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ISSN: 1233-9687
Polish Journal of Pathology
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Original paper

Plasma biopsy by Tag-sequencing: an acceptable alternative to tumor tissue profiling in non-small-cell lung cancer

Anurag Mehta
1
,
Sanjeev Kumar Sharma
2
,
Dushyant Kumar
2
,
Smreti Vasudevan
3

1.
Department of Laboratory and Transfusion Services and Department of Research, Rajiv Gandhi Cancer Institute and Research Centre, India
2.
Molecular Laboratory, Department of Laboratory and Transfusion Services, Rajiv Gandhi Cancer Institute and Research Centre, India
3.
Department of Research, Rajiv Gandhi Cancer Institute and Research Centre, India
Pol J Pathol 2021; 72 (2): 117-123
Online publish date: 2021/09/30
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Introduction

Lung cancer has been the leading killer across the globe [1]. Seeking driver mutation and inhibiting it with a corresponding inhibitor has improved survival in advanced non-small-cell lung cancer (NSCLC) [2, 3]. Predictive biomarker profiling of the core biopsy tissue is the current standard of care. However, inadequate material and potential hazards of a repeat biopsy have encouraged the use of liquid biopsy as a minimally invasive alternative. Tumor cell apoptosis and necrosis lead to extravasation of cell-free nucleic acids (cfNAs) into peripheral blood and eventually into urine or cerebrospinal fluid. This cfNA being tumor-derived retains the molecular signatures of the cancer [4, 5]. However, the low abundance of tumor-derived nucleic acids requires high coverage which in turn can lead to errors of PCR duplicates combined with intrinsic errors of sequencing. Tag-sequencing is an error reduction technique that utilizes unique identifiers to remove errors facilitating error-free detection of low-abundant nucleic acid alterations [6, 7]. In this method, the target gene is first amplified and purified. The targeted amplicons are then amplified with barcode-adapted primers. About 10-15 base pair unique molecular identifier (UMID) sequences label the amplicons.
The barcoded library is purified, size selected, quantified by qPCR, and sequenced. The sequencing reads sharing the same UMIDs are grouped together as one molecular family and read in consensus. A genuine mutation must be seen in the entire family. At least three molecular families should show the genetic alteration to be considered significant. This technique can considerably reduce the error rate of PCR and sequencing. Establishing the effectiveness of this strategy can make plasma biopsy an acceptable tool to detect molecular biomarkers in NSCLC in special circumstances where tissue has exhausted and fresh biopsy is impractical. Repeatability for mutation tracking over time and detecting variants derived through tumor heterogeneity shall further make cfNA testing an attractive proposition.
In a previous study, we validated tumor NGS testing in advanced/ metastatic NSCLC patients with respect to single-gene assay for detecting EGFR mutations and ALK1 rearrangement [8]. Here, we have compared the ability of the novel Tag-sequencing NGS to identify actionable genomic alterations from the plasma sample of NSCLC patients and assessed the performance with tissue biopsy sequencing.

Material and methods

Research setting and patients

The study was initiated after obtaining ethical approval from the Institutional Review Board (RGCIRC/ IRB/ 168/ 2018, dated 1st June 2018) and was conducted in accordance with the Declaration of Helsinki. The study was conducted at a single center from 2018 until the end of 2019. Twenty-one advanced, treatment naïve, NSCLC patients, tested for predictive biomarkers by NGS on tumor tissue were simultaneously tested for biomarkers using plasma and were included in the study. There were nineteen cases of lung adenocarcinoma (LUAD) and two cases of squamous cell carcinoma (SCC) histology, the latter tested being young and non-smoker with a high probability of harboring an actionable mutation.

Tumor tissue sequencing

Tissue NGS was performed in the cohort a priori using OncomineTM Solid Tumor DNA and OncomineTM Solid Tumor Fusion Transcript kit on Ion-Torrent Sequencing platform. The procedure of isolation of nucleic acid from formalin-fixed and paraffin-embedded (FFPE) tumor tissue, library preparation, sequencing, and data analysis have been described earlier [8].

cfNA extraction and sequencing

To avoid temporal bias, the sampling of biopsy tissue and blood was performed simultaneously. Peripheral blood (~10 ml) was drawn in K+EDTA tube and plasma was separated by two rounds of centrifugation (1200 g × 10 minutes followed by 16000 g × 10 minutes). Cell-free nucleic acid was extracted from 2-4 ml of plasma using the QIAamp Circulating Nucleic Acid Kit (Qiagen) as per the vendor’s specification. The nucleic acid concentration was determined on Qubit® 3.0 Fluorometer (Invitrogen Life Technologies). The sequencing library was generated from 50 ng cfNA using OncomineTM Lung Cell-Free Total Nucleic Acid Assay following the user guide (#A35864, MAN0017065). Tag sequencing barcode set (A31830) was employed for generating a barcoded library and ~50 pM was loaded on Ion 530TM Chip (8-plex pooled library). Sequencing was performed on the Ion-Torrent S5 Sequencing platform and the data was analysed in Torrent SuiteTM Software 5.2 and Ion Reporter 5.10 using Lung Liquid Biopsy DNA and TagSeq Liquid Biopsy templates plugin. Sequenced reads were mapped to reference genome GRCh37/hg19 and the variants called on Ion reporter were reaffirmed on VarSome search engine [9]. The clinical significance of the alterations was investigated in the clinical decision support tool OncoKB [10].

Single-gene testing

Wherever tumor tissue was sufficient, testing for EGFR mutations and ALK1 fusion rearrangement was performed by real-time PCR (using Qiagen EGFR Therascreen® RGQ PCR Kit) and immunohistochemistry (VENTANA ALK D5F3 CDx assay), respectively, as described previously [8]. KRAS mutation status (Codons 12/13) of the tumor tissue was confirmed by real-time PCR (using KRAS Mutation Analysis Kit – EntroGen) in selected cases; performed according to the manufacturer’s recommendations.

Statistical analysis

Concordance was defined at both the patient-level (i.e. comparison of the set of all alterations seen in the individual patient) as well as at the variant-level (comparison of individual variants in the study cohort). At the patient-level, finding an identical alteration in all the detected genes was called as concordant, while non-detection of the genomic alteration either in tissue or in plasma/ or a differing genomic alteration in the same gene was considered to be discordant. At the variant-level, detecting identical or lack of an alteration (wild-type/wild-type) was considered to be concordant, while differing mutations observed in the same gene was considered to be partially concordant. Lack of an alteration by one of the two platforms in the same patient was considered to be a discordant result. Descriptive statistics were used to summarize data. The agreement of the two techniques was measured by Cohen’s κ statistics.

Results

The clinical characteristics of the patients have been presented in Table I. The list of genes and rearrangements interrogated by the respective panel has been shown in Supplementary Table I. Individual patient-level and variant-level concordance of the two NGS assays Two LUAD patients had no pathogenic alteration detected by both platforms. In the remaining nineteen patients, deleterious variants were identified in seven genes and in one fusion transcript (Fig. 1). The assay results were in agreement for 12 (57.1%) cases. Five patients showed single gene discordance, three cases differed for two genes, and a single case for three genes (Fig. 1, Supplementary Table II). A total of 47 pathogenic alterations were detected, including 21 in tumor tissue and 26 in plasma cfNA (Fig. 2A, Supplementary Table II). For the variants compared, 14/21 (66.7%) of tissue mutations were captured in plasma, and 14/26 (53.8%) of the cfDNA mutations were detected in the tissue (Fig. 2B, Supplementary Table II). The overall concordance between the two assays for the common thirteen genes/rearrangements interrogated by the panels was 94.87% (259/273). Tag-sequencing in the plasma sample identified seven deleterious/likely pathogenic variants [three in KRAS (two-p.Gly12Cys, p.Gly13Asp), single for ERBB2 (p.Ala771_Tyr772insTyrValMetAla), EGFR (p.Leu858Arg), MET (p.Thr1010Ile) and TP53 (p.Val157Phe)] that were not detected on tissue NGS. Whereas, two variants [BRAF (p.Leu597Gln) and KRAS (p.Gly12Asp)] were observed in the tumor but not in plasma (Fig. 2A and 2B). Notably, five partially concordant mutations, that showed genomic and functional concordance, but locational discordance was observed for the genes KRAS and TP53 (Supplementary Table II).
One non-targeted TRIM24-BRAF gene fusion was called for in the tissue sample of a single subject which we have excluded from the comparative analysis. At the genic-level, excluding 2 patients who had no driver mutations both on tissue and plasma biopsy, the estimates for concordance (both complete and partial) and discordance were 67.86% (19/28), and 32.14% (9/28), respectively (Supplementary Table II). A substantial agreement was attained between the two assays (κ = 0.71, 95% CI: 0.54-0.89). In particular, there was an appreciable agreement between tumor and plasma NGS results for detecting EGFR gene mutation in tumor tissue (95.24% concordance; κ = 0.89, 95% CI: 0.70-1.00).

Clinical implications of discordant gene alterations

Data mining for the therapeutic implication of the alterations was performed on Oncology Knowledge Base, OncoKB, which gives information based on the level-of-evidence to get benefit from a therapeutic agent. The filter was set for non-small-cell lung cancer (Supplementary Table II). Among the nine patients who showed discordant/partially concordant- solid vs. liquid biopsy variants, the plasma biopsy could additionally pick actionable mutations in four patients. These are EGFR (p.Leu858Arg – level 1), ERBB2 (p.Ala771_Tyr772insTyrValMetAla – level 2) in single patient each, and two cases with KRAS (p.Gly12Cys – level 3) mutations (Supplementary Table II, Fig. 2B). All other discordant oncogenic mutations in the genes BRAF, KRAS, MET and TP53 that we observed were implicated as non-actionable in the OncoKB database.

Validation by single-gene assay

The results were validated by single-gene assay for detecting EGFR mutation in 19/21 cases (Table II, Supplementary Table III). The exon 18 EGFRdelGlu709_Thr710insAsp variant observed in both tumor and plasma NGS was not tested by real-time PCR as the test kit lacks primers for the same. The single discordant (p.Leu858Arg) mutation that came positive in plasma NGS was confirmed by real-time PCR of tumor-derived DNA. Also, rearranged ALK1 was tested in 18/21 cases by immunohistochemistry, and showed perfect agreement with the NGS results in both tumor tissue and plasma cfNA (Table II, Supplementary Table III). In addition, we confirmed the three KRAS mutations called in plasma, but not in tissue NGS by real-time PCR of tumor DNA. Among them, one was positive for mutated KRAS whereas two were negative (Table II, Supplementary Table III). In this one case plasma result was true positive using single-gene assay as a reference while the tissue result was a false negative.

Discussion

This study explores the concordance between NGS multigene assay of plasma cfNA using molecular tagging approach and the routine tumor biopsy sequencing. Compared to a previous study that was conducted without the application of molecular barcodes [11], our study demonstrates considerable improvement in concordance. Ligating the region of interest with unique molecular identifiers significantly improved the performance and could pick mutations of low allele fraction in plasma with high accuracy. Substantial agreement between the two assays (κ = 0.71, 95% CI: 0.54-0.89) agrees with earlier studies by Kukita et al. and Tran et al. [6, 12]. However, these studies were undertaken in a lesser gene number as compared to the present study. In a recent study, Luca et al. demonstrated that sequencing based on molecular tagging technology achieves optimum performance for detecting driver gene mutations from the plasma of advanced NSCLC patients. But they mostly evaluated the performance metrics, and no comparison with mutations detected on tumor biopsy sample was undertaken [13]. In another study by Heeke et al. the impact of Tag-sequencing in liquid biopsy was evaluated by comparing the results with Foundation Liquid assay and tumor geno- typing [14]. Our study has assessed the usefulness of Tag-sequencing in liquid biopsy in a treatment naïve setting for advanced NSCLC patients and a comparative analysis with tumor biopsy NGS has been made with respect to pathogenic variants as well as the individual patient.
Strong agreement was observed for detecting clinically actionable EGFR mutations and ALK1 fusion. For the detection of EGFR gene mutations, the plasma cfNA showed a 95.24% concordance with tumor NGS results. In addition, cross-platform evaluation by single-gene assay showed congruent results with plasma NGS. This observation agrees with the previous studies by Veldore et al. where plasma-derived cfNA was tested for EGFR mutations using deep sequencing in a large cohort of 163 patients and validated against allele-specific real-time PCR of tissue biopsy [15]. Supporting is the study by Steendam et al. that compares NGS and ddPCR for detecting primary activating EGFR mutations on cfNA, showing good agreement between the two methods [16]. Of note, in the present study, plasma NGS could also detect less common EGFR exon 18 deletion/insertion mutation. Among the EGFR mutated NSCLC cases, the EGFRdelGlu709_Thr710insAsp variant shows less than 0.1% prevalence and is accepted as a tyrosine kinase inhibitor sensitive mutation [17]. Identifying this rare but potentially actionable mutation adds to the value of NGS-based testing as this mutation is not tested in the current FDA approved real-time PCR-based kit for EGFR sensitizing mutation detection (ie. Cobas® EGFR Mutation Test v2 and Therascreen® EGFR RGQ PCR Kit).
Additionally, as regards to ALK1 fusion rearrangement and PIK3CA, absolute concordance observed, reinforces the suitability of cfNA based multigene assay as a valid testing methodology though the size of the cohort in the current study is small. Conventionally, ALK1 testing is performed using fluorescence in situ hybridization (FISH) and/or immunohistochemistry on formalin-fixed, paraffin-embedded tissue [18, 19, 20]. The early NGS-based platform did not have the capability to identify fusion rearrangements. The contemporary assays, however, are capable of identifying fusions on NGS. The ability to identify fusions on cfNA can allow many more patients to obtain biomarker-based therapies as up to 33% to 53% of patients fail to have adequate tissue on core needle biopsies and fine needle aspirate, respectively [21]. The study revealed three additional KRAS mutations and single variants for ERBB2, EGFR, MET and TP53 that was picked up on plasma Tag-sequencing NGS, but not by routine tissue NGS. One of the KRAS mutations was p.Gly12Cys, which is poised to become actionable [22, 23]. It has been observed that sometimes liquid biopsy shows additional mutations because of intratumoral heterogeneity that tissue biopsy may fail to detect. If the region outside the primary site harbors the mutant allele due to evolving branch mutations, it can be detected in plasma but not by tumor analysis [24]. Another plausible explanation is the ‘Clonal Hematopoiesis of Indeterminate Potential’ responsible for some of these calls [25]. The least plausible, yet possible cause could be second primary lung cancer that has a KRAS mutation but was not considered metastatic by clinical or radiological evaluation [26].
A similar explanation is likely for the TP53 mutation identified only in cfNA. It is important to mention that Tag-sequencing of plasma has the potential to pick-up variants of low frequency due to high coverage, while in most tissue NGS the cut-off for filter is 3-5%. Therefore, plasma biopsy identifies additional mutations that are not detected on tissue biopsy sequencing, and so it is not appropriate to consider them as false positives. At patient-level 9/21 (43%) cases showed discordance between plasma and tumor genotype profile, and the differences were mostly observed for missense variants in the TP53 and/ or KRAS gene (in 7 cases). The TP53 mutations are presently inconsequential for therapeutic decision making, however, they may have prognostic significance. We have not validated the discordant TP53 mutations by single-gene testing as they are not relevant for therapy decisions. However, these may become useful over time for example the commutation of KRAS and TP53 may provide the best results with checkpoint inhibitors [27, 28]. In the present study therapeutic decision was made according to tumor molecular profile. The sample size of our study is small and so we are not able to draw a conclusion regarding which assay results should be considered for selecting effective treatment.
Overall, the study shows that the Tag-sequencing of plasma cfNA achieves comparable performance to tumor NGS for detecting sensitizing EGFR mutations and ALK1 translocation. Plasma biopsy was of value in identifying therapeutically actionable variants in four patients that tumor tissue sequencing failed to pick. Small sample size and lack of follow-up data is the limitation of the study. However, keeping in mind the substantial agreement of liquid biopsy with the tissue biopsy, its utility in tissue deficient cases, in real-time monitoring of tumor status; Tag-sequencing of plasma could help in making treatment decisions, and understanding the mutational landscape in advanced NSCLC.

Conclusions

Using a small but focused gene panel to test cfNA that covers clinically relevant alterations, it is possible to offer biomarker-based therapies to the patients of advanced LUAD without available biopsy or cytology material. With improved outcomes from genome directed therapies, biomarker testing using cfNA in exceptional circumstances is a viable option with high predictive accuracy for biomarkers like EGFR gene mutations and ALK1 rearrangement.
Supplementary Tables are available in online version of this article.
The authors declare no conflict of interest.

References

1. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018; 68: 394-424.
2. Kris MG, Johnson BE, Berry LD, et al. Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. JAMA 2014; 311: 1998-2006.
3. Vestergaard HH, Christensen MR, Lassen UN. A systematic review of targeted agents for non-small cell lung cancer. Acta Oncol 2018; 57: 176-186.
4. Jahr S, Hentze H, Englisch S, et al. DNA fragments in the blood plasma of cancer patients: quantitations and evidence for their origin from apoptotic and necrotic cells. Cancer Res 2001; 61: 1659-1665.
5. Diaz LA, Jr., Bardelli A. Liquid biopsies: genotyping circulating tumor DNA. J Clin Oncol 2014; 32: 579-586.
6. Kukita Y, Matoba R, Uchida J, et al. High-fidelity target sequencing of individual molecules identified using barcode sequences: de novo detection and absolute quantitation of mutations in plasma cell-free DNA from cancer patients. DNA Res 2015; 22: 269-277.
7. Volik S, Alcaide M, Morin RD, et al. Cell-free DNA (cfDNA): Clinical Significance and Utility in Cancer Shaped By Emerging Technologies. Mol Cancer Res 2016; 14: 898-908.
8. Mehta A, Vasudevan S, Sharma SK, et al. Biomarker testing for advanced lung cancer by next-generation sequencing; a valid method to achieve a comprehensive glimpse at mutational landscape. Applied Cancer Research 2020; 40: doi.org/10.1186/s41241-020-00089-8.
9. Kopanos C, Tsiolkas V, Kouris A, et al. VarSome: the human genomic variant search engine. Bioinformatics 2019; 35: 1978-1980.
10. Chakravarty D, Gao J, Phillips SM, et al. OncoKB: A Precision Oncology Knowledge Base. JCO Precis Oncol 2017; 2017: doi: 10.1200/PO.17.00011.
11. Chae YK, Davis AA, Carneiro BA, et al. Concordance between genomic alterations assessed by next-generation sequencing in tumor tissue or circulating cell-free DNA. Oncotarget 2016; 7: 65364-65373.
12. Tran LS, Pham HT, Tran VU, et al. Ultra-deep massively parallel sequencing with unique molecular identifier tagging achieves comparable performance to droplet digital PCR for detection and quantification of circulating tumor DNA from lung cancer patients. PloS One 2019; 14: e0226193.
13. Luca DG, Lastraioli S, Conte R, et al. Performance of the OncomineTM Lung cfDNA Assay for Liquid Biopsy by NGS of NSCLC Patients in Routine Laboratory Practice. Appl Sci 2020; 10: doi.org/10.3390/app10082895.
14. Heeke S, Hofman V, Ilié M, et al. Prospective evaluation of NGS-based liquid biopsy in untreated late stage non-squamous lung carcinoma in a single institution. J Transl Med 2020; 18: doi.org/10.1186/s12967-020-02259-215.
15. Veldore VH, Choughule A, Routhu T, et al. Validation of liquid biopsy: plasma cell-free DNA testing in clinical management of advanced non-small cell lung cancer. Lung Cancer (Auckl) 2018; 9: 1-11.
16. Steendam CMJ, Atmodimedjo P, de Jonge E, et al. Plasma Cell-Free DNA Testing of Patients With EGFR Mutant Non–Small-Cell Lung Cancer: Droplet Digital PCR Versus Next-Generation Sequencing Compared With Tissue-Based Results. JCO Precis Oncol 2019; doi: 10.1200/PO.18.00401.
17. Ackerman A, Goldstein MA, Kobayashi S, et al. EGFR delE709_T710insD: a rare but potentially EGFR inhibitor responsive mutation in non-small-cell lung cancer. J Thorac Oncol 2012; 7: e19-20.
18. Martelli MP, Sozzi G, Hernandez L, et al. EML4-ALK rearrangement in non-small cell lung cancer and non-tumor lung tissues. Am J Pathol 2009; 174: 661-670.
19. Shaw AT, Yeap BY, Mino-Kenudson M, et al. Clinical features and outcome of patients with non-small-cell lung cancer who harbor EML4-ALK. J Clin Oncol 2009; 27: 4247-4253.
20. Conklin CM, Craddock KJ, Have C, et al. Immunohistochemistry is a reliable screening tool for identification of ALK rearrangement in non-small-cell lung carcinoma and is antibody dependent. J Thorac Oncol 2013; 8: 45-51.
21. Schneider F, Smith MA, Lane MC, et al. Adequacy of core needle biopsy specimens and fine-needle aspirates for molecular testing of lung adenocarcinomas. Am J Clin Pathol 2015; 143: 193-200.
22. Canon J, Rex K, Saiki AY, et al. The clinical KRAS(G12C) inhibitor AMG 510 drives anti-tumour immunity. Nature 2019; 575: 217-223.
23. Kettle JG, Cassar DJ. Covalent inhibitors of the GTPase KRAS(G12C): a review of the patent literature. Expert Opin Ther Pat 2020; 30: 103-120.
24. Zhang J, Fujimoto J, Wedge DC, et al. Intratumor heterogeneity in localized lung adenocarcinomas delineated by multiregion sequencing. Science 2014; 346: 256-259.
25. Hu Y, Ulrich BC, Supplee J, et al. False-Positive Plasma Genotyping
26. Due to Clonal Hematopoiesis. Clin Cancer Res 2018; 24: 4437-4443.
27. Tseng LH, De Marchi F, Pallavajjalla A, et al. Clinical Validation of Discordant Trunk Driver Mutations in Paired Primary and Metastatic Lung Cancer Specimens. Am J Clin Pathol 2019; 152: 570-581.
28. Dong ZY, Zhong WZ, Zhang XC, et al. Potential Predictive Value of TP53 and KRAS Mutation Status for Response to PD-1 Blockade Immunotherapy in Lung Adenocarcinoma. Clin Cancer Res 2017; 23: 3012-3024.
29. Wang S, Jiang M, Yang Z, et. al. The role of distinct co-mutation patterns with TP53 mutation in immunotherapy for NSCLC. Genes & Diseases 2020; doi.org/10.1016/j.gendis.2020.04.001.
Copyright: © 2021 Polish Association of Pathologists and the Polish Branch of the International Academy of Pathology This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License (http://creativecommons.org/licenses/by-nc-sa/4.0/), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material, provided the original work is properly cited and states its license.
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