IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-50471-1.html
   My bibliography  Save this article

Tumor detection by analysis of both symmetric- and hemi-methylation of plasma cell-free DNA

Author

Listed:
  • Xu Hua

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center
    Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

  • Hui Zhou

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center
    Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

  • Hui-Chen Wu

    (Columbia University Irving Medical Center
    Columbia University)

  • Julia Furnari

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

  • Corina P. Kotidis

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

  • Raul Rabadan

    (Columbia University Irving Medical Center)

  • Jeanine M. Genkinger

    (Columbia University Irving Medical Center
    Columbia University Mailman School of Public Health)

  • Jeffrey N. Bruce

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

  • Peter Canoll

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

  • Regina M. Santella

    (Columbia University Irving Medical Center
    Columbia University)

  • Zhiguo Zhang

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center
    Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

Abstract

Aberrant DNA methylation patterns have been used for cancer detection. However, DNA hemi-methylation, present at about 10% CpG dinucleotides, has been less well studied. Here we show that a majority of differentially hemi-methylated regions (DHMRs) in liver tumor DNA or plasma cells free (cf) DNA do not overlap with differentially methylated regions (DMRs) of the same samples, indicating that DHMRs could serve as independent biomarkers. Furthermore, we analyzed the cfDNA methylomes of 215 samples from individuals with liver or brain cancer and individuals without cancer (controls), and trained machine learning models using DMRs, DHMRs or both. The models incorporated with both DMRs and DHMRs show a superior performance compared to models trained with DMRs or DHMRs, with AUROC being 0.978, 0.990, and 0.983 in distinguishing control, liver and brain cancer, respectively, in a validation cohort. This study supports the potential of utilizing both DMRs and DHMRs for multi-cancer detection.

Suggested Citation

  • Xu Hua & Hui Zhou & Hui-Chen Wu & Julia Furnari & Corina P. Kotidis & Raul Rabadan & Jeanine M. Genkinger & Jeffrey N. Bruce & Peter Canoll & Regina M. Santella & Zhiguo Zhang, 2024. "Tumor detection by analysis of both symmetric- and hemi-methylation of plasma cell-free DNA," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-50471-1
    DOI: 10.1038/s41467-024-50471-1
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-50471-1
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-024-50471-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Thomas Powles & Zoe June Assaf & Nicole Davarpanah & Romain Banchereau & Bernadett E. Szabados & Kobe C. Yuen & Petros Grivas & Maha Hussain & Stephane Oudard & Jürgen E. Gschwend & Peter Albers & Dan, 2021. "ctDNA guiding adjuvant immunotherapy in urothelial carcinoma," Nature, Nature, vol. 595(7867), pages 432-437, July.
    2. Kuhn, Max, 2008. "Building Predictive Models in R Using the caret Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i05).
    3. Gabriella Ficz & Miguel R. Branco & Stefanie Seisenberger & Fátima Santos & Felix Krueger & Timothy A. Hore & C. Joana Marques & Simon Andrews & Wolf Reik, 2011. "Dynamic regulation of 5-hydroxymethylcytosine in mouse ES cells and during differentiation," Nature, Nature, vol. 473(7347), pages 398-402, May.
    4. Stephen Cristiano & Alessandro Leal & Jillian Phallen & Jacob Fiksel & Vilmos Adleff & Daniel C. Bruhm & Sarah Østrup Jensen & Jamie E. Medina & Carolyn Hruban & James R. White & Doreen N. Palsgrove &, 2019. "Genome-wide cell-free DNA fragmentation in patients with cancer," Nature, Nature, vol. 570(7761), pages 385-389, June.
    5. Netanel Loyfer & Judith Magenheim & Ayelet Peretz & Gordon Cann & Joerg Bredno & Agnes Klochendler & Ilana Fox-Fisher & Sapir Shabi-Porat & Merav Hecht & Tsuria Pelet & Joshua Moss & Zeina Drawshy & H, 2023. "A DNA methylation atlas of normal human cell types," Nature, Nature, vol. 613(7943), pages 355-364, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jun Wang & Jinyong Huang & Yunlong Hu & Qianwen Guo & Shasha Zhang & Jinglin Tian & Yanqin Niu & Ling Ji & Yuzhong Xu & Peijun Tang & Yaqin He & Yuna Wang & Shuya Zhang & Hao Yang & Kang Kang & Xinchu, 2024. "Terminal modifications independent cell-free RNA sequencing enables sensitive early cancer detection and classification," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Kate E. Stanley & Tatjana Jatsenko & Stefania Tuveri & Dhanya Sudhakaran & Lore Lannoo & Kristel Calsteren & Marie Borre & Ilse Parijs & Leen Coillie & Kris Bogaert & Rodrigo Almeida Toledo & Liesbeth, 2024. "Cell type signatures in cell-free DNA fragmentation profiles reveal disease biology," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    3. Michaël Noë & Dimitrios Mathios & Akshaya V. Annapragada & Shashikant Koul & Zacharia H. Foda & Jamie E. Medina & Stephen Cristiano & Christopher Cherry & Daniel C. Bruhm & Noushin Niknafs & Vilmos Ad, 2024. "DNA methylation and gene expression as determinants of genome-wide cell-free DNA fragmentation," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    4. Derek Wong & Maha Tageldein & Ping Luo & Erik Ensminger & Jeffrey Bruce & Leslie Oldfield & Haifan Gong & Nicholas William Fischer & Brianne Laverty & Vallijah Subasri & Scott Davidson & Reem Khan & A, 2024. "Cell-free DNA from germline TP53 mutation carriers reflect cancer-like fragmentation patterns," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    5. Prabal Das & D. A. Sachindra & Kironmala Chanda, 2022. "Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6043-6071, December.
    6. Paulo Infante & Gonçalo Jacinto & Anabela Afonso & Leonor Rego & Pedro Nogueira & Marcelo Silva & Vitor Nogueira & José Saias & Paulo Quaresma & Daniel Santos & Patrícia Góis & Paulo Rebelo Manuel, 2023. "Factors That Influence the Type of Road Traffic Accidents: A Case Study in a District of Portugal," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
    7. Ephrem Habyarimana & Faheem S Baloch, 2021. "Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-23, March.
    8. Alexander Wettstein & Gabriel Jenni & Ida Schneider & Fabienne Kühne & Martin grosse Holtforth & Roberto La Marca, 2023. "Predictors of Psychological Strain and Allostatic Load in Teachers: Examining the Long-Term Effects of Biopsychosocial Risk and Protective Factors Using a LASSO Regression Approach," IJERPH, MDPI, vol. 20(10), pages 1-20, May.
    9. Tang, Kayu & Parsons, David J. & Jude, Simon, 2019. "Comparison of automatic and guided learning for Bayesian networks to analyse pipe failures in the water distribution system," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 24-36.
    10. Daifeng Xiang & Gangsheng Wang & Jing Tian & Wanyu Li, 2023. "Global patterns and edaphic-climatic controls of soil carbon decomposition kinetics predicted from incubation experiments," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    11. Joel Podgorski & Oliver Kracht & Luis Araguas-Araguas & Stefan Terzer-Wassmuth & Jodie Miller & Ralf Straub & Rolf Kipfer & Michael Berg, 2024. "Groundwater vulnerability to pollution in Africa’s Sahel region," Nature Sustainability, Nature, vol. 7(5), pages 558-567, May.
    12. Tranos, Emmanouil & Incera, Andre Carrascal & Willis, George, 2022. "Using the web to predict regional trade flows: data extraction, modelling, and validation," OSF Preprints 9bu5z, Center for Open Science.
    13. Štefan Lyócsa & Petra Vašaničová & Branka Hadji Misheva & Marko Dávid Vateha, 2022. "Default or profit scoring credit systems? Evidence from European and US peer-to-peer lending markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    14. Marcos Rodrigues & Fermín Alcasena & Pere Gelabert & Cristina Vega‐García, 2020. "Geospatial Modeling of Containment Probability for Escaped Wildfires in a Mediterranean Region," Risk Analysis, John Wiley & Sons, vol. 40(9), pages 1762-1779, September.
    15. Giovanny Pillajo-Quijia & Blanca Arenas-Ramírez & Camino González-Fernández & Francisco Aparicio-Izquierdo, 2020. "Influential Factors on Injury Severity for Drivers of Light Trucks and Vans with Machine Learning Methods," Sustainability, MDPI, vol. 12(4), pages 1-28, February.
    16. Zander S. Venter & Adam Sadilek & Charlotte Stanton & David N. Barton & Kristin Aunan & Sourangsu Chowdhury & Aaron Schneider & Stefano Maria Iacus, 2021. "Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis," IJERPH, MDPI, vol. 18(23), pages 1-12, November.
    17. G. Brooke Anderson & Keith W. Oleson & Bryan Jones & Roger D. Peng, 2018. "Classifying heatwaves: developing health-based models to predict high-mortality versus moderate United States heatwaves," Climatic Change, Springer, vol. 146(3), pages 439-453, February.
    18. Van Belle, Jente & Guns, Tias & Verbeke, Wouter, 2021. "Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chains," European Journal of Operational Research, Elsevier, vol. 288(2), pages 466-479.
    19. Ali Al-Ramini & Mohammad A Takallou & Daniel P Piatkowski & Fadi Alsaleem, 2022. "Quantifying changes in bicycle volumes using crowdsourced data," Environment and Planning B, , vol. 49(6), pages 1612-1630, July.
    20. Yagli, Gokhan Mert & Yang, Dazhi & Srinivasan, Dipti, 2019. "Automatic hourly solar forecasting using machine learning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 487-498.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-50471-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.