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. 2026 Jan 27;49(1):31. doi: 10.1007/s13402-025-01152-8

A combined strategy of EGFR-MET bispecific antibody and HER3 ADC to overcome osimertinib resistance in NSCLC

Yuanyuan Wang 1,2,3,#, Haoyue Guo 1,2,3,#, Ruoshuang Han 3,4,#, Yuhan Wu 3,5, Taiping He 1,2,3, Meng Diao 1,2,3, Anwen Xiong 1,2,3, Fei Zhou 1,2,3, Lei Cheng 6, Chao Zhao 6, Xuefei Li 6, Caicun Zhou 1,2,3,✉
PMCID: PMC12847129  PMID: 41591580

Abstract

Purpose

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have been widely used as the standard-of-care first-line treatment for EGFR-mutated non-small cell lung cancer (NSCLC) patients. However, EGFR-TKI resistance has become a major challenge for almost all patients with EGFR-mutated NSCLC. Both amivantamab (EGFR-MET bispecific antibody) and patritumab deruxtecan (HER3 antibody-drug conjugate) have shown promising efficacy in clinical trials for NSCLC resistant to osimertinib. This study aimed to evaluate a novel therapeutic strategy combining amivantamab and patritumab deruxtecan to overcome osimertinib resistance in NSCLC.

Methods

Three osimertinib-resistant non-small cell lung cancer cell lines were established in vitro. Changes in relevant targets between pre- and post-resistance states were explored at the RNA and protein levels. Subsequently, the efficacy and safety of combination therapy were verified in vitro and in vivo respectively. Changes in treated mice immune microenvironment post-combination therapy were analyzed by flow cytometry, while bulk-RNA sequencing was conducted on tumor tissues.

Results

We found that in vitro studies, when combined, amivantamab and patritumab deruxtecan both exhibited a synergistic effect on cell lines that were sensitive or resistant to Osimertinib, and the use of amivantamab increases the expression of HER3 in certain cell lines. Furthermore, the combination therapy polarized macrophages toward the M1 phenotype in vivo, thereby constructing an immune microenvironment unfavorable for tumor growth.

Conclusion

In conclusion, we have proposed a new therapeutic strategy for NSCLC after osimertinib resistance. The combined strategy of amivantamab and patritumab deruxtecan highlight a promising therapeutic avenue, warranting future clinical trials to validate safety and efficacy.

Keywords: Non-small cell lung cancer, Epidermal growth factor receptor, Drug resistance, HER3, Antibody drug conjugate

Introduction

Mutations of the epidermal growth factor receptor (EGFR) constitute one of the common mutation patterns in non-small cell lung cancer (NSCLC) [1, 2]. The most frequent mutation forms of EGFR mutations are exon 19 deletion (Ex19del) and L858R substitution mutations. Osimertinib, as the third-generation EGFR tyrosine kinase inhibitor (TKI), has currently served as the first-line treatment for these patients because of its outstanding therapeutic efficacy [3, 4]. However, almost all patients treated with osimertinib have developed drug resistance [5]. The established spectrum of resistance mechanisms predominantly manifests through two distinct pathways: those directly involving EGFR signaling (notably C797/G796 mutations) and alternative routes bypassing EGFR regulation (principally MET/HER2 amplifications) [6, 7]. However, the resistance mechanisms of many patients remain unclear, and how to develop effective strategies subsequent to osimertinib resistance has emerged as a novel challenge.

As a bispecific antibody targeting both EGFR and MET, Amivantamab (JNJ-61186372) exhibits therapeutic efficacy through ligand blocking, receptor degradation, and immune cell-directing activity—three distinct mechanisms of action (MOAs) that synergistically mediate its pharmacological effects [8–11]. Amivantamab combined with carboplatin-pemetrexed chemotherapy demonstrated superior efficacy versus chemotherapy alone, and has received FDA approval for treating adults with locally advanced or metastatic NSCLC harboring EGFR exon 20 insertion mutations [12]. Meanwhile, studies on NSCLC after resistance to osimertinib are also being carried out vigorously. The CHRYSALIS-2 study (NCT04077463) enrolled patients with EGFR-mutated advanced NSCLC who experienced disease progression on EGFR-TKIs, the objective response rate (ORR) of amivantamab-lazertinib-chemotherapy cohort is 50% [13]. Subsequently, the MARIPOSA-2 (NCT04988295) study enrolled patients with EGFR-mutated (Ex19del or L858R) locally advanced or metastatic NSCLC after disease progression on osimertinib, the progression-free survival (PFS) demonstrated significant prolongation in both amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy treatment arms when compared to chemotherapy alone [6.3 and 8.3 versus 4.2 months, respectively] [14]. All these pieces of evidence fully demonstrate the significance of amivantamab in the investigation of treatment strategies after osimertinib resistance and combination therapy is often superior to monotherapy.

HER3 (Erb-b2 receptor tyrosine kinase 3, encoded by the ERBB3 gene) is a pseudokinase from the same family as EGFR and was observed in 82.7% of the NSCLC primary tumors and 91.2% of brain metastases and studies have revealed that EGFR-TKI therapy could be the compensatory upregulation of HER3 [15–17]. Because of the widely expression, targeting HER3 becomes a potential strategy being tested within ongoing preclinical research frameworks in NSCLC including monoclonal antibodies and antibody-drug conjugate (ADC) [18]. Patritumab deruxtecan (HER3-Dxd; U3-1402) represents an innovative ADC incorporating three essential components: a human HER3-targeting antibody (patritumab), a tetra-peptide based linker, and a topoisomerase I inhibitor (DX-8951 derivative, or DXd) [19]. In the phase I dose-escalation/expansion study U31402-A-U102 (NCT03260491), patritumab deruxtecan demonstrated durable responses and a median overall survival (OS) of 16.2 months in extensively pretreated patients with EGFR-mutated NSCLC, including those with prior third-generation EGFR TKI therapy [20]. Two clinical trials are further evaluating HER3-DXd in EGFR-mutated NSCLC: the phase II HERTHENA-Lung01 (NCT04619004) in patients progressing after EGFR TKI and platinum-based chemotherapy, and the phase III HERTHENA-Lung02 (NCT05338970) comparing HER3-DXd versus platinum-based chemotherapy after disease progression with a third-generation EGFR TKI [20, 21].

Given that the amivantamab and patritumab deruxtecan have achieved encouraging results in the treatment after EGFR-TKI resistance, and studies have confirmed that effective inhibition of EGFR can increase the membrane expression of HER3 [22], we propose a hypothesis that the combination of EGFR-MET bispecific antibody and HER3 ADC after osimertinib resistance can yield a synergistic effect, and continue to explore the underlying mechanism.

Materials and methods

Cell lines and drug compounds

The human lung adenocarcinoma cell lines H1975 (EGFRL858R/T790M) (RRID: CVCL_1511), HCC827(EGFR19del) (RRID: CVCL_2063), PC9(EGFR19del) (RRID: CVCL_B260) were obtained from the Lung Immunology Research Unit at Shanghai Pulmonary Hospital. These cell models were maintained in DMEM (Gibco, Grand Island, NY, USA) supplemented with 10% fetal bovine serum (Gibco) and 1% penicillin-streptomycin (Gibco), cultured under standardized conditions of 37 °C with 5% CO2 in a humidified incubator. Osimertinib (Cat# S7297), amivantamab (Cat# A2601), patritumab deruxtecan (Cat# D4004) was purchased from SelleckChem (Houston, TX, USA). We hereby confirm that all cell lines used in this study have undergone short tandem repeat (STR) profiling analysis. The generated STR profiles were cross-verified with established reference databases (e.g., ATCC, DSMZ) to authenticate species origin and ensure absence of interspecies contamination. All experimental procedures exclusively utilized mycoplasma-free cell cultures.

Generation of osimertinib-resistant (OR) cellular models

Refer to the practices of previous studies [23–25], H1975OR, HCC827OR and PC9OR, were newly established in our laboratory by exposing H1975, HCC827 and PC9 cells to stepwise escalating concentrations of osimertinib starting at 10 nM. Following overnight incubation with osimertinib-supplemented culture medium, drug-free medium replacement was conducted at 48-hour intervals. Subsequent two-fold dose reintroduction was implemented upon confirmation of cellular proliferation recovery, ultimately establishing sustained exposure at 1 µM concentration over 6-month experimental duration. Based on whole exome sequencing (WES) sequencing of these cell lines, we did not detect C797S mutation in EGFR (Supplementary Fig. 1).

Antiproliferation assay

We used Cell Counting Kit-8 (CCK8) (Dojindo, Kumamoto, Japan) to compare the proliferation ability of cell lines before and after treatment with osimertinib. We seeded 3000 cells per well and cultured until adherent. Then, 100 ul of medium containing different concentration gradients of osimertinib was added to each well for treatment. Each concentration gradient was set up in six replicate wells. After incubation for 72 h, the original medium was discarded, and 100 ul of fresh medium containing 10% CCK8 solution was added for further incubation for two hours. The absorbance at 450 nm was detected using Varioskan LUX (Thermo Scientific, Waltham, MA, USA). The half-maximal inhibitory concentration (IC50) of cell lines were calculated by GraphPad Prism 9 (GraphPad, La Jolla, CA, USA). Then, the resistance index (RI) of those cells was calculated with the following formula: IC50 (resistance) / IC50 (sensitive). We employed a similar methodology to calculate the inhibition rates of cells under varying concentrations of amivantamab and patritumab deruxtecan, and utilized the Calcusyn software (http://www.combosyn.com/) to compute their combined effects [26, 27].

Flow cytometry for cell lines

We collected cells and stained for viability (BD Pharmingen, San Diego, CA, USA, Cat#564406, RRID: AB_2869572), blocked with an Fc-block reagent (BD Pharmingen, Cat#553141), stained for surface markers EGFR (Novus, Littleton, CO, USA, Cat#NB600-724PE, PE, RRID: AB_3195682), MET (Novus, Cat#NBP2-44306AF647, AF467, RRID: AB_3308587) and HER3 (BD Pharmingen, Cat#751787, BV650, RRID: AB_2875762). Cellular specimens underwent acquisition via Cytek Aurora flow cytometer (Cytek, Fremont, California, USA) with subsequent analytical processing executed in FlowJo computational platform (Version 10.8.1, TreeStar, Ashland, OR, USA).

Western blot

We collected cells and detect protein expression through Western Blot. Cellular lysis was performed utilizing RIPA buffer supplemented with phosphatase inhibitor and protease inhibitor to preserve phosphorylation signaling integrity. We conducted the Western Blot experiment according to the protocol previously reported [28]. The following antibodies were used: anti-EGFR Antibody (CST, Danvers, MA, USA, Cat# 4267 S, 1:1000, RRID: AB_2246311), anti-Phosphorylated-EGFR Antibody (CST, Cat#3777S, 1:1000, RRID: AB_2096270), anti-MET Antibody (CST, Cat# 8198 S, 1:1000, RRID: AB_10858224), anti-Phosphorylated-MET Antibody (CST, Cat#3077S, 1:1000, RRID: AB_2143884), anti-HER3 Antibody (CST, Cat# 12708 S, 1:1000, RRID: AB_2721919), anti-Phosphorylated-HER3 Antibody (CST, Cat#4791S, 1:1000, RRID: AB_2099709), and anti-β-Tubulin Antibody (CST, Cat#2146S, 1:1000, RRID: AB_2210545).

Bulk RNA sequencing and analysis

Total RNA was extracted using the RNeasy Mini Kit (Qiagen, Duesseldorf, Germany), followed by RNA quantification and quality assessment performed with both the Qubit 3.0 Fluorometer (Life Technologies, Gaithersburg, MD, USA) for precise concentration measurement and the Nanodrop One spectrophotometer (Thermo Fisher) for purity evaluation. Paired-end libraries were synthesized by using the mRNA-seq Lib Prep Kit for Illumina (ABclonal, Wuhan, China) following Sample Preparation Guide. Purified libraries were quantified by Qubit 3.0 Fluorometer (Life Technologies) and validated by Agilent 2100 bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) to confirm the insert size and calculate the mole concentration. Cluster was generated by cBot with the library diluted to 10 pM and then were sequenced on the Illumina NovaSeq 6000 (Illumina, San Diego, CA, USA). Paired-end sequence files (fastq) were mapped to the reference genome (mouse: GRCm39.108; human: GRCh38.108) using Hisat2 (Hierarchical Indexing for Spliced Alignment of Transcripts, version 2.0.5). Gene abundance was expressed as fragments per kilobase of exon per million reads mapped (FPKM). For the detection of differential gene expression, edgeR package was used [29, 30]. Genes meeting statistical significance criteria (FDR < 0.05 or p-value < 0.05) with absolute fold change > 2 were defined as differentially expressed. Transcriptional profiles of DEGs were visualized through heatmap clustering, with hierarchical classification applied to group genes sharing similar expression patterns.

Functional annotation of DEGs was conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and Gene Ontology (GO) category database. Analytical thresholds required a minimum inclusion of five DEGs per GO/KEGG category or pathway for retained categories. Functional enrichment evaluation was executed with the R clusterProfiler package (v3.18.1) to identify statistically overrepresented biological terms [31]. Pathway enrichment evaluation employed the hypergeometric distribution through R’s “phyper” function for statistical verification. Biological categories demonstrating FDR < 0.05 in GO/KEGG analyses were designated as statistically significant, whereas pathways achieving p-value < 0.05 demonstrated statistically relevant enrichment.

In vivo pharmacodynamic study

HCC827OR cell suspensions (1*107 cells mixed with 50% Matrigel, Corning Cat#354248) were subcutaneously inoculated into the right flank of 6-week-old female CB17-SCID mice. Tumor progression was assessed through caliper measurements every four days post-implantation. Upon reaching tumor volumes of 150–250 mm3, animals underwent volume-based randomization into therapeutic groups receiving: Osimertinib (5 mg/kg, qd, i.g), amivantamab (10 mg/kg, biw, i.v), patritumab deruxtecan (10 mg/kg, qw, i.v), amivantamab (5 mg/kg, biw, i.v) combined with patritumab deruxtecan (5 mg/kg, qw, i.v), or PBS control. Tumor dimensions and body mass were recorded every four days during treatment. Humane euthanasia criteria were triggered at tumor volumes > 2000 mm3, followed by collection of tumor tissues, peripheral blood, and spleen specimens for downstream analysis. All experimental protocols were approved by the ethics committee of Shanghai Pulmonary Hospital. Animal experiments complied with institutional and national guidelines for welfare, including the use of anesthesia and humane endpoints. This research strictly followed ethical standards.

Flow cytometry for immune cells

We collected immune cells from the spleen by grinding and centrifugation, and from peripheral blood by centrifugation. Then we lysed red blood cells using the Lysing Buffer(BD Pharmingen, Cat#555899) and stained for viability (BD Pharmingen, Cat#564406), blocked with an Fc-block reagent (BD Pharmingen, Cat#553141), stained for surface markers CD45 (BD Pharmingen, Cat#557659, APC-Cy7, RRID: AB_396774), CD11b (BD Pharmingen, Cat#557396, FITC, RRID: AB_396679), F4/80 (BD Pharmingen, Cat#565411, BV421, RRID: AB_2734779), CD86 (BD Pharmingen, Cat#740877, BV786, RRID: AB_2740528), Ly-6 C (BD Pharmingen, Cat#560594, V450, RRID: AB_1727559), NK1.1 (BD Pharmingen, Cat#551114, PerCP-Cy5.5, RRID: AB_394052) and Ly-6G (BD Pharmingen, Cat#563005, BV605, RRID: AB_2737946). Following cell processing, intracellular staining was performed using the Fixation/Permeablization Kit (BD Pharmingen, Cat#554714), with subsequent targeting the CD206 epitope (Biolegend, Cat#141720, PE/Cyanine7, RRID: AB_2562248). Cell acquisition and detection were conducted on the Cytek Aurora cytometer (Cytek, USA), followed by computational analysis via FlowJo software (Version 10.8.1, USA).

Immune infiltration estimation

RNA-seq datasets were subjected to computational deconvolution via the CIBERSORT algorithm for systematic evaluation of tumor-infiltrating immune cell (TIIC) quantify proportions and distributions [32, 33]. The LM22 signature algorithm was applied for precise determination of 22 tumor-infiltrating immune cell (TIIC) subtype abundances. Parallel computational analysis implemented the ESTIMATE algorithm (Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data) to derive sample-specific immune scores (indicating proportional representation of immune cells) and stromal scores (denoting stromal cell prevalence) [34]. The marker genes corresponding to immune cell types in mouse were identified from a single-cell RNA sequencing (scRNA-seq) dataset (GSE195965).

Data analysis

All computational procedures were executed in GraphPad Prism 9 (GraphPad, USA) with implementation of Student’s t-test, Chi-squared test, and ANOVA for statistical comparisons contingent upon data characteristics. The threshold for biological significance was established at probability values below 0.05 (p < 0.05).

Results

The characteristics of osimertinib-resistant (OR) cell lines

To investigate the therapy of osimertinib-resistant NSCLC, we take establishing three types of osimertinib-resistant cell lines with different initial gene expressions as the first step, including H1975 (EGFRL858R/T790M), HCC827(EGFR19del) and PC9(EGFR19del). After a long period of continuous exposure to increasing doses of osimertinib, these cell lines acquired new characteristics. We examine the proliferation of these cell lines by employing the CCK8 assay to obtain the IC50 value and then to calculate the RI of H1975OR, HCC827OR and PC9OR, the results are 12104.4, 75.16 and 258.8 respectively (Fig. 1a). Next, we detected the expression of these three relative targets (EGFR, MET, and HER3) at the mRNA and protein levels in these cell lines. Based on the results of RNA sequencing, we found that the expression of EGFR was lower in the HCC827OR and PC9OR cell lines compared to the cell lines before obtaining osimertinib resistance, the expression of MET was lower in the H1975OR and HCC827OR cell lines but obviously higher in the PC9OR cell line. In the expression of HER3, merely the HCC827OR cell line exhibited an increase, whereas the expression of H1975OR and PC9OR cell lines declined to a point of almost no expression (Fig. 1b). Subsequently, we employed western blot to examine the total protein expression of these three targets within the cells, a trend essentially replicating the same result as that of RNA sequencing was observed (Fig. 1c). As these proteins are expressed in multiple locations within the cell [35–37], and considering the characteristics of drug action, it is requisite for us to employ flow cytometry to detect the protein expression on the cell membrane. Based on the percentage of positive cells on the cell surface and the median fluorescence intensity (MFI) of positive cells, we found that the relevant surface targets of the H1975OR and PC9OR cell lines had lessened to various extents, while the HCC827OR cell line had remained essentially unchanged (Fig. 1d-f). Hence, through integrating the outcomes of total protein expression and protein expression on the cell membrane, the HCC827OR cell line was selected for tumor model construction in the subsequent in vivo experiments.

Fig. 1.

Fig. 1

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Molecular profiling of acquired osimertinib resistance (OR) in NSCLC cell lines. (a) The proliferative capacity of cell lines was evaluated using CCK-8 assay after 72-hour exposure to osimertinib at concentrations ranging from 0.01 nM to 100 µM, with subsequent determination of the half-maximal inhibitory concentration (IC50). Error bars represent mean ± standard error of the mean (SEM). N = 6. (b) The relative mRNA expression of cell lines. The FPKM in each group was compared using the Student’s t-test. Error bars represent mean ± standard error of the mean (SEM). N = 3. (c) The total protein expression examined by western blot. (d) Flow cytometry gating protocol was established as follows: Cell doublets were excluded through FSC-A vs. FSC-H parameter analysis, followed by identification of viable cells using a viability dye exclusion strategy (negative selection). Determine the boundary between the positive and negative groups using positive control with single dye and negative control. N = 3. (e) The proportion of positive cells among the live single cells was compared using the Student’s t-test. Error bars represent mean ± standard error of the mean (SEM). N = 3. (f) The median fluorescence intensity (MFI) of positive cells among the live single cells was compared using the Student’s t-test. Error bars represent mean ± standard error of the mean (SEM). N = 3. (g) Volcano plots of differential genes detected by RNA-seq. (h) Heatmaps of differential genes detected by RNA-seq. N = 3. (i) GO enrichment heatmap depending the mRNA rich factor; (j) KEGG enrichment heatmap depending the mRNA rich factor. N = 3. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001

We attempted to identify the osimertinib resistance mechanisms of these three pairs of cell lines through RNA sequencing and carried out differential gene analysis and clustered the differential genes to generate heatmaps. For each pair of cell lines, we identified over 3,000 differentially expressed genes (Fig. 1g-h), which were enriched in different pathways in the KEGG and GO databases, such as ERBB2 − EGFR signaling pathway, regulation of SMAD protein complex assembly, type II transforming growth factor beta receptor binding, positive regulation of nuclear cell cycle DNA replication and so on (Fig. 1i-j, high-resolution versions of these figures have been provided as Supplementary Fig. 3–4). However, no obvious common pathways altered after the same osimertinib resistance model establishing process were found among these cell lines, which is consistent with the current research status of the complex and not fully elucidated EGFR-TKI resistance mechanisms [6]. Further clarifying the mechanism of resistance will be the direction of our future efforts.

Osimertinib’s effect on resistant cell lines in vitro

To further confirm the resistance of these cell lines, we treated these three pairs of cell lines with different concentrations of osimertinib in vitro for 8 h and detected the relative protein expression levels (Fig. 2a). As the concentration of osimertinib increased, the phosphorylation of EGFR was inhibited to varying degrees in all tested cell lines, the expression of HER3 in all tested cell lines was elevated to varying degrees, and this phenomenon was more pronounced in experiments with higher concentration gradients (Supplementary Fig. 2a), which is consistent with previous published studies: effective inhibition of EGFR can increase the expression of HER3 [22]. Except for the H1975 cell line that has not been treated with osimertinib, the expression of pHER3 is low or not expressed in the other cell lines, which also indicates that although the expression of HER3 is increased after EGFR is inhibited, the process of phosphorylation of HER3 has not been improved.

Fig. 2.

Fig. 2

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Cell viability and molecular phenotypic modulation in tumor cell lines under differential in vitro intervention paradigms. (a) Following 8-hour in vitro exposure to gradient concentrations of osimertinib (0, 0.1, 0.01, 1µM), western blot analysis was employed to assess corresponding alterations in protein expression profiles across treated cell lines. (b) Cells were treated with different concentrations of amivantamab and patritumab deruxtecan for 72 h. Fraction affected (Fa)-CI plots were used to determine whether there were interactions between the two drugs when combined. The CI values for amivantamab and patritumab deruxtecan were calculated according to Chou-Talalay’s method by CompuSyn software at the 72 h time point and plotted with the percent of cell growth inhibition as the fraction affected (Fa) cells. CI values < 1 indicating drug synergism, CI values = 1 indicating an additive effect and CI values > 1 indicating antagonism. (c) Following 72-hour in vitro exposure to graded concentrations of amivantamab, western blot analysis of cellular lysates was performed to evaluate corresponding alterations in protein expression profiles

Combining amivantamab with patritumab deruxtecan may result in synergistic effects in vitro

In vitro, we set up three groups with five increasing dosage gradients to explore the efficacy of combined medication, including amivantamab monotherapy group (0.25, 0.5, 1, 2, 4 mg/ml), patritumab deruxtecan monotherapy group (0.05, 0.1, 0.2, 0.4, 0.8 mg/ml), and combination group (the above-mentioned corresponding doses be added together). The cell inhibition rate increases with the increase in drug concentration (Supplementary Fig. 2b), and synergistic effects are observed across all concentration combinations whether in the osimertinib sensitive or resistant cell lines (Fig. 2b).

It should be noted that the mechanisms of action of amivantamab have been clearly established, including ligand blocking, receptor degradation, and immune cell-directing activity [8–11]. Since immune cells were not added in vitro culture environment, the mechanisms of action of amivantamab in monotherapy here were limited, so the exploration of efficacy in vitro is not comprehensive.

Amivantamab treatment of some cell lines leads to elevated HER3 expression levels

The combination therapy group achieved better efficacy compared to the monotherapy group, so we investigated whether there were other mechanisms of interaction between the two drugs. We detected the expression of HER3 in cells treated with amivantamab in vitro for 72 h to verify whether amivantamab, as an EGFR-MET bispecific antibody, can also increase HER3 expression like osimertinib after effectively inhibiting EGFR.

As an EGFR - MET bispecific antibody, amivantamab exhibits inhibitory effects on EGFR phosphorylation solely in the H1975 and HCC827 cell lines, and also shows inhibitory effects on MET phosphorylation in the HCC827 cell line. We observed in the H1975 and PC9 cell lines that as the concentration of amivantamab increased, the expression of HER3 also increased; in the H1975OR and HCC827OR cell lines, it was observed that after intervention with a small dose of amivantamab, the expression of HER3 was increased, and when the dose was increased, the expression of HER3 remained unchanged or even decreased (Fig. 2c). This indicates that amivantamab can increase the expression of HER3 under certain conditions, but how to control the dose becomes a problem that needs to be further explored. In the results of this in vitro study, amivantamab did not ultimately lead to an increase in HER3 expression due to EGFR inhibition, unlike osimertinib in other studies.

The combination of amivantamab and patritumab deruxtecan effectively inhibits the growth of HCC827OR xenografts in CB-17 mice

Based on the research data obtained from in vitro studies, we chose the cell line HCC827OR, which showed the most appropriate biomarker expression, to establish cell-derived xenografts. We evaluated the efficacy and safety of these drugs by monitoring the tumor volume, body weight of mice during model establishment and drugs treatment, and by obtaining peripheral blood, spleen, and tumor samples at the observation endpoint for further testing (Fig. 3a).

Fig. 3.

Fig. 3

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Quantitative assessment of antitumor efficacy in xenograft mouse models. (a) Graphical abstract of in vivo experimental design and implementation workflow. (b) Longitudinal body weight trajectories were quantitatively assessed at 4-day intervals throughout the experimental duration. N = 3. (c) Photographic documentation of neoplastic lesions following 16-day therapeutic regimen. N = 3. (d) The tumor growth dynamics were assessed through longitudinal measurements of tumor volume at 4-day intervals, with final endpoint tumor volumes statistically compared among experimental groups using single-factor analysis of variance (ANOVA). Error bars represent mean ± standard error of the mean (SEM). N = 3. (e) Gating strategy of flow cytometry analysis. First, gate the cells into myeloid cells and lymphocytes based on their size and granularity. The cellular aggregates were excluded through dual-parameter FSC-A/FSC-H threshold gating, followed by identification of viable cells via negative selection using fluorescent viability staining, neutrophils were gated by CD11b + Ly6G+, CD11b + Ly6G- cells were divided into macrophages(F4/80+) and monocytes(F4/80-), macrophages were further subdivided into M0(CD86- CD206-), M1(CD86 + CD206-) and M2(CD206+). NK cells were gating according to NK1.1+. (f) Percentage of M0, M1 and M2 macrophages in the total macrophages under different treatments. (g) The proportion of cells was compared with the combination group (amivantamab + patritumab deruxtecan) using two-way ANOVA. Error bars represent mean ± standard error of the mean (SEM). N = 3. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001

In the process of the in vivo experiment, there was little change in mouse weight in five groups, which preliminarily confirmed the safety of combination therapy (Fig. 3b). The tumor volume in the osimertinib group and the control group continued to grow over time. There was little difference between the two groups at the endpoint, further confirming the acquired resistance of the HCC827OR cell line. Amivantamab monotherapy and patritumab deruxtecan monotherapy effectively inhibited tumor growth, with no significant difference between the two groups. It is encouraging that the combination therapy group achieved better efficacy than the monotherapy group, with a statistically significant difference (Fig. 3c-d).

The combination of amivantamab and patritumab deruxtecan promoted the polarization of macrophages to M1 type in vivo

To explore the reasons for the better therapeutic effect of combination therapy other than the simple additive effect, we performed flow cytometry analysis on the spleen and peripheral blood of each mouse respectively to explore the changes in the immune system (Fig. 3e). In the analysis of myeloid cells, we found that the proportion of macrophages in the spleen of the combination therapy group was significantly higher, especially the proportion of M1-type macrophage was higher than that of the other four groups, and the proportion of M2-type macrophage was lower than that of the other four groups, and all had statistical differences, indicating that the macrophages in the spleen of the combination therapy group are more inclined to polarize to M1-type macrophages (Fig. 3f-g).

The proportion of NK cells in the spleen was higher in the amivantamab monotherapy group and the combination therapy group, which might be related to the antibody-dependent cellular cytotoxicity (ADCC) effect of amivantamab [10, 11]. In the peripheral blood, the composition of macrophages did not show obvious differences as in the spleen. However, the significantly lower proportion of M2-type macrophages in the combination therapy group compared to the amivantamab monotherapy group was also a manifestation of the immune system that was not conducive to tumor growth (Fig. 3g).

The combination of amivantamab and patritumab deruxtecan promoted the infiltration of immune cells in vivo

After identifying the differentially expressed genes by conducting RNA-seq on the tumors in mice(Fig. 4a-b), we performed functional annotation using the KEGG database and found that compared with the amivantamab or patritumab deruxtecan monotherapy group, the combination group showed differences in multiple tumor proliferation or metastasis-related signaling pathways or biological processes, such as DNA replication, TNF signaling pathway, Toll-like receptor signaling pathway, TCA cycle, ErbB signaling pathway and so on. (Fig. 4c). Next, after matching the mouse genome, we conducted immune-related analyses. We found that the immune score of the combination group had a tendency to increase compared with other groups by used the ESTIMATE algorithm (Supplementary Fig. 2c). We employ the known scRNA-seq dataset (GSE195965) for deconvolution to undertake further analyze the composition of immune cells infiltrating in the tumor and found that, except for neutrophils, the expressions of most related genes of monocytes, macrophages and dendritic cells in the combination group were significantly higher than those in other groups (Supplementary Fig. 2d). Then we use the CIBERSORT algorithm to quantify the proportions and distributions of tumor-infiltrating immune cells. The conclusion of flow cytometry was basically reproduced except for monocytes, the proportion of M1-type macrophages and activated NK cells in the tumors of the combination group was the highest (Supplementary Fig. 2e).

Fig. 4.

Fig. 4

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RNA-seq based tumor bioinformatics profiling. (a) Volcano plots of differential genes detected by RNA-seq. (b) Heatmaps of differential genes detected by RNA-seq. (c) Bubble diagrams of KEGG enrichment depending the mRNA rich factor

Discussion

During the last several decades, research on EGFR-mutated NSCLC has continuously advanced, and a series of excellent drugs such as gefitinib, erlotinib, afatinib, and osimertinib have emerged successively, improving the outcomes of the vast majority of EGFR-mutated NSCLC patients. However, drug resistance that almost all patients experience has become a challenging problem in current research. Currently, numerous preclinical and clinical studies are underway to address resistance to third-generation EGFR-TKIs [38]. As previously mentioned, amivantamab is being comprehensively explored as a monotherapy or part of combination therapy for the first-line treatment of EGFR-mutated NSCLC and for treating resistance to third-generation EGFR-TKIs. HER3, as a highly anticipated new target, has also seen significant research progress in the ADC field. HER3 is a distinctive member of the EGFR family that has little intracellular tyrosine kinase activity. It needs to form heterodimers with another receptor such as EGFR, HER2, MET and so on to smoothly proceed with downstream phosphorylation reactions [39, 40]. Patritumab deruxtecan targets HER3 and then enters cells to release toxins to destroy tumor cells. Our study is the first to propose the combined use of EGFR-MET bispecific antibody and HER3 ADC for the treatment of NSCLC after osimertinib resistance.

We established three osimertinib-resistant cell lines as research models, explored the efficacy and related molecular phenotypes of the resistant cell lines in vitro, and established a CDX model for in vivo efficacy verification and Immunology research. In vitro experiments revealed that short-term application of osimertinib or amivantamab led to an increase in HER3 expression in some cell lines. The upregulation of HER3 caused by amivantamab might be the mechanism underlying the synergistic effect between amivantamab and patritumab deruxtecan, but more research on the underlying mechanisms is needed to confirm this. However, we also found that HER3 expression was heterogeneously downregulated in osimertinib-resistant cell lines developed via chronic osimertinib exposure relative to their parental counterparts. Currently, there are no large-scale clinical studies confirming the changes in HER3 expression before and after osimertinib resistance, indicating that we need to continue exploring. Besides, current data show that HER3 expression is relatively high in NSCLC, with higher levels in adenocarcinoma than non-adenocarcinoma subtypes and in EGFR-mutated patients compared to wild-type EGFR patients [41]. In clinical studies evaluating patritumab deruxtecan for EGFR-mutated NSCLC progressing post-EGFR TKI and platinum-based chemotherapy, pretreatment HER3 membrane H-score quantification across evaluable tumors confirmed universal expression, antitumor responses were detected throughout the expression continuum, with no significant association emerging between baseline HER3 membrane H-score magnitude and clinical outcomes, which was also discovered in our in vitro research [20, 21]. Consequently whether HER3 expression detection is necessary before the application of HER3 ADC still requires more research to support.

We generally classify polarized macrophages into pro-inflammatory M1-type (classically activated) and pro-tumorigenic M2-type (alternatively activated) [42, 43]. In the in vivo study, we found that compared with the monotherapy group, macrophages in the combination group polarized more towards the M1-type. Previous research has reported if osimertinib is used in combination with anti-HER3 antibodies for treatment, it can stimulate the production of cGAMP by cGAS in cancer cells, transactivating STING in macrophages, reprogram tumor-associated macrophages (TAMs) into the M1-type, and subsequently initiate an anti-tumor immune response [44]. Therefore, in addition to the binding of the Fc region of amivantamab to immune cells triggered by immune cell-directing activity, the combination group may elicit STING-dependent immune responses to promote M1 polarization of macrophages and create an environment that inhibits tumor growth.

Our research also has many limitations. In the in vivo experiments, our animal sample size is too small and exhibits significant bias. Further validation is required using a larger sample size and more cell line models. Due to the small volume of tumor samples at the observation endpoint, there were not enough samples for flow cytometry detection of tumor-infiltrating immune cells. Only RNA-seq was detected and deconvolution was performed to estimate the proportion of immune cells, which may have a gap from the actual situation. The use of different detection methods rendered the results unsuitable for direct comparison. Specifically, some studies comparing flow cytometry and gene expression data deconvolution have found that there is a relatively high consistency between the two methods in certain subsets (such as T cells) [45], but there are significant differences in the ability to distinguish the polarization state of macrophages and the functional subtypes of NK cells. In addition, due to the limitations of experimental conditions, we were unable to establish a humanized mouse model to simulate the human immune environment, and due to ethical restrictions, we were not able to conduct more validations in patient-derived tumor xenografts. Our research mainly demonstrated a phenomenon where combined medication yields better results, but did not conduct detailed studies or explanations on its underlying mechanism of action. This also represents the direction of our future work.

In summary, our study is the first to propose the application of amivantamab combined with patritumab deruxtecan in osimertinib-resistant NSCLC, demonstrated favorable efficacy in both in vitro and in vivo experiments, and provides some directions for future mechanism research. This work provides a novel direction for addressing EGFR-TKI resistance in NSCLC patients in future research.

Author contributions

Yuanyuan Wang, Haoyue Guo and Ruoshuang Han completed the experimental design, data analysis and interpretation. Yuhan Wu, Taiping He and Meng Diao completed the data acquisition and curation. Xuefei Li, Chao Zhao and Lei Cheng provided the experimental technical guidance. Caicun Zhou, Anwen Xiong and Fei Zhou were responsible for project supervision and management. Yuanyuan Wang completed the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by grants from the National Natural Science Foundation of China (No. 82141101), Shanghai Innovative Collaboration Project (No. 2020CXJQ02), Shanghai Shenkang Hospital Development Center (No. SHDC2020CR1036B), Natural Science Foundation of Shanghai (No. 23ZR1453500), and Wu Jieping Medical Foundation (No. 320.6750.2024-16-17).

Data availability

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

All experimental protocols were approved by the ethics committee of Shanghai Pulmonary Hospital (Ethics approval number: K21-313Z). Animal experiments complied with institutional and national guidelines for welfare, including the use of anesthesia and humane endpoints. This research strictly followed ethical standards.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Yuanyuan Wang, Haoyue Guo and Ruoshuang Han contributed equally to this work.

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Associated Data

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Data Availability Statement

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

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