Abstract
Background
High-throughput sequencing of blood cell-free DNA (cfDNA) techniques offer an opportunity to characterize and monitor cancer rapidly in a non-invasive and real-time manner. Nonetheless, there lacks a tool within therapeutic arsenal to identify multi-omics alterations simultaneously from a single biopsy. In current times, bisulfite-based sequencing detects 5mC and 5hmC at single-base resolution is the golden standard of DNA methylation, while the degradation of DNA and biased sequencing data are the problems of this method.
Objective
To identify the consistency analysis of methylation and genetic variation with single library, we presented a platform detecting multi-omics data simultaneously from a single blood biopsy using bisulfite-free method of genomic methylation sequencing (GM-seq) mediated by TET enzyme.
Methods
We detected methylomic and genetic changes simultaneously from a single blood biopsy in NA12878 and randomly chose ten blood biopsies from colorectal cancer or lung cancer patients to validate the ability of GM-seq.
Results
Similar cytosine methylation level between whole genome bisulfite sequencing (WGBS) and GM-seq were identified in NA12878. Moreover, longer insert size, CpGs coverage and GC distribution were outperformed than WGBS. In addition, the comparison of the single nucleotide polymorphism (SNP), insertion-deletion (Indel) and copy number variation (CNV) in NA12878 or ctDNA from liver cancer between GM-seq and whole genome sequencing (WGS) show a good consistency, indicating that this method is feasible for detecting genetic variation in blood.
Conclusion
In conclusion, our work demonstrated a method for identification of the methylated modification and genetic variations simultaneously from a single blood biopsy.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
References
Booth MJ, Branco MR, Ficz G, Oxley D, Krueger F, Reik W, Balasubramanian S (2012) Quantitative sequencing of 5-methylcytosine and 5-hydroxymethylcytosine at single-base resolution. Science 336:934–937
Cescon DW, Bratman SV, Chan SM, Siu LL (2020) Circulating tumor DNA and liquid biopsy in oncology. Nat Cancer 1:276–290
Gandara DR, Paul SM, Kowanetz M, Schleifman E, Zou W, Li Y, Rittmeyer A, Fehrenbacher L, Otto G, Malboeuf C et al (2018) Blood-based tumor mutational burden as a predictor of clinical benefit in non-small-cell lung cancer patients treated with atezolizumab. Nat Med 24:1441–1448
Garraway LA, Lander ES (2021) Lessons from the cancer genome. Cell 153:17–37
Greenberg MVC, Bourc’his D (2019) The diverse roles of DNA methylation in mammalian development and disease. Nat Rev Mol Cell Biol 20:590–607
Ignatiadis M, Sledge GW, Jeffrey SS (2021) Liquid biopsy enters the clinic - implementation issues and future challenges. Nat Rev Clin Oncol 18:297–312
Klutstein M, Nejman D, Greenfield R, Cedar H (2016) DNA methylation in cancer and aging. Cancer Res 76:3446–3450
Kobayashi H, Kono T (2012) DNA methylation analysis of germ cells by using bisulfite-based sequencing methods. Methods Mol Biol 825:223–235
Koch A, Joosten SC, Feng Z, de Ruijter TC, Draht MX, Melotte V, Smits KM, Veeck J, Herman JG, Nest LV et al (2018) Author correction: analysis of DNA methylation in cancer: location revisited. Nat Rev Clin Oncol 15:467
Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760
Li Y, Xu H, Su S, Ye J, Chen J, Jin X, Lin Q, Zhang D, Ye C, Chen C (2017) Clinical validation of a highly sensitive assay to detect EGFR mutations in plasma cell-free DNA from patients with advanced lung adenocarcinoma. PLoS ONE 12:e0183331
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, 1000 Genome Project Data Processing Subgroup (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25:2078–2079
Liu Y, Siejka-Zielinska P, Velikova G, Bi Y, Yuan F, Tomkova M, Bai C, Chen L, Schuster-Bockler B, Song CX (2019) Bisulfite-free direct detection of 5-methylcytosine and 5-hydroxymethylcytosine at base resolution. Nat Biotechnol 37:424–429
Odegaard JI, Vincent JJ, Mortimer S, Vowles JV, Ulrich BC, Banks KC, Fairclough SR, Zill OA, Sikora M, Mokhtari R et al (2018) Validation of a plasma-based comprehensive cancer genotyping assay utilizing orthogonal tissue and plasma-based methodologies. Clin Cancer Res 24:3539–3549
Olova N, Krueger F, Andrews S, Oxley D, Berrens RV, Branco MR, Reik W (2018) Comparison of whole-genome bisulfite sequencing library preparation strategies identifies sources of biases affecting DNA methylation data. Genome Biol 19:33
Siejka-Zielińska P, Cheng J, Jackson F, Liu Y, Soonawalla Z, Reddy S, Silva M, Puta L, McCain M, Culver E et al (2021) Cell-free DNA TAPS provides multimodal information for early cancer detection. Sci Adv 7:eabh0534
SmithMeissner ZD (2013) A DNA methylation: roles in mammalian development. Nat Rev Genet 14:204–220
Tanaka K, Okamoto A (2007) A Degradation of DNA by bisulfite treatment. Bioorg Med Chem Lett 17:1912–1915
Unnikrishnan A, Freeman WM, Jackson J, Wren JD, Porter H, Richardson A (2019) A The role of DNA methylation in epigenetics of aging. Pharmacol Ther 195:172–185
Vaisvila R, Ponnaluri VKC, Sun Z, Langhorst BW, Saleh L, Guan S, Dai N, Campbell MA, Sexton BS, Marks K et al (2021) Enzymatic methyl sequencing detects DNA methylation at single-base resolution from picograms of DNA. Genome Res 31:1280–1289
Yu M, Hon GC, Szulwach KE, Song CX, Zhang L, Kim A, Li X, Dai Q, Shen Y, Park B et al (2012) Base-resolution analysis of 5-hydroxymethylcytosine in the mammalian genome. Cell 149:1368–1380
Zhao LY, Song J, Liu Y, Song CX, Yi C (2020) Mapping the epigenetic modifications of DNA and RNA. Protein Cell 11:792–808
Funding
This work was supported by Shenzhen Post-doctoral Funding to Dr. Yinpeng Xie.
Author information
Authors and Affiliations
Contributions
XY, LY and XX conceived the idea of the present study. JL, LS, WW and MZ performed the sequence process. XC, JL, QL, QZ, HL, GL, QL analyzed the data. XC, YX wrote the manuscript. ZY and XX reviewed the manuscript.
Corresponding author
Ethics declarations
Conflict of interest
Xiaomin Chen, Jiahui Liu, Jun Li, Yinpeng Xie, Zichen Yu, Lu Shen, Qingfeng Liu, Wei Wu, Qiang Zhao, Haoxiang Lin, Gaotong Liu, Qiuping Luo, Ling Yang, Yi Huang, Meiru Zhao, Xin Yi and Xuefeng Xia declare that they have no conflicts of interest.
Ethical approval and consent to participate
All procedures performed in studies involving human participants were in accordance with the Helsinki Declaration (as revised in 2013). Written informed consent was obtained from the patient. The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Consent for publication
Written informed consent for publication was obtained from all participants.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Chen, X., Liu, J., Li, J. et al. Identification of DNA methylation and genetic alteration simultaneously from a single blood biopsy. Genes Genom 45, 627–635 (2023). https://doi.org/10.1007/s13258-022-01340-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13258-022-01340-y