Comparison of Targeted Next Generation Sequencing Assays in Non-small cell lung cancer Patients

Comparison of Targeted Next Generation Sequencing Assays in Non-small cell lung cancer Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparison of Targeted Next Generation Sequencing Assays in Non-small cell lung cancer Patients Ieva Drejeriene, Jurate Gruode, Saulius Cicenas, Charalambos Loizides, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4176050/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer the mutational spectrum of which has been extensively characterized. Treatment of patients with NSCLC based on their molecular profile is now part of the standard clinical care. The aim of this study was firstly to investigate two different NGS-based tumor profile genetic tests and secondly to assess the clinical actionability of the mutations and their association with survival and clinicopathological characteristics. Overall, 52 mutations were identified in 31 patients by either one or both assays. The most frequently mutated genes were TP53 (40.4%), KRAS (13.46%) and EGFR (9.62%). TP53 and KRAS mutations were associated with worst overall survival while KRAS was positively correlated with adenocarcinoma. The two methods showed a high concordance for the commonly covered genomic regions (97.14%). Ten mutations were identified in a genomic region exclusively covered by the NIPD Genetics custom tumor profile assay. Likewise, one MET mutation was identified by the Ion Amliseq assay in a genomic region exclusively covered by Ion Amliseq. In conclusion both assays showed highly similar results in the commonly covered genomic areas, however, the NIPD Genetics assay identified additional clinically actionable mutations that can be applied in clinical practice for personalized treatment decision making for patients with NSCLC. NSCLC mutational profile clinical utility next generation sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Lung cancer is the third leading type of cancer globally with an incidence of 22 cases per 100,000 people annually and has the highest mortality rate 1 . NSCLC accounts for approximately 85% of the lung cancer cases 2 . There is an increasing incidence of lung cancer in women with a more favorable prognosis as compared to NSCLC in men 3 . In addition, female patients with NSCLC have an improved benefit compared to men in regard to their treatment response with EGFR inhibitors versus chemotherapy 4 . Molecular targeted therapies against driver mutations of patients with NSCLC are already improving patients’ survival over traditional chemotherapy. Consequently, molecular testing is now applied as part of routine clinical practise 5 . An essential part of the diagnostic procedure in guiding the appropriate treatment for NSCLC is the molecular characterization of the tumor. A variety of techniques are employed to detect molecular alterations including protein-based methods (immunohistochemistry), fluorescence in situ hybridization (FISH) and chromogenic in situ hybridization (CISH) 6 . Most of these methods predominantly depend on a qualitative assessment and can therefore represent a challenge to standarise 6 . NGS testing has been increasingly applied to clinical practice in recent years and is now recommended by professional guidelines for NSCLC molecular profiling 5 , 7 . NGS is a sensitive and sufficiently quick method which can simultaneously identify a large number of driver mutations in oncogenes that are associated with targeted therapy and acquired drug-resistance and has been increasingly applied to clinical practice in recent years 8 , 9 , 10 . Patients with EGFR sensitizing mutations in the tumor can now receive EGFR tyrosine kinase inhibitor (TKI) treatment as a first line therapy 5 . Following TKI treatment, if EGFR resistant mutations are identified (e.g EGFT T790M), then osimertinib treatment is recommended 11 , 12 . Likewise patients with BRAF V600E mutated tumors can receive dabrafenib, a BRAF inhibitor and trametinib, a MEK inhibitor as first line therapy 5 , 13 . MET exon 14 skipping mutated tumors show sensitivity to capmatinib, a MET inhibitor 5 , 14 . Moreover, several genes are now emerging as potential biomarkers to identify novel targeted therapies for patients with NSCLC and serve as inclusion criteria in clinical trials 15 . For example, patients with ERBB2 (HER2) exon 20 mutations show encouraging clinical response to pan-HER2 blocking drugs 16 . Likewise, activating mutations in the JAK2 gene are shown to confer sensitivity to both JAK2 inhibitors and anti-PD1 immunotherapy in patients with NSCLC 17 . Multi-gene NGS assays have also enabled the simultaneous analysis of multiple genes from a single tumor. It is now clear that a subset to NSCLC patients carry co-existing driver mutations that could explain the heterogeneity in clinical outcomes upon targeted treatment 18 . The biggest challenge for molecular testing is tissue availability of the patient’s tumor. In many cases the amount of formalin fixed paraffin embedded (FFPE) tumor tissue remaining after pathologists’ analysis is limited. The formalin fixation and paraffin -embedding process reduces DNA quality via fragmentation, cross-linking and chemical modifications that introduce DNA damage 19 . These limitations highlight the importance of selecting the appropriate molecular test that can overcome these challenges by introducing quality control checkpoints to ensure high quality molecular data. In addition, the selection of the most appropriate test is of outmost importance to ensure robust diagnostic power by covering the highest number of clinically actionable mutations. In this study the main objective was the comparison of two different NGS-based tests to investigate their sensitivity and clinical utility in identifying clinically actionable mutations in female patients diagnosed with NSCLC. To this end, we analyzed FFPE tissue samples using two different NGS-based assays: i) Ion AmpliSeq Colon and Lung Cancer Research V2 Panel (Ion Torrent PGM platform), an amplicon-based assay that covers hotspot regions in 22 genes associated with lung and colorectal cancer and ii) NIPD Genetics custom- tumor profile assay, that relies on hybrid capture technology and covers hotspot regions and selected targeted regions in 49 genes primarily associated with NSCLC. Sequencing data were compared between the two methods for the commonly covered genomic regions. Moreover, mutations identified in genomic areas exclusively covered by each method are also reported. The diagnostic yield and clinical utility of each assay as well as correlation of molecular findings with clinicopathological parameters is discussed. 2. Results 2.1 Experimental strategy and patient characteristics Sections were cut from the FFPE block of the primary tumor tissue biopsy for all 51 patients and were subjected to DNA extraction. For 39 patients, the same DNA sample was analyzed by both assays. For 12 patients, different DNA samples (extracted from different sections of the same FFPE block) were analyzed by only one assay, either the Ion Ampliseq Colon Lung v2 assay or the NIPD Genetics custom tumor profile assay ( Figure 1A, C ). Out of 51 patients, 39 patients had samples that met quality control criteria and were subjected to targeted sequencing with the two different assays ( Figure 1C ). A total of 12 DNA samples were excluded from analysis by both assays due to low or poor DNA quality. The average age of patients was 60.8 years (±9.2). Out of 39 patients, 38.5% were smokers. Most of the patients were diagnosed with adenocarcinoma (74.3%) and 25.7% of them with squamous cell carcinoma. Five patients (12.8%) were diagnosed with stage IV disease, 35.9% of the patients were diagnosed with stage III, 25.6% with stage II and 25.7% with stage I. Out of 29 adenocarcinoma patients 18 (62%) and out of 10 squamous cell carcinoma 8 (80%) patients had either lymph node or distant metastasis ( Table 1 ). 2.2. Concordance analysis Overall 31 patients (79.5%) had mutations identified in their tumor specimens by either assay, 27 of which had mutations identified by both assays (69.23%) ( Figure 2A ). Concordance analysis was performed on sequencing data generated by both assays as described above for the genomic region commonly covered by both methods using the same DNA samples (originating from the same FFPE sections). This commonly covered region consists of hotspot regions of 18 genes with a total genomic size of 8.6 Kb ( Figure 1A, B ). Thirty-four variants in 25 patients were identified by both methods while one extra variant -the KRAS G13C at 5.9% VAF- was identified only by the NIPD tumor profile assay in patient 1 ( Table 2 ). The IonAmpliseq assay failed to detect this variant above the minimum acceptable threshold of 5%, however, it was detected at VAF=3.78%. Hence, concordance between the two assays was estimated at 97.14% ( Figure 2B ). The frequencies of the concordant mutations in both assays were highly similar (r 2 =0.9156, Figure 2B ). 2.3. Intra-tumor variability The processing of DNA samples originating from different sections at different layers of the same patients’ FFPE tissue biopsy block enabled the investigation of intra-tumor heterogeneity. As shown in Figure 2D , two commonly covered variants, TP53 V227G and BRAF V600E were not identified in all sections tested from the same tumor ( Figure 2D , Table S1 ). Given that the two methods have shown performance similarities, this variability does not necessarily reflect differences in the sensitivity of each method but instead could be a result of the heterogeneity of the tissue biopsy samples with different spatial origin within the primary tumor. However, to conclusively characterize the extend of intra-tumor heterogeneity and investigate its clinical importance a large-scale study is required. 2.4. Assessment of the molecular profile for NSCLC patients Data from all the regions covered from the two assays combined (including overlapping and exclusively covered regions) were used to assess the mutation profile of these patients. A total of 52 mutations were identified in 31 patients. Sixteen patients (51.6%) had just 1 mutation identified in their tumor biopsy ( Figure 3A ). The total number of mutations did not show significant correlation with tumor content in the FFPE specimens ( Supplemental figure 1A ). However, there’s a statistically significant increase allele frequency in FFPE samples with tumor content >70% as compared with FFPE samples with tumor content ≤70% ( Supplemental figure 1B ). The most frequent mutations were identified in TP53 (21 patients, 40.4%), KRAS (7 patients, 13.46%), EGFR (5 patients, 9.62%) and PIK3CA (4 patients, 7.7%) ( Figure 3B ). Mutations in TP53 were predominantly identified in the DNA binding domain (amino acids 98-292) 20 , a region known to harbor the majority of deleterious mutations in this gene ( Figure 4A ). KRAS mutations were predominantly localized on codon 12, a widely studied recurrent region in multiple cancer types while 1 mutation was identified in codon 13 ( Figure 4B ). All KRAS mutations identified were associated with reduced sensitivity to TKI inhibitors 21 . EGFR mutations were identified in the tyrosine kinase domain ( Figure 4C ); four in-frame exon19 deletions and one exon 21 L858R substitution, all known to confer sensitivity to EGFR inhibitors such as gefitinib, afatinib and erlotinib 22 . Eleven mutations were identified in regions exclusively covered by only one assay. A MET N375S mutation was identified in patient 42 by the Ion Amliseq assay, while 10 more mutations of clinical significance in STK11, RET, PTEN, GNAS, TP53, BRCA2, PALB2, CHEK2, and PIK3CA were exclusively covered and identified by the NIPD tumor profile assay in 10 patients ( Figure 3A, Table S2 ). Moreover, oncodriver mutations in BRAF, EGFR, KRAS and exon 10/exon21 PIK3CA were found to be mutually exclusive in this cohort ( Table 2, Figure 3 ). 2.5. Comparison of clinical utility In total, 52 unique mutations were identified, 50 mutations with the NIPD tumor profile assay and 40 mutations with the Ion Ampliseq assay ( Table 2, Table S1, Table S2) . These, mutations were assessed based on i) their clinical utility including their association with sensitivity to an approved therapy, ii) resistance to an approved therapy (contraindicated therapy), iii) association with an approved therapies in a different cancer type and iv) their investigation in clinical trials (either for their prognostic or potential therapeutic significance). The NIPD Genetics custom tumor profile assay identified more mutations associated with approved therapy in NSCLC as compared to the Ion Ampliseq (6 versus 5 mutations respectively). In addition, 7 mutations associated with resistance to approved therapy (contra-indicated for use) were identified by the NIPD Genetics assay as compared to 6 mutations with the Ion Ampliseq assay. Furthermore, the NIPD Genetics assay identified 8 mutations associated with approved therapy for a different cancer type compared with 3 mutations identified with the Ion Amlpiseq assay. Thirteen mutations identified by the NIPD assay were included in NCCN guidelines for NSCLC as compared to 11 mutations identified with the Ion Ampliseq assay. Finally, 49 mutations associated with clinical trials were identified by the NIPD Genetics assay compared to 40 mutations identified by the Ion Amliseq assay ( Figure 5, Table S3 ). 2.6. Association of mutations with patient survival and clinicopathological characteristics The prognostic significance with respect to overall survival (OS) of the mutations identified in these patients was explored. Patients were divided in early (stage I-II) and late (III-IV) stage NSCLC with or without mutations in TP53 or KRAS. Although there was no statistically significant difference between the 4 groups, a trend was observed for improved OS in late-stage patients with wt KRAS or TP53 ( Figure 6 ). Due to the limited number of patients in the cohort it was not possible to investigate the prognostic significance of each gene separately. Next, associations of mutations in the 4 most frequently mutated genes with clinicopathological characteristics such as age, histology, smoking status were evaluated. A statistically significant association between KRAS status and histology was observed (p=0.03099). Mutated KRAS was positively correlated with adenocarcinoma as opposed to squamous cell carcinoma ( Table 3 ). However, due to the small size of the patient cohort, the results should be interpreted with caution. 3. Discussion The purpose of this study was firstly to compare two different NGS-based tests for their clinical utility in patients with NSCLC and secondly to assess the clinical significance of the mutations identified and their associated with clinicopathological parameters. To this end, we employed two different assays; The Ion Ampliseq Colon Lung v2 assay (22 genes) and the NIPD Genetics custom tumor profile assay (49 genes). We first compared the results of both assays in the commonly covered regions with highly similar results and high concordance of VAF. The NIPD Genetics assay identified one additional mutation in the KRAS gene in this region, a KRAS G13C mutation of high diagnostic significance as it is associated with resistance to TKI EGFR inhibitors 23 . The IonAmpliseq assay failed to detect it above threshold (set at ≥ 5%), but was detected in lower VAF = 3.78%). An essential part of NIPD Genetics capture technology is the design of TACS 24 . These are specifically designed to tolerate the presence of mismatches without compromising hybridisation efficiency and enrichment uniformity. Additionally, TACS capture flanking regions that may not be easily captured with amplicon based assays 25 . Most importantly, they ensure capture of all fragments thus providing a better representation of the complexity of the original DNA in the patient’s tumor. These fundamental differences between the two methods can potentially explain the difference observed in regard to the KRA G13C mutation Tumor heterogeneity is a challenge in clinical practice using FFPE tissue sections. It is well known that FFPE sections can only provide a snapshot of the tumor’s molecular profile and cannot capture intra-tumor heterogeneity. Molecular heterogeneity is a well-known event in non-small cell lung cancer that can be attributed to different mechanisms related to structural chromosomal instability, somatic mutations, tumor mutational burden and genomic instability 8 , 26 . In our results, we evaluated the degree of intra-tumor heterogeneity by analyzing different sets of FFPE sections from the patient’s block by either assay. We observed differences in detection rate and allele frequencies of detectable variants that do not necessarily highlight differences between the two methods but are suggestive of intra-tumor heterogeneity. Due to the comprehensive genomic coverage of the NIPD Genetics custom tumor profile assay, a higher number of mutations were identified as compared to the Ion Amliseq method. The additional mutations identified are clinically actionable mutations with either available approved treatments or ongoing trials that investigate their prognostic and/or therapeutic significance. For example, a PIK3CA V344G mutation was identified in a region covered exclusively by the NIPD Genetics’ assay. This mutation resides in the C2 domain of the membrane-binding region of PI3K p110a and has shown sensitivity to p110a/PIK3CA-specific inhibitor alpelisib, a drug recently approved for the treatment of PIK3CA mutated HER2-negative metastatic breast cancer 27 , 28 . Furthermore, mutations identified in BRCA2 and PALB2, genes that play a critical role in the homologous recombination repair (HRR) mechanism, could represent potential therapeutic targets for poly(ADP-ribose) polymerase (PARP) 1, 2, 3 inhibitors such as rucaparib. A phase 2 study is currently investigating rucaparib for the treatment of solid tumors including lung cancer associated with deleterious mutations in HRR genes (NCT04171700) 29 . In addition, a GNAS R844C mutation has been identified by the NIPD Genetics’ assay. This mutation lies within a GTP binding region of the Gnas protein resulting in a loss of the GTPase activity and consequently leading to constitutive downstream pathway 30 . The GNAS R844C is shown to associate with resistance to targeted therapy in colorectal patients treated with vemurafenib, cetuximab and irinotecan combination treatment 31 . The clinical significance of this gene in NSCLC is under investigation 32 . Other mutations identified in genes such as PTEN and STK11 are also under investigation for their significance as potential targets of targeted therapy 29 . Furthermore, associations of NGS findings with OS and clinicopathological characteristics were investigated. KRAS or TP53 mutated NSCLC exhibited worse OS in the late-stage NSCLC. This finding is in agreement with previous studies showing that TP53 and KRAS are correlated with adverse prognosis in NSCLC 33 , 34 . KRAS mutated tumors were also correlated with adenocarcinoma in our study. KRAS mutations predominately occur in lung adenocarcinomas with a frequency of 17% and are more rare in squamous cell carcinomas (4%) according with data retrieved from the COSMIC database 35 . The small sample size of this study does not allow for a conclusive association of molecular findings with clinical characteristics and highlights the need for larger validation studies. In conclusion, both assays exhibited similar technical performance both in pre-analytical and post-analytical parameters in the commonly covered genomic areas. However, the more comprehensive coverage of the NIPD Genetics custom tumor profile assay in clinically significant genes remarkably expands the potential for identifying additional clinically actionable mutations. These additional mutations were mostly associated with approved therapies in other cancer types as well as clinical trials. Considering the rapid advancements in the molecular etiology of NSCLC and corresponding advancement in molecularly-targeted therapies, the expanded coverage of the custom-made NIPD Genetics assay could potentially allow a more personalized clinical management for an increased number of patients. 4. Materials and Methods 4.1. Patients The study (No. 158200-13-688-219) has been approved by Vilnius Regional Biomedical Research Ethics Committee (Vilnius, Lithuania). All participants of the study have signed the informed consent to participate before study specific procedures started. Tumor tissue samples were collected at National Cancer Institute (Vilnius, Lithuania) and Vilnius University Hospital Santaros Klinikos (Vilnius, Lithuania). 4.2. DNA preparation Fresh frozen or FFPE tumor tissue biopsy were collected from each patient. DNA extraction was performed using the Qiagen DNeasy blood and tissue kit and the QIAamp DNA FFPE Tissue Kit (Qiagen) for fresh frozen and FFPE tissue respectively, following the manufacturers’ instructions. Tumor content was evaluated on FFPE specimens as the percentage of tumor cells in the total number of nucleated cells using hematoxylin/eosin staining. Minimum tumor content was 10% and maximum tumor content was 95%. DNA was quantified using a spectrophotometric assay (Cary 60 UV-Vis, Agilent Technologies) for fresh frozen tissue derived DNA and a fluorometric based assay for FFPE tissue-derived DNA (Qubit flex fluorometer, Qubit dsDNA high sensitivity assay, Thermo Scientific). A minimum of 10 ng of DNA and a minimum DNA concentration of 1 ng/µl (as measured by a fluorometric based method for FFPE samples) were used as thresholds for library preparation for both assays. DNA quality was assessed using Agilent D1000 ScreenTape analysis (cat.no. 5067–5582). 4.3. Ion AmpliSeq Colon and Lung Cancer Research Panel library preparation and sequencing Libraries were amplified using Ion AmpliSeq Colon and Lung Cancer Research Panel (Ion Torrent by Life Technologies) which analyzes amplicons in hotspots and target regions of 22 oncogenes (Fig. 1 A) covering single nucleotide variants (SNVs) and insertions and deletions (Indels) involved in colon and lung cancers. 10 ng of DNA were amplified using Ion AmpliSeq Library Kit 2.0 (Thermo Fisher Scientific) following the manufacturers’ instructions. The library concentration was quantified with Ion Library TaqMan Quantitation Kit (Thermo Fisher Scientific). Each library was diluted to reach a concentration of 100pM and amplified using emulsion PCR. Sequencing was performed on the Ion PGM (Thermo Fisher Scientific) using the Ion PGM 200 Sequencing Kit (Thermo Fisher Scientific). Sequencing libraries were loaded onto a 316 chip following the manufacturers’ instructions. 4.4. NIPD Genetics custom tumor profile library preparation and sequencing DNA libraries were prepared from sheared DNA based on previously established protocols 37 . Briefly, blunt ending and 5′ phosphorylation was performed using T4 polymerase and T4 kinase respectively. Following adaptor ligation using T4 Ligase (New England Biolabs, Ipswich, UK), nicks were removed using Bst polymerase (New England Biolabs). Unique barcodes were assigned to all samples in a final PCR reaction using Herculase II Fusion Polymerase (Agilent Technologies, Santa Clara, CA). At each step, products were purified using magnetic beads. DNA enrichment for the genomic regions of interest, was carried out using an in solution- hybridization based method using TACS (TArget Capture Sequences) specifically designed to capture selected loci in the genes of interest. Biotinylated TACS were then immobilized on streptavidin coated magnetic beads for subsequent hybridization with the DNA libraries. Eluted samples were amplified using outer-bound adaptor primers. Enriched DNA libraries were then normalized and subjected to sequencing on an Illumina sequencing platform. The NIPD Genetics tumor profile panel was used for the identification of single nucleotide variants SNVs and indels in hotspot regions and selected targeted genomic loci of 49 genes (Fig. 1 A). 4.5. Bioinformatics and data analysis Sequencing data were de-multiplexed with bcl2fastq (v.2.16.0) and aligned to the human genome build 37 (hg19) to generate alignment (bam) files. Specifically, for each sample, paired-end DNA sequencing reads were processed with cutadapt (v.1.8.1) to remove adapter sequences and poor-quality reads. The remaining sequences were aligned to the human reference genome build 37 (hg19) using the Burrows-Wheeler alignment algorithm (bwa mem). For the NIPD Genetics custom tumor profile assay duplicate read entries were removed to convert aligned reads to a binary (BAM) file containing uniquely aligned read entries only. Per base allele-specific read-depth information was retrieved from this final BAM file. All samples with a minimum depth of coverage of 250 reads proceeded to variant calling with vardict 38 . For concordance analysis, a list of selected targeted genomic coordinates that were commonly covered by both the Ion Ampliseq method and the NIPD Genetics custom tumor profile assay was used. A threshold for VAF (variant allele frequency) for data generated by either method was set at ≥ 5%. Analysis was also performed in the genomic regions exclusively covered by either the Ion Ampliseq or the NIPD Genetics custom tumor profile assay. Assessment of somatic/germline status was not assessed as germline DNA was not available for this patient cohort. 4.6. Assessment of clinical utility Assessment of clinical significance was performed by retrieving information from multiple databases. Specifically, pharmacological information was retrieved from the PharmGKB database which consolidates available data on therapies approved by various regulatory authorities including the Food and drug administration (FDA) and the European Medicines Agency (EMA) 39 . Information on association of genes and clinical trials for the indicated cancer type were retrieved from Clinical.trials.gov, a resource provided by the U.S National Library of Medicine 29 . 4.7. Statistical analysis Survival analysis was carried out in R, using the Kaplan-Meier estimator (survival package in R) 40 . The G-test (R package DescTools) was used to test association for 2x2 contingency tables, specifically between age group, smoking status and histology findings against mutational findings from selected genes 41 . Declarations Author Contributions: Conceptualization, PCP, JG, GK ; methodology ID, AE,KT; formal analysis ID, AA, CL, AE; investigation, AE.; resources, PCP,GK, JG.; data curation, ID, AA, CL, AK, DS.; writing—original draft preparation, ID, JG.; writing—review and editing, AE, MI, CL, AA, DS.; supervision, GK,AE, EK, MI, SC.; project administration, AK.; funding acquisition, PCP. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding Institutional Review Board Statement: The study (No. 158200-13-688-219) has been approved by Vilnius Regional Biomedical Research Ethics Committee (Vilnius, Lithuania). All participants of the study have signed the informed consent to participate before study specific procedures started. Tumor tissue samples were collected at National Cancer Institute (Vilnius, Lithuania) and Vilnius University Hospital Santaros Klinikos (Vilnius, Lithuania). The study was conducted according to the guidelines of the Declaration of Helsinki. Informed consent was obtained from all subjects involved in the study. Data Availability Statement: The data presented in this study are available on request from the corresponding author. Acknowledgments: The authors are indebted to patients and their families for their trust and participation in the present registry. The authors wish to thank Chrysovalanto Marinou, Louisa Constantinou, Charalambos Kkoufou for their laboratory assistance. Conflicts of Interest: CL: Employed by NIPD Genetics has filed a PCT patent application for Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); AA: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); has filed a PCT patent application for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); EK: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); has filed a PCT patent application for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); KT: Employed by NIPD Genetics, has filed a PCT patent application for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); AE: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); MI: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1), has filed a PCT patent application for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); GK: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); has filed a PCT patent application for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); PCP: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); has filed a PCT patent application for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); The rest of the authors declare no conflict of interest. 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CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer. Nat. Genet. 49 , 170–174 (2017). Massarelli, E. et al. KRAS mutation is an important predictor of resistance to therapy with epidermal growth factor receptor tyrosine kinase inhibitors in non-small cell lung cancer. Clin. Cancer Res. (2007). doi:10.1158/1078-0432.CCR-06-3043 Koumbaris, G. et al. Cell-Free DNA analysis of targeted genomic regions in maternal plasma for non-invasive prenatal testing of trisomy 21, trisomy 18, trisomy 13, and fetal sex. Clin. Chem. 62 , 848–855 (2016). Samorodnitsky, E. et al. Evaluation of Hybridization Capture Versus Amplicon-Based Methods for Whole-Exome Sequencing. Hum. Mutat. (2015). doi:10.1002/humu.22825 Marino, F. Z. et al. Molecular heterogeneity in lung cancer: From mechanisms of origin to clinical implications. Int. J. Med. Sci. (2019). doi:10.7150/ijms.34739 Packer, L. M. et al. PI3K inhibitors synergize with FGFR inhibitors to enhance antitumor responses in FGFR2mutant endometrial cancers. Mol. Cancer Ther. (2017). doi:10.1158/1535-7163.MCT-16-0415 Lama Tamang, T. G. et al. Use of alpelisib in the treatment of hormone receptor positive metastatic breast cancer: An institutional experience. J. Clin. Oncol. (2020). doi:10.1200/jco.2020.38.15_suppl.e15216 Clinical trials.gov. U.S. National Institutes of Health (2015). Huang, L. et al. The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations. J. Am. Med. Informatics Assoc. (2017). doi:10.1093/jamia/ocw148 Hong, D. S. et al. Phase IB study of vemurafenib in combination with irinotecan and cetuximab in patients with metastatic colorectal cancer with BRAFV600E mutation. Cancer Discov. (2016). doi:10.1158/2159-8290.CD-16-0050 Ritterhouse, L. L. et al. GNAS mutations in primary mucinous and non-mucinous lung adenocarcinomas. Mod. Pathol. (2017). doi:10.1038/modpathol.2017.88 Svaton, M. et al. The prognostic role of kras mutation in patients with advanced NSCLC treated with second-or third-line chemotherapy. Anticancer Res. (2016). Gu, J. et al. TP53 mutation is associated with a poor clinical outcome for non-small cell lung cancer: Evidence from a meta-analysis. Mol. Clin. Oncol. (2016). doi:10.3892/mco.2016.1057 Forbes, S. A. et al. COSMIC: Somatic cancer genetics at high-resolution. Nucleic Acids Res. 45 , D777–D783 (2017). Rathi, V. et al. Clinical validation of the 50 gene AmpliSeq Cancer Panel V2 for use on a next generation sequencing platform using formalin fixed, paraffin embedded and fine needle aspiration tumour specimens. Pathology (2017). doi:10.1016/j.pathol.2016.08.016 Neofytou, M. C. et al. Targeted capture enrichment assay for noninvasive prenatal testing of large and small size sub-chromosomal deletions and duplications. PLoS One (2017). doi:10.1371/journal.pone.0171319 Lai, Z. et al. VarDict: A novel and versatile variant caller for next-generation sequencing in cancer research. Nucleic Acids Res. (2016). doi:10.1093/nar/gkw227 Whirl-Carrillo, M. et al. Pharmacogenomics knowledge for personalized medicine. Clinical Pharmacology and Therapeutics (2012). doi:10.1038/clpt.2012.96 Kaplan, E. L. & Meier, P. Nonparametric Estimation from Incomplete Observations. in (1992). doi:10.1007/978-1-4612-4380-9_25 Quine, M. P. & Robinson, J. Efficiencies of Chi-Square and Likelihood Ratio Goodness-of-Fit Tests. Ann. Stat. (2007). doi:10.1214/aos/1176349550 Tables Tables 1 to 3 are available in the Supplementary Files section. Supplementary Tables Supplementary Tables S1, S2 and S3 are not available with this version. Additional Declarations No competing interests reported. Supplementary Files Table123.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 04 Jul, 2024 Reviews received at journal 02 Jul, 2024 Reviewers agreed at journal 28 Jun, 2024 Reviews received at journal 24 Apr, 2024 Reviewers agreed at journal 18 Apr, 2024 Reviewers invited by journal 04 Apr, 2024 Editor assigned by journal 03 Apr, 2024 Submission checks completed at journal 03 Apr, 2024 First submitted to journal 27 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4176050","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":288147091,"identity":"12fe4be5-8671-4e1d-bbb1-cfe4b45b8f75","order_by":0,"name":"Ieva Drejeriene","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIie2OMUvDQBTH33EQl6jrEyX5CgldOhQ/y4VAOnUSipNeEC5LuicI+jUccxykS+nsJHTpnIJDHMReg0KXnBkF7wfv8b/h9/4HYLH8QZyfTThApaOHQLkO4+HKCHXUAXFIV0dUdLZBOTvJwwbmbx7NFptq9zKZlkWUynfAu9777kp/ZX0zIvkykOUqmT1ixNWVocXBhCERLEqLBNSpULOng4Imxd/GrVbu0+ctqE/xNfV+VZDWhxZGCgcUERW71IpsTIob12O2ZmGaJyAXIg7LfMMVBHjBexQ/kw+vzZz5YVbT5kNc+7iM1a69nZz3tXQwPeHxUeoGRuG77vhB2gGGxWKx/Bv2axVWHpnvIHMAAAAASUVORK5CYII=","orcid":"","institution":"Vilnius University","correspondingAuthor":true,"prefix":"","firstName":"Ieva","middleName":"","lastName":"Drejeriene","suffix":""},{"id":288147092,"identity":"31588229-baf4-458a-9228-00a9cc03a56a","order_by":1,"name":"Jurate Gruode","email":"","orcid":"","institution":"Klaipeda University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jurate","middleName":"","lastName":"Gruode","suffix":""},{"id":288147094,"identity":"99aac1e0-f9e5-4345-9316-5da82639846f","order_by":2,"name":"Saulius Cicenas","email":"","orcid":"","institution":"National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Saulius","middleName":"","lastName":"Cicenas","suffix":""},{"id":288147096,"identity":"feb8cffe-d1a7-4a78-ad67-1756c8b505fb","order_by":3,"name":"Charalambos Loizides","email":"","orcid":"","institution":"MEDICOVER Genetics","correspondingAuthor":false,"prefix":"","firstName":"Charalambos","middleName":"","lastName":"Loizides","suffix":""},{"id":288147097,"identity":"3940acb1-849e-4019-9bf2-691031c38ff2","order_by":4,"name":"Alexia Eliades","email":"","orcid":"","institution":"MEDICOVER Genetics","correspondingAuthor":false,"prefix":"","firstName":"Alexia","middleName":"","lastName":"Eliades","suffix":""},{"id":288147098,"identity":"64aa885e-5a98-43fb-8372-404aa4e638ae","order_by":5,"name":"Achilleas Achilleos","email":"","orcid":"","institution":"MEDICOVER Genetics","correspondingAuthor":false,"prefix":"","firstName":"Achilleas","middleName":"","lastName":"Achilleos","suffix":""},{"id":288147099,"identity":"d359e5ac-f226-4e9d-9d10-a3cf56f3ec33","order_by":6,"name":"Elena Kypri","email":"","orcid":"","institution":"MEDICOVER Genetics","correspondingAuthor":false,"prefix":"","firstName":"Elena","middleName":"","lastName":"Kypri","suffix":""},{"id":288147100,"identity":"f6e35466-6afb-4894-9eed-fd15b2fc9b9d","order_by":7,"name":"Kyriakos Tsangaras","email":"","orcid":"","institution":"MEDICOVER Genetics","correspondingAuthor":false,"prefix":"","firstName":"Kyriakos","middleName":"","lastName":"Tsangaras","suffix":""},{"id":288147101,"identity":"3861c0cb-75cc-4fde-b733-3c4ec1615154","order_by":8,"name":"Marios Ioannides","email":"","orcid":"","institution":"MEDICOVER Genetics","correspondingAuthor":false,"prefix":"","firstName":"Marios","middleName":"","lastName":"Ioannides","suffix":""},{"id":288147102,"identity":"239500a6-d4d6-414f-b75d-bfc1bed1f74e","order_by":9,"name":"George Koumbaris","email":"","orcid":"","institution":"MEDICOVER Genetics","correspondingAuthor":false,"prefix":"","firstName":"George","middleName":"","lastName":"Koumbaris","suffix":""},{"id":288147103,"identity":"256147bf-60f1-47c7-bc1e-83123d513b51","order_by":10,"name":"Diana Stanciute","email":"","orcid":"","institution":"National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Diana","middleName":"","lastName":"Stanciute","suffix":""},{"id":288147104,"identity":"7913915a-be2b-4a8c-9949-2bf606158ea2","order_by":11,"name":"Arnoldas Krasauskas","email":"","orcid":"","institution":"Vilnius University","correspondingAuthor":false,"prefix":"","firstName":"Arnoldas","middleName":"","lastName":"Krasauskas","suffix":""}],"badges":[],"createdAt":"2024-03-27 12:29:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4176050/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4176050/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54322420,"identity":"705f5d7a-6f5e-4903-86e4-7f443c2ddce8","added_by":"auto","created_at":"2024-04-08 19:49:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":66322,"visible":true,"origin":"","legend":"\u003cp\u003eDescription of the assays and experimental strategy used. \u003cstrong\u003eA.\u003c/strong\u003e List of genes covered in the two assays used for molecular profiling of NSCLC tumor specimens. The IonAmliseq assay covers hotspot regions of 22 genes while the NIPD Genetics custom tumor profile assay covers hotspots and other exonic regions of 49 genes. With red are the genes commonly covered by both assays. \u003cstrong\u003eB.\u003c/strong\u003e Venn diagram showing the size of the genomic area covered by both assays as well as their overlapping genomic coverage. \u003cstrong\u003eC. \u003c/strong\u003eExperimental strategy followed: FFPE specimens from 51 patients diagnosed with NSCLC were subjected to sectioning. For 39 patients, adequate amount of DNA was extracted from the same set of sections and sent to two labs for subsequent analysis with the Ion Ampliseq and the NIPD assays. For 12 patients DNA derived from different sections of the same FFPE block was sent to the two labs for downstream processing. A total of 39 patients met QC parameters and proceeded to NGS. Available sequencing data were used for concordance analysis and estimation of the molecular profile of each tumor sample.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4176050/v1/9aa6d2a0dc3b7c3417596769.png"},{"id":54322421,"identity":"7a9ad850-f9a3-496d-aff9-29f2132feb27","added_by":"auto","created_at":"2024-04-08 19:49:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":45874,"visible":true,"origin":"","legend":"\u003cp\u003eConcordance analysis in the commonly covered regions by both assays.\u003cstrong\u003e A. \u003c/strong\u003eFrequency of NSCLC tumors with mutations identified by either one or both methods (concordant mutations).\u003cstrong\u003e B.\u003c/strong\u003e Venn diagram indicating the number of variants identified by either assay. 34 variants were commonly identified by both assays, while one extra variant was identified by the NIPD Genetics custom tumor profile assay (the KRAS G13C variant was detect below threshold level at VAF\u0026lt;5% with the IonAmliseq and thus was excluded). \u003cstrong\u003eC.\u003c/strong\u003e Distribution of variant allele frequencies (VAF) for the concordant mutations identified by each assay. \u003cstrong\u003eD. \u003c/strong\u003eVariability of mutation detection and VAF for NGS data originating from different sections for the same FFPE biopsy.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4176050/v1/3cc8fdca5eb7569548904d53.png"},{"id":54322425,"identity":"2cfbdc28-9a6b-4227-a845-2cec162838fe","added_by":"auto","created_at":"2024-04-08 19:49:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":161922,"visible":true,"origin":"","legend":"\u003cp\u003eMutational profile of NSCLC tumors.\u003cstrong\u003e A.\u003c/strong\u003e Diagram depicting all the mutations identified by either both or at least one of the two assays. \u003cstrong\u003eB. \u003c/strong\u003eFrequency of mutations per gene identified in all patients.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4176050/v1/35c0aba8b75a36677087edfb.png"},{"id":54322426,"identity":"d584d204-bafc-43f0-b220-32c6667260d2","added_by":"auto","created_at":"2024-04-08 19:49:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":47685,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of mutations in the most frequently mutated genes. Lollipop plots showing the distribution of mutations across the coding region of \u003cstrong\u003eA.\u003c/strong\u003eTP53 \u003cstrong\u003eB.\u003c/strong\u003e KRAS \u003cstrong\u003eC.\u003c/strong\u003e EGFR.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4176050/v1/0c9c0dfbcf99b8fb252e58a2.png"},{"id":54322424,"identity":"ee0dae37-b6b0-4f8b-ac49-1739d3bb19a0","added_by":"auto","created_at":"2024-04-08 19:49:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":35528,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of clinical utility of the two assays. The number of genes with mutations associated with sensitivity to approved therapy, resistance, or low sensitivity to therapy (contra-indicated), sensitivity to drugs approved for other cancer types and inclusion in clinical trials is indicated.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4176050/v1/e7dce82edab47a0295171808.png"},{"id":54322427,"identity":"8a774996-b33c-41c9-a2bd-83663542d921","added_by":"auto","created_at":"2024-04-08 19:49:47","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":49068,"visible":true,"origin":"","legend":"\u003cp\u003eOverall survival (OS) in patients with and without mutations in KRAS or TP53 in early (I-II) and late (III-IV) stage NSCLC. Red= Stage I-II/mutated, Green=StageI-II/wild type, blue=stageIII-IV/mutated, purple=stage III-IV/wild type.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-4176050/v1/bbef98b85917e06d26b83d83.png"},{"id":54323116,"identity":"15d6b1cf-a34c-4b19-9e14-80dcf496c61e","added_by":"auto","created_at":"2024-04-08 19:57:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":706817,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4176050/v1/b1ec2365-7c73-47ad-8327-adf7441d0e6d.pdf"},{"id":54322422,"identity":"69e9dc9d-365f-43a8-8f4b-fd68c48b27b8","added_by":"auto","created_at":"2024-04-08 19:49:47","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":91529,"visible":true,"origin":"","legend":"","description":"","filename":"Table123.docx","url":"https://assets-eu.researchsquare.com/files/rs-4176050/v1/2b50f46561fde81120d363b8.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison of Targeted Next Generation Sequencing Assays in Non-small cell lung cancer Patients","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eLung cancer is the third leading type of cancer globally with an incidence of 22 cases per 100,000 people annually and has the highest mortality rate\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. NSCLC accounts for approximately 85% of the lung cancer cases\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. There is an increasing incidence of lung cancer in women with a more favorable prognosis as compared to NSCLC in men\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In addition, female patients with NSCLC have an improved benefit compared to men in regard to their treatment response with EGFR inhibitors versus chemotherapy\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Molecular targeted therapies against driver mutations of patients with NSCLC are already improving patients\u0026rsquo; survival over traditional chemotherapy. Consequently, molecular testing is now applied as part of routine clinical practise\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAn essential part of the diagnostic procedure in guiding the appropriate treatment for NSCLC is the molecular characterization of the tumor. A variety of techniques are employed to detect molecular alterations including protein-based methods (immunohistochemistry), fluorescence \u003cem\u003ein situ\u003c/em\u003e hybridization (FISH) and chromogenic \u003cem\u003ein situ\u003c/em\u003e hybridization (CISH)\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Most of these methods predominantly depend on a qualitative assessment and can therefore represent a challenge to standarise\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. NGS testing has been increasingly applied to clinical practice in recent years and is now recommended by professional guidelines for NSCLC molecular profiling\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. NGS is a sensitive and sufficiently quick method which can simultaneously identify a large number of driver mutations in oncogenes that are associated with targeted therapy and acquired drug-resistance and has been increasingly applied to clinical practice in recent years\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Patients with EGFR sensitizing mutations in the tumor can now receive EGFR tyrosine kinase inhibitor (TKI) treatment as a first line therapy\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Following TKI treatment, if EGFR resistant mutations are identified (e.g EGFT T790M), then osimertinib treatment is recommended\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Likewise patients with BRAF V600E mutated tumors can receive dabrafenib, a BRAF inhibitor and trametinib, a MEK inhibitor as first line therapy\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. MET exon 14 skipping mutated tumors show sensitivity to capmatinib, a MET inhibitor\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Moreover, several genes are now emerging as potential biomarkers to identify novel targeted therapies for patients with NSCLC and serve as inclusion criteria in clinical trials\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. For example, patients with ERBB2 (HER2) exon 20 mutations show encouraging clinical response to pan-HER2 blocking drugs\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Likewise, activating mutations in the JAK2 gene are shown to confer sensitivity to both JAK2 inhibitors and anti-PD1 immunotherapy in patients with NSCLC\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eMulti-gene NGS assays have also enabled the simultaneous analysis of multiple genes from a single tumor. It is now clear that a subset to NSCLC patients carry co-existing driver mutations that could explain the heterogeneity in clinical outcomes upon targeted treatment\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe biggest challenge for molecular testing is tissue availability of the patient\u0026rsquo;s tumor. In many cases the amount of formalin fixed paraffin embedded (FFPE) tumor tissue remaining after pathologists\u0026rsquo; analysis is limited. The formalin fixation and paraffin -embedding process reduces DNA quality via fragmentation, cross-linking and chemical modifications that introduce DNA damage\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. These limitations highlight the importance of selecting the appropriate molecular test that can overcome these challenges by introducing quality control checkpoints to ensure high quality molecular data. In addition, the selection of the most appropriate test is of outmost importance to ensure robust diagnostic power by covering the highest number of clinically actionable mutations.\u003c/p\u003e\u003cp\u003eIn this study the main objective was the comparison of two different NGS-based tests to investigate their sensitivity and clinical utility in identifying clinically actionable mutations in female patients diagnosed with NSCLC. To this end, we analyzed FFPE tissue samples using two different NGS-based assays: i) Ion AmpliSeq Colon and Lung Cancer Research V2 Panel (Ion Torrent PGM platform), an amplicon-based assay that covers hotspot regions in 22 genes associated with lung and colorectal cancer and ii) NIPD Genetics custom- tumor profile assay, that relies on hybrid capture technology and covers hotspot regions and selected targeted regions in 49 genes primarily associated with NSCLC. Sequencing data were compared between the two methods for the commonly covered genomic regions. Moreover, mutations identified in genomic areas exclusively covered by each method are also reported. The diagnostic yield and clinical utility of each assay as well as correlation of molecular findings with clinicopathological parameters is discussed.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"2. Results","content":"\u003cp\u003e2.1 Experimental strategy and patient characteristics\u003c/p\u003e\n\u003cp\u003eSections were cut from the FFPE block of the primary tumor tissue biopsy for all 51 patients and were subjected to DNA extraction. For 39 patients, the same DNA sample was analyzed by both assays. For 12 patients, different DNA samples (extracted from different sections of the same FFPE block) were analyzed by only one assay, either the Ion Ampliseq Colon Lung v2 assay or the NIPD Genetics custom tumor profile assay (\u003cstrong\u003eFigure 1A, C\u003c/strong\u003e). Out of 51 patients, 39 patients had samples that met quality control criteria and were subjected to targeted sequencing with the two different assays (\u003cstrong\u003eFigure 1C\u003c/strong\u003e). A total of 12 DNA samples were excluded from analysis by both assays due to low or poor DNA quality. The average age of patients was 60.8 years (\u0026plusmn;9.2). Out of 39 patients, 38.5% were smokers. Most of the patients were diagnosed with adenocarcinoma (74.3%) and 25.7% of them with squamous cell carcinoma. \u0026nbsp;Five patients (12.8%) were diagnosed with stage IV disease, 35.9% of the patients were diagnosed with stage III, 25.6% with stage II and 25.7% with stage I. Out of 29 adenocarcinoma patients 18 (62%) and out of 10 squamous cell carcinoma 8 (80%) patients had either lymph node or distant metastasis (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e2.2. Concordance analysis\u003c/p\u003e\n\u003cp\u003eOverall 31 patients (79.5%) had mutations identified in their tumor specimens by either assay, 27 of which had mutations identified by both assays (69.23%) (\u003cstrong\u003eFigure 2A\u003c/strong\u003e). Concordance analysis was performed on sequencing data generated by both assays as described above for the genomic region commonly covered by both methods using the same DNA samples (originating from the same FFPE sections). This commonly covered region consists of hotspot regions of 18 genes with a total genomic size of 8.6 Kb (\u003cstrong\u003eFigure 1A, B\u003c/strong\u003e). Thirty-four variants in 25 patients were identified by both methods while one extra variant -the KRAS G13C at 5.9% VAF- was identified only by the NIPD tumor profile assay in patient 1 (\u003cstrong\u003eTable 2\u003c/strong\u003e). The IonAmpliseq assay failed to detect this variant above the minimum acceptable threshold of 5%, however, it was detected at VAF=3.78%. Hence, concordance between the two assays was estimated at 97.14% (\u003cstrong\u003eFigure 2B\u003c/strong\u003e). The frequencies of the concordant mutations in both assays were highly similar (r\u003csup\u003e2\u003c/sup\u003e=0.9156, \u003cstrong\u003eFigure 2B\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e2.3. Intra-tumor variability\u003c/p\u003e\n\u003cp\u003eThe processing of DNA samples originating from different sections at different layers of the same patients\u0026rsquo; FFPE tissue biopsy block enabled the investigation of intra-tumor heterogeneity. As shown in \u003cstrong\u003eFigure 2D\u003c/strong\u003e, two commonly covered variants, TP53 V227G and BRAF V600E were not identified in all sections tested from the same tumor (\u003cstrong\u003eFigure 2D\u003c/strong\u003e, \u003cstrong\u003eTable S1\u003c/strong\u003e). Given that the two methods have shown performance similarities, this variability does not necessarily reflect differences in the sensitivity of each method but instead could be a result of the heterogeneity of the tissue biopsy samples with different spatial origin within the primary tumor. However, to conclusively characterize the extend of intra-tumor heterogeneity and investigate its clinical importance a large-scale study is required.\u003c/p\u003e\n\u003cp\u003e2.4. Assessment of the molecular profile for NSCLC patients\u003c/p\u003e\n\u003cp\u003eData from all the regions covered from the two assays combined (including overlapping and exclusively covered regions) were used to assess the mutation profile of these patients. A total of 52 mutations were identified in 31 patients. Sixteen patients (51.6%) had just 1 mutation identified in their tumor biopsy (\u003cstrong\u003eFigure 3A\u003c/strong\u003e). The total number of mutations did not show significant correlation with tumor content in the FFPE specimens (\u003cstrong\u003eSupplemental figure 1A\u003c/strong\u003e). However, there\u0026rsquo;s a statistically significant increase allele frequency in FFPE samples with tumor content \u0026gt;70% as compared with FFPE samples with tumor content \u0026le;70% (\u003cstrong\u003eSupplemental figure 1B\u003c/strong\u003e). The most frequent mutations were identified in TP53 (21 patients, 40.4%), KRAS (7 patients, 13.46%), EGFR (5 patients, 9.62%) and PIK3CA (4 patients, 7.7%) (\u003cstrong\u003eFigure 3B\u003c/strong\u003e). \u0026nbsp; Mutations in TP53 were predominantly identified in the DNA binding domain (amino acids 98-292)\u003csup\u003e20\u003c/sup\u003e, a region known to harbor the majority of deleterious mutations in this gene (\u003cstrong\u003eFigure 4A\u003c/strong\u003e). KRAS mutations were predominantly localized on codon 12, a widely studied recurrent region in multiple cancer types while 1 mutation was identified in codon 13 (\u003cstrong\u003eFigure 4B\u003c/strong\u003e). All KRAS mutations identified were associated with reduced sensitivity to TKI inhibitors\u003csup\u003e21\u003c/sup\u003e. \u0026nbsp;EGFR mutations were identified in the tyrosine kinase domain (\u003cstrong\u003eFigure 4C\u003c/strong\u003e); four in-frame exon19 deletions and one exon 21 L858R substitution, all known to confer sensitivity to EGFR inhibitors such as gefitinib, afatinib and erlotinib\u003csup\u003e22\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eEleven mutations were identified in regions exclusively covered by only one assay. A MET N375S mutation was identified in patient 42 by the Ion Amliseq assay, while 10 more mutations of clinical significance in STK11, RET, PTEN, GNAS, TP53, BRCA2, PALB2, CHEK2, and PIK3CA were exclusively covered and identified by the NIPD tumor profile assay in 10 patients (\u003cstrong\u003eFigure 3A, Table S2\u003c/strong\u003e). Moreover, oncodriver mutations in BRAF, EGFR, KRAS and exon 10/exon21 PIK3CA were found to be mutually exclusive in this cohort (\u003cstrong\u003eTable 2, Figure 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e2.5. Comparison of clinical utility\u003c/p\u003e\n\u003cp\u003eIn total, 52 unique mutations were identified, 50 mutations with the NIPD tumor profile assay and 40 mutations with the Ion Ampliseq assay (\u003cstrong\u003eTable 2, Table S1, Table S2)\u003c/strong\u003e. These, mutations were assessed based on i) their clinical utility including their association with sensitivity to an approved therapy, ii) resistance to an approved therapy (contraindicated therapy), iii) association with an approved therapies in a different cancer type and iv) their investigation in clinical trials (either for their prognostic or potential therapeutic significance). The NIPD Genetics custom tumor profile assay identified more mutations associated with approved therapy in NSCLC as compared to the Ion Ampliseq (6 versus 5 mutations respectively). In addition, 7 mutations associated with resistance to approved therapy (contra-indicated for use) were identified by the NIPD Genetics assay as compared to 6 mutations with the Ion Ampliseq assay. Furthermore, the NIPD Genetics assay identified 8 mutations associated with approved therapy for a different cancer type compared with 3 mutations identified with the Ion Amlpiseq assay. Thirteen mutations identified by the NIPD assay were included in NCCN guidelines for NSCLC as compared to 11 mutations identified with the Ion Ampliseq assay. Finally, 49 mutations associated with clinical trials were identified by the NIPD Genetics assay compared to 40 mutations identified by the Ion Amliseq assay (\u003cstrong\u003eFigure 5, Table S3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e2.6. Association of mutations with patient survival and clinicopathological characteristics\u003c/p\u003e\n\u003cp\u003eThe prognostic significance with respect to overall survival (OS) of the mutations identified in these patients was explored. Patients were divided in early (stage I-II) and late (III-IV) stage NSCLC with or without mutations in TP53 or KRAS. Although there was no statistically significant difference between the 4 groups, a trend was observed for improved OS in late-stage patients with wt KRAS or TP53 (\u003cstrong\u003eFigure 6\u003c/strong\u003e). Due to the limited number of patients in the cohort it was not possible to investigate the prognostic significance of each gene separately. Next, associations of mutations in the 4 most frequently mutated genes with clinicopathological characteristics such as age, histology, smoking status were evaluated. A statistically significant association between KRAS status and histology was observed (p=0.03099). Mutated KRAS was positively correlated with adenocarcinoma as opposed to squamous cell carcinoma (\u003cstrong\u003eTable 3\u003c/strong\u003e). \u0026nbsp;However, due to the small size of the patient cohort, the results should be interpreted with caution.\u003c/p\u003e"},{"header":"3. Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe purpose of this study was firstly to compare two different NGS-based tests for their clinical utility in patients with NSCLC and secondly to assess the clinical significance of the mutations identified and their associated with clinicopathological parameters. To this end, we employed two different assays; The Ion Ampliseq Colon Lung v2 assay (22 genes) and the NIPD Genetics custom tumor profile assay (49 genes). We first compared the results of both assays in the commonly covered regions with highly similar results and high concordance of VAF. The NIPD Genetics assay identified one additional mutation in the KRAS gene in this region, a KRAS G13C mutation of high diagnostic significance as it is associated with resistance to TKI EGFR inhibitors\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The IonAmpliseq assay failed to detect it above threshold (set at \u0026ge;\u0026thinsp;5%), but was detected in lower VAF\u0026thinsp;=\u0026thinsp;3.78%). An essential part of NIPD Genetics capture technology is the design of TACS \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. These are specifically designed to tolerate the presence of mismatches without compromising hybridisation efficiency and enrichment uniformity. Additionally, TACS capture flanking regions that may not be easily captured with amplicon based assays\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Most importantly, they ensure capture of all fragments thus providing a better representation of the complexity of the original DNA in the patient\u0026rsquo;s tumor. These fundamental differences between the two methods can potentially explain the difference observed in regard to the KRA G13C mutation\u003c/p\u003e \u003cp\u003eTumor heterogeneity is a challenge in clinical practice using FFPE tissue sections. It is well known that FFPE sections can only provide a snapshot of the tumor\u0026rsquo;s molecular profile and cannot capture intra-tumor heterogeneity. Molecular heterogeneity is a well-known event in non-small cell lung cancer that can be attributed to different mechanisms related to structural chromosomal instability, somatic mutations, tumor mutational burden and genomic instability\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. In our results, we evaluated the degree of intra-tumor heterogeneity by analyzing different sets of FFPE sections from the patient\u0026rsquo;s block by either assay. We observed differences in detection rate and allele frequencies of detectable variants that do not necessarily highlight differences between the two methods but are suggestive of intra-tumor heterogeneity.\u003c/p\u003e \u003cp\u003eDue to the comprehensive genomic coverage of the NIPD Genetics custom tumor profile assay, a higher number of mutations were identified as compared to the Ion Amliseq method. The additional mutations identified are clinically actionable mutations with either available approved treatments or ongoing trials that investigate their prognostic and/or therapeutic significance. For example, a PIK3CA V344G mutation was identified in a region covered exclusively by the NIPD Genetics\u0026rsquo; assay. This mutation resides in the C2 domain of the membrane-binding region of PI3K p110a and has shown sensitivity to p110a/PIK3CA-specific inhibitor alpelisib, a drug recently approved for the treatment of PIK3CA mutated HER2-negative metastatic breast cancer \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Furthermore, mutations identified in BRCA2 and PALB2, genes that play a critical role in the homologous recombination repair (HRR) mechanism, could represent potential therapeutic targets for poly(ADP-ribose) polymerase (PARP) 1, 2, 3 inhibitors such as rucaparib. A phase 2 study is currently investigating rucaparib for the treatment of solid tumors including lung cancer associated with deleterious mutations in HRR genes (NCT04171700)\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. In addition, a GNAS R844C mutation has been identified by the NIPD Genetics\u0026rsquo; assay. This mutation lies within a GTP binding region of the Gnas protein resulting in a loss of the GTPase activity and consequently leading to constitutive downstream pathway\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. The GNAS R844C is shown to associate with resistance to targeted therapy in colorectal patients treated with vemurafenib, cetuximab and irinotecan combination treatment\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The clinical significance of this gene in NSCLC is under investigation\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Other mutations identified in genes such as PTEN and STK11 are also under investigation for their significance as potential targets of targeted therapy\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFurthermore, associations of NGS findings with OS and clinicopathological characteristics were investigated. KRAS or TP53 mutated NSCLC exhibited worse OS in the late-stage NSCLC. This finding is in agreement with previous studies showing that TP53 and KRAS are correlated with adverse prognosis in NSCLC\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. KRAS mutated tumors were also correlated with adenocarcinoma in our study. KRAS mutations predominately occur in lung adenocarcinomas with a frequency of 17% and are more rare in squamous cell carcinomas (4%) according with data retrieved from the COSMIC database\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. The small sample size of this study does not allow for a conclusive association of molecular findings with clinical characteristics and highlights the need for larger validation studies.\u003c/p\u003e \u003cp\u003eIn conclusion, both assays exhibited similar technical performance both in pre-analytical and post-analytical parameters in the commonly covered genomic areas. However, the more comprehensive coverage of the NIPD Genetics custom tumor profile assay in clinically significant genes remarkably expands the potential for identifying additional clinically actionable mutations. These additional mutations were mostly associated with approved therapies in other cancer types as well as clinical trials. Considering the rapid advancements in the molecular etiology of NSCLC and corresponding advancement in molecularly-targeted therapies, the expanded coverage of the custom-made NIPD Genetics assay could potentially allow a more personalized clinical management for an increased number of patients.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"4. Materials and Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Patients\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe study (No. 158200-13-688-219) has been approved by Vilnius Regional Biomedical Research Ethics Committee (Vilnius, Lithuania). All participants of the study have signed the informed consent to participate before study specific procedures started. Tumor tissue samples were collected at National Cancer Institute (Vilnius, Lithuania) and Vilnius University Hospital Santaros Klinikos (Vilnius, Lithuania).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.2. DNA preparation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFresh frozen or FFPE tumor tissue biopsy were collected from each patient. DNA extraction was performed using the Qiagen DNeasy blood and tissue kit and the QIAamp DNA FFPE Tissue Kit (Qiagen) for fresh frozen and FFPE tissue respectively, following the manufacturers\u0026rsquo; instructions. Tumor content was evaluated on FFPE specimens as the percentage of tumor cells in the total number of nucleated cells using hematoxylin/eosin staining. Minimum tumor content was 10% and maximum tumor content was 95%. DNA was quantified using a spectrophotometric assay (Cary 60 UV-Vis, Agilent Technologies) for fresh frozen tissue derived DNA and a fluorometric based assay for FFPE tissue-derived DNA (Qubit flex fluorometer, Qubit dsDNA high sensitivity assay, Thermo Scientific). A minimum of 10 ng of DNA and a minimum DNA concentration of 1 ng/\u0026micro;l (as measured by a fluorometric based method for FFPE samples) were used as thresholds for library preparation for both assays. DNA quality was assessed using Agilent D1000 ScreenTape analysis (cat.no. 5067\u0026ndash;5582).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Ion AmpliSeq Colon and Lung Cancer Research Panel library preparation and sequencing\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eLibraries were amplified using Ion AmpliSeq Colon and Lung Cancer Research Panel (Ion Torrent by Life Technologies) which analyzes amplicons in hotspots and target regions of 22 oncogenes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) covering single nucleotide variants (SNVs) and insertions and deletions (Indels) involved in colon and lung cancers. 10 ng of DNA were amplified using Ion AmpliSeq Library Kit 2.0 (Thermo Fisher Scientific) following the manufacturers\u0026rsquo; instructions. The library concentration was quantified with Ion Library TaqMan Quantitation Kit (Thermo Fisher Scientific). Each library was diluted to reach a concentration of 100pM and amplified using emulsion PCR. Sequencing was performed on the Ion PGM (Thermo Fisher Scientific) using the Ion PGM 200 Sequencing Kit (Thermo Fisher Scientific). Sequencing libraries were loaded onto a 316 chip following the manufacturers\u0026rsquo; instructions.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.4. NIPD Genetics custom tumor profile library preparation and sequencing\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eDNA libraries were prepared from sheared DNA based on previously established protocols\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Briefly, blunt ending and 5\u0026prime; phosphorylation was performed using T4 polymerase and T4 kinase respectively. Following adaptor ligation using T4 Ligase (New England Biolabs, Ipswich, UK), nicks were removed using Bst polymerase (New England Biolabs). Unique barcodes were assigned to all samples in a final PCR reaction using Herculase II Fusion Polymerase (Agilent Technologies, Santa Clara, CA). At each step, products were purified using magnetic beads. DNA enrichment for the genomic regions of interest, was carried out using an in solution- hybridization based method using TACS (TArget Capture Sequences) specifically designed to capture selected loci in the genes of interest. Biotinylated TACS were then immobilized on streptavidin coated magnetic beads for subsequent hybridization with the DNA libraries. Eluted samples were amplified using outer-bound adaptor primers. Enriched DNA libraries were then normalized and subjected to sequencing on an Illumina sequencing platform. The NIPD Genetics tumor profile panel was used for the identification of single nucleotide variants SNVs and indels in hotspot regions and selected targeted genomic loci of 49 genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Bioinformatics and data analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSequencing data were de-multiplexed with bcl2fastq (v.2.16.0) and aligned to the human genome build 37 (hg19) to generate alignment (bam) files. Specifically, for each sample, paired-end DNA sequencing reads were processed with cutadapt (v.1.8.1) to remove adapter sequences and poor-quality reads. The remaining sequences were aligned to the human reference genome build 37 (hg19) using the Burrows-Wheeler alignment algorithm (bwa mem). For the NIPD Genetics custom tumor profile assay duplicate read entries were removed to convert aligned reads to a binary (BAM) file containing uniquely aligned read entries only. Per base allele-specific read-depth information was retrieved from this final BAM file. All samples with a minimum depth of coverage of 250 reads proceeded to variant calling with vardict\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. For concordance analysis, a list of selected targeted genomic coordinates that were commonly covered by both the Ion Ampliseq method and the NIPD Genetics custom tumor profile assay was used. A threshold for VAF (variant allele frequency) for data generated by either method was set at \u0026ge;\u0026thinsp;5%. Analysis was also performed in the genomic regions exclusively covered by either the Ion Ampliseq or the NIPD Genetics custom tumor profile assay. Assessment of somatic/germline status was not assessed as germline DNA was not available for this patient cohort.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.6. Assessment of clinical utility\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAssessment of clinical significance was performed by retrieving information from multiple databases. Specifically, pharmacological information was retrieved from the PharmGKB database which consolidates available data on therapies approved by various regulatory authorities including the Food and drug administration (FDA) and the European Medicines Agency (EMA)\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Information on association of genes and clinical trials for the indicated cancer type were retrieved from Clinical.trials.gov, a resource provided by the U.S National Library of Medicine\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.7. Statistical analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSurvival analysis was carried out in R, using the Kaplan-Meier estimator (survival package in R)\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. The G-test (R package DescTools) was used to test association for 2x2 contingency tables, specifically between age group, smoking status and histology findings against mutational findings from selected genes\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eConceptualization, PCP, JG, GK ; methodology ID, AE,KT; formal analysis ID, AA, CL, AE; investigation, AE.; resources, PCP,GK, JG.; data curation, ID, AA, CL, AK, DS.; writing\u0026mdash;original draft preparation, ID, JG.; writing\u0026mdash;review and editing, AE, MI, CL, AA, DS.; supervision, GK,AE, EK, MI, SC.; project administration, AK.; funding acquisition, PCP. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research received no external funding\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u0026nbsp;\u003c/strong\u003eThe study (No. 158200-13-688-219) has been approved by Vilnius Regional Biomedical Research Ethics Committee (Vilnius, Lithuania). All participants of the study have signed the informed consent to participate before study specific procedures started. Tumor tissue samples were collected at National Cancer Institute (Vilnius, Lithuania) and Vilnius University Hospital Santaros Klinikos (Vilnius, Lithuania). The study was conducted according to the guidelines of the Declaration of Helsinki. Informed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eThe data presented in this study are available on request from the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The authors are indebted to patients and their families for their trust and participation in the present registry. The authors wish to thank Chrysovalanto Marinou, Louisa Constantinou, Charalambos Kkoufou for their laboratory assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eCL: Employed by NIPD Genetics has filed a PCT patent application for Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); \u0026nbsp;AA: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); has filed a PCT patent application for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); \u0026nbsp;EK: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); has filed a PCT patent application for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); KT: Employed by NIPD Genetics, has \u0026nbsp;filed a PCT patent application \u0026nbsp;for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); AE: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); MI: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1), has filed a PCT patent application for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); GK: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); has filed a PCT patent application for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); PCP: Employed by NIPD Genetics; has filed a PCT patent application for the Target-enriched multiplexed parallel analysis for assessment of tumor biomarkers (WO2019/008172A1); has filed a PCT patent application for the Enrichment of Targeted Genomic Regions for Multiplexed Parallel Analysis (WO2019/008148A9); The rest of the authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli dir=\"LTR\"\u003eF. 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C. \u003cem\u003eet al.\u003c/em\u003e Targeted capture enrichment assay for noninvasive prenatal testing of large and small size sub-chromosomal deletions and duplications. \u003cem\u003ePLoS One\u003c/em\u003e (2017). doi:10.1371/journal.pone.0171319\u003c/li\u003e\n \u003cli dir=\"LTR\"\u003e Lai, Z. \u003cem\u003eet al.\u003c/em\u003e VarDict: A novel and versatile variant caller for next-generation sequencing in cancer research. \u003cem\u003eNucleic Acids Res.\u003c/em\u003e (2016). doi:10.1093/nar/gkw227\u003c/li\u003e\n \u003cli dir=\"LTR\"\u003e Whirl-Carrillo, M. \u003cem\u003eet al.\u003c/em\u003e Pharmacogenomics knowledge for personalized medicine. \u003cem\u003eClinical Pharmacology and Therapeutics\u003c/em\u003e (2012). doi:10.1038/clpt.2012.96\u003c/li\u003e\n \u003cli dir=\"LTR\"\u003e Kaplan, E. L. \u0026amp; Meier, P. Nonparametric Estimation from Incomplete Observations. in (1992). doi:10.1007/978-1-4612-4380-9_25\u003c/li\u003e\n \u003cli dir=\"LTR\"\u003e Quine, M. P. \u0026amp; Robinson, J. Efficiencies of Chi-Square and Likelihood Ratio Goodness-of-Fit Tests. \u003cem\u003eAnn. Stat.\u003c/em\u003e (2007). doi:10.1214/aos/1176349550\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e\n"},{"header":"Supplementary Tables","content":"\u003cp\u003eSupplementary Tables S1, S2 and S3 are not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"NSCLC, mutational profile, clinical utility, next generation sequencing","lastPublishedDoi":"10.21203/rs.3.rs-4176050/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4176050/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNon-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer the mutational spectrum of which has been extensively characterized. Treatment of patients with NSCLC based on their molecular profile is now part of the standard clinical care. The aim of this study was firstly to investigate two different NGS-based tumor profile genetic tests and secondly to assess the clinical actionability of the mutations and their association with survival and clinicopathological characteristics. Overall, 52 mutations were identified in 31 patients by either one or both assays. The most frequently mutated genes were TP53 (40.4%), KRAS (13.46%) and EGFR (9.62%). TP53 and KRAS mutations were associated with worst overall survival while KRAS was positively correlated with adenocarcinoma. The two methods showed a high concordance for the commonly covered genomic regions (97.14%). Ten mutations were identified in a genomic region exclusively covered by the NIPD Genetics custom tumor profile assay. Likewise, one MET mutation was identified by the Ion Amliseq assay in a genomic region exclusively covered by Ion Amliseq.\u0026nbsp;In conclusion both assays showed highly similar results in the commonly covered genomic areas, however, the NIPD Genetics assay identified additional clinically actionable mutations that can be applied in clinical practice for personalized treatment decision making for patients with NSCLC.\u003c/p\u003e","manuscriptTitle":"Comparison of Targeted Next Generation Sequencing Assays in Non-small cell lung cancer Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-08 19:49:42","doi":"10.21203/rs.3.rs-4176050/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-04T14:02:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-02T08:51:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"7514743680142576429326723811921543258","date":"2024-06-28T05:11:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-24T06:29:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"282b8886-c83d-497a-b21c-f7eb345ed2b3","date":"2024-04-18T18:51:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-04T05:49:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-03T12:45:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-03T12:45:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2024-03-27T12:24:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e1d8eaa7-6f36-4805-a674-7cd0d7dc7619","owner":[],"postedDate":"April 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-09-18T13:44:41+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-08 19:49:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4176050","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4176050","identity":"rs-4176050","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}