Plasma cfDNA analysis of alectinib resistance-related gene alterations in the J-ALEX study

Abstract

Background

Resistance to alectinib, the standard first-line therapy for anaplastic lymphoma kinase (ALK)-rearranged non-small-cell lung cancer (NSCLC), remains a major clinical challenge. This study aimed to investigate resistance mechanisms using next-generation sequencing (NGS) of plasma cell-free DNA (cfDNA).

Materials and methods

Plasma samples from 67 patients in the alectinib group of the J-ALEX study were collected at baseline, on day 57, and at treatment discontinuation. cfDNA was extracted and analyzed using NGS to detect ALK secondary mutations (SMs) and other resistance-related genetic alterations. Progression-free survival (PFS) was compared between patients with and without detectable SMs.

Results

Alectinib-resistant ALK SMs were detected in 9 of the 67 patients (13%), including resistance mutations, such as L1196M and G1202R. Patients with detected SMs had a significantly shorter PFS [15.2 months; 95% confidence interval (CI) 10.2-25.2 months] compared with those without detectable SMs [34.1 months; 95% CI 20.3-55.0 months; hazard ratio 2.28, 95% CI 1.01-5.16, P = 0.005]. Additional actionable mutations were identified, including MET amplification and KRAS G12D/NRAS G13S. KRAS and NRAS mutations, observed in two patients with a shorter PFS (2.9 and 4.4 months), suggested a potential link to primary resistance.

Conclusions

Plasma cfDNA analysis using NGS is feasible and offers insights into alectinib resistance mechanisms. Early detection of resistance-associated mutations may guide personalized treatment strategies. Larger prospective studies are needed to validate these findings.

Highlights

• •Liquid NGS of cfDNA from <3 ml plasma detected resistance-associated gene alterations in ALK-rearranged NSCLC.
• •PFS with alectinib was significantly shorter in cases with ALK secondary resistance mutations detected.
• •KRAS G12D or NRAS G13S mutation was detected at baseline and may be associated with primary resistance.
• •MET amplification and other alterations were identified at progression suggesting potential acquired resistance mechanisms.

Introduction

Lung cancer is the leading cause of cancer-related mortality worldwide. Various tyrosine kinase inhibitors (TKIs) have significantly improved the survival of patients with lung cancer, particularly those with non-small-cell lung cancer (NSCLC). Anaplastic lymphoma kinase (ALK) rearrangement defines a distinct subset of NSCLC, occurring in ∼5% of patients.^1,2 NSCLC with ALK rearrangements is highly sensitive to ALK TKIs, which effectively induce apoptosis.³

The first approved ALK inhibitor, crizotinib, significantly prolonged progression-free survival (PFS) compared with chemotherapy in patients with advanced ALK-rearranged NSCLC.⁴ Subsequently, next-generation ALK TKIs, including alectinib, ceritinib, brigatinib, and lorlatinib, have shown remarkable clinical efficacy in patients with ALK-rearranged NSCLC.5, 6, 7, 8, 9 In the global phase III ALEX study, alectinib demonstrated superior PFS compared with crizotinib, with a favorable safety profile and a clinically meaningful improvement in overall survival.⁶ Similarly, the J-ALEX study, which directly compared the efficacy and safety of alectinib and crizotinib in Japanese patients with advanced ALK-rearranged NSCLC, yielded results consistent with those of the ALEX study.⁵ As a result, alectinib is preferred over crizotinib as a first-line treatment. However, although patients initially respond to ALK TKIs, most experience disease progression due to various resistance mechanisms.

Mechanisms of resistance to crizotinib in ALK-rearranged NSCLC have recently been identified, including secondary mutations (SMs) and the activation of bypass signaling pathways, such as human epidermal growth factor receptor 2 (HER2), KIT proto-oncogene, receptor tyrosine kinase (KIT), MET proto-oncogene, receptor tyrosine kinase (MET), and insulin-like growth factor 1 receptor (IGF1R).10, 11, 12, 13 Furthermore, several ALK SMs associated with resistance to alectinib, including V1180L, L1196M, G1202R, and L1171T/N/S, have been reported.¹² Coexisting mutations in TP53 have also been associated with early resistance to alectinib.¹⁴ Next-generation sequencing (NGS) analysis of cell-free DNA (cfDNA) is a well-established and robust method for detecting alectinib-resistant mutations at baseline.¹⁵ Although resistance mutations can also be identified through serial tissue biopsies, repeated tumor biopsies are often risky and sometimes unfeasible. Consequently, plasma-based NGS analysis is emerging as a minimally invasive alternative to tissue biopsy, capable of assessing tumor heterogeneity and capturing the genomic profiles of primary and metastatic lesions.

This exploratory analysis used NGS to examine cfDNA isolated from plasma samples collected before treatment, during treatment (day 57), and after the end of treatment. Using pooled data from the phase III J-ALEX study, we sought to improve the understanding of alectinib resistance mechanisms in patients treated with alectinib as the initial ALK TKI therapy.

Materials and methods

Patients

The J-ALEX study (JapicCTI-132316; JO28928) enrolled Japanese patients with advanced NSCLC harboring ALK rearrangements. Eligible patients were either ALK inhibitor-naive and chemotherapy-naive or had received one prior chemotherapy regimen. Written informed consent was obtained from all participants before enrollment in this randomized, open-label phase III study, which compared the efficacy and safety of crizotinib and alectinib. Additionally, patients provided consent for participation in the Chugai Clinical Sample Repository project. In the J-ALEX study, participants were randomized to receive either alectinib (n = 103) or crizotinib (n = 104) until progressive disease, unacceptable toxicity, death, or withdrawal. This analysis focused on patients in the alectinib group who received oral alectinib 300 mg twice daily. Full details of the J-ALEX study methodology have been previously published.⁵

Mutation analysis

Plasma samples (∼2 ml each) were collected to investigate alectinib resistance mechanisms. Among the 103 patients randomized to the alectinib group in the J-ALEX study, baseline plasma samples were available for 67 patients. This study utilized a total of 180 plasma samples collected at three time points: before treatment initiation, during treatment (day 57), and after treatment discontinuation. Circulating tumor DNA (ctDNA) was isolated and analyzed from all available plasma samples. Plasma cell-free total nucleic acid (cfTNA) was extracted using the MagMAX Cell-Free Total Nucleic Acid Isolation Kit (Applied Biosystems, Foster City, CA) according to the manufacturer’s protocol. Targeted NGS for cfTNA was carried out using the Oncomine Lung cfTNA Research Assay following the manufacturer’s protocol (Ion Torrent, Guilford, CT). Library construction and subsequent NGS of cfTNA and genomic DNA were undertaken as previously described.¹⁶ In most samples, 10-20 ng of cfTNA was used for library construction. Sequencing reads were aligned to hg19 and variant calling was carried out using Torrent Suite 5.10.1 (Thermo Fisher Scientific, Guilford, CT) and Ion Reporter 5.10.3.0 (Thermo Fisher Scientific, Carlsbad, CA) software, respectively, as previously reported.¹⁷

Statistical analysis

Differences in categorical clinical characteristics between patients with and without secondary ALK mutations were assessed using two-sided Fisher’s exact test. All PFS assessments were performed by an independent review facility according to RECIST version 1.1. Maximum changes from baseline were compared between patients with and without detectable ALK SMs using the Wilcoxon rank-sum test. Kaplan–Meier plots and multivariable Cox proportional hazards models were used to evaluate outcomes. Differences in survival curves were assessed using the log-rank test. The Cox models were adjusted for age (≥65 or <65 years), sex, Eastern Cooperative Oncology Group (ECOG) performance status (PS) (0, 1, or 2), and smoking history. Subgroup analyses were carried out to evaluate PFS differences across clinical and genetic factors using interaction tests in the Cox model. Statistical analyses were conducted using Stata version 18.0 (StataCorp LLC, College Station, TX). All statistical tests were two-sided, with a significance threshold set at P < 0.05.

Results

Baseline characteristics

Of the 103 patients who received alectinib in the J-ALEX study, plasma samples were available for analysis from 67 patients. Among these, 15 patients developed ALK SMs during treatment. Known alectinib resistance mutations (Table 1) included L1196M (three patients), G1202R (five patients), and G1202R, R1275L (one patient) (Figure 1 and Supplementary Table S1, available at https://doi.org/10.1016/j.esmoop.2025.105574).

Table 1.

Alectinib sensitivity in SM

ALK mutation	Alectinib resistant
G1128A
F1174L
L1196M	〇
G1202R	〇
F1245L
R1275L
R1275Q
G1202R, R1275L	〇

The circles ‘〇’ indicate ALK secondary mutations that are known to confer resistance to alectinib.

Figure 1.

Overview of patient disposition in the J-ALEX study. A total of 103 patients were enrolled in the alectinib group, and plasma samples were available for analysis in 67 patients. Of these, 15 patients harbored ALK secondary mutations associated with alectinib resistance. ALK, anaplastic lymphoma kinase.

Table 2 summarizes the baseline characteristics of the 67 patients. Of these, nine patients had ALK SMs known to confer alectinib resistance, detected in plasma samples either during treatment or at the end of treatment. The median age of the cohort was 62 years (range 29-86 years). Alectinib was administered as the first-line NSCLC treatment in 37 patients (55.2%), while 30 patients (44.8%) had received prior therapy, including chemotherapy (n = 26) or chemoradiotherapy (n = 4). Two patients (2.9%) were diagnosed with squamous-cell carcinoma. Baseline characteristics were generally balanced between patients with and without detectable ALK SMs. Baseline characteristics were generally balanced between patients with and without detectable ALK SMs. Among patients with ALK SMs, an ECOG PS of 1 was the most common (88.9%), and no patient had a PS of 2.

Table 2.

The clinical characteristics of the patients

	Total (N = 67)	Secondary mutation detected (n = 9)	Secondary mutation not detected (n = 58)	P valuea
Median age, years (range)	62 (29-86)	53 (36-73)	63 (29-86)
Sex, n (%)				0.485
Male	29 (43.3)	5 (55.6)	24 (41.4)
Female	38 (56.7)	4 (44.4)	34 (58.6)
ECOG PS, n (%)				0.030
0	34 (50.7)	1 (11.1)	33 (56.9)
1	31 (46.3)	8 (88.9)	23 (39.7)
2	2 (3.0)	0 (0.0)	2 (3.4)
Smoking history, n (%)				0.723
No	36 (53.7)	4 (44.4)	32 (55.2)
Yes	31 (46.3)	5 (55.6)	26 (44.8)
Treatment line, n (%)				1.000
First	37 (55.2)	5 (55.6)	32 (55.2)
Second	30 (44.8)	4 (44.4)	26 (44.8)
Age, n (%)				0.724
<65 years	39 (58.2)	6 (66.7)	33 (56.9)
≥65 years	28 (41.8)	3 (33.3)	25 (43.1)
Clinical stage, n (%)				1.000
ⅢB	2 (3.0)	0 (0)	2 (1.9)
Ⅳ	49 (73.1)	7 (77.8)	42 (71.2)
Post-operative recurrence	16 (23.9)	2 (22.2)	14 (26.9)
Histology, n (%)				1.000
Adenocarcinoma	65 (97.1)	9 (100)	56 (98.1)
Squamous-cell carcinoma	2 (2.9)	0 (0)	2 (1.9)

ECOG, Eastern Cooperative Oncology Group; PS, performance status.

^aP values were estimated with Fisher’s exact test.

PFS analysis based on ALK SM status in the plasma

We compared PFS between patients with detected alectinib-resistant SMs and those without detectable SMs. PFS was significantly shorter in patients with detected SMs [n = 9, 15.2 months, 95% confidence interval (CI) 10.2-25.2 months] compared with those without detectable SMs [n = 58, 34.1 months, 95% CI 20.3-55.0 months, hazard ratio (HR) 2.28 (1.01-5.16), stratified log-rank P = 0.005] (Figure 2 and Supplementary Figure S1, available at https://doi.org/10.1016/j.esmoop.2025.105574).

Figure 2.

Progression-free survival (PFS) in patients with detected and undetected ALK secondary mutations (SMs). Kaplan–Meier estimates of PFS. ALK, anaplastic lymphoma kinase; CI, confidence interval.

In a separate analysis that included both known and unknown alectinib-resistant SMs (Supplementary Table S1, available at https://doi.org/10.1016/j.esmoop.2025.105574), PFS remained significantly shorter for patients with detected SMs (n = 15, 15.2 months, 95% CI 10.2-25.2 months) compared with those without detectable SMs [n = 52, 46.9 months, 95% CI 20.3-55.0 months, HR 2.40 (1.07-5.37)] (Supplementary Figure S2, available at https://doi.org/10.1016/j.esmoop.2025.105574). No significant differences in PFS were observed between patients harboring known alectinib-resistant SMs and those with unknown SMs (Supplementary Figure S3, available at https://doi.org/10.1016/j.esmoop.2025.105574). Additionally, no significant differences in PFS were observed among subgroups stratified by sex, ECOG PS, treatment line, age, or smoking history (Supplementary Figure S1, available at https://doi.org/10.1016/j.esmoop.2025.105574).

Maximum tumor reduction rate in patients with ALK SMs

The maximum tumor reduction rate, as assessed by an independent review facility, was available for 54 patients (80.6%) with measurable disease. Among these 54 patients, there was no significant difference in the median maximum tumor reduction rate between patients with known alectinib-resistant SMs [n = 8, −78.7%, interquartile range (IQR) −72.5% to −82.2%] and those without detectable SMs (n = 46, −79.1%, IQR −67.8% to −87.5%) (Figure 3A). However, complete responses (CRs) were observed only in patients without detectable SMs. None of the patients with detected SMs achieved CR (Figure 3B).

Figure 3.

Tumor response to alectinib according to ALK secondary mutation status. (A) Maximum change from baseline in tumor size for patients with measurable disease. (B) Best overall response to alectinib. A waterfall plot analysis of the best overall response to alectinib. CR, complete response; IQR, interquartile range; MCB, maximum change from baseline; SMs, secondary mutations.

Resistance mechanisms other than ALK SMs

Several actionable gene mutations were detected in pre-alectinib plasma samples (Table 3). Among these, two patients harbored RAS mutations (KRAS G12D and NRAS G13S) with a PFS of 2.9 and 4.4 months, respectively, suggesting a potential association with early resistance. In the patient with the NRAS G13S mutation who had measurable target lesions, the maximum tumor reduction rate was limited to 36.1%, lower than the overall median reduction of 78.7% (Supplementary Figure S4, available at https://doi.org/10.1016/j.esmoop.2025.105574). In contrast, patients with MAP2K1 P124L and cMET Y1248H mutations had a PFS of 20.2 months and 45 months, respectively.

Table 3.

Co-existence of actionable gene alterations found at pretreatment

Patient ID	54005	51503	51603	52303
KRAS mut	G12D
NRAS mut		G13S
MAP2K1			P124L
cMET mut				Y1248H
PFS (months)	2.9	4.4	20.2	45

PD, progressive disease; PFS, progression-free survival.

Additionally, several gene alterations associated with acquired resistance were identified in plasma samples collected at progression on alectinib from five patients (Table 4). Two patients harbored the PIK3CA E545K mutation, while cMET amplification, MAP2K1 E203K, and BRAF V600E mutations were each detected in one patient. These alterations were observed exclusively at the end of alectinib treatment. Notably, patients with MAP2K1 or BRAF mutations exhibited PFS exceeding 50 months, indicating prolonged disease control. Among the two patients with PIK3CA mutations, one had a very short PFS of 2.8 months, while the other’s PFS exceeded 50 months.

Table 4.

Mechanism of acquired resistance found at PD

Patient ID	52902	52812	52202	51502	53512
PIK3CA mut	E545K				E545K
cMET amp		Positive
BRAF mut				V600E
MAP2K1			E203K
PFS (months)	2.8	20.3	50.5	55	58.5

PD, progressive disease; PFS, progression-free survival.

In a previous report, PFS was significantly shorter in patients with coexisting TP53 mutations and ALK rearrangements based on NGS analysis of tissue samples¹⁴; however, in this study, no significant difference in PFS was observed between patients with and without coexisting TP53 mutations in plasma samples (Supplementary Figure S5, available at https://doi.org/10.1016/j.esmoop.2025.105574).

Discussion

The results of this exploratory analysis using pooled plasma samples from the J-ALEX study suggest that plasma cfDNA NGS analysis can guide personalized treatment strategies based on resistance mechanisms, even with small blood volumes. Approximately 13% of patients receiving alectinib were found to harbor ALK SMs that conferred resistance to alectinib. Baseline characteristics were generally balanced between the subgroups, except for ECOG PS, which was lower in patients with ALK SMs (11.1% ECOG PS 0) compared with those without SMs (56.9%). This imbalance may have contributed to the observed difference in PFS. The median PFS was shorter in patients with ALK SMs compared with those without SMs. Similar findings have been reported for patients whose plasma samples tested positive for ALK SMs following treatment with crizotinib.¹⁸ Notably, both SMs detected in this study, L1196M and G1202R, are expected to respond to other ALK TKIs, such as brigatinib and lorlatinib.^12,19 These results emphasize the importance of molecular monitoring to inform subsequent treatment decisions. Continuous cfDNA monitoring during treatment, as previously demonstrated in epidermal growth factor receptor (EGFR)-mutant NSCLC, may enable early detection of molecular progression and facilitate timely switching to alternative TKIs, potentially improving outcomes.²⁰ However, in this study, there was no significant difference in tumor shrinkage rates between patients with and without ALK SMs; therefore, it is difficult to conclude whether tumors with higher residual cell burdens are more likely to develop SMs.

In the present analysis, alectinib-resistant ALK SMs were detected on day 57 in only 1 out of 67 patients (1.5%). In the analysis including all SMs regardless of known sensitivity, SMs were detected in five patients (7.5%) on day 57. This low detection rate may reflect the early antitumor effect of alectinib, which likely reduced tumor burden and ctDNA shedding, limiting detection sensitivity. In support, a previous NSCLC study showed that ctDNA levels increased at a median of 1.5 months before radiographic progression.²¹ Thus, while single early assessments may miss resistance mutations, serial cfDNA monitoring remains important for detecting molecular progression before imaging-defined progression.

We also conducted an exploratory analysis including all ALK SMs and observed shorter PFS in patients with any SM than in those without (Supplementary Figure S2, available at https://doi.org/10.1016/j.esmoop.2025.105574; log-rank P = 0.01). Furthermore, no significant difference in PFS was observed between patients in whom SMs were detected on day 57 and those detected at the end of treatment (Supplementary Figure S6, available at https://doi.org/10.1016/j.esmoop.2025.105574). This suggests that early emergence of ALK SMs may reflect the expansion of resistant subclones contributing to subsequent progression. These findings support the potential utility of comprehensive plasma genotyping during treatment to inform clinical monitoring and treatment planning.

Several resistance-related gene mutations activating bypass signaling pathways independent of ALK were detected in plasma samples collected before or at progression on alectinib. For example, MET amplification, a known mechanism of resistance to EGFR TKIs,^22,23 was identified in one patient. Previous studies have demonstrated the efficacy of MET inhibitors, such as crizotinib and capmatinib, in ALK-rearranged NSCLC with MET amplification resistant to second-generation ALK TKIs.^24,25 Similarly, the combination of alectinib with dabrafenib and trametinib has shown efficacy in preclinical models of BRAF V600E co-mutations, and ALK TKIs combined with MEK inhibitors have been effective against MAP2K1-mutant cell lines.^25,26 These findings suggest that integrating targeted therapies against bypass pathways, such as MET amplification, BRAF V600E, and MAP2K1 mutations, could overcome resistance to alectinib and improve patient outcomes.

KRAS G12D and NRAS G13S mutations were detected in two patients before alectinib treatment, with a PFS of 2.9 and 4.4 months, respectively (Table 5). These findings are consistent with previous reports indicating primary resistance to crizotinib in ALK-rearranged NSCLC with RAS co-mutations.²⁷ Although data on alectinib are limited, our results suggest that it may have limited efficacy in cases with RAS co-mutations. In such instances, platinum-based chemotherapy might be a more appropriate first-line treatment, and the potential for initial resistance should be carefully considered.

Table 5.

Characteristics of patients with NRAS or KRAS mutations

Patient ID	RAS mutations	Sex	Age (years)	ECOG PS	Smoking status	PFS (months)	Size (mm, target lesion)	MCB (%)
51503	NRAS G13S	Female	51	0	Never smoker	4.4	91.7	−36.1
54005	KRAS G12D	Female	74	0	Never smoker	2.9	None	No target

ECOG, Eastern Cooperative Oncology Group; MCB, maximum change from baseline; PFS, progression-free survival; PS, performance status.

Never smokers were defined as patients with self-reported absence of any tobacco use history (all tobacco products) based on patient declaration at study entry.

Although prior studies have linked TP53 co-mutations to a shorter PFS in patients treated with alectinib, this analysis found no significant difference in PFS between patients with and without TP53 co-mutations.¹⁴ This discrepancy may be attributed to clonal hematopoiesis of indeterminate potential (CHIP), a phenomenon characterized by somatic mutations in blood stem cells, which is common in older adults and can be exacerbated by cytotoxic therapies.28, 29, 30 CHIP-associated mutations, such as TP53, may confound plasma-based NGS analysis by introducing non-tumor-derived mutations. When TP53 mutations are detected in plasma samples, the possibility of CHIP should be considered, particularly in older patients or those with a history of chemotherapy.

This study has several limitations. Firstly, the use of cfDNA for detecting resistance mechanisms depends on tumor shedding into the bloodstream, which may result in false negatives for patients with low tumor burden or limited shedding. Additionally, the plasma volume available for cfDNA extraction was ∼2 ml, which may have further constrained the detection sensitivity. To address this limitation, we used the term ‘SM not detected’ instead of ‘negative’ to describe cases where SMs were not identified, acknowledging the possibility of limited detection sensitivity. Additionally, the retrospective design and small sample size limit the generalizability of these findings. Larger, prospective studies are needed to confirm these observations and further refine the role of plasma-based NGS in managing ALK-rearranged NSCLC.

Conclusions

NGS analysis of plasma samples collected from patients who received alectinib in the J-ALEX study identified several genetic abnormalities that could improve patient prognosis by enabling timely treatment changes at the stage of molecular progression before RECIST-defined progression. Carrying out minimally invasive liquid biopsies during alectinib treatment may provide a valuable strategy for monitoring resistance mechanisms and optimizing therapeutic interventions.

Disclosure

HM, KF, and SY are employees of Chugai Pharmaceutical Co., Ltd. RK has received research grants from Chugai Pharmaceutical Co., Ltd. ST has received research grants and speaker fees from Chugai Pharmaceutical Co., Ltd. All other authors have declared no conflicts of interest.