Chaelin Lee; Sheehyun Kim; Soyeon Kim; Taekeun Park; Miso Kim; Bhumsuk Keam; Tae Min Kim; Dong-Wan Kim; Jeonghwan Youk

doi:10.4143/crt.2025.279

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Original Article Preferential Sensitivity of the EGFR L858M/L861R Mutation to Second-Generation EGFR Tyrosine Kinase Inhibitors in Non–Small Cell Lung Cancer: Chaelin Lee¹, Sheehyun Kim², Soyeon Kim^1,3, Taekeun Park⁴, Miso Kim^1,4, Bhumsuk Keam^1,4, Tae Min Kim^1,2,4, Dong-Wan Kim^1,4, Jeonghwan Youk^1,4; DOI: https://doi.org/10.4143/crt.2025.279
Published online: August 20, 2025

¹Cancer Research Institute, Seoul National University, Seoul, Korea

²Department of Genomic Medicine, Seoul National University Hospital, Seoul, Korea

³Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea

⁴Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea

Correspondence: Jeonghwan Youk, Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea
Tel: 82-2-2072-3773 E-mail: jhyouk@snu.ac.kr

• Received: March 11, 2025 • Accepted: August 19, 2025

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract

Purpose
Non–small cell lung cancer (NSCLC) frequently harbors targetable epidermal growth factor receptor (EGFR) mutations. However, rare variants such as EGFR L858M or L861R remain poorly characterized. This study aimed to elucidate the oncogenic potential and EGFR tyrosine kinase inhibitors (TKIs) sensitivity of the EGFR L858M/L861R mutation to inform personalized treatment strategies.
Materials and Methods
Tumor samples from an NSCLC patient were analyzed using targeted panel sequencing and confirmed with the FoundationOne Liquid CDx assay. EGFR-mutant constructs, including L858M, L858R, L861R, L861Q, L858M/L861R, and L858R/L861Q, were generated and transduced into various cell lines. Cell viability, immunoblot, and soft agar colony formation assays were conducted to assess the oncogenicity and drug sensitivity, while computational protein modeling and docking simulations evaluated the drug-binding affinities of EGFR-TKIs.
Results
Ba/F3 cells expressing the EGFR L858M/L861R mutation exhibited robust interleukin-3–independent proliferation accompanied by markedly increased EGFR phosphorylation, while NIH-3T3 cells showed anchorage-independent colony formation. Compared to other mutations, cells expressing EGFR L858M/L861R mutation were less sensitive to first-generation EGFR-TKIs (gefitinib, erlotinib) and third-generation EGFR-TKIs (osimertinib, lazertinib), whereas second-generation EGFR-TKIs (afatinib, poziotinib) demonstrated potent inhibitory effects. Computational modeling revealed a narrower drug-binding efficiency of first-generation inhibitors.
Conclusion
The EGFR L858M/L861R mutation drives strong oncogenic signaling and exhibits preferential sensitivity to second-generation EGFR-TKIs. These findings underscore the importance of accurate molecular diagnosis for guiding effective, personalized therapeutic strategies in NSCLC.
Key words: Non-small cell lung carcinoma, EGFR, Tyrosine kinase inhibitors, EGFR L858M, EGFR L861R

Introduction

Lung cancer is the leading cause of cancer-related deaths globally, with non–small cell lung cancer (NSCLC) comprising the majority of cases [1,2]. Among NSCLC patients, epidermal growth factor receptor (EGFR) mutations are the most prevalent targetable mutations, with exon 19 deletions and the L858R substitution representing approximately 85% of all EGFR-activating mutations [3]. These mutations are well-established predictive markers for sensitivity to EGFR tyrosine kinase inhibitors (TKIs) [3,4].

In addition to these common mutations, targeted panel sequencing continues to uncover rare EGFR mutations, including G719X, S768I, or L861Q [5,6]. Although much rarer, EGFR L858M or L861R mutation have been reported [5]. A case study reported that EGFR L858M/L861R mutation were initially undetected using a conventional peptide nucleic acids (PNA)–clamping assay but were later identified through next-generation sequencing (NGS) [7]. The patient misdiagnosed with EGFR L858R/L861Q mutation treated with gefitinib exhibited no clinical response, ultimately leading to death [7]. In contrast, another case study reported that a patient correctly identified with EGFR L858M/L861Q mutation via NGS demonstrated a positive response to the second-generation EGFR-TKI, afatinib [8]. These cases underscore the critical importance of accurate mutations detection to guide appropriate treatment strategies and highlight the need for research into rare EGFR mutations.

While EGFR L858R or L861Q mutation have been extensively studied [9,10], there remains a significant knowledge gap regarding the oncogenic potential and EGFR-TKIs sensitivities of uncommon EGFR mutation such as L858M/L861R. Consequently, there is no established treatment strategy for patients harboring these rare mutations. Our study identified an NSCLC patient with EGFR L858M/L861R mutation who exhibited limited responses to the first-generation EGFR-TKI, erlotinib, highlighting the need for further research to optimize treatment approaches.

To address the knowledge gap, we conducted a comprehensive study to elucidate the oncogenic properties and therapeutic strategies of the EGFR L858M/L861R mutation.

Materials and Methods

1. Patient sample collection and analysis

A biopsy sample was obtained from a 78-year-old female patient diagnosed with stage IV lung adenocarcinoma. DNA was extracted from the formalin-fixed, paraffin-embedded lung cancer biopsy tissue of the primary right lower lobe lung mass, obtained prior to first-line chemotherapy. The FiRST Lung Cancer Panel (LCP) at Seoul National University Hospital (SNUH), a customized institutional targeted sequencing platform specifically for lung cancer covering 75 DNA and 151 RNA genes [11,12], was used to detect targetable mutations. Independently, blood DNA, which was also collected before the initiation of first-line chemotherapy, was sent for the FoundationOne Liquid CDx assay [13].

2. Cell lines and reagents

The Ba/F3 cell line was obtained from DSMZ, the NIH-3T3 cell line from American Type Culture Collection (ATCC), and the PC9 cell line from the RIKEN BioResource Research Center. Ba/F3 cells were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS), 1% penicillin/streptomycin, 2 mM L-glutamine, and 4 ng/mL interleukin-3 (IL-3) (ProSpec). NIH-3T3 cells were cultured in Dulbecco’s modified Eagle’s medium supplemented with 10% FBS and 1% penicillin/streptomycin. PC9 cells were cultured in RPMI-1640 medium supplemented with 10% FBS, 1% penicillin/streptomycin, 2 mM L-glutamine. Gefitinib, erlotinib, afatinib, poziotinib, and lazertinib were purchased from Selleck Chemicals. Osimertinib was generously provided by AstraZeneca.

3. Cloning and construction of EGFR-mutants cell lines

The pBabe-puro EGFR^WT plasmid was generously provided by Matthew Meyerson (Addgene plasmids #11011, Dana-Farber Cancer Research Institute). The pBabe-puro EGFR L858M, L858R, L861R, L861Q, L858M/L861R, and L858R/L861Q mutants were generated through site-directed mutagenesis (Agilent Technologies) of the pBabe-puro EGFR^WT plasmid following the manufacturer’s protocols using specific primers (S1 Table). Each EGFR-mutant construct was transduced into Ba/F3, NIH-3T3, or PC9 cells, followed by puromycin selection.

4. Polymerase chain reaction and sequencing

The DNA from the EGFR-mutant Ba/F3 and NIH-3T3 cell lines was extracted using the Exgene Cell SV mini kit (GeneAll). Polymerase chain reaction (PCR) was performed to amplify EGFR exon 18 to exon 25 regions using specific primers (S1 Table), and the resulting DNA sequences were analyzed by Sanger sequencing.

5. Cell viability assay

The EGFR-mutant Ba/F3 and PC9 cells were plated in 96-well plates and treated with EGFR-TKIs in RPMI-1640 medium for 72 hours. EGFR-TKIs were prepared in dilutions ranging from 10 mM to 0.01 nM. Cell viability was assessed using the Cell Titer Glo-Luminescent cell viability assay (Promega). IC₅₀ values were calculated using SigmaPlot 10.0 software (Systat Software Inc.), and graphs were generated using GraphPad Prism 8 software (GraphPad Software).

6. Immunoblot assay

The EGFR-mutant Ba/F3 and PC9 cells were cultured in 6-well plates and treated with EGFR-TKIs for 4 or 24 hours. After treatment, cells were lysed using 10× cell lysis buffer (Cell Signaling Technology) supplemented with phenylmethylsulfonyl fluoride (Sigma), PhosSTOP (Roche), and a proteinase inhibitor cocktail (Merck). Protein concentrations were determined using a protein assay dye reagent concentrate (Bio-Rad). Subsequently, the protein samples were loaded onto NuPAGE Bis-Tris Gels (Invitrogen) for electrophoresis. After separation, the proteins were transferred onto polyvinylidene difluoride membranes (Bio-Rad), followed by detection using ECL Prime Western Blotting Detection Reagent (GE Healthcare). Antibodies against total EGFR (#4267), phospho-EGFR (#3777), total Akt (#4685), phospho-Akt (#4060), total Erk p42/p44 (#9102), phospho-Erk (#9106), caspase-3 (#9662), cleaved caspase-3 (#9661), poly(ADP-ribose) polymerase (PARP; #9542), and glyceraldehyde 3-phosphate dehydrogenase (GAPDH; #5174) were purchased from Cell Signaling Technology. The immunoblot bands were quantified using ImageJ software.

7. Soft agar colony formation assay

Agar solutions of 1% and 0.7% were prepared using select agar (Thermo Fisher Scientific). For the bottom layer, 1% agar was diluted to 0.5% agar using culture media and then distributed into each well of 6-well or 12-well plates. For the top layer, 0.7% agar was diluted to 0.35% agar using culture media containing EGFR-mutant NIH-3T3 cells, which was then poured over the bottom layer. After allowing the agar to solidify, culture media containing the drug was added, and the cells were incubated for 3 weeks with regular media changes every 3 days. Colonies that formed were stained with nitro blue tetrazolium (Promega) and imaged using the EVOS Cell Imaging System (Thermo Fisher Scientific). The number and size of colonies were quantified with ImageJ software.

8. Computational protein modeling of EGFR-mutants and drug docking simulation

The computational EGFR L858M/L861R and L858R/L861Q protein models were constructed using Swiss-Model [14-18] based on the EGFR wild-type model (PDB ID: 4ZAU) available in the Protein Data Bank (PDB). Docking simulations on the constructed models were performed using SwissDock [19-22]. The constructed models and drug docking results were visualized and measured using University of California, San Francisco (UCSF) Chimera [23,24].

Results

1. Clinical and molecular characterization of the patient

A 78-year-old female never-smoker presented with a persistent cough lasting over three months, without significant weight loss. A chest X-ray revealed a mass in the right lower lung field, prompting further evaluation with computed tomography (CT), which identified a 3 cm lung mass in the right lower lobe, along with multiple regional lymph node metastases and distant metastases to both lungs, the left adrenal gland, and the brain. A biopsy confirmed the diagnosis of lung adenocarcinoma.

Initial PNA-mediated PCR clamping failed to detect relatively common EGFR mutations, including G719X, exon 19 deletions, T790M, S768I, exon 20 insertions, L858R, and L861Q. Additionally, the tumor was negative for ALK immunohistochemistry and had PD-L1 tumor proportion scores of 5% (22C3) and 3% (SP263). Based on these molecular findings, the patient received palliative chemotherapy with pembrolizumab, pemetrexed, and carboplatin, along with gamma knife surgery (GKS) to treat brain oligo-metastases. The best response to first-line chemotherapy was stable disease (SD) with a 7.4% decrease in the target lesion.

After six cycles of chemotherapy, the patient experienced disease progression, including an increase in bilateral lung nodule size, the development of a new right adrenal metastasis, and progression of previously treated brain metastases. As a result, she was switched to second-line chemotherapy with docetaxel and underwent additional GKS for progressing brain lesions. After three cycles of docetaxel, she achieved a partial response with a 32.1% decrease in the target lesion; however, routine 3-month brain magnetic resonance imaging detected multiple new brain metastases. She subsequently underwent whole brain radiotherapy and NGS panel testing using the institutional FiRST LCP and the FoundationOne Liquid CDx assay.

While awaiting sequencing results, she received two cycles of third-line gemcitabine. Unfortunately, the disease continued to progress (progressive disease), with a 23.8% increase in the target lesion, leading to worsening of cough and dyspnea. A summary of her clinical history is provided in Fig. 1A.

The FiRST LCP identified EGFR c.2572C>A (L858M) and c.2582T>G (L861R) mutation occurring in cis within the same reads, with variant allele frequencies of 24.41% and 24.18%, respectively (Fig. 1B, S2 Table). These findings were further confirmed by the FoundationOne Liquid CDx (S3 Table).

Currently, there are no established therapeutic strategies for treating EGFR L858M/L861R mutation with EGFR-TKIs. However, considering that EGFR L858R and L861Q are known EGFR-sensitive mutant positions, the patient opted for treatment with an EGFR-TKI. She received 150 mg of erlotinib daily for 4 weeks, resulting in an improvement in her cough and dyspnea, as well as a reduction in ground-glass opacities in both lungs on chest X-ray. A CT scan performed six weeks after starting erlotinib indicated SD with a 7.7% decrease in the target lesion, and a reduction in the right pleural effusion, leading to improved respiratory symptoms. Unfortunately, thirteen weeks after initiating erlotinib treatment, the patient contracted coronavirus disease 2019 (COVID-19). Despite no evidence of tumor progression, she succumbed to respiratory failure caused by COVID-19. Due to the patient’s death from COVID-19, further assessment of her response to EGFR-TKIs was not possible (Fig. 1A).

In this patient, the first-generation EGFR-TKI erlotinib resulted in only modest antitumor activity against lung cancer with EGFR L858M/L861R mutation. The clinical response was weaker compared to the typical. Therefore, we decided to investigate the oncogenic potential of the EGFR L858M/L861R mutation and their response to various EGFR-TKIs.

2. Oncogenicity of the EGFR L858M/L861R mutation

To evaluate the oncogenic potential of the EGFR L858M/L861R mutation, we established Ba/F3 and NIH-3T3 cell lines harboring this mutation. Additionally, to compare with well-known mutations in the same positions including L858R and L861Q, we also established cell lines expressing these variants. Genetically modified cell lines were successfully validated by Sanger sequencing (S4 and S5 Figs.).

All Ba/F3 cell lines expressing EGFR L858M, L858R, L861R, L861Q, L858M/L861R, and L858R/L861Q mutation exhibited robust growth in IL-3–depleted media, whereas parental Ba/F3 cells did not survive under these conditions, demonstrating their oncogenic potential (Fig. 2A). Among the six mutations, the two cell lines expressing EGFR L861R and L861Q exhibited slower growth rates compared to those expressing EGFR L858M or L858R mutation, regardless of co-occurrence with L861R or L861Q (p=0.014 for EGFR L861R vs. L858M/L861R; p=0.018 for EGFR L861Q vs. L858R/L861Q) (Fig. 2A).

To further assess EGFR pathway activation, we conducted immunoblot assay to evaluate phospho-EGFR levels (Fig. 2B). The EGFR L858M/L861R mutation showed the highest phospho-EGFR expression, indicating strong constitutive activation of EGFR signaling pathways.

We further confirmed the oncogenic potential of these mutations using a soft agar colony formation assay in NIH-3T3 cell lines. (Fig. 2C, S6 Fig.). All six NIH-3T3 cell lines expressing EGFR mutations successfully formed colonies, demonstrating NIH-3T3 cell lines expressing EGFR mutations can grow anchorage-independently. Notably, cells expressing co-occurring mutation L858M/L861R and L858R/L861Q formed a high number of colonies compared to those expressing single mutation (L858M, L858R, L861R, or L861Q), suggesting that co-occurring mutation confers greater oncogenic potential (Fig. 2C, S6 Fig.).

3. Efficacy of EGFR-TKIs on the viability of EGFR L858M/L861R-expressing cells

To assess the therapeutic potential of EGFR-TKIs, we evaluated their efficacy in Ba/F3 cell lines expressing various oncogenic EGFR mutations (Fig. 3A-F). Among the six EGFR-mutant Ba/F3 cell lines, cells expressing EGFR L858M/L861R mutation exhibited the poorest response to first-generation EGFR-TKIs. Specifically, gefitinib (IC₅₀, 65.631±28.315 nM) and erlotinib (IC₅₀, 83.056±31.054 nM) showed significantly reduced efficacy in these cells compared to those with the EGFR L858R/L861Q mutation, where IC₅₀ values were approximately 76- to 530-fold lower (p=0.016 for gefitinib, p=0.010 for erlotinib) (Fig. 3E, S7 Table). These findings indicate that first-generation EGFR-TKIs are not optimal for targeting the EGFR L858M/L861R mutation (Fig. 3E and F).

When comparing the IC₅₀ values of EGFR-TKIs across all mutations, second-generation EGFR-TKIs (afatinib and poziotinib) demonstrated the strongest inhibitory effects, with IC₅₀ values ranging from 0.001 to 0.042 nM. Third-generation EGFR-TKIs (osimertinib and Lazertinib) showed moderate efficacy, with IC₅₀ values between 0.002 to 12.027 nM (S8 Fig.). However, even among third-generation EGFR-TKIs, the efficacy was notably reduced in EGFR L858M/L861R mutation compared to EGFR L858R/L861Q mutation, with IC₅₀ values approximately 338- to 1,459-fold higher, respectively (p=0.063 for osimertinib, p=0.143 for lazertinib). Interestingly, second-generation EGFR-TKIs were the only class of inhibitors that exhibited comparable efficacy in EGFR L858M with or without L861R mutation (Fig. 3G and H, S7 Table).

Overall, second-generation EGFR-TKIs demonstrated the highest efficacy across all six EGFR-mutant Ba/F3 cell lines, followed by third-generation EGFR-TKIs. In contrast, first-generation EGFR-TKIs showed efficacy only in Ba/F3 cells expressing EGFR L858R or L858R/L861Q mutation (Fig. 3B and F, S8A and S8B Fig.).

Therefore, our findings strongly suggest that first-generation EGFR-TKIs are not suitable for targeting the EGFR L858M/L861R mutation. Third-generation EGFR-TKIs exhibit moderate efficacy but are surpassed by second-generation EGFR-TKIs, which emerge as the most effective therapeutic option for treating EGFR L858M/L861R mutant NSCLC.

4. Efficacy of EGFR-TKIs on the EGFR signaling in EGFR L858M/L861R-expressing cells

After confirming the efficacy of EGFR-TKIs on cell viability, we next investigated their effects on EGFR signaling pathways in EGFR-mutant–expressing cell lines.

Immunoblot assays were conducted to evaluate the effects of erlotinib, afatinib, and osimertinib (Fig. 4A-F). The results showed that phospho-EGFR signaling patterns closely aligned with the trends observed in the cell viability assays (Fig. 3).

Erlotinib, a first-generation EGFR-TKI, exhibited an inhibitory effect on EGFR signaling only in Ba/F3 cells expressing the EGFR L858R and L858R/L861Q mutation (Fig. 4B and F). In contrast, erlotinib failed to suppress phospho-EGFR expression in Ba/F3 cells expressing L858M, L861R, L861Q, and L858M/L861R mutation (Fig. 4A, C, D, and E). On the other hand, afatinib, a second-generation EGFR-TKI, significantly reduced phospho-EGFR levels in all six EGFR-mutant Ba/F3 cell lines, reinforcing its strong inhibitory potential (Fig. 4A-F). Osimertinib, a third-generation EGFR-TKI, showed efficacy in Ba/F3 cell lines expressing five types of EGFR-mutants, but was ineffective in L858M-expressing Ba/F3 cell lines (Fig. 4A-F). However, osimertinib showed partial inhibition in L858M/L861R co-occurring mutant cell lines, suggesting that the presence of L861R may slightly enhance osimertinib sensitivity (Fig. 4A and E).

When comparing the two co-occurring mutations, in EGFR L858R/L861Q-expressing cell line, all three EGFR-TKIs effectively reduced phospho-EGFR expression and its downstream effectors phospho-Akt and phospho-Erk (Fig. 4F). In contrast, in EGFR L858M/L861R-expressing cell line, erlotinib failed to inhibit phospho-EGFR, while osimertinib displayed a weaker response compared to EGFR L858R/L861Q (Fig. 4E). However, afatinib remained the most potent inhibitor, significantly reducing phospho-EGFR levels in EGFR L858M/L861R-expressing cell line (Fig. 4E).

5. Efficacy of EGFR-TKIs in human NSCLC cells harboring EGFR L858M/L861R mutation

Although we previously demonstrated the oncogenic potential of the EGFR L858M/L861R mutation and its sensitivity to EGFR-TKIs using murine cell lines, including Ba/F3 and NIH-3T3, we further characterized the functional characteristics of this mutation in a more clinically relevant human lung cancer model. We employed the PC9 cell line, derived from a human lung adenocarcinoma harboring an EGFR exon 19 deletion, which is known to confer high sensitivity to EGFR-TKIs. PC9 cells were engineered to express either EGFR L858M/L861R or the comparative variant EGFR L858R/L861Q.

In PC9 cells harboring EGFR L858M/L861R, afatinib demonstrated the highest efficacy among the three EGFR-TKIs including erlotinib, afatinib, and osimertinib, as evidenced by the lowest IC₅₀ value (erlotinib, 10.065±3.032 nM; afatinib, 0.081±0.039 nM; Osimertinib, 0.495±0.39 nM) (S9A and S9B Fig.). Phosphorylation assays revealed that erlotinib exhibited relatively weak inhibition of EGFR phosphorylation in PC9 cells harboring EGFR L858M/L861R compared to those harboring EGFR L858R/L861Q (S9C Fig.). Also, among the EGFR-TKIs tested—erlotinib, afatinib, and osimertinib—erlotinib demonstrated the least potency in suppressing EGFR phosphorylation (S9C Fig.).

To further investigate the effects of EGFR-TKIs on downstream signaling and apoptosis, we examined key signaling intermediates and apoptotic markers, including phospho-Akt, phospho-Erk, cleaved PARP, and cleaved caspase-3, in PC9 cells harboring EGFR L858M/L861R. Afatinib and osimertinib both markedly reduced phospho-Akt levels. In addition, cleaved caspase-3 was most strongly induced by afatinib (S9D Fig.).

Taken together, these results demonstrate that afatinib efficiently suppresses tumor cell viability and induces apoptosis in human NSCLC cell lines harboring EGFR L858M/L861R mutation compared to erlotinib. Moreover, afatinib revealed numerically lower IC₅₀ value and greater apoptotic activity than osimertinib, highlighting its potential as a preferred therapeutic option for tumors harboring this rare mutation.

6. Structural differences between EGFR L858M/L861R and L858R/L861Q mutation

To investigate the structural differences between the two co-occurring mutations, we assessed the drug binding affinities using AutoDock Vina of SwissDock [25] for three EGFR-TKIs, erlotinib, afatinib, and osimertinib across six EGFR-mutants (L858M, L858R, L861R, L861Q, L858M/L861R, and L858R/L861Q). The estimated average binding affinity values were consistent with our in vitro results as follows: afatinib (–6.29±0.28 kcal/mol) > osimertinib (–6.08±0.4 kcal/mol) > erlotinib (–5.37±0.25 kcal/mol) (S10 Table).

Specifically, erlotinib’s calculated drug affinity was lower in the EGFR L858M/L861R model (–5.11±0.7 kcal/mol) compared to the L858R/L861Q model (–5.63±0.45 kcal/mol) (Fig. 5A, S10 Table). Additionally, computational protein modeling revealed distinct binding patterns: erlotinib penetrated more deeply into the drug-binding pocket in the EGFR L858R/L861Q model than in the L858M/L861R model (Fig. 5B and C). Structural analysis indicated that in the EGFR L858R/L861Q model, arginine 858 (R858) forms interactions with lysine 875 (K875) in the activation loop, stabilizing the protein in the active state (S11A Fig.) [26]. This stabilizing interaction was absent in the EGFR L858M/L861R model, likely contributing to the reduced erlotinib binding efficiency (S11B Fig.).

To further investigate, we measured the total solvent accessible surface area (SASA), which quantifies the surface area exposed to the solvent and is related to van der Waals interactions and hydrophobic/hydrophilic effects [27,28]. We found that the EGFR L858M/L861R model had a reduced SASA (16,144.3 Å²) compared to the L858R/L861Q model (16,184.7 Å²) (S11C and S11D Fig.). This suggests that the EGFR L858M/L861R mutation result in a narrower drug-binding pocket, potentially hindering EGFR-TKI binding and reducing drug efficacy.

Discussion

With the increase of NGS panel tests, the identification of uncommon EGFR mutations, such as L858M/L861R, has become more frequent. However, there is insufficient data on the efficacy of EGFR-TKIs to the newly identified EGFR mutations [5,6]. This study aimed to elucidate the oncogenic properties of the EGFR L858M/L861R mutation and assess their response to different generations of EGFR-TKIs.

Our findings confirm that EGFR L858M/L861R mutation possess strong oncogenic potential, as demonstrated by robust growth in IL-3–depleted media in Ba/F3 cell lines and anchorage-independent colony formation in NIH-3T3 cells expressing the mutation. These results underscore the transformative potential of this mutation in driving tumorigenesis and highlight its clinical significance despite its rarity.

Among the EGFR-TKIs, afatinib demonstrated superior efficacy in Ba/F3 and NIH-3T3 cell lines expressing EGFR L858M/L861R. Consistent with a previous report [7] and our clinical observation, first-generation EGFR-TKIs exhibited significantly reduced activity against this mutation. Furthermore, we also validated the enhanced efficacy of afatinib in human lung cancer cells expressing EGFR L858M/L861R, as evidenced by its lowest IC₅₀ value and the highest induction of apoptotic markers. These findings suggest that afatinib may confer therapeutic benefit in patients harboring EGFR L858M/L861R mutation, supporting the notion that second-generation EGFR-TKIs, with their broader spectrum of EGFR inhibition, represent a promising therapeutic strategy for rare EGFR mutations.

Through computational protein modeling, difference in the drug-binding pocket may hinder effective drug binding, explaining lower responsiveness of EGFR L858M/L861R mutation to first-generation EGFR-TKIs.

In all EGFR-mutant cell line models in this study, afatinib demonstrated greater in vitro efficacy than osimertinib. This observation aligns with previous findings [29], which exhibited that second-generation EGFR-TKIs possess higher potency than third-generation EGFR-TKIs in cell line models harboring EGFR exon 19 deletion and L858R.

Although afatinib may appear more potent than osimertinib in vitro cell line models, this efficacy has not been proven in vivo model or clinical cohorts. Therefore, its clinical superiority remains uncertain. Third-generation EGFR-TKIs are more effective against EGFR T790M mutation, the most prevalent resistance mechanism following first- and second-generation EGFR-TKIs [29]. Moreover, osimertinib has superior central nervous system penetration and clinical efficacy in treating brain metastasis [30]. Given the osimertinib’s efficacy against resistance mutations and its activity in the brain, further animal model studies and clinical studies are required to determine whether afatinib offers superior clinical benefit over osimertinib in patients with EGFR L858M/L861R mutation. These further investigations will guide optimal treatment strategies in patients with rare mutation.

In conclusion, our study underscores the potential of mutation-specific treatment strategies for NSCLC patients harboring rare EGFR L858M/L861R mutation, with second-generation EGFR-TKIs like afatinib demonstrating promising activity. By addressing the specific oncogenic and therapeutic characteristics of this mutation, our findings contribute to the advancement of precision medicine strategies aimed at maximizing therapeutic benefits and improving patient outcomes in the era of targeted cancer therapies.

Electronic Supplementary Material

Supplementary materials are available at Cancer Research and Treatment website (https://www.e-crt.org).

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NOTES

Ethical Statement

This study was conducted after the review and approval of the institutional review board (IRB approval number: H-2408-127-1563) and in accordance with the Declaration of Helsinki. Comprehensive data on patient characteristics, treatments, response, and survival were collected. Written informed consent was obtained from the patient.

Author Contributions

Conceived and designed the analysis: Lee C.

Collected the data: Lee C, Kim S (Sheehyun Kim), Youk J.

Contributed data or analysis tools: Lee C, Kim S (Sheehyun Kim), Youk J.

Performed the analysis: Lee C, Kim S (Sheehyun Kim).

Wrote the paper: Lee C, Kim S (Sheehyun Kim), Kim S (Soyeon Kim), Park T, Kim M, Keam B, Kim TM, Kim DW, Youk J.

Conflicts of Interest

Dr. J Youk received advisory or consulting fees from Boryung and Daiichi Sankyo. Additionally, Dr. J Youk received honoraria for lectures or presentations from Astellas, AstraZeneca, Merck, Novartis, Celltrion, Yuhan, and Boryung. Furthermore, Dr. J Youk received support from Genentech for meeting attendance and/or travel expenses.

Dr. D-W Kim’s institution, Seoul National University Hospital, received research funding from Alpha Biopharma, Amgen, AstraZeneca, Bristol-Myers Squibb (BMS), Boehringer Ingelheim, Bridge Biotherapeutics, Chong Kun Dang, Daiichi Sankyo, GlaxoSmithKline (GSK), Hanmi, IMBDx, InnoN, IQVIA, Janssen, Merck, Merus, Mirati Therapeutics, MSD, Novartis, ONO Pharmaceutical, Pfizer, Roche/Genentech, Takeda, TP Therapeutics, Xcovery, and Yuhan. Additionally, Dr. D-W Kim received fees for medical writing assistance from Amgen, AstraZeneca, BMS, Boehringer Ingelheim, Bridge Biotherapeutics, Chong Kun Dang, Daiichi Sankyo, GSK, IMBDx, Janssen, Merus, Mirati Therapeutics, MSD, Merck, Novartis, Pfizer, Roche, Takeda, and Yuhan.

Dr. TM Kim’s institution, Seoul National University Hospital, received clinical trial funding from AbbVie, Amgen, AstraZeneca/MedImmune, Bayer, BeiGene, Black Diamond Therapeutics, Blueprint Medicines, Boehringer Ingelheim, Boryung, Bristol Myers Squibb, Celgene, Daiichi Sankyo, Dizal Pharma, EMD Serono Inc., Enliven Therapeutics, F. Hoffmann-La Roche Ltd./Genentech, Inc., Fore Biotherapeutics, Hanmi, Genmab, Incyte, Janssen, Merck & Co., Inc., Novartis, Pfizer, RAPT Therapeutics, Regeneron, and Samsung. Additionally, Dr. TM Kim received consulting fees from AstraZeneca, Daiichi Sankyo, HK inno.N, IMBDx Inc., Janssen, Merck KGaA, Novartis, Regeneron, Roche/Genentech, Samsung Bioepis, and Chong Kun Dang Pharmaceutical. Furthermore, Dr. TM Kim received payments for speaker’s bureau engagements from AstraZeneca/MedImmune, Amgen, Janssen Research & Development, and Takeda.

Dr. TM Kim also received fees for participation on a data safety monitoring board or advisory board from AstraZeneca, Janssen, Regeneron, Roche/Genentech, Samsung Bioepis, and Takeda. Dr. M Kim received advisory or consulting fees from Yuhan, Pfizer, MSD, Janssen, Astellas Pharma, Bayer, Merck, Boryung, Takeda, Ono Pharmaceutical, Bristol-Myers Squibb, and Boehringer Ingelheim. Additionally, Dr. M Kim received honoraria for lectures or presentations from Astellas Pharma, Merck, Ono Pharmaceutical, Janssen, and Bristol-Myers Squibb. Furthermore, Dr. M Kim received support from Regeneron Pharmaceuticals for meeting attendance and/or travel expenses.

All these conflicts of interest are outside the scope of the submitted work. The other authors declare no potential conflicts of interest.

Funding

This research was supported by Research Program 2023 from the Seoul National University College of Medicine Research Foundation (800-20230540).

Fig. 1.

Clinical history and genomic profiling of the patient. (A) Timeline of the patient’s clinical history, with computed tomography images taken at different time points, as indicated by connecting lines. (B) Integrative Genomics Viewer (IGV) capture displaying epidermal growth factor receptor (EGFR) mutation at the L858 and L861 sites. Carbo, carboplatin; chemo, chemotherapy; COVID-19, coronavirus disease 2019; Doce, docetaxel; Erlo, erlotinib; Gem, gemcitabine; GKS, gamma knife surgery; LUAD, lung adenocarcinoma; meta, metastasis; PD, progressive disease; Pem, pemetrexed; Pembro, pembrolizumab; PNA, peptide nucleic acid; PR, partial response; SD, stable disease; VAFs, variant allele frequencies; WBRT, whole brain radiation therapy.

Fig. 2.

Oncogenic potential of epidermal growth factor receptor (EGFR) L858M/L861R mutation. (A) Growth curves of EGFR-mutant Ba/F3 cell lines. Cells were cultured in interleukin 3 (IL-3)–free media, with Ba/F3 parental cells serving as a control. The p-values for the comparisons were as follows: L861R vs. L858M/L861R, p=0.014; L861Q vs. L858R/L861Q, p=0.019. Statistical significance was determined using an unpaired t test (^*p < 0.05). (B) Relative phospho-EGFR expression normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) control. (C) Soft agar colony formation assay for NIH-3T3 cell lines harboring EGFR mutation. The images represent the central nine regions of the total assay area.

Fig. 3.

Efficacy of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) on cell viability of EGFR-mutant cell lines. (A-F) Cell viability assay results for Ba/F3 cell lines expressing various EGFR mutations, including L858M (A), L858R (B), L861R (C), L861Q (D), L858M/L861R (E), and L858R/L861Q (F) following treatment with EGFR-TKIs for 72 hours. Data are presented as mean±standard deviation. (G) Heat map visualization of IC₅₀ values for EGFR-TKIs across different EGFR-mutant–expressing Ba/F3 cell lines. (H) Graph comparing IC₅₀ values, with data transformed into log2 values.

Fig. 4.

Effects of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) on EGFR signaling in EGFR-mutant cell lines. Immunoblot assay of EGFR signaling in Ba/F3 cell lines expressing L858M (A), L858R (B), L861R (C), L861Q (D), L858M/L861R (E), and L858R/L861Q (F) mutation following 4-hour treatment with EGFR-TKIs. GAPDH, glyceraldehyde 3-phosphate dehydrogenase; NT, no treatment.

Fig. 5.

Computational modeling of drug affinity and binding patterns for epidermal growth factor receptor (EGFR) L858M/L861R vs. L858R/L861Q. (A) Heatmap of drug binding affinity (kcal/mol), where larger negative values indicate higher affinity. (B) Protein surface representation of EGFR L858R/L861Q docked with erlotinib. (C) Protein surface representation of EGFR L858M/L861R docked with erlotinib. The EGFR protein is shown in light gray, and erlotinib is highlighted in hot pink.

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Preferential Sensitivity of the EGFR L858M/L861R Mutation to Second-Generation EGFR Tyrosine Kinase Inhibitors in Non–Small Cell Lung Cancer

DOI: https://doi.org/10.4143/crt.2025.279

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Preferential Sensitivity of the EGFR L858M/L861R Mutation to Second-Generation EGFR Tyrosine Kinase Inhibitors in Non–Small Cell Lung Cancer

Fig. 1. Clinical history and genomic profiling of the patient. (A) Timeline of the patient’s clinical history, with computed tomography images taken at different time points, as indicated by connecting lines. (B) Integrative Genomics Viewer (IGV) capture displaying epidermal growth factor receptor (EGFR) mutation at the L858 and L861 sites. Carbo, carboplatin; chemo, chemotherapy; COVID-19, coronavirus disease 2019; Doce, docetaxel; Erlo, erlotinib; Gem, gemcitabine; GKS, gamma knife surgery; LUAD, lung adenocarcinoma; meta, metastasis; PD, progressive disease; Pem, pemetrexed; Pembro, pembrolizumab; PNA, peptide nucleic acid; PR, partial response; SD, stable disease; VAFs, variant allele frequencies; WBRT, whole brain radiation therapy.

Fig. 2. Oncogenic potential of epidermal growth factor receptor (EGFR) L858M/L861R mutation. (A) Growth curves of EGFR-mutant Ba/F3 cell lines. Cells were cultured in interleukin 3 (IL-3)–free media, with Ba/F3 parental cells serving as a control. The p-values for the comparisons were as follows: L861R vs. L858M/L861R, p=0.014; L861Q vs. L858R/L861Q, p=0.019. Statistical significance was determined using an unpaired t test (*p < 0.05). (B) Relative phospho-EGFR expression normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) control. (C) Soft agar colony formation assay for NIH-3T3 cell lines harboring EGFR mutation. The images represent the central nine regions of the total assay area.

Fig. 3. Efficacy of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) on cell viability of EGFR-mutant cell lines. (A-F) Cell viability assay results for Ba/F3 cell lines expressing various EGFR mutations, including L858M (A), L858R (B), L861R (C), L861Q (D), L858M/L861R (E), and L858R/L861Q (F) following treatment with EGFR-TKIs for 72 hours. Data are presented as mean±standard deviation. (G) Heat map visualization of IC50 values for EGFR-TKIs across different EGFR-mutant–expressing Ba/F3 cell lines. (H) Graph comparing IC50 values, with data transformed into log2 values.

Fig. 4. Effects of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) on EGFR signaling in EGFR-mutant cell lines. Immunoblot assay of EGFR signaling in Ba/F3 cell lines expressing L858M (A), L858R (B), L861R (C), L861Q (D), L858M/L861R (E), and L858R/L861Q (F) mutation following 4-hour treatment with EGFR-TKIs. GAPDH, glyceraldehyde 3-phosphate dehydrogenase; NT, no treatment.

Fig. 5. Computational modeling of drug affinity and binding patterns for epidermal growth factor receptor (EGFR) L858M/L861R vs. L858R/L861Q. (A) Heatmap of drug binding affinity (kcal/mol), where larger negative values indicate higher affinity. (B) Protein surface representation of EGFR L858R/L861Q docked with erlotinib. (C) Protein surface representation of EGFR L858M/L861R docked with erlotinib. The EGFR protein is shown in light gray, and erlotinib is highlighted in hot pink.

Fig. 1.

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Fig. 4.

Fig. 5.

Preferential Sensitivity of the EGFR L858M/L861R Mutation to Second-Generation EGFR Tyrosine Kinase Inhibitors in Non–Small Cell Lung Cancer