https://orcid.org/0000-0002-5516-8914
Figures
Abstract
The validation of several predictive biomarkers has improved the clinical outcomes of non-small cell lung carcinoma (NSCLC) patients. Single tests do not cover the mutational co-occurrences, so they do not detect other alterations, which in many cases are responsible for disease progression. We describe the development and implementation of a customized next generation sequencing (NGS) panel. We analyzed 236 formalin-fixed paraffin-embedded (FFPE) NSCLC samples from the Clinical University Hospital of Santiago de Compostela (Galicia, Northwest Spain) in 2020. Detection of EGFR, KRAS, NRAS, BRAF mutations and ALK, ROS1 rearrangements were determined by real-time polymerase chain reaction (RT-PCR), immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). These results were compared with those obtained by the NGS panel to evaluate the performance of the NGS method and to identify potential novel mutations. Ten discrepancies between NGS and the orthogonal methods were found: 2 cases in the EGFR gene, 1 in the KRAS gene, 5 in the BRAF gene and 2 in the ALK gene. The most prevalent pathogenic alterations detected by NGS were: TP53 (48.7%), KRAS (23.7%), STK11 (9.7%), EGFR (8.5%), PIK3CA (5.5%), CDKN2A (4.7%), BRAF (3.4%) and MET exon skipping 14 (3%); rearrangements were found in ALK and RET (3.5% and 1.7%, respectively). 41.5% of NSCLC patients are harbored co-occurring mutations. Our findings confirmed the robustness, sensitivity and specificity of NGS compared to conventional approaches. NGS has a role not only in the detection of actionable alterations (including concurrent mutations), but also in stratifying patients for therapy.
Citation: Abdulkader-Nallib I, Cameselle-Teijeiro JM, Lesende-Rodríguez I, Pérez-Becerra R, Antúnez-López JR, García-González J, et al. (2025) Next-Generation Sequencing (NGS) in non-small cell lung carcinoma: A real-world experience in the public health system of Galicia (Northwest Spain). PLoS One 20(7): e0326336. https://doi.org/10.1371/journal.pone.0326336
Editor: Federico Pio Fabrizio, Kore University of Enna: Universita degli Studi di Enna 'Kore', ITALY
Received: August 1, 2024; Accepted: May 28, 2025; Published: July 1, 2025
Copyright: © 2025 Abdulkader-Nallib et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data generated in the present study may be found in the Sequence Read Archive (SRA) under accession number PRJNA1118257 or at the following URL: http://www.ncbi.nlm.nih.gov/sra/PRJA1118257.
Funding: This work was partially supported by Instituto de Salud Carlos III (ISCIII), Spain, grant PI23/00722, co-funded by the European Union and by Agilent Technologies though the Codigo 100 program of The Health Knowledge Agency (ACIS) of the Galician Public Health System (Spain).
Competing interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: IAN: none declared; JMCT: none declared; ILR: none declared; RPB: none declared; JRAL: none declared; JGG: fees for membership of an advisory board, consultancy role, speaker’s and receives support for attending meetings from Astrazeneca, Bristol Myers Squibb, Janssen, MSD, Pfizer, Roche, Sanofi and Takeda; LLM: fees for membership of an advisory board, consultancy role, speaker’s and receives support for attending meetings from Astrazeneca, Bristol Myers Squibb, Janssen, MSD, Pfizer, Roche, Sanofi and Takeda; MSA: speaker´s fee for Roche Diagnostics and Lilly and receives support for attending meetings from Roche Diagnostics, Astrazeneca, Agilents, MSD, Pfizer and Qiagen. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Introduction
In the current era of precision medicine, the validation of several predictive biomarkers has dramatically improved the clinical outcomes of advanced cancer patients. This concept has revolutionized the diagnosis and therapy management of diseases, with great strides made in the field of oncology [1–3]. Lung cancer remains the leading cause of cancer mortality worldwide. Non-small cell lung cancer (NSCLC) accounts for around 84% of all lung cancer cases [4,5]. The treatment landscape for NSCLC has rapidly evolved and become associated with several addictive oncogenic driver alterations. The assessment of several specific alterations, including epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene (BRAF), rearranged during transfection (RET), hepatocyte growth factor receptor (MET), receptor tyrosine-protein kinase erbB-2 (ERBB2/HER2), Kirsten rat sarcoma viral oncogene homolog (KRAS), neuregulin (NRG1), fibroblast growth factor receptor (FGFR) and neuro- trophic tyrosine receptor kinase (NTRK) genes, are now recommended in all patients with newly diagnosed NSCLC. The guidelines of several scientific groups (College of American Pathologists [CAP], International Association for the Study of Lung Cancer [IASLC], Association for Molecular Pathology Guideline [AMP]) suggest that molecular testing should be completed at the time of a diagnosis of advanced disease or recurrence [6–8].
Improvements in the understanding of the molecular biology of NSCLC development have led to its categorization into molecular subtypes that facilitate the use of targeted therapies [7]. Co-existence of mutations may have important consequences regarding treatment. Although initially many of these driver alterations were thought to be mutually exclusive, increasing evidence shows this may not be so. Single tests do not cover the mutational co-occurrences, but such alterations could be responsible for tumor progression [9–11].
Characterizing genomic aberrations in tumors for predictive and prognostic purposes by means of genome sequencing has become an integral part of the precision medicine approach [12]. Until recently, most techniques used for this purpose included low- and medium-throughput traditional techniques such as Sanger sequencing, pyrosequencing, real time polymerase chain reaction (RT-PCR), fluorescence in situ hybridization (FISH) or immunohistochemistry (IHC). On the other hand, the study of comprehensive molecular typing of neoplasias is limited by the amount of cytological samples and/or formalin-fixed paraffin-embedded (FFPE) tissue samples, as well as by the response time required for the targeted evaluation of different genes.The increased discovery rate of clinically relevant biomarkers due to extensive characterization of cancer genomes has also necessitated the testing of multiple genes per tumor as the standard of care. Unfortunately, the aforementioned traditional technologies are unable to meet this demand. The revolutionary next-generation sequencing (NGS) technologies provide a viable alternative given their massively parallel sequencing capability, which enables the simultaneous screening of multiple genes in multiple samples [13]. Furthermore, the CAP, National Comprehensive Cancer Network (NCCN) and the European Society for Medical Oncology (ESMO) have proposed the use of expanded panels for broader molecular analysis to identify in NSCLC patients, rare driver mutations for which effective drugs are already available or under development in clinical trials [7,14–16].
Here we describe the development and implementation of CHUS-LUNG, a hybridization capture-based NGS panel capable of detecting all protein coding mutations, copy number variations (CNVs), selected promoter mutations and structural rearrangements in 48 NSCLC associated genes from FFPE samples of NSCLC. The results obtained with this NGS panel were compared with those obtained by traditional techniques, such as RT-PCR, FISH and IHC, to evaluate the performance of the NGS method and to identify novel mutations.
Materials and methods
Patients
We analyzed 236 FFPE tumor tissue specimens NSCLC received in the Department of Pathology at the Clinical University Hospital of Santiago de Compostela (Galicia, Northwest Spain) from March 2020 to December 2020, consecutively, from all patients who underwent molecular study according to the clinical guides of our institution [7,14–16]. The clinico-pathological features of these patients are summarized in Table 1. The mean age of the patients (165 males and 71 females), was 65.9 years, ranging from 36 to 88 years. A majority of patients (231; 97.8%) had stage IV disease, and the majority of tumors were adenocarcinomas (161; 68.2%). Sample types included 167 (70.8%) small biopsies (core and/or bronchoscopic biopsies), 59 (25%) cell blocks (endobronchial ultrasound-guided fine-needle aspiration and pleural effusion), 7 (2.9%) surgical samples and 3 (1.3%) cytological extensions.
The study was carried out following the recommendations of the Declaration of Human Rights, the Conference of Helsinki [17] and the protocol of the study was approved by the Hospital Ethics Committee (code nº: 2019/629; date: 02/18/2020). Signed informed consent was obtained from all patients.
Workflow
FFPE blocks were cut into 5 μm thick tissue sections for molecular analysis in the following order: first hematoxylin and eosin (H&E) stained slide; 3 slides prepared for immunohistochemistry and FISH analysis; 5–10 tissue sections for DNA extraction and a final H&E stained slide (S1 Fig). For all FFPE samples, an experienced pathologist, identified and marked on the second H&E the tumor rich regions of interest to avoid the risk of false negative results. All FFPE samples were scored for tumor cell percentage by standard histological assessment. The percentage of tumor content ranged from 10 to 90%. Tissue material was macrodissected using the H&E slide as a guide, and DNA was extracted from FFPE samples and cytological extensions using Qiagen’s Deparaffinization Solution (catalog number 19093; Qiagen, Hilden, Germany) and the QIAamp DNA FFPE Tissue kit (catalog number 56404; Qiagen, Hilden, Germany) according to the manufacturer’s protocol. The only modification made was to the QIAamp FFPE tissue protocol which used an overnight lysis incubation time at 56°C instead of the suggested 1 hour.
For EGFR, KRAS, NRAS and BRAF study by traditional methods, the DNA quantity and quality obtained from the samples were analysed spectrophotometrically (NanoDrop 1000, Thermo Scientific, Waltham, MA). The quality of extracted DNA was evaluated using an absorbance ratio of 260 nm to 280 nm (A260/A280). For NGS, DNA quality (DNA Integrity Number, DIN) and quantity, of the same DNA, were measured using the Genomic DNA ScreenTape system on the 4200 TapeStation system (catalog numbers 5067–5365 and 5067–5366; Agilent, Santa Clara, CA) according to the manufacturer. Samples with less than 10% of tumor cells, DIN equal to 0 and a concentration ≤ 1 ng/µl were excluded for the NGS study.
Detection of EGFR, KRAS, NRAS, BRAF mutations and ALK, ROS1 rearrangements
EGFR mutation status was determined using the RT-PCR based Cobas EGFR mutation test v2 (catalog number 07248563190; CE-IVD, Roche Diagnostics, Basel, Switzerland) according to the manufacturer’s protocol. This kit can identify 42 different EGFR mutations in exons 18, 19, 20, and 21, using the Roche Cobas Z480 thermocycler (Roche Diagnostic, Basel, Switzerland). KRAS, NRAS and BRAF mutation status was determined using the KRAS v2 mutation test (LSR) (catalog number 078927001) and BRAF/NRAS mutation test (LSR) (catalog number 07659962001) kits in the Roche Cobas z480 system (Roche Diagnostic, Basel, Switzerland) according to the manufacturer’s instructions. These RT- PCR tests examined the most common mutations in codons 12, 13, 59, 61, 117 and 146 in the KRAS and NRAS genes; and in codons 466, 469, 600 and 601 of the BRAF gene. Data analysis was performed by uploading files to the online LSR Data Analysis tool https://lifescience.roche.com/en_nl/brands/oncology-research-kits.html.
A third method was used to further analyze some of the samples having a discordant result between the RT-PCR and NGS assays. The Idylla™ EGFR Mutation Test (catalog number A0060/6), an automatic cartridge-based RT-PCR assay, was performed using the Biocartis Idylla™ System (Biocartis, Mechelen, Belgium), according to the manufacturer’s indications, in the cases with discordant results in EGFR. KRAS and BRAF genes were reanalyzed using the Therascreen KRAS Pyro Kit (catalog number 970460) and Therascreen BRAF Pyro Kit (catalog number 971470) (Qiagen, Hilden, Germany) according to manufacturer’s recommendation, respectively. Pyrosequencing was performed on the PyroMark Q24 platform (Qiagen, Hilden, Germany) using the PyroMark Gold Q24 reagents. Pyrograms were generated with PyroMark Q24 software (v.2.0.6.) and the data were analyzed manually or with a plug-in tool provided by Qiagen (Qiagen, Hilden, Germany).
ALK and ROS1 rearrangements were studied by IHC employing the VENTANA ALK (D5F3) CDx Assay (catalog number 790−4796; Roche Diagnostics, Basel, Switzerland) and IHC ROS1 Clone D4D6 (catalog number 3287S; Cell Signaling Technology, Danvers, MA, USA), respectively. Positive IHC ALK assays were confirmed by fluorescence in situ hybridization employing Vysis ALK Break Apart FISH Probe kit (catalog number 06N38-023; Abbot, Abbot Park, IL).
Design of the custom cancer panel
Custom RNA probes in this study were designed for targeted sequencing for all exons, 3´UTR (unstranlated region) and 5´UTR regions and at least, 25 bp 5′ and 3′ flanking intronic sequences of 48 NSCLC-related genes for detection of single-nucleotide variants (SNVs), insertions and deletions (indels), and CNVs: AKT1 (AKT serine/threonine kinase 1, NM_05163), AKT3 (AKT serine/threonine kinase 3, NM_005465), ALK (NM_004304), APC (APC regulator of WNT signaling pathway, NM_000038), BRAF (NM_004333), BRCA1 (BRCA1 DNA repair associated, NM_007294), BRCA2 (BRCA2 DNA repair associated, NM_000059), CDKN2A (cyclin dependent kinase inhibitor 2A, NM_000077), CTNNB1 (catenin beta 1, NM_001904), DDR2 (discoidin domain receptor tyrosine kinase 2, NM_001014796), EGFR (NM_005228), ERBB2 (NM_004448), ERBB3 (erb-b2 receptor tyrosine kinase 3, NM_001982), ERBB4 (erb-b2 receptor tyrosine kinase 4, NM_005235), FGFR1 (fibroblast growth factor receptor 1, NM_023110), FGFR2 (fibroblast growth factor receptor 2, NM_000141), FGFR3 (fibroblast growth factor receptor 3, NM_000142), HRAS (HRas proto-oncogene, GTPase, NM_00534), IDH1 (isocitrate dehydrogenase (NADP(+)) 1, NM_005896), IDH2 (isocitrate dehydrogenase (NADP(+)) 2, NM_002168), JAK1 (Janus kinase 1, NM_002227), JAK2 (Janus kinase 2, NM_004972), KEAP1 (kelch like ECH associated protein 1, NM_203500), KIT (KIT proto-oncogene, receptor tyrosine kinase, NM_000222), KRAS (NM_033360), MAP2K1 (mitogen-activated protein kinase kinase 1, NM_002755), MAP2K2 (mitogen-activated protein kinase kinase 2, NM_030662), MET (NM_000245.), MYC (MYC proto-oncogene, bHLH transcription factor, NM_002467), NF1 (neurofibromin 1, NM_00026), NRAS (NRAS proto-oncogene, GTPase, NM_002524), NRG1 (NM_013962), NTRK1 (neurotrophic receptor tyrosine kinase 1, NM_002529), NTRK2 (neurotrophic receptor tyrosine kinase 2, NM_006180), NTRK3 (neurotrophic receptor tyrosine kinase 3, NM_001012338), PDGFRA (platelet derived growth factor receptor alpha, NM_006206), PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha, NM_006218), POLD1 (DNA polymerase delta 1, catalytic subunit, NM_002691), POLE (DNA polymerase epsilon, catalytic subunit, NM_006321), PTEN (phosphatase and tensin homolog, NM_000314), RB1 (RB transcriptional corepressor 1, NM_000321), RET (NM_020975), ROS1 (NM_002944), SLC34A2 (solute carrier family 34 member 2, NM_006424.3), SOX2 (SRY-box transcription factor 2, NM_003106), STK11 (serine/threonine kinase 11, NM_000455), TERT (telomerase reverse transcriptase, NM_198253), TP53 (tumor protein p53, NM_000546). In addition, the panel was also designed to identify rearrangements by detecting the intronic breakpoints previously described in 11 genes (ALK, RET, ROS1, NTRK1, NTRK2, NTRK3, NGR1, FGFR1, FGFR2, FGFR3 and BRAF genes). The oligonucleotides are 120 bp in length and were manufactured by Agilent-developed sureprint technology, the software to create the 93856 probes was SureDesign (Agilent, Santa Clara, CA) which uses different algorithms to create the probes based on the percentage of Guanine-Cytosine (GC) and the repetitive regions of the genome. The user only needs to select the genomic region and the software creates the probes to ensure the best possible capture of area of interest. The probes are 5’biotinylated oligonucleotide. After isolating probes annealed to complementary fragments with streptavidin-coated beads, the library fragments were sequenced by adding an adapter compatible with this sequencing system (Illumina, Inc, San Diego CA). This means that it was not the probes that were sequenced, but the regions that were complimentary to these probes. This strategy makes it possible to detect fusions of these genes with any other partner throughout the genome. The panel includes the main actionable biomarkers relevant for the therapy, prognosis, and diagnosis of NSCLC, as well as other genes associated with therapies being tested in clinical trials or susceptible to being developed in the future in several solid tumor types.
The genes were selected based on clinical guidelines such as National Comprehensive NCCN Guidelines®, ESMO and the National Consensus of the Spanish Society of Pathology and the Spanish Society of Medical Oncology [18], as well as recommendations of international organizations such as the Food & Drug Administration (FDA) and the European Medicines Agency (EMA).
Library construction and sequencing
All reactions were performed in the range of 50–200 ng of the total genomic DNA (gDNA) that was fragmented in the Covaris M220 focused-ultrasonicator (Covaris Inc., Woburn, MA) to generate DNA fragments between 150–200 bp. Libraries were prepared using the SureSelect XT HS Target Enrichment system using the Magnis NGS Prep system (catalog number G9771D; Agilent, Santa Clara, CA) following the manufacturer’s protocol. Libraries were validated and quantified using the High Sensitivity D1000 ScreenTape system on the 4200 TapeStation system (catalog numbers 5067–5584 and 5067–5585; Agilent, Santa Clara, CA) according to the manufacturer’s protocol. Pooled libraries were subsequently sequenced using the NextSeq 550 Mid Output Kit v2.5 (150 cycles) on the Illumina NextSeq 550 system as 2 × 76-bp paired-end reads (catalog number 20024904; Illumina, Inc., San Diego, CA), running 24 samples for each sequencing run to obtain an average coverage of about 400x (>95% of the gene’s target nucleotides are covered at 200x, after removing the duplication reads). This platform collects all the information in demultiplexed and paired FASTQ files for subsequent bioinformatic analysis.
Data analysis and classification of variants
The obtained FASTQ files were aligned to the NCBI human reference genome (hg19-Genome Reference Consortium GRCh37). The alignment and variant calling were assessed through SureCall software v.4.2 (Agilent, Santa Clara, CA), with interpretation and priorization by Alissa Interpret Analysis Software v.5.3.4 (Agilent, Santa Clara, CA) using a filtering tree. CNVs were identified using open source software called CNVkit [19]. Variants were visually examined using the Integrative Genome Viewer (IGV) from the Broad Institute (http://www.broadinstitute.org/igv). In order to assess the pathogenicity of the detected sequence variants several databases were used: Catalogue of Somatic Mutations in Cancer (COSMIC, http://cancer.sanger.ac.uk/cosmic), Single Nucleotide Polymorphism Database (dbSNPs, http://www.ncbi.nlm.nih.gov/snp), NCBI’s Clinical Variants (ClinVar, http://www.ncbi.nlm.nih.gov/clinvar), My Cancer Genome (MCG, http://www.mycancergenome.org) and Oncology Knowledge Base (OncoKB, https://www.oncokb.org/).
Analytical validation: Sensitivity, specificity and reproducibility analysis
The validation analysis was performed using 18 well-characterized samples to evaluate the presence or absence of somatic variants. The sensitivity and specificity were determined by comparing NGS testing with conventional methods for routinely tested alterations. All mutations were detected, resulting in an analytical sensitivity of 100%. No other mutations were detected in the total of 18 samples analyzed, thus resulting in an analytical specificity of greater than 99%. To calculate reproducibility, the closeness between the results of successive analyses of the same panel carried out under different measurement conditions was analyzed. The conditions that changed in the reproducibility tests were: a) the origin of the sample, b) the operator who performed the test, and c) the reagents used and the measurement equipment with which the test was carried out. The same 3 samples were analyzed in two different assays with different operators, kits with different batches and different sequencing equipment. The 3 variants were detected in both assays, which gave a reproducibility of 100%. The minimum detection limit was 1%. To evaluate the performance of the NGS assay for a minimum detection limit of 1%, 3 samples with known variants were selected and diluted with a negative sample for the same variant until reaching an allelic frequency of 1%. They were analyzed in triplicate in the same assay, and in triplicate in a second assay to evaluate the reproducibility parameter. The 3 selected samples had the following mutations: EGFR exon 19 deletion, ALK translocation and p.Q61H point mutation in the KRAS gene. The set of mutations was detected in the 3 samples and in the two series, resulting in values greater than 95% for repeatability with variants at an allelic frequency of 5% reaching the minimum detection limit.
Results
Mutations detected by orthogonal methods and NGS
Table 2 summarizes all EGFR, KRAS and BRAF mutations detected by both NGS and RT-PCR. We detected mutated EGFR in 8.5% of NSCLC patients by targeted NGS, and by RT-PCR. 23.7% of patients had a KRAS gene mutation according to targeted NGS. All tumors containing an EGFR mutation and 91.1% of KRAS mutated cases were adenocarcinomas. 50% of patients carrying an EGFR mutation were women, whereas 73.2% of the patients with a KRAS mutation were men and 26.7% women. BRAF mutation was detected in 3.4% of patients with NSCLC according to targeted NGS and 1% by RT-PCR. Almost all samples with BRAF mutation (87.5%), seven out of eight, were adenocarcinomas and 75% were men. Rearrangements were found in ALK in eight patients (3.5%) by NGS and six patients (2.6%) by IHC/FISH, 57.2% of them women (S2 Fig). NRAS mutation was found in one patient by both methods. No ROS1 rearrangement was found.
Concordance between NGS and orthogonal methods
Table 3 shows a very high concordance of the results between NGS and RT-PCR. There were only 10 discrepancies between the NGS and the other methods. We have not identified any correlation between discordant results and clinicopathological characteristics (S1 Table). Two discordant EGFR mutation results were detected; one mutation (insertion exon 20) was detected by RT-PCR but not by NGS; in contrast indel p.E709_T710delinsD in exon 18 was found in NGS but not in the Cobas assay. The first sample was reanalyzed using the Idylla™ EGFR Mutation Test (Biocartis, Mechelen, Belgium) with no mutation detected. Thus, we concluded NGS to be the correct assay. In the second case, indel is not targeted in the design of the Cobas assay and was not considered discordant.
One discrepancy was found in the 67 NSCLC patients tested for KRAS; a G13X mutation was detected by RT-PCR but not by NGS. This sample was reanalyzed using the Therascreen KRAS Pyro Kit (Qiagen, Hilden, Germany) with a negative result, thus showing a false positive detected by RT-PCR.
Five discordant BRAF mutations were detected in NSCLC patients, four mutations (1 case p.G464V, 2 cases p.G469V, 1 case p.V600E were detected by NGS but not by RT-PCR and 1 variant (V600E/E2/D) detected by RT-PCR but not by NGS. These samples were reanalyzed by pyrosequencing yielding results concordant with NGS. Mutation p.G464V is not targeted in the BRAF/NRAS mutation test design (LSR) (Roche Diagnostic, Basel, Switzerland) and was not considered discordant (S3 Fig).
Out of 233 patients tested, 6 (2,5%) were positive for ALK rearrangements in both NGS and ST and 2 were discordant. One case was analyzed by FISH and the result was positive; in the other, the study could not be carried out due to the absence of material.
The pathogenic alterations detected by NGS are shown in Fig 1. The most prevalently mutated gene was TP53 (48.7%) followed by KRAS (23.7%), STK11 (9.7%), EGFR (8.5%), PIK3CA (5.5%), CDKN2A (4.7%), BRAF (3,4%) and MET exon skipping 14 (3%). Rearrangements were found in ALK and RET (3.5% and 1.7%, respectively).
NGS, next-generation sequencing; NSCLC, non-small cell lung cancer.
Ninety-eight (41.5%) of the 236 NSCLC patients harbored co-occurring mutations. In 73 (74.5%) patients there were two molecular alterations and 25 (25.5%) patients had three or more. TP53 was present in 78 of 98 co-occurring mutations. KRAS and TP53 was the most frequent combination (n = 14) followed by KRAS and STK11 (n = 12). Seven EGFR mutations appeared in concurrency with TP53 mutations. Two patients carried a deletion in exon 19 of the EGFR gene accompanied by mutations in PIK3CA and CTNNB1 genes, respectively. Two EGFR mutated patients harbored a double concurrent mutation, one with TP53 and STK11 mutations and the other with a TP53 mutation and EGFR gain/amplification. One EGFR mutated patient had concurrent mutations in TP53, CDKN2A and CTNNB1 genes. Among the 56 KRAS mutated samples, fourteen were in concurrency with TP53 mutations, twelve with STK11 mutations, seven KRAS with two concurrent mutations (CDKN2A, NRAS, PIK3CA, RB1, STK11, TP53 and/or MYC amplification), and one KRAS with three concurrent mutations (BRCA1, NF1 and TP53). BRAF mutation was found in concurrency with STK11 (n = 2), TP53 (n = 1) and one case with concurrent mutations in STK11, PIK3CA and MET exon 14 skipping. NRAS was concomitant in one sample with KRAS and TP53. One patient with ALK rearrangement also had a concurrent TP53 mutation (Fig 2).
P, patient; R, rearrangement; CNV; copy number variation; NSCLC, non-small cell lung cancer.
NGS identified clinically relevant genomic alterations in 55% of NSCLC patients (Fig 3). The most prevalent was detected in KRAS (23.7%) followed by STK11 (9.7%) and EGFR (8.5%). BRAF mutation and MET exon 14 skipping were detected in 3.4% and 3% respectively. Duplication and insertions exon 20 (1.7%) were found in ERBB2. Eight patients showed fusions between ALK and EML4 (Echinoderm microtubule-associated protein-like 4), all these rearrangements involving exon 20 of ALK. In three patients the rearrangement included exon 13, (EML4(13)::ALK(20), variant 1), in two patients exon 20 (EML4(20)::ALK(20), variant 2), in one patient exon 2 (EML4(2)::ALK(20), variant 5) and in another exon 6 (EML4(6)::ALK(20), variant 3). Four patients presented rearrangements in RET, two of them involving the kinesin family member 5B (KIF5B) (KIF5B(15)::RET(12)) and the other two involving the coiled-coil domain containing 6 (CCDC6) (CCDC6(1)::RET(12)) and the ankyrin repeat and sterile alpha motif domain containing 1B (ANKS1B) (ANKS1B(8)::RET(12)), respectively.
NSCLC, non-small cell lung cancer; NGS, next-generation sequencing.
Discussion
The integration of a high-throughput technology into clinical routine practice of a public health system represents a major challenge [20–22]. In this study, we show that NGS technology is able to efficiently amplify and sequence multiple genes with small amounts of DNA from FFPE samples, as well as analyze different genomic alteration events (SNVs, indels, CNVs and/or fusions) (S2 Table). We screened for EGFR, KRAS, BRAF mutations and ALK and ROS1 rearrangements in NSCLC by targeted NGS and conventional methods. Our findings confirm the excellent sensitivity and specificity of NGS compared with single-gene targeted assays. The use of these panels requires a shorter run time than sequential studies, as shown in S3 Table. In addition, these panels are cost-effective, maximize coverage, and minimize off-target effects [23–26]. Overall, concordance of our results was very high, and we detected only ten discrepant results between NGS and the orthogonal methods: two cases in the EGFR gene, one in the KRAS gene, five in the BRAF gene and two in the ALK gene.
Regarding EGFR mutations, we found a patient with squamous cell carcinoma who tested positive with the Cobas® assay (insertion exon 20) and not mutated by NGS. The absence of the insertion was confirmed by Idylla. The possibility of Cobas® EGFR being able to generate false positive results for exon 20 insertion mutations has been previously described. In their article, Kanaoka et al reported four Cobas® EGFR results positive for exon 20 insertion in four patients with squamous cell carcinoma that later tested negative using NGS and fragment analysis. As the authors mentioned, more studies are necessary to determine the mechanism responsible for these false positives [27]. Our results highlight the need to validate this type of alterations by a second method to select the correct treatment for the patient. In another case, an insertion in exon 18 of EGFR was detected by NGS but not by Cobas. This mutation is not included in the Cobas test, which highlights one of the limitations of this PCR method, which only identifies the most common loci. With advances in NGS technology, the regions of interest can be sequenced to improve the chances of identifying rare variants which are susceptible to treatment with EGFR-TKI. Rare EGFR mutations could also be equally important targets in the treatment of advanced-stage lung cancer; therefore, detailed information regarding EGFR mutation type is needed to apply appropriate therapies. These results indicate the use of targeted sequencing with improved sensitivity to identify mutations of low frequency. In our experience, the additional mutations detected by targeted sequencing were helpful to understand the clinical course of some of the patients in each group.
Concerning KRAS testing, we detected one discordant case. One sample was positive by RT-PCR assay but negative by NGS. This sample was re-tested using a pyrosequencing assay, which then provided results concordant with the NGS assay. The most usual technique to identify KRAS mutations is PCR. Thus far, their detection in isolation has not been recommended, but should be included in NGS panels [28]. At our institution, KRAS was not routinely tested in all patients by RT-PCR; it was only carried out later in those patients who were positive in NGS using the same DNA. After years without effective therapies, several inhibitors have been developed that have shown activity in phase II trials against the KRAS p.G12C mutation, such as sotorasib and adagrasib [29,30]. These drugs have been approved by the FDA, although their benefit in monotherapy or in combination, as well as the profile of the patients to which they should be administered, are being studied in phase III trials [22].
For BRAF mutations, there were five discordant cases between NGS and Cobas. In the NGS study, we found four patients with BRAF mutation non p.V600E that were negative by RT-PCR. Current approved targeted inhibitors for BRAF driven lung cancers include dabrafenib and vemurafenib, which are only effective toward p.V600E mutation. Nevertheless, in patients with lung cancer, approximately 70% of BRAF mutations are non-V600 mutations, leaving these patients without a targeted therapy. Mechanistic studies supported by structural modeling strongly suggest that although the p.G469V substitution activates BRAF, it also renders it sensitive to direct targeting by the EGFR TKIs [31]. Another study by Noeparast et al., investigated a patient cohort of NSCLC and demonstrated that non-V600 BRAF mutations, resulting in either high or impaired kinase activity, confer sensitivity to combined dabrafenib and trametinib treatment [32]. Therefore, BRAF testing with sequencing assays is mandatory for the correct diagnosis and treatment of patients with advanced NSCLC given that they could benefit from these treatments.
Concerning ALK rearrangements, in our cohort, we observed two fusions by NGS not identified by IHC. One case was reanalyzed by FISH and resulted positive; in the other case, the study could not be carried out due to the absence of material. The patients’ medical history was reviewed and in both cases the patients are being treated with ALK inhibitors and have shown response. Some of the reasons associated with false negative results are: a) the use of pre-cut slides that can cause differences in the intensity of IHC staining, at times even causing unequivocally false negative results; b) suboptimal simple fixation; c) suboptimal analytical phase, and/or d) the presence of fewer than 50 tumor cells [33]. Our data are consistent with those of Velizheva et al., who demonstrate the greater robustness and reliability of targeted NGS for fusion detection, compared to isolated tests such as FISH [34]. Overall, NGS has proven to be a valid alternative to conventional molecular testing in terms of diagnostic accuracy [35].
Mutations in the EGFR gene are identified in approximately 10–16% of NSCLCs, with a higher frequency among patients with adenocarcinoma and non-smoking patients. We found EGFR gene mutations in 8.5% of patients, in line with frequencies reported in Spain and western countries, when taking into consideration that in our series 69.9% were men and only 68.2% adenocarcinomas. EGFR mutation subtypes p.L858R and deletions in exon 19 were the most frequent in our cohort in accordance with what is described in other articles [10,36,37]. Mutations in KRAS are identified in 25% of patients with NSCLC. They are found in all histological subtypes of adenocarcinoma, although more common in the invasive mucinous subtype [38]. In our series, 23.7% of patients have KRAS mutations, and mutations p.G12C, p.G12V, and p.G12D were the most frequent, fitting well with previous reports [39]. For BRAF mutations, our NGS study revealed a percentage of 2.5%, similar to that reported in the literature [36,40]. ALK rearrangements are present in 3.5% of patients in our study, which is within the 2–5% previously reported [41,42]. Our percentage of 1% of NRAS is the same as that found in other series of the Spanish population [36]. No ROS1 rearrangements were detected in this study, which can be explained by the epidemiological and clinico-pathological characteristics of our series together with the low prevalence of ROS1 rearrangement reported in NSCLC [43,44].
Our study has shown concurrent mutations in 41.5% of patients, which exemplifies the complexity of the molecular biology of NSCLC. This is a rather high proportion in comparison to another series, which previously reported at a frequency of 2–12.3% [10,45,46] and also higher when compared to another study in a Spanish population, which was 35% [36]. In some cases, the co-existence occurs among non-activating mutations, but frequently it involves well known activating mutations. The rate of co-existence can vary among the different techniques, depending on their sensitivity. Won et al found a 4.4% EGFR and ALK co-existence frequency in ALK positive patients screened by Sanger sequencing. This was further raised to a 15% frequency when high sensitivity NGS methodology was applied [47]. Importantly, our study uncovered an underappreciated utility of NGS testing. EGFR and TP53 co-mutation was associated with poorer progression free survival (PFS) outcomes when treated with first-line EGFR TKI than when compared with a single EGFR mutation. This was especially seen in EGFR p.L858R mutation patients, with no significant difference in EGFR exon 19 deletion patients [24,48]. STK11 mutations are present in variable percentages in different tumor types. The frequency of STK11 mutations in lung cancer varies from 5% to 30%. In a real-world study by Shire NJ et al. [49], a prevalence of 13.6% for mutated STK11 was found, with co-occurring KRAS mutations in 6.5% of patients. The prevalence of STK11 in our study was 9.7%, which is within the range previously reported. About half (5.1%) of the patients with STK11 mutations had a co-mutation in KRAS, which is also consistent with the frequency of co-mutations previously reported in the literature [49]. Co-existence of other oncogenic alterations such as ERBB2 and MET amplifications and PIK3CA, PTEN and RB1 mutations have also been associated with poorer responses to therapy [11]. Additionally, NGS has the benefit of detecting the specific fusion variant and partner, which in ALK rearranged NSCLC, may have prognostic and therapeutic implications [9].
A limitation of the present study has been the lack of data available to establish a correlation between the molecular alterations and the treatment of the patients. The NGS panel is limited to 48 genes. Nor is it possible to establish any correlation between stage and type of mutations. Another additional limitation of this work is that it has not been designed to compare the response time between orthogonal methods and NGS.
In summary, 55% of NSCLC patients harbored a potential clinically actionable alteration, consistent with previous studies [36,50] and according to current guidelines [7,16,22], confirming the applicability of these technologies in precision medicine. Multiple biomarker testing has become a major challenge for molecular diagnostic laboratories given the increasing number of approved targeted. NGS therefore has a role, not only in detecting actionable alterations, but also in stratifying patients for therapy.
Supporting information
S1 Table. Clinico-pathological characteristics of discordant results.
NGS, next-generation sequencing; M, male; F, female.
https://doi.org/10.1371/journal.pone.0326336.s001
(DOCX)
S2 Table. Main characteristics of the customized CHUS-LUNG panel compared to commercial panels.
https://doi.org/10.1371/journal.pone.0326336.s002
(DOCX)
S3 Table. Comparison of the main advantages and disadvantages between NGS and conventional sequencing methods.
NGS, next-generation sequencing.
https://doi.org/10.1371/journal.pone.0326336.s003
(DOCX)
S1 Fig. Diagram of the workflow of samples from patients with non-small cell lung carcinoma (NSCLC).
First, the tumor areas were identified and marked, quantifying the percentage of tumor cells. Then, 3 slides were prepared for immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). Next, DNA extraction was carried out, including quality and quantity controls. Finally, the orthogonal and next generation sequencing (NGS) studies were carried out. In cases with discordant results, an additional alternative methodology was used.
https://doi.org/10.1371/journal.pone.0326336.s004
(TIF)
S2 Fig. Immunohistochemical and fluorescence in situ hybridization (FISH) images in non-small cell lung carcinoma (NSCLC).
(A) Lung adenocarcinomas showing immunohistochemical positivity (brown staining) (A) and negativity (B) for ALK. FISH image showing ALK rearrangements (arrows)(C). ALK FISH negative specimen (D). Immunohistochemical negativity for ROS1 in a case of the present series (E), and positive control for ROS1 (F). Lung adenocarcinomas with and without ALK and ROS1 rearrangements have been used as positive and negative controls, respectively.
https://doi.org/10.1371/journal.pone.0326336.s005
(TIF)
S3 Fig. Pyrograms of KRAS (codon 13) and BRAF (codons 469 and 600) of discordant results between NGS and RT-PCR assays.
The left column shows the results of the pyrosequencing studies that are consistent with those obtained by NGS. The right colum shows the negative and positive controls. Wild-type codon 13 of KRAS gene (A) and positive control of mutated codon 13 of KRAS (arrow) (B). Pyrogram showing a mutation in codon 469 of BRAF gene (arrow) (C), and wild-type control of codon 469 of BRAF (D). Pyrogram showing a mutation in codon 600 of BRAF gene (arrow) (E), and wild-type control of codon 600 of BRAF gene (F). Wild-type codon 600 of BRAF gene (G), and positive control of mutated codon 600 of BRAF gene (arrow) (H).
https://doi.org/10.1371/journal.pone.0326336.s006
(TIF)
References
- 1. Vargas AJ, Harris CC. Biomarker development in the precision medicine era: lung cancer as a case study. Nat Rev Cancer. 2016;16(8):525–37. pmid:27388699
- 2. Han Y, Li J. Sample types applied for molecular diagnosis of therapeutic management of advanced non-small cell lung cancer in the precision medicine. Clin Chem Lab Med. 2017;55(12):1817–33.
- 3. Gambardella V, Tarazona N, Cejalvo JM, Lombardi P, Huerta M, Roselló S. Personalized medicine: recent progress in cancer therapy. Cancers. 2020;12(4):1009.
- 4. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.
- 5. Kerr KM, Bibeau F, Thunnissen E, Botling J, Ryška A, Wolf J, et al. The evolving landscape of biomarker testing for non-small cell lung cancer in Europe. Lung Cancer. 2021;154:161–75. pmid:33690091
- 6. Kalemkerian GP, Narula N, Kennedy EB, Biermann WA, Donington J, Leighl NB, et al. Molecular testing guideline for the selection of patients with lung cancer for treatment with targeted tyrosine kinase inhibitors: American society of clinical oncology endorsement of the college of american pathologists/international association for the study of lung cancer/association for molecular pathology clinical practice guideline update. J Clin Oncol. 2018;36(9):911–9. pmid:29401004
- 7. Lindeman NI, Cagle PT, Aisner DL, Arcila ME, Beasley MB, Bernicker EH, et al. Updated molecular testing guideline for the selection of lung cancer patients for treatment with targeted tyrosine kinase inhibitors: guideline from the college of american pathologists, the international association for the study of lung cancer, and the association for molecular pathology. J Thorac Oncol. 2018;13(3):323–58.
- 8. Yates LR, Seoane J, Le Tourneau C, Siu LL, Marais R, Michiels S, et al. The European Society for Medical Oncology (ESMO) precision medicine glossary. Ann Oncol. 2018;29(1):30–5. pmid:29140430
- 9. Lin JJ, Zhu VW, Yoda S, Yeap BY, Schrock AB, Dagogo-Jack I. Impact of EML4-ALK variant on resistance mechanisms and clinical outcomes in ALK-positive lung cancer. J Clin Oncol. 2018;36(12):1199–206.
- 10. Martín MP, Huerta M, Compañ QA, Abellán R, Seda E, Blesa S, et al. Coexistence of EGFR, KRAS, BRAF, and PIK3CA mutations and ALK rearrangement in a comprehensive cohort of 326 consecutive Spanish nonsquamous NSCLC patients. Clin Lung Cancer. 2017;18(6):e395–e402.
- 11. Rosell R, Karachaliou N. Co-mutations in EGFR driven non-small cell lung cancer. EBioMedicine. 2019;42:18–9. pmid:30904603
- 12. Richer AL, Friel JM, Carson VM, Inge LJ, Whitsett TG. Genomic profiling toward precision medicine in non-small cell lung cancer: getting beyond EGFR. Pharmgenomics Pers Med. 2015;8:63–79.
- 13. Luthra R, Chen H, Roy-Chowdhuri S, Singh RR. Next-generation sequencing in clinical molecular diagnostics of cancer: advantages and challenges. Cancers (Basel). 2015;7(4):2023–36.
- 14. Jennings LJ, Arcila ME, Corless C, Kamel-Reid S, Lubin IM, Pfeifer J, et al. Guidelines for validation of next-generation sequencing-based oncology panels: a joint consensus recommendation of the association for molecular pathology and college of american pathologists. J Mol Diagn. 2017;19(3):341–65. pmid:28341590
- 15. Planchard D, Popat S, Kerr K, Novello S, Smit EF, Faivre-Finn C, et al. Metastatic non-small cell lung cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2018;29(Suppl 4):iv192–237.
- 16. Ettinger DS, Wood DE, Aisner DL, Akerley W, Bauman JR, Bharat A, et al. NCCN guidelines® insights: non-small cell lung cancer, version 2.2023. J Natl Compr Canc Netw. 2023;21(4):340–50.
- 17. World Medical Association. World medical association declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191–4. pmid:24141714
- 18. Garrido P, Conde E, de Castro J, Gómez-Román JJ, Felip E, Pijuan L, et al. Updated guidelines for predictive biomarker testing in advanced non-small-cell lung cancer: a National consensus of the Spanish society of pathology and the Spanish society of medical oncology. Clin Transl Oncol. 2020;22(7):989–1003. pmid:31598903
- 19. Talevich E, Shain AH, Botton T, Bastian BC. CNVkit: genome-wide copy number detection and visualization from targeted DNA sequencing. PLoS Comput Biol. 2016;12(4):e1004873. pmid:27100738
- 20. Mosele F, Remon J, Mateo J, Westphalen CB, Barlesi F, Lolkema MP, et al. Recommendations for the use of next-generation sequencing (NGS) for patients with metastatic cancers: a report from the ESMO precision medicine working group. Ann Oncol. 2020;31(11):1491–505. pmid:32853681
- 21. Fountzilas E, Tsimberidou AM, Vo HH, Kurzrock R. Clinical trial design in the era of precision medicine. Genome Med. 2022;14(1):101. pmid:36045401
- 22. Isla D, Lozano MD, Paz-Ares L, Salas C, de Castro J, Conde E, et al. New update to the guidelines on testing predictive biomarkers in non-small-cell lung cancer: a national consensus of the Spanish society of pathology and the spanish society of medical oncology. Clin Transl Oncol. 2023;25(5):1252–67.
- 23. Han J-Y, Kim SH, Lee Y-S, Lee S-Y, Hwang J-A, Kim JY, et al. Comparison of targeted next-generation sequencing with conventional sequencing for predicting the responsiveness to epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) therapy in never-smokers with lung adenocarcinoma. Lung Cancer. 2014;85(2):161–7. pmid:24857785
- 24. Tan AC, Lai GGY, Tan GS, Poon SY, Doble B, Lim TH, et al. Utility of incorporating next-generation sequencing (NGS) in an Asian non-small cell lung cancer (NSCLC) population: incremental yield of actionable alterations and cost-effectiveness analysis. Lung Cancer. 2020;139:207–15. pmid:31835042
- 25. Park E, Shim HS. Detection of targetable genetic alterations in korean lung cancer patients: a comparison study of single-gene assays and targeted next-generation sequencing. Cancer Res Treat. 2020;52(2):543–51. pmid:31726498
- 26. Murakami S, Yokose T, Shinada K, Isaka T, Katakura K, Ushio R, et al. Comparison of next-generation sequencing and cobas EGFR mutation test v2 in detecting EGFR mutations. Thorac Cancer. 2022;13(22):3217–24. pmid:36203199
- 27. Kanaoka K, Tamiya A, Inagaki Y, Taniguchi Y, Nakao K, Takeda M, et al. Possible false results with cobas® EGFR mutation test v2 and oncomine Dx target test for EGFR mutation. Anticancer Res. 2023;43(6):2771–6. pmid:37247929
- 28. Reck M, Carbone DP, Garassino M, Barlesi F. Targeting KRAS in non-small-cell lung cancer: recent progress and new approaches. Ann Oncol. 2021;32(9):1101–10. pmid:34089836
- 29. Skoulidis F, Li BT, Dy GK, Price TJ, Falchook GS, Wolf J, et al. Sotorasib for lung cancers with KRAS p.G12C mutation. N Engl J Med. 2021;384(25):2371–81. pmid:34096690
- 30. Ou S-HI, Jänne PA, Leal TA, Rybkin II, Sabari JK, Barve MA, et al. First-in-human phase I/IB dose-finding study of adagrasib (MRTX849) in patients with advanced KRASG12C solid tumors (KRYSTAL-1). J Clin Oncol. 2022;40(23):2530–8. pmid:35167329
- 31. Huo K-G, Notsuda H, Fang Z, Liu NF, Gebregiworgis T, Li Q, et al. Lung cancer driven by BRAFG469V mutation is targetable by EGFR kinase inhibitors. J Thorac Oncol. 2022;17(2):277–88. pmid:34648945
- 32. Noeparast A, Teugels E, Giron P, Verschelden G, De Brakeleer S, Decoster L, et al. Non-V600 BRAF mutations recurrently found in lung cancer predict sensitivity to the combination of Trametinib and Dabrafenib. Oncotarget. 2016;8(36):60094–108. pmid:28947956
- 33. Hernandez S, Conde E, Alonso M, Illarramendi A, Bote de Cabo H, Zugazagoitia J, et al. A narrative review of methods for the identification of ALK fusions in patients with non-small cell lung carcinoma. Transl Lung Cancer Res. 2023;12(7):1549–62. pmid:37577307
- 34. Velizheva NP, Rechsteiner MP, Valtcheva N, Freiberger SN, Wong CE, Vrugt B. Targeted next-generation-sequencing for reliable detection of targetable rearrangements in lung adenocarcinoma-a single center retrospective study. Pathol Res Pract. 2018;214(4):572–8.
- 35. Biswas B. Clinical performance evaluation of molecular diagnostic tests. J Mol Diagn. 2016;18(6):803–12. pmid:27639547
- 36. Simarro J, Murria R, Pérez-Simó G, Llop M, Mancheño N, Ramos D, et al. Development, implementation and assessment of molecular diagnostics by next generation sequencing in personalized treatment of cancer: experience of a public reference healthcare Hospital. Cancers (Basel). 2019;11(8):1196. pmid:31426418
- 37.
Sholl LM, Cooper WA, Kerr KM, Tan DSW, Tsao MS, Yang JCH. IASLC atlas of molecular testing in lung cancer. Denver, CO: IALSC; 2023.
- 38. Duma N, Santana-Davila R, Molina JR. Non-small cell lung cancer: epidemiology, screening, diagnosis, and treatment. Mayo Clin Proc. 2019;94(8):1623–40. pmid:31378236
- 39. Veluswamy R, Mack PC, Houldsworth J, Elkhouly E, Hirsch FR. KRAS G12C-mutant non-small cell lung cancer: biology, developmental therapeutics, and molecular testing. J Mol Diagn. 2021;23(5):507–20.
- 40. Planchard D, Johnson BE. BRAF Adds an additional piece of the puzzle to precision oncology-based treatment strategies in lung cancer. Arch Pathol Lab Med. 2018;142(7):796–7. pmid:29648886
- 41. Zugazagoitia J, Biosca M, Oliveira J, Olmedo ME, Dómine M, Nadal E, et al. Incidence, predictors and prognostic significance of thromboembolic disease in patients with advanced ALK-rearranged non-small cell lung cancer. Eur Respir J. 2018;51(5):1702431. pmid:29563169
- 42. Tan AC, Tan DSW. Targeted therapies for lung cancer patients with oncogenic driver molecular alterations. J Clin Oncol. 2022;40(6):611–25. pmid:34985916
- 43. Boland JM, Wampfler JA, Jang JS, Wang X, Erickson-Johnson MR, Oliveira AM, et al. Pulmonary adenocarcinoma with signet ring cell features: a comprehensive study from 3 distinct patient cohorts. Am J Surg Pathol. 2014;38(12):1681–8. pmid:25007143
- 44. Drilon A, Jenkins C, Iyer S, Schoenfeld A, Keddy C, Davare MA. ROS1-dependent cancers - biology, diagnostics and therapeutics. Nat Rev Clin Oncol. 2021;18(1):35–55.
- 45. Kris MG, Johnson BE, Berry LD, Kwiatkowski DJ, Iafrate AJ, Wistuba II, et al. Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. JAMA. 2014;311(19):1998–2006. pmid:24846037
- 46. Li S, Li L, Zhu Y, Huang C, Qin Y, Liu H, et al. Coexistence of EGFR with KRAS, or BRAF, or PIK3CA somatic mutations in lung cancer: a comprehensive mutation profiling from 5125 Chinese cohorts. Br J Cancer. 2014;110(11):2812–20. pmid:24743704
- 47. Won JK, Keam B, Koh J, Cho HJ, Jeon YK, Kim TM, et al. Concomitant ALK translocation and EGFR mutation in lung cancer: a comparison of direct sequencing and sensitive assays and the impact on responsiveness to tyrosine kinase inhibitor. Ann Oncol. 2015;26(2):348–54. pmid:25403583
- 48. Le X. Partners in crime: co-occurring genetic alterations in EGFR-mutant NSCLC. J Thorac Oncol. 2024;19(2):190–2. pmid:38325977
- 49. Shire NJ, Klein AB, Golozar A, Collins JM, Fraeman KH, Nordstrom BL, et al. STK11 (LKB1) mutations in metastatic NSCLC: prognostic value in the real world. PLoS One. 2020; 15(9):e0238358.
- 50. Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature. 2014;511(7511):543–50.