Rare mutation-dominant compound EGFR-positive NSCLC is associated with enriched kinase domain-resided variants of uncertain significance and poor clinical outcomes
BMC Medicine volume 21, Article number: 73 (2023)
Compound epidermal growth factor receptor (EGFR) mutations are less responsive to tyrosine kinase inhibitors (TKIs) than single EGFR mutations in non-small cell lung cancer (NSCLC). However, the detailed clinical characteristics and prognosis of various compound EGFR mutations remain to be elucidated.
We retrospectively studied the next-generation sequencing (NGS) data of treatment-naïve tumors from 1025 NSCLC patients with compound EGFR mutations, which were sub-categorized into different combinations of common mutations (19-Del and EGFR exon 21 p.L858R), rare mutations, and variants of uncertain significance (VUSs). Prognosis and drug resistance to first-line TKIs were analyzed in 174 and 95 patients, respectively.
Compound EGFR mutations were enriched with EGFR exon 21 p.L858R and rare mutations, but not 19-Del (P < 0.001). The common + rare and rare + rare subtypes had fewer concurrent mutations in the PI3K pathway (P = 0.032), while the rare + rare and common + VUSs subtypes showed increased association with smoking- and temozolomide-related mutational signatures, respectively (P < 0.001). The rare mutation-dominant subtypes (rare + VUSs and rare + rare) had the worst clinical outcomes to first-line TKIs (P < 0.001), which was further confirmed using an external cohort (P = 0.0066). VUSs in the rare + VUSs subtype selectively reside in the EGFR kinase domain (P < 0.001), implying these tumors might select additional mutations to disrupt the regulation/function of the kinase domain.
Different subtypes of compound EGFR mutations displayed distinct clinical features and genetic architectures, and rare mutation-dominant compound EGFR mutations were associated with enriched kinase domain-resided VUSs and poor clinical outcomes. Our findings help better understand the oncogenesis of compound EGFR mutations and forecast prognostic outcomes of personalized treatments.
Lung cancer is the second most frequent cancer and the leading cause of cancer-related death worldwide . Non-small cell lung cancer (NSCLC) is the major type of lung cancer, and around 14–38% of NSCLC patients harbor genetic alterations in epidermal growth factor receptor (EGFR) , with the incidence of EGFR mutations higher in East Asian patients than in Caucasian patients [3, 4]. Short in-frame deletions in exon 19 (19-Del) and point mutations in EGFR exon 21 p.L858R are the most common activating mutations in EGFR, accounting for approximately 90% of all EGFR mutations in NSCLC [5, 6]. EGFR tyrosine kinase inhibitors (TKIs) have shown profound clinical benefits and are thus used as the first-line treatment in EGFR-mutated NSCLC patients [7,8,9,10,11,12]. Besides 19-Del and EGFR exon 21 p.L858R, extensive research has uncovered a wide array of rare EGFR activating or resistant mutations in NSCLC, including EGFR exon 18 p.G719X, EGFR exon 20 p.S768I, EGFR exon 21 p.L861Q, EGFR exon 20 p.T790M, and EGFR exon 20 insertions (20ins). Qin et al. found that EGFR 20ins had at least 80 different insertion patterns, and lung cancer patients with EGFR 20ins showed different clinical responses to various EGFR TKIs . The EGFR exon 20 p.T790M mutation confers drug resistance to first-generation EGFR TKIs, and it has been shown to occur in 1–2% of treatment-naïve EGFR-mutated NSCLC patients [14, 15]. In addition to these well-studied common and rare EGFR mutations, EGFR variants of uncertain significance (VUS) were observed in lung cancer patients, but the clinical relevance and TKI sensitivity of these VUSs are largely unknown [16, 17].
Although the majority of EGFR-positive NSCLC patients harbor a single EGFR mutation, recent advances in next-generation sequencing (NGS) technologies have revealed that around 10% of patients harbor compound EGFR mutations, defined by the presence of double or multiple distinct EGFR genetic alterations at baseline [18,19,20]. Several groups reported that patients with compound EGFR mutations tended to be less responsive to TKI therapies than those with a single EGFR mutation [21,22,23,24]. Furthermore, researchers found that the different types of EGFR compound mutations might be associated with distinct treatment efficacies [18, 19]. Despite the potential clinical implications of EGFR compound mutations, most of the previous studies were based on limited patient cohorts, so it is imperative to perform large-scale analyses to gain a deeper insight into the complexity and diversity of compound EGFR mutations in NSCLC. In the present study, we retrospectively studied the NGS data of treatment-naïve tumor samples from 8485 EGFR-mutated NSCLC patients, of whom 1025 had compound EGFR mutations. We explored the clinical characteristics and genetic architecture of different types of compound EGFR mutations, as well as their responses to EGFR TKIs and the associated drug-resistant mechanisms.
Patients and sample collection
Qualified NGS data from a total of 1025 NSCLC patients harboring compound EGFR mutations at baseline from Fudan University Shanghai Cancer Center and Wuxi Branch of Ruijin Hospital were collected as part of the routine diagnosis and treatment. This study was approved by the Ethics Committee of the Fudan University Shanghai Cancer Center, Shanghai Cancer Center Institutional Review Board (SCCIRB), and in accordance with the Declaration of Helsinki (ethics approval number: 2004216–19-2005). Targeted NGS tests were performed in a CLIA-certified and CAP-accredited clinical testing laboratory (Nanjing Geneseeq Technology Inc., Nanjing, China) from April 2016 to October 2020. Of these, 305 were sequenced using a target panel covering 14 key lung cancer-related genes (TETRADECAN™, Geneseeq Technology Inc.) , 312 were sequenced by a 139 lung cancer gene panel (PULMOCAN™, Geneseeq Technology Inc.) , and 408 were profiled by pan-cancer gene panel covering 425 cancer-relevant genes (GENESEEQPRIME™, Geneseeq Technology Inc.) . Specifically, 5 to 10 mL of peripheral blood was collected from each patient in EDTA-coated tubes (BD Biosciences). Plasma was extracted within 2 h of blood collection and shipped to the central testing laboratory within 48 h. Tumor purity of formalin-fixed paraffin-embedded (FFPE) tumor tissue blocks/sections or fresh tumor tissues was confirmed by the pathologists from the centralized clinical testing center. Written consent was collected from each patient.
DNA extraction, quantification, and library preparation
DNA extraction, quantification, and library preparation were performed as previously described . In brief, FFPE samples were de-paraffinized with xylene, and DNA was extracted using the QIAamp DNA FFPE Tissue Kit (Qiagen) according to the manufacturer’s protocols. Genomic DNA from fresh tumor tissue was extracted using the DNeasy Blood & Tissue Kit (Qiagen) according to the manufacturer’s protocols. Peripheral blood samples were centrifuged at 1800 g for 10 min. Then, the plasma was isolated for extraction of cfDNA and the genomic DNA of white blood cells in sediments served as normal controls. The circulating nucleic acid kit (Qiagen, Germany) was used to purify cfDNA from the plasma. The genomic DNA from white blood cells was extracted using the DNeasy Blood and Tissue Kit (Qiagen). Genomic DNA was qualified using a Nanodrop2000 (Thermo Fisher Scientific, Waltham, MA), and cfDNA fragment distribution was analyzed on a Bioanalyzer 2100 using the High Sensitivity DNA Kit (Agilent Technologies, Santa Clara, CA). All DNA was quantified using the dsDNA HS assay kit on a Qubit 3.0 fluorometer (Life Technology, USA) according to the manufacturer’s recommendations. Sequencing libraries were prepared using the KAPA Hyper Prep kit (KAPA Biosystems) with an optimized manufacturer’s protocol and sequenced as previously described .
The mean coverage depth was 1402 × for tissue samples, 5655 × for cfDNA samples, and 162 × for matched control samples. Sequencing data were processed as previously described . In brief, mutation calling Trimmomatic was used for FASTQ file quality control, and leading/trailing low-quality (quality reading below 20) or N bases were removed. Qualified reads were mapped to the reference human genome hg19 using Burrows-Wheller Aligner with default parameters, and Genome Analysis Toolkit (GATK 3.4.0) was employed to apply the local realignment around indels and base quality score recalibration. Picard was used to remove PCR duplicates, and samples with mean dedup depth < 30 × were removed. VarScan2 was employed for the detection of single-nucleotide variations (SNVs) and insertion/deletion mutations. SNVs were filtered out if the mutant allele frequency (MAF) was less than 1% for tumor tissue and 0.3% for plasma samples. Variants were further filtered with the following parameters: (i) minimum read depth = 20, (ii) minimum base quality = 15, (iii) minimum variant supporting reads = 5, (iv) variant supporting reads mapped to both strands, (v) strand bias no greater than 10%, (vi) if present in > 1% population in the 1000 Genomes Project or the Exome Aggregation Consortium (ExAC) 65,000 exomes database, and (vii) filtered by an internally collected list of recurrent sequencing errors using a normal pool of 100 samples. Parallel sequencing of matched white blood cells from each patient was performed to further remove sequencing artifacts, germline variants, and clonal hematopoiesis. The copy number alterations were analyzed as previously described [29, 30]. The tumor purities were first estimated using ABSOLUTE . Somatic copy number alteration events were assigned based on sample-ploidy values calculated in the FACETS algorithm . Loss-of-heterozygosity (LOH) was also calculated using FACETS and determined using the minor copy number estimates of each segment for genes in the targeted panel. The minor copy number is by definition 0 in a LOH event [33, 34]. Structural variants were detected using FACTERA with default parameters . The fusion reads were further manually reviewed and confirmed on Integrative Genomics Viewer (IGV).
Tumor mutational burden (TMB, mutation per Megabase) was determined based on the number of somatic base substitutions and indels in the targeted regions of the gene panel covering 0.85 Mb of coding genome, excluding known driver mutations as they are over-represented in the panel. Chromosome instability score (CIS) was defined as the proportion of the genome with aberrant (purity-adjusted segment-level copy number ≥ 3 or ≤ 1) segmented copy number .
Mutation signature analysis
The samples with the number of synonymous/non-synonymous mutations of ≥ 5 were included for mutation signature analysis , which was conducted using the “maftools” and “sigminer” R packages. Based on the description of the 30 mutational signatures listed on the COSMIC website (https://cancer.sanger.ac.uk/signatures/signaturesv2/), we classified the signatures into 10 groups, including age (COSMIC1), APOBEC (COSMIC2 and COSMIC13), BRCA (COSMIC3), smoking (COSMIC4), dMMR (COSMIC6, COSMIC15, COSMIC20, and COSMIC26), ultraviolet (COSMIC7), immunoglobulin (COSMIC9), POLE (COSMIC10), temozolomide (COSMIC11), and others (the rest of the signatures). The contribution of each signature was the proportion of the selected signature over all the detected signatures in that specific patient, which was calculated based on previous literature [38,39,40].
Kaplan–Meier survival curve was used to analyze the progression-free survival (PFS) of various patient groups, and the statistical difference was analyzed using the log‐rank test. Fisher’s exact test was used to test the categorical variables. The Kruskal–Wallis test was conducted to compare multiple groups. Statistical analyses were performed using the R (v4.1.0), and a two-sided P-value of < 0.05 was considered to be statistically significant (*P < 0.05, **P < 0.01, ***P < 0.001).
Patient characteristics and study plan
A total of 1025 (12.1%, 1025/8485) patients harbored compound EGFR mutations at baseline, that is, two or more distinct EGFR mutations were concomitantly detected in a single tumor sample. We sub-categorized compound EGFR mutations into different combinations of common EGFR mutations (i.e., EGFR 19-Del and EGFR exon 21 p.L858R), rare EGFR mutations (i.e., EGFR exon 18 p.G719X, EGFR exon 20 p.S768I, EGFR exon 21 p.L861Q, EGFR exon 20 p.T790M, and EGFR 20ins), and/or VUSs. Of the 1025 patients, 570 (55.6%) were older than 60 years, and more than half of the patients (57.8%) were females (Additional file 1: Table S1). The majority of the patients (83.1%) were diagnosed with lung adenocarcinoma (ADC), while other patients had lung squamous cell carcinoma (SCC), adenosquamous carcinoma of the lung (ASC), or unknown histologic subtypes (Additional file 1: Table S1). Clinical features, such as programmed death-ligand 1 (PD-L1) expression, disease stage, and tumor mutation burden (TMB) were also available for 20–40% of the patients (Additional file 1: Table S1). Based on the NGS and clinical data from the 1025 patients, we aimed to investigate compound EGFR mutations from various aspects, including the correlation between different types of compound EGFR mutations and the clinical/molecular features, as well as delineating therapeutic response to different first-line EGFR TKIs and potential resistant mechanisms, using patients with available post-TKI follow-up information (n = 174) and patients with paired baseline and progressive disease (PD) samples (n = 95), respectively (Fig. 1A).
Distinct association between compound EGFR mutation subtype and basic clinical features
Among the 1025 compound EGFR mutation-positive patients, only 27 (2.6%) harbored multiple (> 2) EGFR mutations while 97.4% of the patients had dual EGFR mutations (Table 1 and Additional file 1: Fig. S1A). As shown in Additional file 1: Table S2, the presence of multiple EGFR mutations was significantly associated with higher TMB (P = 0.034). For patients with double EGFR mutations, the most frequent combination was common EGFR mutation plus VUSs (common + VUSs; 48.2%), followed by rare EGFR mutation plus VUSs (rare + VUSs; 17.2%), common + rare (12.7%), and rare + rare (12.6%) (Table 1). In contrast, the common + common (i.e., 19-Del + p.L858R) combination was extremely rare, accounting for only 2.3% of the patients (Table 1).
Several clinical features, including age, sex, and TMB, were differentially associated with the type of dual EGFR mutations (Additional file 1: Table S3). Specifically, the rare + VUSs subtype was more likely to occur in younger patients (≤ 60 years old) whereas the co-occurrence of EGFR 19-Del and EGFR exon 21 p.L858R mutations was more frequent in older patients (> 60 years old); in addition, the common + VUSs subtype was more often observed in male patients, and the VUSs + VUSs subtype happened more in patients with higher mutational loads (Additional file 1: Table S3). We also compared compound EGFR mutation-positive patients based on whether or not harboring a common EGFR mutation. Around two-thirds of these patients (64.7%) were positive for common EGFR mutations, and they were more likely to be female and PD-L1 negative (Additional file 1: Table S4). Overall, the different subtypes of compound EGFR mutations demonstrated distinct preferences for certain clinical features in NSCLC patients.
Fewer EGFR 19-Del and more EGFR exon 21 p.L858R and rare EGFR mutations in patients with compound EGFR mutations
In order to compare the difference in EGFR mutational frequency between patients with single EGFR mutation and those with compound EGFR mutations, we categorized compound mutation-positive patients according to the priority from common mutations to rare mutations to VUSs. Therefore, based on the highest priority EGFR mutation, patients with compound EGFR mutations can be divided into three groups, including common (i.e., common + common, common + rare, or common + VUSs), rare (i.e., rare + rare or rare + VUSs), and VUSs (i.e., VUSs + VUSs). Intriguingly, compared with patients with single EGFR mutations, compound EGFR mutation-positive patients had fewer common and more rare EGFR mutations (Fig. 1B). In compound mutation-positive patients with only one common mutation, we performed comparisons between those with EGFR 19-Del and EGFR exon 21 p.L858R. The lowered incidence of common mutations in compound EGFR (64.7% vs 88.0%, P < 0.0001) was mainly due to a decrease in the frequency of EGFR 19-Del (11.5% vs 43.9%, P < 0.0001), whereas EGFR exon 21 p.L858R was more common compared with patients with single EGFR mutations (52.2% vs 44.1%, P < 0.0001; Fig. 1C). In addition, EGFR 19-Del and EGFR exon 21 p.L858R also differed in their concomitant EGFR mutations. EGFR 19-Del was more frequently accompanied by baseline mutations such as EGFR exon 21 p.T790M and EGFR 20ins (P = 0.045 and 0.0029, respectively), while EGFR exon 21 p.L858R more often co-existed with EGFR exon 20 p.S768C/I (P = 0.056) (Fig. 1D).
EGFR VUSs were the commonest co-occurring mutations for both EGFR exon 21 p.L858R and EGFR 19-Del (Fig. 1D). As the function of most VUSs was largely unknown, we evaluated VUSs based on their locations in different EGFR protein domains, including the extracellular domain, transmembrane domain (TM), juxtamembrane domain (JM), kinase domain (KD), and C-terminal tail (Fig. 2A). Intriguingly, the rare + VUSs subtype was highly enriched for KD-located VUSs than other VUS-containing compound EGFR mutation subtypes (Fisher’s exact test P < 0.001; Fig. 2A and Additional file 1: Table S5), implying the potential importance of additional KD aberrations to reinforce the oncogenic activities of rare EGFR mutations.
Genomic characteristics of different types of compound EGFR mutations
A total of 720 patients had baseline tumor samples genetically profiled for 139 key lung cancer-related genes, including EGFR (see the “Methods” section for more details), which enabled the investigation of concurrent genetic alterations. TP53 (50.1%) was the most frequently mutated gene, followed by PIK3CA (10.6%), CTNNB1 (8.9%), and RB1 (7.9%), across the 720 patients (Additional file 1: Fig. S1B). The frequencies of PIK3CA mutations among different compound EGFR mutation subtypes were not uniformly distributed (Fig. 2B). Particularly, patients with common + rare and rare + rare subtypes had lower frequencies of PIK3CA mutations (Fig. 2B). Similarly, the PI3K pathway was under-represented in the common + rare and rare + rare groups (Fig. 2C and Additional file 1: Table S6). In addition, the rare + rare group also had fewer mutations in genes in the RAS/RAF/MEK pathway (Fig. 2C). In contrast, patients with the VUSs + VUSs subtype tended to have the highest proportion of aberrations in almost all the tested oncogenic pathways (Fig. 2C).
Of the 720 patients, 408 underwent large panel targeted sequencing of 425 cancer-relevant genes, including the abovementioned 139 lung cancer-related genes and 286 genes that are frequently mutated in cancers. We performed mutational signature and chromosome instability analyses based on previous studies [41, 42]. An increased number of compound EGFR mutations showed little association with the mutational signature (Additional file 1: Fig. S2). On the other hand, the type of compound EGFR mutations demonstrated a significant relationship with mutational signatures of age, smoking, immunoglobulin, and temozolomide (Fig. 3A). Particularly, the common + rare subtype displayed more age-related signature, the common + VUSs and rare + rare subtypes were more likely to be associated with the smoking signature, and the common + VUSs subtype also had higher immunoglobulin- and temozolomide-related signatures (Fig. 3A). In terms of chromosome instability, patients with double and multiple EGFR mutations had comparable chromosomal instability scores (CISs) (Fig. 3B), whereas patients with the common + common subtype tended to have lower CIS than those with other compound EGFR mutation subtypes (Fig. 3C).
Prognosis of compound EGFR mutation-positive patients in response to first-line EGFR TKIs
Next, we investigated the first-line TKI response in 174 compound EGFR mutation-positive patients who had available follow-up data. Consistent with previous research, compound EGFR mutations were associated with worse progression-free survival (PFS) than single EGFR mutations, and to a higher extent when compared with single EGFR 19-Del mutation (Fig. 4A). As only three out of 174 patients had more than 2 EGFR mutations, we mainly focused our analysis on those with double EGFR mutations. As shown in Fig. 4B, the type of dual EGFR mutations had a significant impact on PFS, with common EGFR mutation-containing subtypes (common + X) associating with improved PFS than the rare EGFR mutation-dominant (rare + VUSs and rare + rare) subtypes (P < 0.001). The poor clinical outcome of rare EGFR mutation-dominant subtypes was further validated using an external cohort of 22 compound EGFR mutation-positive NSCLC patients obtained from the Memorial Sloan Kettering Cancer Center (MSKCC) database (Additional file 1: Fig. S3A). We also divided all patients by the type of first-line EGFR TKIs they received, and the second-generation TKI treatment showed a trend toward having the worst PFS (P = 0.23; Fig. 4C).
Subgroup survival analyses comparing different types of dual EGFR mutations were performed. Patients were subdivided into common EGFR mutation-containing subtypes (common + X), rare EGFR mutation-dominant subtypes (rare + VUSs and rare + rare), and VUS-containing subtypes (any subtypes that contain VUSs). Among patients with common EGFR mutation-containing subtypes, neither the type of common EGFR mutations nor the kind of first-line TKIs had any significant effects on PFS (Additional file 1: Fig. S3B-D). Notably, patients with the 19-Del + X and the L858R + X subtype showed differential survival outcomes to first-line second-generation TKIs, with the 19-Del + X group having a better response and L858R + X displaying unfavorable outcomes. However, the results did not reach statistical significance due to the limited sample size of the subgroups (Additional file 1: Fig. S3E,F). For patients with rare EGFR mutation-dominant subtypes, their PFS could not be further stratified by either mutation subtypes or the specific TKI treatments (Additional file 1: Fig. S4A,B). Lastly, we studied patients with VUS-containing subtypes based on the sites of VUSs on EGFR protein, that is, within KD (KD +) versus outside KD (KD −), and we found that the location of VUSs itself could not effectively separate responders from non-responders (Additional file 1: Fig. S5A). However, upon co-analysis with the other EGFR mutation, patients with the rare + VUSs (KD +) subtype had significantly shorter PFS than those with the common + VUSs (KD +) subtype (P < 0.001) or those with the common + VUSs (KD −) subtype (P < 0.001) (Fig. 4D). Only one patient had the rare + VUSs (KD −) subtype and was not included in the Kaplan–Meier analysis in Fig. 4D; nevertheless, this patient had a PFS of 14 months, which was also significantly better than the median PFS (mPFS) of 6.8 months for patients with the rare + VUSs (KD +) subtype. In addition, we studied the impact of specific types of TKIs in patients with VUS-containing subtypes. The third-generation TKIs tended to be associated with better and worse PFS in VUS (KD +) patients and VUS (KD −) patients, respectively, although neither result reached statistical significance due to the limited patient number (Additional file 1: Fig. S5B,C).
Resistant mechanisms in patients with paired baseline and PD samples
In order to understand the EGFR TKI-resistant mechanisms, we studied 95 compound EGFR mutation-positive patients who had paired baseline and PD NGS data. EGFR exon 20 p.T790M was the most prevalent EGFR-resistant mutation to first-line TKIs, ranging from 9.5% in the baseline samples to 40% in the PD samples (Fig. 5A), and the majority of the acquired EGFR exon 20 p.T790M mutation (22/29; 75.9%) occurred in patients with the common + VUSs subtype (P < 0.001, Additional file 1: Table S7). Additional gained EGFR mutations in PD samples were also observed, including EGFR exon 18 p.L718V, EGFR 20ins, and EGFR exon 20 p.C797S (Fig. 5A). We further investigated the potential off-target resistance mechanisms (Additional file 1: Fig. S6) and found no genetic alterations or signaling pathways that were significantly different between the baseline and the PD samples (Fig. 5B, C). Notably, when comparing patients based on the baseline compound EGFR mutation type, the common + VUSs subtype acquired more mutations in the RAS/RAF/MEK pathway than other subtypes (11.4% vs 0%, P = 0.266, Fig. 5D). Overall, the different compound EGFR mutation types might rely on differential TKI-resistant mechanisms, with the common + VUSs subtype specifically enriched for EGFR exon 20 p.T790M and/or other RAS/RAF/MEK pathway-related mutations.
We performed a large-scale retrospective study of 1025 NSCLC patients who harbored baseline compound EGFR mutations. Intriguingly, compound EGFR mutations had a significantly higher frequency of EGFR exon 21 p.L858R and rare EGFR mutations and a dramatically lower rate of EGFR 19-Del mutation than single EGFR mutation. Different types of compound EGFR mutations demonstrated distinct subtypes of mutated genes, aberrant signaling pathways, mutational signatures, and chromosomal instability. Notably, the rare EGFR mutation-dominant subtypes were associated with significantly shorter FPS. In addition, VUSs in the rare + VUSs subtype were more likely to locate at the EGFR kinase domain, and patients with rare + VUSs (KD +) had worse PFS than those with other VUS-containing subtypes. In terms of TKI-resistant mechanism, the common + VUSs subtype was highly enriched for EGFR exon 20 p.T790M and/or other RAS/RAF/MEK pathway-related mutations. Therefore, different compound EGFR mutation subtypes had distinct clinical/genetic characteristics and therapeutic responses.
The first-generation EGFR TKIs (e.g., gefitinib and erlotinib) are ATP‑competitive small molecules that reversibly target the EGFR tyrosine kinase domain. Despite its significant clinical benefits when compared with chemotherapies in NSCLC patients, drug resistance inevitably developed . To overcome the resistance to first-generation TKIs, the second-generation TKIs (e.g., afatinib and dacomitinib), which are irreversible inhibitors, were designed. Although second-generation TKIs generally showed improved EGFR inhibition, they also exhibited high potency against wild-type EGFR, leading to lower maximum dose tolerance, more adverse events, and limited clinical utilities [44, 45]. One of the most common resistance mechanisms against both the first- and second-generation TKIs is EGFR exon 20 p.T790M mutation [46,47,48]. The gatekeeper hypothesis suggests that the steric hindrance between the methionine residue on the gatekeeper side chain of EGFR exon 20 p.T790M and the aniline moiety of first-generation TKIs is the underlying mechanism of the drug resistance, although other putative mechanisms have been proposed, including elevated ATP-binding affinity for EGFR exon 20 p.T790M, changes in the catalytic domain, and variations in the conformational dynamics [49, 50]. In our study, we found that a significant proportion of patients with common + VUSs subtype (44%) acquired EGFR exon 20 p.T790M mutation after EGFR TKI treatments, but not for other EGFR subtypes. Because the percentage of acquiring EGFR exon 20 p.T790M is similar between the common + VUSs subtype in our study and other studies using patients with a single EGFR common mutation , we speculate that the common + VUSs subtype might resemble the function of a single EGFR common mutation. In particular, the EGFR VUSs in the common + VUSs subtype might be passenger mutations and did not contribute to the oncogenic activation of EGFR. In contrast, some EGFR compound mutation subtypes (e.g., rare + rare and rare + VUSs) are less likely to acquire EGFR exon 20 p.T790M, implying that these subtypes might rewire the signaling network to make them prone to utilize other resistance mechanisms to bypass first- and second-generation TKIs. The third-generation TKIs, especially osimertinib, demonstrated satisfactory efficacy against EGFR exon 20 p.T790M. Osimertinib formed irreversible covalent bonds with the cysteine 797 residue in the ATP-binding site, and it exhibited selective potency against the mutant EGFR rather than wild-type EGFR, resulting in its accelerated approval by US Food and Drug Administration to treat EGFR-mutated NSCLC . One patient in our cohort gained EGFR exon 20 p.C797S mutation after first-line TKIs and became resistant to osimertinib. This patient might be treated with TKI combinations or next-generation TKIs to overcome this resistance mutation .
Around 12.1% of EGFR-positive NSCLC patients in our cohort harbored compound EGFR mutations, which is consistent with previous studies [18,19,20]. Only around 2% of all compound EGFR mutation-positive patients had more than 2 baseline EGFR mutations, and these patients generally had high tumor mutation loads. Kauffmann-Guerrero et al. reported that compound EGFR mutations were more often observed in patients with a smoking history . Although our patient cohort did not have complete records of the patient’s smoking status, the mutational signature results suggested that not all subtypes of compound EGFR mutations had the same level of smoking-related signatures, with common + VUSs and rare + rare subtypes being more likely to occur in smokers than other subtypes. Additionally, Kim et al. found that compound EGFR mutations were frequently co-mutated with some actionable genes, such as ALK rearrangement, KRAS mutation, and PIK3CA mutations . We also detected multiple co-mutated genes, which exhibited distinct subtypes according to the specific type of compound EGFR mutations. Particularly, unlike other compound EGFR mutations, the rare + rare subtype had a significantly low frequency of mutations in the PI3K and RAS/RAF/MEK signaling pathways, implying that tumors harboring double rare EGFR mutations might less rely on these oncogenic pathways. On the other hand, the VUSs + VUSs subtype had the highest mutational frequency in almost all the tested oncogenic pathways. This indicates that many of the detected EGFR VUSs might have little or very mild oncogenic activities, and tumors harboring the VUSs + VUSs subtype had to heavily depend on other oncogenic mutations for tumorigenesis and maintenance.
Another interesting observation of our study is that compound EGFR mutations had a much lower frequency of EGFR 19-Del and a significantly higher frequency of EGFR exon 21 p.L858R than the single EGFR mutation. The two types of common EGFR mutations also had different preferences in the co-existed EGFR mutations. Furthermore, the EGFR 19-Del + X subtype and EGFR exon 21 p.L858R + X subtype had opposite trends in the therapeutic response to second-generation TKIs. Multiple previous studies on single EGFR mutation have found that EGFR 19-Del and EGFR exon 21 p.L858R demonstrated different clinical features and treatment outcomes. Hong’s group reported that patients with a single EGFR 19‑Del mutation had significantly improved clinical outcomes than patients with a single EGFR exon 21 p.L858R mutation following first‑line TKI, but not first‑line chemotherapy or second‑line TKI . NSCLC patients with EGFR 19-Del also had a higher risk of lymph node metastasis than those with EGFR exon 21 p.L858R . Despite the clinical difference between EGFR exon 21 p.L858R and EGFR 19-Del, the underlying mechanism is still elusive. Sordella et al. discovered that EGFR exon 21 p.L858R and EGFR 19-Del had differential levels of EGFR autophosphorylation on some specific sites, which may affect their drug sensitivity to TKIs . Nevertheless, future studies are needed to elucidate the distinguishing preference of EGFR exon 21 p.L858R and EGFR 19-Del in compound EGFR mutations.
We found that patients with compound EGFR mutations tended to be less responsive to EGFR TKIs than those with single EGFR mutation, especially the patients with single EGFR 19-Del, which is consistent with previous studies [21,22,23,24]. Additionally, we discovered that different subtypes of compound EGFR mutations were also significantly associated with patient’s prognosis to first-line TKIs. Specifically, the presence of a common mutation in compound EGFR mutations can sufficiently predict prognosis, regardless of the type and location of the other EGFR mutation. However, for rare EGFR mutation-containing patients, their prognosis is likely to highly rely on the type of mutation combinations. In particular, rare + common was associated with good PFS, rare + VUSs (KD −) might be related to good to intermediate PFS, while rare + rare and rare + VUSs (KD +) are likely to associate with short PFS. Therefore, both the type of EGFR mutations (common vs rare vs VUSs) and the specific combination of compound mutations might contribute to the overall prognosis of NSCLC patients.
The common + common subtype was extremely rare, accounting for only 2.3% of patients in our cohort. Given that common EGFR mutations could efficiently activate EGFR kinase activity and promote tumorigenesis, it is highly unlikely that a single tumor would acquire two EGFR common mutations simultaneously. As a result, we suspect that the two different EGFR common mutations might mainly reside in different tumor cells. In other words, we think those patients might have two subclones of cancer cells, one is driven by EGFR exon 21 p.L858R and the other is driven by EGFR 19-Del, and both of them are likely to be sensitive to EGFR TKIs. For the common + rare and common + VUSs subtypes, the two EGFR mutations could be either in the same or in different tumor cells. However, if some common and rare EGFR mutations are in the same cancer cells, they might interfere with the response to certain EGFR TKIs. For example, Yu et al. found that if lung cancer patients had co-occurred baseline common EGFR mutation and baseline EGFR exon 20 p.T790M, they had poor responses to first-generation TKIs . Indeed, several previous studies reported that common EGFR mutations and EGFR exon 20 p.T790M were almost always in cis configurations in order to confer resistance to first-generation EGFR TKIs . Additionally, we found that rare EGFR mutations were specifically enriched for EGFR VUS (KD +) mutations. We speculate that EGFR VUSs (KD +) and rare EGFR mutations are within the same cancer cell or even on the same allele, and the additional KD aberrations from the VUSs might help reinforce the oncogenic activities of rare EGFR mutations. Strikingly, we found that patients with the rare + VUSs (KD +) subtype are generally associated with a poorer prognosis than those with other subtypes, which further implies that they might reside in the same cancer cells to drive tumorigenesis and/or tumor progression. Nevertheless, our NGS results were not ideal to elucidate whether the compound EGFR mutations were from the same cancer cell/DNA allele or not. Among the 1025 patients in our cohort, the compound EGFR mutations of 282 patients were on the same exon. We then analyzed whether the mutations were on the same sequencing read (i.e., the same allele) or not. Strikingly, in 98.9% (279/282) of cases, the compound EGFR mutations were located on the same allele, which also infers that they were in the same cancer cell (Additional file 1: Table S8). Future studies using more appropriate approaches (e.g., NGS on multi-site sampling tissues, single-cell sequencing, sequencing complementary DNAs, long-read sequencing, or fluorescent in situ hybridization) are necessary to further check the cis/trans configuration and cellular distribution of compound mutations.
There were several limitations of our study. Firstly, a large proportion of patients had missing clinical information, including the PD-L1 expression and disease stages, which can potentially impede thorough analyses of the correlation between the clinical characteristics and compound EGFR mutation subtypes. Secondly, because the tumor samples were collected by different hospitals spanning the past 4.5 years, the samples were generically profiled by 3 different targeted sequencing panels. Fortunately, all 3 targeted sequencing panels were designed and performed by the same sequencing institute. Specifically, all the assay validations were performed using a method-based validation approach to detect a specific type of mutation at a specific sequencing depth under the entire NGS system, and all three sequencing panels showed a similar capacity to detect mutations (cross-panel accuracy > 97%). Therefore, the result of overlapping genes from the three sequencing panels is comparable. Lastly, only 95 patients who had paired baseline and PD samples were available for drug resistance analyses, and future studies with larger patient sizes are necessary to fully elucidate the differential resistant mechanisms for various compound EGFR mutations.
In conclusion, by performing a large-scale analysis in 1025 compound EGFR mutation-positive NSCLC patients, we found that different subtypes of compound EGFR mutations were associated with distinct demographic features, co-mutated genes, mutational signatures, and chromosomal instability levels, as well as distinguishing prognosis to first-line EGFR TKIs. Our study helps better understand the clinical characteristics of compound EGFR mutations and emphasizes the importance of determining the specific types of EGFR mutations, which can potentially direct prognosis prediction and provide personalized treatments to NSCLC patients.
Availability of data and materials
The data generated in this study are available within the article and its supplementary data files. The raw sequencing data are not publicly available due to privacy or ethical restrictions but are available upon reasonable request from the corresponding author.
Short in-frame deletions in exon 19
Exon 20 insertions
Adenosquamous carcinoma of the lung
Chromosome instability score
- EGFR :
Epidermal growth factor receptor
Exome aggregation consortium
Integrative genomics viewer
Mutant allele frequency
Median progression-free survival
Non-small cell lung cancer
Programmed death-ligand 1
Lung squamous cell carcinoma
Tyrosine kinase inhibitor
Tumor mutational burden
Variant of uncertain significance
Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49.
Zhang YL, Yuan JQ, Wang KF, Fu XH, Han XR, Threapleton D, et al. The prevalence of EGFR mutation in patients with non-small cell lung cancer: a systematic review and meta-analysis. Oncotarget. 2016;7(48):78985–93.
Zhou W, Christiani DC. East meets West: ethnic differences in epidemiology and clinical behaviors of lung cancer between East Asians and Caucasians. Chin J Cancer. 2011;30(5):287–92.
Lindeman NI, Cagle PT, Beasley MB, Chitale DA, Dacic S, Giaccone G, et al. Molecular testing guideline for selection of lung cancer patients for EGFR and ALK tyrosine kinase inhibitors: guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology. J Thorac Oncol. 2013;8(7):823–59.
Pao W. Defining clinically relevant molecular subsets of lung cancer. Cancer Chemother Pharmacol. 2006;58(Suppl 1):s11–5.
Penzel R, Sers C, Chen Y, Lehmann-Muhlenhoff U, Merkelbach-Bruse S, Jung A, et al. EGFR mutation detection in NSCLC–assessment of diagnostic application and recommendations of the German Panel for Mutation Testing in NSCLC. Virchows Arch. 2011;458(1):95–8.
Maemondo M, Inoue A, Kobayashi K, Sugawara S, Oizumi S, Isobe H, et al. Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR. N Engl J Med. 2010;362(25):2380–8.
Mitsudomi T, Morita S, Yatabe Y, Negoro S, Okamoto I, Tsurutani J, et al. Gefitinib versus cisplatin plus docetaxel in patients with non-small-cell lung cancer harbouring mutations of the epidermal growth factor receptor (WJTOG3405): an open label, randomised phase 3 trial. Lancet Oncol. 2010;11(2):121–8.
Rosell R, Carcereny E, Gervais R, Vergnenegre A, Massuti B, Felip E, et al. Erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer (EURTAC): a multicentre, open-label, randomised phase 3 trial. Lancet Oncol. 2012;13(3):239–46.
Inoue A, Kobayashi K, Maemondo M, Sugawara S, Oizumi S, Isobe H, et al. Updated overall survival results from a randomized phase III trial comparing gefitinib with carboplatin-paclitaxel for chemo-naive non-small cell lung cancer with sensitive EGFR gene mutations (NEJ002). Ann Oncol. 2013;24(1):54–9.
Zhou C, Wu YL, Chen G, Feng J, Liu XQ, Wang C, et al. Final overall survival results from a randomised, phase III study of erlotinib versus chemotherapy as first-line treatment of EGFR mutation-positive advanced non-small-cell lung cancer (OPTIMAL, CTONG-0802). Ann Oncol. 2015;26(9):1877–83.
Yoshioka H, Shimokawa M, Seto T, Morita S, Yatabe Y, Okamoto I, et al. Final overall survival results of WJTOG3405, a randomized phase III trial comparing gefitinib versus cisplatin with docetaxel as the first-line treatment for patients with stage IIIB/IV or postoperative recurrent EGFR mutation-positive non-small-cell lung cancer. Ann Oncol. 2019;30(12):1978–84.
Qin Y, Jian H, Tong X, Wu X, Wang F, Shao YW, et al. Variability of EGFR exon 20 insertions in 24 468 Chinese lung cancer patients and their divergent responses to EGFR inhibitors. Mol Oncol. 2020;14(8):1695–704.
Lavdovskaia ED, Iyevleva AG, Sokolenko AP, Mitiushkina NV, Preobrazhenskaya EV, Tiurin VI, et al. EGFR T790M mutation in TKI-naive clinical samples: frequency, tissue mosaicism, predictive value and awareness on artifacts. Oncol Res Treat. 2018;41(10):634–42.
Lettig L, Sahnane N, Pepe F, Cerutti R, Albeni C, Franzi F, et al. EGFR T790M detection rate in lung adenocarcinomas at baseline using droplet digital PCR and validation by ultra-deep next generation sequencing. Transl Lung Cancer Res. 2019;8(5):584–92.
Kohsaka S, Nagano M, Ueno T, Suehara Y, Hayashi T, Shimada N, et al. A method of high-throughput functional evaluation of EGFR gene variants of unknown significance in cancer. Sci Transl Med. 2017;9(416):eaan6566.
Yang J, Li H, Li B, Li W, Guo Q, Hu L, et al. Profiling oncogenic germline mutations in unselected Chinese lung cancer patients. Front Oncol. 2021;11:647598.
Wu SG, Chang YL, Hsu YC, Wu JY, Yang CH, Yu CJ, et al. Good response to gefitinib in lung adenocarcinoma of complex epidermal growth factor receptor (EGFR) mutations with the classical mutation pattern. Oncologist. 2008;13(12):1276–84.
Hata A, Yoshioka H, Fujita S, Kunimasa K, Kaji R, Imai Y, et al. Complex mutations in the epidermal growth factor receptor gene in non-small cell lung cancer. J Thorac Oncol. 2010;5(10):1524–8.
Attili I, Passaro A, Pisapia P, Malapelle U, de Marinis F. Uncommon EGFR compound mutations in non-small cell lung cancer (NSCLC): a systematic review of available evidence. Curr Oncol. 2022;29(1):255–66.
Tam IY, Leung EL, Tin VP, Chua DT, Sihoe AD, Cheng LC, et al. Double EGFR mutants containing rare EGFR mutant types show reduced in vitro response to gefitinib compared with common activating missense mutations. Mol Cancer Ther. 2009;8(8):2142–51.
Kauffmann-Guerrero D, Huber RM, Reu S, Tufman A, Mertsch P, Syunyaeva Z, et al. NSCLC patients harbouring rare or complex EGFR mutations are more often smokers and might not benefit from first-line tyrosine kinase inhibitor therapy. Respiration. 2018;95(3):169–76.
Kim EY, Cho EN, Park HS, Hong JY, Lim S, Youn JP, et al. Compound EGFR mutation is frequently detected with co-mutations of actionable genes and associated with poor clinical outcome in lung adenocarcinoma. Cancer Biol Ther. 2016;17(3):237–45.
Kobayashi S, Canepa HM, Bailey AS, Nakayama S, Yamaguchi N, Goldstein MA, et al. Compound EGFR mutations and response to EGFR tyrosine kinase inhibitors. J Thorac Oncol. 2013;8(1):45–51.
Li J, Li X, Wang W, Shao Y, Zhang Y, Song Z. Gene alterations in paired supernatants and precipitates from malignant pleural effusions of non-squamous non-small cell lung cancer. Transl Oncol. 2020;13(8):100784.
Zhang C, Zhang J, Xu FP, Wang YG, Xie Z, Su J, et al. Genomic landscape and immune microenvironment features of preinvasive and early invasive lung adenocarcinoma. J Thorac Oncol. 2019;14(11):1912–23.
Li B, Qu H, Zhang J, Pan W, Liu M, Yan X, et al. Genomic characterization and outcome evaluation of kinome fusions in lung cancer revealed novel druggable fusions. NPJ Precis Oncol. 2021;5(1):81.
Yang Z, Yang N, Ou Q, Xiang Y, Jiang T, Wu X, et al. Investigating novel resistance mechanisms to third-generation EGFR tyrosine kinase inhibitor osimertinib in non-small cell lung cancer patients. Clin Cancer Res. 2018;24(13):3097–107.
Tang WF, Wu M, Bao H, Xu Y, Lin JS, Liang Y, et al. Timing and origins of local and distant metastases in lung cancer. J Thorac Oncol. 2021;16(7):1136–48.
Li H, Shan C, Wu S, Cheng B, Fan C, Cai L, et al. Genomic profiling identified novel prognostic biomarkers in Chinese midline glioma patients. Front Oncol. 2020;10:607429.
Carter SL, Cibulskis K, Helman E, McKenna A, Shen H, Zack T, et al. Absolute quantification of somatic DNA alterations in human cancer. Nat Biotechnol. 2012;30(5):413–21.
Shen R, Seshan VE. FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Nucleic Acids Res. 2016;44(16):e131.
Ng CKY, Bidard FC, Piscuoglio S, Geyer FC, Lim RS, de Bruijn I, et al. Genetic heterogeneity in therapy-naive synchronous primary breast cancers and their metastases. Clin Cancer Res. 2017;23(15):4402–15.
Oh S, Geistlinger L, Ramos M, Morgan M, Waldron L, Riester M. Reliable analysis of clinical tumor-only whole-exome sequencing data. JCO Clin Cancer Inform. 2020;4:321–35.
Newman AM, Bratman SV, Stehr H, Lee LJ, Liu CL, Diehn M, et al. FACTERA: a practical method for the discovery of genomic rearrangements at breakpoint resolution. Bioinformatics. 2014;30(23):3390–3.
Turajlic S, Xu H, Litchfield K, Rowan A, Chambers T, Lopez JI, et al. Tracking cancer evolution reveals constrained routes to metastases: TRACERx Renal. Cell. 2018;173(3):581-94 e12.
Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, et al. Signatures of mutational processes in human cancer. Nature. 2013;500(7463):415–21.
Alexandrov LB, Ju YS, Haase K, Van Loo P, Martincorena I, Nik-Zainal S, et al. Mutational signatures associated with tobacco smoking in human cancer. Science. 2016;354(6312):618–22.
Yoshida K, Gowers KHC, Lee-Six H, Chandrasekharan DP, Coorens T, Maughan EF, et al. Tobacco smoking and somatic mutations in human bronchial epithelium. Nature. 2020;578(7794):266–72.
Li L, Sun J, Liu N, Yu R, Zhang J, Pang J, et al. Clinical outcome-related cancer pathways and mutational signatures in patients with unresectable esophageal squamous cell carcinoma treated with chemoradiotherapy. Int J Radiat Oncol Biol Phys. 2022.
Li Z, Huang W, Yin JC, Na C, Wu X, Shao Y, et al. Comprehensive next-generation profiling of clonal hematopoiesis in cancer patients using paired tumor-blood sequencing for guiding personalized therapies. Clin Transl Med. 2020;10(7):e222.
Zhang S, Xu Y, Zhao P, Bao H, Wang X, Liu R, et al. Integrated analysis of genomic and immunological features in lung adenocarcinoma with micropapillary component. Front Oncol. 2021;11:652193.
Huang L, Fu L. Mechanisms of resistance to EGFR tyrosine kinase inhibitors. Acta Pharm Sin B. 2015;5(5):390–401.
Miller VA, Hirsh V, Cadranel J, Chen YM, Park K, Kim SW, et al. Afatinib versus placebo for patients with advanced, metastatic non-small-cell lung cancer after failure of erlotinib, gefitinib, or both, and one or two lines of chemotherapy (LUX-Lung 1): a phase 2b/3 randomised trial. Lancet Oncol. 2012;13(5):528–38.
Ellis PM, Shepherd FA, Millward M, Perrone F, Seymour L, Liu G, et al. Dacomitinib compared with placebo in pretreated patients with advanced or metastatic non-small-cell lung cancer (NCIC CTG BR.26): a double-blind, randomised, phase 3 trial. Lancet Oncol. 2014;15(12):1379–88.
Shih JY, Gow CH, Yang PC. EGFR mutation conferring primary resistance to gefitinib in non-small-cell lung cancer. N Engl J Med. 2005;353(2):207–8.
Pao W, Miller VA, Politi KA, Riely GJ, Somwar R, Zakowski MF, et al. Acquired resistance of lung adenocarcinomas to gefitinib or erlotinib is associated with a second mutation in the EGFR kinase domain. PLoS Med. 2005;2(3):e73.
Tanaka K, Nosaki K, Otsubo K, Azuma K, Sakata S, Ouchi H, et al. Acquisition of the T790M resistance mutation during afatinib treatment in EGFR tyrosine kinase inhibitor-naive patients with non-small cell lung cancer harboring EGFR mutations. Oncotarget. 2017;8(40):68123–30.
Cheng H, Nair SK, Murray BW. Recent progress on third generation covalent EGFR inhibitors. Bioorg Med Chem Lett. 2016;26(8):1861–8.
Ko B, Paucar D, Halmos B. EGFR T790M: revealing the secrets of a gatekeeper. Lung Cancer (Auckl). 2017;8:147–59.
Sequist LV, Waltman BA, Dias-Santagata D, Digumarthy S, Turke AB, Fidias P, et al. Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci Transl Med. 2011;3(75):75ra26.
He J, Huang Z, Han L, Gong Y, Xie C. Mechanisms and management of 3rd-generation EGFR-TKI resistance in advanced non-small cell lung cancer (review). Int J Oncol. 2021;59(5):90.
Duggirala KB, Lee Y, Lee K. Chronicles of EGFR tyrosine kinase inhibitors: targeting EGFR C797S containing triple mutations. Biomol Ther (Seoul). 2022;30(1):19–27.
Hong W, Wu Q, Zhang J, Zhou Y. Prognostic value of EGFR 19-del and 21–L858R mutations in patients with non-small cell lung cancer. Oncol Lett. 2019;18(4):3887–95.
Zhang Y, He D, Fang W, Kang S, Chen G, Hong S, et al. The difference of clinical characteristics between patients with exon 19 deletion and those with L858R mutation in nonsmall cell lung cancer. Medicine (Baltimore). 2015;94(44):e1949.
Sordella R, Bell DW, Haber DA, Settleman J. Gefitinib-sensitizing EGFR mutations in lung cancer activate anti-apoptotic pathways. Science. 2004;305(5687):1163–7.
Yu HA, Arcila ME, Hellmann MD, Kris MG, Ladanyi M, Riely GJ. Poor response to erlotinib in patients with tumors containing baseline EGFR T790M mutations found by routine clinical molecular testing. Ann Oncol. 2014;25(2):423–8.
Hidaka N, Iwama E, Kubo N, Harada T, Miyawaki K, Tanaka K, et al. Most T790M mutations are present on the same EGFR allele as activating mutations in patients with non-small cell lung cancer. Lung Cancer. 2017;108:75–82.
We owe thanks to the patients in our study and their family members.
This study was supported by the National Natural Science (81302009).
Ethics approval and consent to participate
This study was approved by the Ethics Committee of the Fudan University Shanghai Cancer Center, Shanghai Cancer Center Institutional Review Board (SCCIRB), and in accordance with the Declaration of Helsinki (ethics approval number: 2004216–19-2005). Informed consent was obtained from all the participating patients. All patients provided written informed consent to participate and publication.
Consent for publication
YX, QW, CL, JCY, QO, XW, and YS are employees of Nanjing Geneseeq Technology Inc. All the remaining authors declare that they have no competing interests.
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Table S1. The demographic and clinical characteristics ofthe 1,025 lung cancer patients with baseline compound EGFR mutations. Table S2. The correlation of clinical features with thenumber concurrent EGFR mutations. Table S3. The correlation of clinicalfeatures with the subtype of compound EGFRmutations. Table S4. The correlationof clinical features with the presence or absence of common EGFR mutations. Table S5. The enrichment of different subtypes of compound EGFR mutations in various domains ofEGFR protein. Table S6. The involvedgenes of each path during the pathway analysis. EGFR has been excluded from RTKpathway analysis. Table S7. The gainof EGFR exon 20 p.T790M mutation inprogressive disease (PD) samples after front-line EGFR TKI treatment inpatients with different subtypes of compound EGFR mutations. Table S8.The distribution of compound EGFRmutations for 282 patients with their compound EGFR mutations on the same exon. Fig. S1. The type of compound EGFRmutations and the concurrent genetic alterations. Fig. S2. The mutational signature analysis for patients withdifferent numbers of EGFR mutations. Fig. S3. The correlation between thecommon EGFR mutation-containingsubtype and patients’ prognosis to first-line EGFR TKIs. Fig. S4. The correlation between the rare EGFR mutation-dominant subtype and patients’ prognosis tofirst-line EGFR TKIs. Fig. S5. Thecorrelation between the EGFRVUSs-containing subtype and patients’ prognosis to first-line EGFR TKIs. Fig. S6. The difference of the geneticprofile between the baseline sample and the paired PD samples.
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Zhao, W., Song, A., Xu, Y. et al. Rare mutation-dominant compound EGFR-positive NSCLC is associated with enriched kinase domain-resided variants of uncertain significance and poor clinical outcomes. BMC Med 21, 73 (2023). https://doi.org/10.1186/s12916-023-02768-z
- Compound EGFR mutations
- Non-small cell lung cancer
- Tyrosine kinase inhibitors
- Precision medicine
- Resistant mechanism