Epidermal Growth Factor Receptor Aberrations Identified by Next-Generation Sequencing in Patients with Metastatic Cancers

Minkyue Shin; Dae-Ho Choi; Jaeyun Jung; Deok Geun Kim; Minae An; Sung Hee Lim; Seung Tae Kim; Jung Yong Hong; Se Hoon Park; Joon Oh Park; Kyoung-Mee Kim; Jeeyun Lee

doi:10.4143/crt.2024.564

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Original Article General Epidermal Growth Factor Receptor Aberrations Identified by Next-Generation Sequencing in Patients with Metastatic Cancers: Minkyue Shin^1,2, Dae-Ho Choi¹, Jaeyun Jung¹, Deok Geun Kim^2,3, Minae An⁴, Sung Hee Lim¹, Seung Tae Kim¹, Jung Yong Hong¹, Se Hoon Park¹, Joon Oh Park¹, Kyoung-Mee Kim⁵, Jeeyun Lee¹; Cancer Research and Treatment : Official Journal of Korean Cancer Association 2025;57(4):932-941.
DOI: https://doi.org/10.4143/crt.2024.564
Published online: February 21, 2025

¹Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

²Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea

³Department of Clinical Genomic Center, Samsung Medical Center, Seoul, Korea

⁴Experimental Therapeutics Development Center, Samsung Medical Center, Seoul, Korea

⁵Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

Correspondence: Jeeyun Lee, Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Korea
Tel: 82-2-3410-3459 E-mail: jyunlee@skku.edu

^*Minkyue Shin and Dae-Ho Choi contributed equally to this work.

• Received: June 17, 2024 • Accepted: January 21, 2025

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

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Abstract

Purpose
The epidermal growth factor receptor (EGFR) is a therapeutic target with confirmed clinical efficacy for several cancer types. We aimed to identify EGFR aberrations and their associations with other genomic alterations in patients with metastatic diseases of various cancers.
Materials and Methods
We used real-world data from the next-generation sequencing (NGS) of 3,286 patients with metastatic cancer at the Samsung Medical Center. We analyzed the distribution of EGFR amplification, mutation, and fusion, as well as their correlations with microsatellite instability (MSI), tumor mutation burden (TMB), and other gene aberrations.
Results
A total of 3,286 patients were tested using NGS of a panel covering 523 cancer-related genes (TSO500, Illumina) as part of clinical practice between October 2019 and October 2022. Patients with lung cancer and gliomas were not included in the analysis. Of the 3,286 patients, 175 (5.3%) had EGFR amplification, 38 (1.2%) had EGFR mutations, and eight (0.2%) had EGFR fusion. All 175 patients with EGFR amplifications had microsatellite-stable tumors, but 102 had co-amplifications in other cancer-related genes, and 78 had mutations with clinical significance (tier I/II). Among the 38 patients with EGFR mutations, three (8%) showed MSI-high status, and 11 (29%) demonstrated high TMB (≥ 10 mutations/Mb). Among eight patients with EGFR fusion, three exhibited possible functionalities of the EGFR gene.
Conclusion
EGFR aberrations, mainly amplification, followed by mutation and fusion, were present in 6.4% of patients with metastatic solid tumors.
Key words: EGFR amplification, EGFR mutation, EGFR fusion, High-throughput nucleotide sequencing, Prognosis, Real-world data

Introduction

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase and one of the most potent oncogenic drivers [1,2]. It is activated by dimerization and associated with cell proliferation, survival, and migration through downstream signaling via the PI3K, RAS, and JAK/STAT pathways [3-5]. Therefore, it is considered the main target of targeted therapies, including the anti-EGFR antibody cetuximab for colorectal cancer (CRC) and EGFR tyrosine kinase inhibitors (TKIs) erlotinib and gefitinib for non–small cell lung cancer (NSCLC), and has been extensively investigated within the last two decades [6-8]. However, these drugs have not been successful enough to change the therapeutic paradigm for other cancers despite the success of EGFR TKIs for NSCLC. In addition, EGFR aberrations have not had a significant therapeutic effect on other cancers, although several of them have been identified [9-11]. As a result, the unmet clinical need has not yet been addressed and the outcomes for patients continue to be limited.

Next-generation sequencing (NGS) is transforming clinical practice. It facilitates the detection of multiple genomic alterations in a single assay. Developments in NGS have provided new clinical opportunities for patients and clinicians and, in addition to improving our understanding of the cancer genome, advanced treatment into previously unreachable areas. However, our understanding of EGFR aberration remains limited. A study used the cancer genome atlas (The Cancer Genome Atlas) datasets to analyze the associations between EGFR aberrations across tumor types and patient survival [12]. However, the clinical implications of EGFR aberrations in patients with metastatic cancers treated with palliative chemotherapies have not been established.

In this study, we analyzed the frequency and types of EGFR aberrations via pan-tumor analysis using NGS and determined their associations with survival outcomes. We also identified other cancer-related genes. These were aimed at establishing the clinical implications of EGFR aberrations.

Materials and Methods

DNA extraction and library preparation were performed as previously described [13] using the AllPrep DNA/RNA FFPE Kit (Qiagen) and the TruSight Oncology 500 DNA/RNA NextSeq Kit. Sequence data were analyzed for clinically relevant classes of genomic alterations, including single-nucleotide variants (SNVs), small insertions and deletions (indels), copy-number variations, and rearrangements/fusi-ons. SNVs and small indels with a variant allele frequency of less than 2% were excluded. An average of more than three copy-number variations was considered a gain (amplification). GRCh37/hg19 was used as the reference genome. Data outputs exported from the TSO 500 pipeline (Illumina) were annotated using the Ensembl Variant Effect Predictor annotation engine with information from databases such as dbSNP, gnomAD genome and exome, 1000 genomes, ClinVar, COSMIC, RefSeq, and Ensembl. The processed genomic changes were categorized according to the 4-tier system proposed by the American Society of Clinical Oncology/College of American Pathologists and annotated with proper references. A TSO 500 pipeline (Illumina) was used to determine the tumor mutational burden (TMB) and microsatellite instability (MSI) status. To determine the TMB, any variant with an observed allele count of ≥ 10 in any of the GnomAD exome, genome, and 1000 genomes databases was excluded. In contrast, the following were included: (1) variants in the coding region (RefSeq Cds), (2) variant frequency ≥ 5%, (3) coverage ≥ 50×, (4) SNVs and indels, and (5) nonsynonymous and synonymous variants. The effective panel size for TMB was the total coding region with a coverage of > 50×. The MSI was calculated from the microsatellite sites for evidence of instability relative to a set of baseline normal samples based on information entropy metrics. The proportion of MSI sites that were unstable was reported as the sample-level microsatellite score. The fusion events were evaluated using Integrative Genomics Viewer, with EGFR domain annotations based on Pfam.

Results

1. Patient characteristics

A total of 3,286 patients with stage IV cancer were tested using NGS of a panel covering 523 cancer-related genes (TSO500, Illumina) as part of clinical practice at the Samsung Medical Center between October 2019 and October 2022. This study excluded patients with lung cancer due to the uniqueness of the EGFR gene in this cancer type. Additionally, patients with gliomas were not included in this study, as more in-depth analysis of data from those patients was previously reported in another study [14]. The most prevalent cancer types in this cohort were CRC (n=1,117, 34%), gastric cancer (GC) (n=793, 24.1%), and cholangiocarcinoma (CCC) (n=271, 8.2%) (Fig. 1A). Overall, 209 patients (6.4%) had EGFR aberrations in their tumor samples (Fig. 1B). Specifically, 175 (5.3%) patients had EGFR amplification, 38 (1.2%) had EGFR mutations, and eight (0.2%) had EGFR fusion. The most common cancer type with EGFR amplification was CRC (n=83), followed by GC (n=41), CCC (n=11), melanoma (n=8), sarcoma (n=7), and gallbladder cancer (n=6) (Fig. 1C). The most common cancer type associated with EGFR mutations in our cohort was CRC (n=15), followed by GC (n=8), CCC (n=6), and bladder cancer (n=4) (Fig. 1D).

2. EGFR amplification

For the 175 patients with EGFR amplification, the EGFR copy numbers ranged from 3.0 to 324.8 (median 5.4), and 76% of the copy numbers were less than 10 (x < 5: n=74, 42% and 5 ≤ x < 10: n=59, 34%) (Fig. 2A). Notably, few patients had very high copy numbers greater than 100: seven patients with GC (ranging from 102.1 to 324.8), two patients with CRC (138.8 and 168.8), and a single patient each with pancreatic cancer (2232.5), CCC (189), head and neck cancer (145), and small bowel cancer (126.9). The mean copy number was the highest for small bowel cancer (126.9), followed by pancreatic cancer (118.8) and head and neck cancer (50.8) (Fig. 2B). In contrast, the average copy number was the lowest for prostate cancer and kidney cancer (both 4.0). To identify chromosome 7 polysomy, we assessed the co-occurrences of copy number gains in other oncogenes located on chromosome 7. Two patients demonstrated a copy number gain for all four genes (EGFR, MET, CDK6, and BRAF); one patient had CCC and the other had pancreatic cancer.

We further assessed the association between EGFR amplification and other genomic characteristics including gene mutations (Fig. 2C). EGFR-amplified tumors were 100% microsatellite stable (MSS), 18% (32/175) TMB-high (≥ 10 mutations/Mb), and 69% (52/75) programmed death-ligand 1 (PD-L1)–positive (combined positive score ≥ 1). Their most frequent mutations were found in TP53 (n=132, 75%), followed by APC (n=81, 46%), NOTCH3 (n=55, 31%), LRP1B (n=46, 26%), and FAT1 (n=40, 23%). Among 3,331 mutations found in the EGFR-amplified tumors, 101 with clinical significance (tier I/II) were found in 45% (78/175) of the patients; these were most common in KRAS, followed by PIK3CA, TP53, and BRAF (S1 Table). In addition, 58% (102/175) of the patients with EGFR-amplified tumors had 179 co-amplifications of other cancer-related genes, most commonly MYC, followed by RICTOR, MET, ERBB2, KRAS, and MDM2 (S2 Table). Among them, 73 had 101 clinically significant co-amplifications (tier I/II), which were most common in MET, followed by ERBB2, MDM2, and PIK3CA.

3. EGFR mutation

Of the 38 patients with EGFR-mutated tumors, 36 had single mutations and two had double mutations. The most common single-nucleotide variation was C to T (n=17), followed by C to A (n=6), and T to G (n=4) (Fig. 3A). Recurrent mutations were identified in the juxtamembrane domain (L675R, R677C/H, G682D, and I698T), kinase domain (D770_N771insGL and V786M), and C-terminal tail (A1048V) (Fig. 3B). Of these, only L675R and V786M were found in three patients, whereas the others were found in two patients. Other mutations in the kinase domain are also present in patients with CRC (Y727N, E746_A750del, and R836C), melanoma (L747_T751del), bladder cancer (S768I), and head and neck cancer (H773dup). EGFR-mutated tumors were 8% (3/38) MSI-high, 29% (11/38) TMB-high, and 82% (14/17) PD-L1–positive (Fig. 3C). In EGFR-mutated tumors, mutations in TP53 (n=26, 68%), BARD1 (n=14, 37%), NOTCH3 (n=13, 34%), BRCA2 (n=11, 29%), and LRP1B (n=11, 29%) were the most frequent.

4. EGFR fusion

Among the eight patients with EGFR fusion, two had GC, two had CRC, two had bladder cancer, one had small bowel cancer, and one had sarcoma. Four fusion events were found in a patient with CRC, two fusion events were found in a patient with small bowel cancer, and a single fusion event was found in the other patients. Among the 12 fusion events, two were in-frame EGFR fusions, five were out-of-frame EGFR fusions, and the remaining five had intronic breakpoints. Of the seven in-frame or intronic breakpoint fusions, only one from CRC contained the full EGFR kinase domain (exons 18-24), two from bladder cancer contained partial EGFR kinase domains, and the remaining four lacked the EGFR kinase domain. The detailed fusion information is presented in Table 1 and Fig. 4A-C. Therefore, three patients had EGFR fusion events with possible functionality of the EGFR gene.

Discussion

In this study, we demonstrated that 209 of 3,286 patients (6.4%) with metastatic cancer had EGFR aberrations tested using NGS at the Samsung Medical Center. Among them, 175 (5.3%) had EGFR amplification, 38 (1.2%) had EGFR mutations, and eight (0.2%) had EGFR fusion. Seven had concurrent EGFR amplification and mutations, and five had concurrent EGFR mutations and fusion.

The median EGFR amplification copy number was less than 10 for all cancers except small bowel and pancreatic cancer for which it was greater than 30. However, no differences in the copy number alterations were observed in the colorectal, gastric, and biliary cancers, which represent the largest proportion of cancers. Remarkably, all patients with EGFR amplification had MSS status, which resembles our previous finding that all patients with human epidermal growth factor receptor 2 (HER2) amplification had MSS status [13]. In this study, we reasoned that precise DNA replication may not occur in MSI-high status. This is also in agreement with the result from a study on metastatic CRC, in which all patients with EGFR amplification had MSS status [15]. Given the clinical unmet needs of patients with MSS tumors, it is crucial to identify clinically actionable genomic alterations in these patients.

EGFR mutations include a large number of missense mutations, and several patients have mutations in the juxtamembrane region rather than in the kinase domain. This differs from NSCLC, which is mainly characterized by the deletion of exon 19 in the kinase domain or L858R in exon 21 [16-18]. Mutations in the juxtamembrane domain of EGFR can induce the localization of PIP2, activate the PI3K pathway, or stabilize the dimerization of the EGFR group, resulting in cell proliferation. However, they also play an autoinhibitory role in receptor tyrosine kinases [19,20], and the role of EGFR mutations in the juxtamembrane domain in prognosis and tumorigenesis is unclear. These results suggest that EGFR TKIs may not be effective against cancers other than NSCLC, which are predominantly characterized by mutations in the ATP-binding site. However, there is evidence supporting the efficacy of osimertinib in CRC with the EGFR T790M mutation; therefore, it is likely that the mutation site will be a predictor of EGFR TKI efficacy for tumors with EGFR mutations [21,22].

Among the 12 EGFR fusion events found in our analysis, only three had possible functionality of the EGFR gene. Out-of-frame fusions, which have disruptions in the reading frame, generally result in non-functional proteins due to premature stop codons [23]. In contrast, intronic breakpoint fusions typically lead to functional proteins because the reading frame of the coding exons are preserved [24,25]. The three partner genes in possibly functional fusion events have not been previously reported, according to a fusion gene database [26] and more recent studies on EGFR fusions [27,28]. Considering that previous studies reported a high prevalence of EGFR fusions in glioma and lung cancer [27,28], the exclusion of these cancer types likely contributed to the low frequency of EGFR fusions observed in our study.

A comprehensive biomarker assessment is required for combinational treatment with an EGFR inhibitor and other targeted agents. For example, the combination of encorafenib with cetuximab or panitumumab is indicated for CRC with the BRAF V600E mutation [29]. Furthermore, amplifications of HER2 and MET are well-recognized mechanisms of resistance to EGFR inhibition [30], meaning that patients with these amplifications may benefit from dual pathway inhibition. Indeed, amivantamab, an EGFR-MET bispecific antibody, demonstrated promising efficacy for CRC in a phase 1b/2 study [31] and is being tested for gastroesophageal cancer in a phase 2 trial (NCT05117931). Previous studies on gastroesophageal cancer have reported that 70% of patients with EGFR amplification had co-amplifications of other targetable oncogenes, and the extent of co-amplification is associated with poor prognosis following EGFR inhibition [32,33]. Similarly, in our cohort, 71% (29/41) of patients with EGFR-amplified gastric cancer had 54 co-amplifications in other cancer-related genes. Furthermore, a phase 2 study on CRC demonstrated that re-administration of cetuximab after initial response and acquired resistance could be effective when combined with an immune checkpoint inhibitor (ICI) [34]. In addition, a patient with EGFR-amplified, PD-L1–positive gastric cancer experienced complete response after treatment with cetuximab combined with an ICI [35].

Our study has several strengths. First, this study improves our understanding of EGFR aberrations by identifying their distribution and detailed genomic changes through pan-cancer analysis using NGS. While this study was conducted in a single center, it involved one of the largest cohorts based on real-world data. Secondly, we identified the types and frequencies of cancer-related gene alterations associated with EGFR aberrations. This finding may have clinical implications for clinicians administering EGFR inhibitors. Co-mutations in cancer-related genes were identified to determine the frequency of mutations in the EGFR downstream, PI3K, RAS pathway, and JAK/STAT pathways. Specifically, KRAS mutations were identified in 15% of patients with EGFR amplification and 25% of patients with EGFR mutations. In addition, PTEN mutations, which are related to the PI3K pathway, were identified in 20% of patients with EGFR mutations. Further proteogenomic studies are warranted to gain a deeper understanding of EGFR aberrations. For example, a recent study identified that recurrent glioblastomas with EGFR aberrations exhibit reduced EGFR protein expression and phosphorylation compared to primary tumors [14].

The treatment of EGFR aberrations has paved the way for targeted therapies, including EGFR TKIs such as gefitinib and erlotinib for NSCLC, as well as cetuximab for CRC. Subsequently, remarkable progress has been achieved in clinical outcomes, and research on resistance mechanisms has also advanced [36,37]. However, most studies on EGFR aberrations have been limited to NSCLC. EGFR aberrations, present in 6.4% of other cancers, remain a significant unmet need. Our study is among the largest real-world cohort studies using NGS to expand the clinical landscape of EGFR aberrations. The findings provide foundational insights for further research on EGFR aberrations.

Electronic Supplementary Material

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

crt-2024-564_S1_Table.pdf

crt-2024-564_S2_Table.pdf

NOTES

Ethical Statement

The tumor specimens and clinical data used in this study were collected after obtaining approval from the Institutional Review Board of Samsung Medical Center (No. 2021-09-052). All participants provided written informed consent before enrollment. This study was performed in accordance with the principles of the Declaration of Helsinki and Korean Good Clinical Practice guidelines.

Author Contributions

Conceived and designed the analysis: Shin M, Choi DH, Lee J.

Collected the data: Lim SH, Kim ST, Hong JY, Park SH, Park JO, Kim KM, Lee J.

Contributed data or analysis tools: Jung J, Kim DG, An M.

Performed the analysis: Shin M.

Wrote the paper: Shin M, Choi DH, Lee J.

Conflicts of Interest

Conflict of interest relevant to this article was not reported.

Funding

This research was supported by the Bio&Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT) (No. RS-2023-00222838).

Fig. 1.

Overview of the study cohort and prevalence of epidermal growth factor receptor (EGFR) aberrations. (A) Pie chart of cancer types included in the study cohort. (B) Pie chart showing the proportion of patients with EGFR aberrations (left) and Venn diagram representing the number of patients with EGFR amplification, mutations, and/or fusion (right). (C) Prevalence of EGFR amplification for each cancer type. (D) Prevalence of EGFR mutations for each cancer type.

Fig. 2.

Epidermal growth factor receptor (EGFR) copy number and genomic landscape of patients with EGFR amplification. (A) Stacked bar chart showing the number of patients for ranges of EGFR copy numbers. (B) Boxplot of EGFR copy numbers for each cancer type. Black diamond points represent the mean copy number. (C) Genomic landscape of patients with EGFR amplifications ordered by EGFR copy number. Top panel: copy number of EGFR. Middle: age, sex, cancer type, microsatellite instability (MSI), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1; measured by combined positive score). Bottom: Oncoprint showing concurrent mutations colored by mutation types. Left: Genes and their mutation frequencies are plotted together. CPS, combined positive score; IHC, immunohistochemistry; MSS, microsatellite stable; N/A, not available.

Fig. 3.

Number of epidermal growth factor receptor (EGFR) mutations and genomic landscape of patients with EGFR mutations. (A) Stacked bar chart showing the number of patients for each nucleotide change. (B) Lollipop plot highlighting the position and number of specific EGFR mutations described as amino acid changes. (C) Genomic landscape of patients with EGFR mutations ordered by tumor mutational burden (TMB). Top panel: TMB score. Middle: age, sex, cancer type, microsatellite instability (MSI), TMB positivity, and programmed death-ligand 1 (PD-L1) (measured by combined positive score). Bottom: Oncoprint showing concurrent mutations colored by mutation types. Left: Genes and their mutation frequencies are plotted together. CPS, combined positive score; IHC, immunohistochemistry; MSS, microsatellite stable; N/A, not available.

Fig. 4.

Illustrations of epidermal growth factor receptor (EGFR) fusion events with possible functionality. (A) EGFR-ITGB8 fusion. (B) ANKRD17-EGFR fusion. (C) COL4A2-EGFR fusion.

Table 1.

Detailed information on EGFR fusion events with possible functionality

Cancer type	ChrA	GeneA	BreakpointA	ChrB	GeneB	BreakpointB
Bladder cancer	chr7	EGFR	chr7:55260533	chr7	ITGB8	chr7:20394291
Bladder cancer	chr4	ANKRD17	chr4:74123992	chr7	EGFR	chr7:55248984
CRC	chr13	COL4A2	chr13:111156448	chr7	EGFR	chr7:55209978

CRC, colorectal cancer; EGFR, epidermal growth factor receptor.

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Epidermal Growth Factor Receptor Aberrations Identified by Next-Generation Sequencing in Patients with Metastatic Cancers

Cancer Res Treat. 2025;57(4):932-941. Published online February 21, 2025

DOI: https://doi.org/10.4143/crt.2024.564

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Abstract
Introduction
Materials and Methods
Results
Discussion
Electronic Supplementary Material
NOTES
REFERENCES

Clinical Practice Recommendations for the Use of Next-Generation Sequencing in Patients with Solid Cancer: A Joint Report from KSMO and KSP

Epidermal Growth Factor Receptor Aberrations Identified by Next-Generation Sequencing in Patients with Metastatic Cancers

Fig. 1. Overview of the study cohort and prevalence of epidermal growth factor receptor (EGFR) aberrations. (A) Pie chart of cancer types included in the study cohort. (B) Pie chart showing the proportion of patients with EGFR aberrations (left) and Venn diagram representing the number of patients with EGFR amplification, mutations, and/or fusion (right). (C) Prevalence of EGFR amplification for each cancer type. (D) Prevalence of EGFR mutations for each cancer type.

Fig. 2. Epidermal growth factor receptor (EGFR) copy number and genomic landscape of patients with EGFR amplification. (A) Stacked bar chart showing the number of patients for ranges of EGFR copy numbers. (B) Boxplot of EGFR copy numbers for each cancer type. Black diamond points represent the mean copy number. (C) Genomic landscape of patients with EGFR amplifications ordered by EGFR copy number. Top panel: copy number of EGFR. Middle: age, sex, cancer type, microsatellite instability (MSI), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1; measured by combined positive score). Bottom: Oncoprint showing concurrent mutations colored by mutation types. Left: Genes and their mutation frequencies are plotted together. CPS, combined positive score; IHC, immunohistochemistry; MSS, microsatellite stable; N/A, not available.

Fig. 3. Number of epidermal growth factor receptor (EGFR) mutations and genomic landscape of patients with EGFR mutations. (A) Stacked bar chart showing the number of patients for each nucleotide change. (B) Lollipop plot highlighting the position and number of specific EGFR mutations described as amino acid changes. (C) Genomic landscape of patients with EGFR mutations ordered by tumor mutational burden (TMB). Top panel: TMB score. Middle: age, sex, cancer type, microsatellite instability (MSI), TMB positivity, and programmed death-ligand 1 (PD-L1) (measured by combined positive score). Bottom: Oncoprint showing concurrent mutations colored by mutation types. Left: Genes and their mutation frequencies are plotted together. CPS, combined positive score; IHC, immunohistochemistry; MSS, microsatellite stable; N/A, not available.

Fig. 4. Illustrations of epidermal growth factor receptor (EGFR) fusion events with possible functionality. (A) EGFR-ITGB8 fusion. (B) ANKRD17-EGFR fusion. (C) COL4A2-EGFR fusion.

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Fig. 4.

Epidermal Growth Factor Receptor Aberrations Identified by Next-Generation Sequencing in Patients with Metastatic Cancers

Cancer type	ChrA	GeneA	BreakpointA	ChrB	GeneB	BreakpointB
Bladder cancer	chr7	EGFR	chr7:55260533	chr7	ITGB8	chr7:20394291
Bladder cancer	chr4	ANKRD17	chr4:74123992	chr7	EGFR	chr7:55248984
CRC	chr13	COL4A2	chr13:111156448	chr7	EGFR	chr7:55209978

Table 1. Detailed information on EGFR fusion events with possible functionality

CRC, colorectal cancer; EGFR, epidermal growth factor receptor.