFR exon 21 L858R mutation were less likely to respond to osimertinib. In our study, however, no statistically significant difference was found between each subgroup as previous data have shown, mainly because our sample size was relatively small, and some patients have received local treatment such as radiotherapy, which might improve the survival for brain metastases. The ORR rates observed herein were lower than historic data (21% in the AURA1 study, and 28% in the TREM study), probably because 22.5% of patients had received more than 1 line of systematic antitumor treatment prior to third-generation EGFR-TKI. Among the patients who were confirmed to be T790M-negative by NGS, 39.3% were determined to be T790M-positive with a relatively low abundance via further gene testing using ddPCR. This subset of patients had a trend of longer PFS receiving third-generation TKIs compared to those who were T790M-negative via ddPCR, whereas no significant difference was observed, which may account for the limited sample size of our study. However, the trend of superior PFS in Group B compared to Group C indicated the value of ddPCR in detecting T790M mutations and guiding the treatment strategies for patients who initially tested T790M-negative via NGS assay. According to previous studies, intracranial metastases were less commonly detected via ctDNA than other distant extracranial metastatic relapses²⁴. Our findings that T790M-negative patients who had intracranial-only progression benefited more from third-generation TKIs than those who had estracranial-only progression from prior TKIs might be attributed to the false-negative result of the T790M mutation via NGS.

These results may be a representation of the correlation of the abundance of the EGFR T790M mutation and the efficacy of third-generation EGFR-TKIs. A previous study has indicated the predictive value of relative EGFR mutations in TKI treatment for NSCLC patients, showing a PFS benefit in patients with a high abundance of EGFR mutations²⁵. Nevertheless, regarding ORR and OS, no difference was observed in patients with different levels of EGFR abundance²⁵. A study in China found that the abundance of EGFR-sensitizing mutations via the ARMS assay was significantly related to the ORR and mPFS of EGFR-TKIs, while no significant correlation between T790M abundance and PFS of EGFR-TKIs was observed²⁶. However, the abovementioned study included a relatively small sample size with the T790M mutations (13 out of the 201 patients enrolled), therefore it may not comprehensively reveal the relevance between T790M abundance and survival. Moreover, most of the patients achieving a PR to EGFR-TKIs (77.8%, 7/9) had a low abundance of T790M mutations, indicating that an abundance of T790M mutation may have a negative influence on PFS²⁶. We further compared the efficacy of third-generation TKIs in T790M-negative patients with or without EGFR-sensitizing comutations via NGS tests and found a relatively superior mPFS and ORR, and a significantly higher DCR in those without EGFR-sensitizing comutations. A previous study evaluated the relationship between treatment efficacy and EGFR-sensitizing mutations and T790M in cfDNA by ddPCR in advanced NSCLC patients receiving osimertinib²⁷. The results showed that the PFS of patients with act-EGFR mutant allele frequencies (MAF) of > 2.6% and < 2.6% were significantly different (10 months vs. NR, P = 0.03), while patients with T790M/act-EGFR ≤ 0.22 had an inferior mPFS than those with a ratio of > 0.22 (6 months vs. NR, P = 0.01)²⁷, indicating potential markers for the efficacy of osimertinib. In a retrospective study that explored the role of T790M quantification in cfDNA by ddPCR to predict response and clinical outcomes to osimertinib, the results showed inferior mPFS and mOS in the high mutant copy group than in low copy group (5.5 months vs. NR, p < 0.01; 9.1 months vs. NR, P < 0.01)²⁸. It was therefore possible that high mutant copy numbers might indicate higher tumor burden and more aggressive tumors²⁸. In our study, the undetectable EGFR-sensitive mutations may be owe to the low abundance of mutations in ctDNA and may also lead to false-negative results in T790M mutations. With a higher sensitivity, ddPCR may contribute to detecting patients with lower T790M abundance than NGS, which explains why a subset of T790M-negative patients via NGS still benefited from third-generation TKI treatment, especially those without EGFR-sensitive comutations.

The limitations of our study are listed below. First, our sample size has limited the subgroup analysis, and thus, further exploration is needed for more evidence of ddPCR application in the detection and quantification of the T790M mutation as a supplement to NGS in liquid biopsies and to select populations that would benefit from the administration of third-generation EGFR-TKIs. Furthermore, since ddPCR was applied to detect the T790M mutation instead of activating EGFR mutations, the data of the T790M to EGFR-activating mutation ratio were not available for calculation or analysis. Therefore, the reason that patients without EGFR-activating mutations may benefit more than those with sensitizing mutations still remains to be explored in future studies.

This study indicates that ddPCR may contribute as a supplement to NGS in liquid biopsies for T790M detection in EGFR-TKIs relapsed patients and help to optimize the treatment strategies, especially for those without EGFR-sensitive comutations.

Ethics approval and consent to participate

This study was approved by the Ethics Committee of the National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (No. 2021020718314802). Written consents were signed by patients before enrollment for gene detection.

Consent for publication

We have obtained consent to publish from the participant to report individual patient data.

Availability of data and materials

Data and material are available on request.

Competing interests

The authors declare that they have no competing interests.

Funding

None.

Authors' contributions

Ziyi Xu has conducted the follow-up, data analysis, and composed the manuscript. Yan Li has contributed in study design, performing NGS and ddPCR, and manuscript revision. Lin Wang and Xuezhi Hao have contributed in sample collection. Jianming Ying has contributed in methodology and supported the investigation. Junling Li and Puyuan Xing have supervised on the administration of the study and the clinical management of enrolled patients.

Acknowledgements

Not applicable.

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Table 1 Demographic features of all enrolled EGFR-mutant NSCLC patients progressed from first-/second generation TKIs and received third-generation TKIs based on genetic results via ddPCR and NGS.

Characteristics	n	%
Age (Median/IQR)
Gender
Male	16	40.0
Female	24	60.0
Smoking status
Current/former	11	27.5
Never	29	72.5
EGFR mutation at diagnosis
Exon 19 deletion	20	50.0
Exon 21 mutation (L858R)	17	42.5
Exon 18 mutation	3	7.5
EGFR mutation retained at progression
Present	23	57.5
Absent	17	42.5
EGFR sensitive co-mutations at progression via NGS
Present	25	62.5
Absent	15	37.5
T790M status at progression
Positive via NGS (Group A)	12	30.0
Negative via NGS	28	70.0
Positive by ddPCR (Group B)	11	39.3*
Negative by ddPCR (Group C)	17	60.7*
Previous TKI treatment
First-generation TKIs	26	65.0
Second-generation TKIs	14	35.0
Duration on initial EGFR-TKIs (median, range)	16.3 months	3.8-77.2 months
Metastatic mode of previous TKI treatment
Intracranial metastases only	11	27.5
Extracranial metastases only	29	72.5
BOR to prior EGFR-TKI
CR/PR	20	50.0
SD/PD	9	22.5
No measurable lesions	11	27.5
Lines of prior systemic therapy
1	31	77.5
2	7	17.5
3	2	5.0
Brain metastasis prior to third-generation TKI
Present	14	35.0
Absent	26	65.0
Third-generation regimen
Osimertinib	35	87.5
Aumolertinib	3	7.5
Furmonertinib	2	5.0

n, number; IQR, interquartile range

*The percentage of patients with or without the T790M mutation via ddPCR in those who were T790M-negative via NGS (n=28).

The percentages might not equal 100% on account of rounding.

Table 2 The overall best response to third-generation TKIs in 32 included patients with at least one target lesion

Overall best response	N (%) All patients (n=32)	N (%) Group A (n=11)	N (%) Group B (n=7)	N (%) Group C (n=14)
CR	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)
PR	8 (25.0)	4 (36.4)	2 (28.6)	2 (14.3)
SD	17 (53.1)	7 (63.6)	4 (57.1)	6 (42.9)
PD	7 (21.9)	0 (0.0)	1 (14.3)	6 (42.9)
ORR	8 (25.0)	4 (36.4)	2 (28.6)	2 (12.5)
DCR	25 (78.1)	11 (100.0)	6 (85.7)	8 (57.1)

n, number

Table 3 The overall best response to third-generation TKIs in T790M-negative patients via NGS with at least one measurable lesion

Overall best response	N (%) All T790M- patients (n=21)	N (%) Patients with EGFR sensitive co-mutations (n=7)	N (%) Patients without EGFR sensitive co-mutations (n=14)	P value
CR	0 (0.0)	0 (0.0)	0 (0.0)	-
PR	4 (19.0)	0 (0.0)	4 (28.6)	-
SD	10 (47.6)	2 (28.6)	8 (57.1)	-
PD	7 (33.3)	5 (71.4)	2 (14.3)	-
ORR	4 (19.0)	0 (0.0)	2 (28.6)	0.326
DCR	14 (66.7)	2 (28.6)	12 (71.4)	0.033

n, number

No competing interests reported.

Supplementarymaterials.docx

Efficacy of third-generation EGFR-TKIs in advanced NSCLC with different T790M statuses tested via ddPCR and NGS

Status:

Version 1

Abstract

Objective

Methods

Results

Conclusion

Figures

1. Introduction

2. Methods

2.1 Study design

2.2 Clinical assessment

2.3 ctDNA extraction and next-generation sequencing (NGS)

2.4 Droplet digital polymerase chain reaction (ddPCR)

2.5 Statistical analysis

3. Results

3.1 Characteristics of patients

3.2 Previous treatment

3.3 T790M status at progression via NGS and ddPCR

3.4 Clinical efficacy

3.5 Progression events and risk factors

4. Discussion

5. Conclusion

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1