IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-33248-2.html
   My bibliography  Save this article

Characterizing DNA methylation signatures of retinoblastoma using aqueous humor liquid biopsy

Author

Listed:
  • Hong-Tao Li

    (University of Southern California, Norris Comprehensive Cancer Center)

  • Liya Xu

    (University of Southern California)

  • Daniel J. Weisenberger

    (University of Southern California, Norris Comprehensive Cancer Center
    Keck School of Medicine, University of Southern California)

  • Meng Li

    (University of Southern California)

  • Wanding Zhou

    (University of Pennsylvania, Children’s Hospital of Philadelphia)

  • Chen-Ching Peng

    (University of Southern California)

  • Kevin Stachelek

    (University of Southern California)

  • David Cobrinik

    (University of Southern California
    University of Southern California, Norris Comprehensive Cancer Center
    Keck School of Medicine, University of Southern California
    Children’s Hospital Los Angeles)

  • Gangning Liang

    (University of Southern California, Norris Comprehensive Cancer Center
    Keck School of Medicine, University of Southern California)

  • Jesse L. Berry

    (University of Southern California
    Keck School of Medicine, University of Southern California
    Children’s Hospital Los Angeles)

Abstract

Retinoblastoma (RB) is a cancer that forms in the developing retina of babies and toddlers. The goal of therapy is to cure the tumor, save the eye and maximize vision. However, it is difficult to predict which eyes are likely to respond to therapy. Predictive molecular biomarkers are needed to guide prognosis and optimize treatment decisions. Direct tumor biopsy is not an option for this cancer; however, the aqueous humor (AH) is an alternate source of tumor-derived cell-free DNA (cfDNA). Here we show that DNA methylation profiling of the AH is a valid method to identify the methylation status of RB tumors. We identify 294 genes directly regulated by methylation that are implicated in p53 tumor suppressor (RB1, p53, p21, and p16) and oncogenic (E2F) pathways. Finally, we use AH to characterize molecular subtypes that can potentially be used to predict the likelihood of treatment success for retinoblastoma patients.

Suggested Citation

  • Hong-Tao Li & Liya Xu & Daniel J. Weisenberger & Meng Li & Wanding Zhou & Chen-Ching Peng & Kevin Stachelek & David Cobrinik & Gangning Liang & Jesse L. Berry, 2022. "Characterizing DNA methylation signatures of retinoblastoma using aqueous humor liquid biopsy," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33248-2
    DOI: 10.1038/s41467-022-33248-2
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-33248-2
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-022-33248-2?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. Dvir Aran & Marina Sirota & Atul J. Butte, 2015. "Systematic pan-cancer analysis of tumour purity," Nature Communications, Nature, vol. 6(1), pages 1-12, December.
    2. Ilya Kupershmidt & Qiaojuan Jane Su & Anoop Grewal & Suman Sundaresh & Inbal Halperin & James Flynn & Mamatha Shekar & Helen Wang & Jenny Park & Wenwu Cui & Gregory D Wall & Robert Wisotzkey & Satnam , 2010. "Ontology-Based Meta-Analysis of Global Collections of High-Throughput Public Data," PLOS ONE, Public Library of Science, vol. 5(9), pages 1-13, September.
    3. Jing Liu & Daniela Ottaviani & Meriem Sefta & Céline Desbrousses & Elodie Chapeaublanc & Rosario Aschero & Nanor Sirab & Fabiana Lubieniecki & Gabriela Lamas & Laurie Tonon & Catherine Dehainault & Cl, 2021. "A high-risk retinoblastoma subtype with stemness features, dedifferentiated cone states and neuronal/ganglion cell gene expression," Nature Communications, Nature, vol. 12(1), pages 1-20, December.
    4. Jinghui Zhang & Claudia A. Benavente & Justina McEvoy & Jacqueline Flores-Otero & Li Ding & Xiang Chen & Anatoly Ulyanov & Gang Wu & Matthew Wilson & Jianmin Wang & Rachel Brennan & Michael Rusch & Am, 2012. "A novel retinoblastoma therapy from genomic and epigenetic analyses," Nature, Nature, vol. 481(7381), pages 329-334, January.
    5. Hyo-Jin Park & Mi-Jung Kim & Christina Rothenberger & Ashok Kumar & Edith M. Sampson & Dalian Ding & Chul Han & Karessa White & Kevin Boyd & Senthilvelan Manohar & Yong-Hwan Kim & Maria S. Ticsa & Aar, 2019. "GSTA4 mediates reduction of cisplatin ototoxicity in female mice," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Grayson A. Herrgott & James M. Snyder & Ruicong She & Tathiane M. Malta & Thais S. Sabedot & Ian Y. Lee & Jacob Pawloski & Guilherme G. Podolsky-Gondim & Karam P. Asmaro & Jiaqi Zhang & Cara E. Cannel, 2023. "Detection of diagnostic and prognostic methylation-based signatures in liquid biopsy specimens from patients with meningiomas," Nature Communications, Nature, vol. 14(1), pages 1-19, December.

    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. Miles C. Andrews & Junna Oba & Chang-Jiun Wu & Haifeng Zhu & Tatiana Karpinets & Caitlin A. Creasy & Marie-Andrée Forget & Xiaoxing Yu & Xingzhi Song & Xizeng Mao & A. Gordon Robertson & Gabriele Roma, 2022. "Multi-modal molecular programs regulate melanoma cell state," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    2. Michael J. P. Crowley & Bhavneet Bhinder & Geoffrey J. Markowitz & Mitchell Martin & Akanksha Verma & Tito A. Sandoval & Chang-Suk Chae & Shira Yomtoubian & Yang Hu & Sahil Chopra & Diamile A. Tavarez, 2023. "Tumor-intrinsic IRE1α signaling controls protective immunity in lung cancer," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. Xiaomei Li & Lin Liu & Gregory J Goodall & Andreas Schreiber & Taosheng Xu & Jiuyong Li & Thuc D Le, 2020. "A novel single-cell based method for breast cancer prognosis," PLOS Computational Biology, Public Library of Science, vol. 16(8), pages 1-20, August.
    4. Christopher J. Hanley & Sara Waise & Matthew J. Ellis & Maria A. Lopez & Wai Y. Pun & Julian Taylor & Rachel Parker & Lucy M. Kimbley & Serena J. Chee & Emily C. Shaw & Jonathan West & Aiman Alzetani , 2023. "Single-cell analysis reveals prognostic fibroblast subpopulations linked to molecular and immunological subtypes of lung cancer," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    5. Philip East & Gavin P. Kelly & Dhruva Biswas & Michela Marani & David C. Hancock & Todd Creasy & Kris Sachsenmeier & Charles Swanton & Julian Downward & Sophie de Carné Trécesson, 2022. "RAS oncogenic activity predicts response to chemotherapy and outcome in lung adenocarcinoma," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    6. Birthe Dorgau & Joseph Collin & Agata Rozanska & Darin Zerti & Adrienne Unsworth & Moira Crosier & Rafiqul Hussain & Jonathan Coxhead & Tamil Dhanaseelan & Aara Patel & Jane C. Sowden & David R. FitzP, 2024. "Single-cell analyses reveal transient retinal progenitor cells in the ciliary margin of developing human retina," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    7. María-Jesús Lobón-Iglesias & Mamy Andrianteranagna & Zhi-Yan Han & Céline Chauvin & Julien Masliah-Planchon & Valeria Manriquez & Arnault Tauziede-Espariat & Sandrina Turczynski & Rachida Bouarich-Bou, 2023. "Imaging and multi-omics datasets converge to define different neural progenitor origins for ATRT-SHH subgroups," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    8. Yin Li & Manling Jiang & Ling Aye & Li Luo & Yong Zhang & Fengkai Xu & Yongqi Wei & Dan Peng & Xiang He & Jie Gu & Xiaofang Yu & Guoping Li & Di Ge & Chunlai Lu, 2024. "UPP1 promotes lung adenocarcinoma progression through the induction of an immunosuppressive microenvironment," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    9. José Caldas & Susana Vinga, 2014. "Global Meta-Analysis of Transcriptomics Studies," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-11, February.
    10. Tianwei Yu, 2018. "A new dynamic correlation algorithm reveals novel functional aspects in single cell and bulk RNA-seq data," PLOS Computational Biology, Public Library of Science, vol. 14(8), pages 1-22, August.
    11. Chunman Zuo & Yijian Zhang & Chen Cao & Jinwang Feng & Mingqi Jiao & Luonan Chen, 2022. "Elucidating tumor heterogeneity from spatially resolved transcriptomics data by multi-view graph collaborative learning," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    12. Shannon Coy & Shu Wang & Sylwia A. Stopka & Jia-Ren Lin & Clarence Yapp & Cecily C. Ritch & Lisa Salhi & Gregory J. Baker & Rumana Rashid & Gerard Baquer & Michael Regan & Prasidda Khadka & Kristina A, 2022. "Single cell spatial analysis reveals the topology of immunomodulatory purinergic signaling in glioblastoma," Nature Communications, Nature, vol. 13(1), pages 1-24, December.
    13. Jian He & Rui Gao & Mei Meng & Miao Yu & Chengrong Liu & Jingquan Li & Yizhi Song & Hui Wang, 2021. "Lysophosphatidic Acid Receptor 6 (LPAR6) Is a Potential Biomarker Associated with Lung Adenocarcinoma," IJERPH, MDPI, vol. 18(21), pages 1-25, October.
    14. Rachel Marty Pyke & Dattatreya Mellacheruvu & Steven Dea & Charles W. Abbott & Lee McDaniel & Devayani P. Bhave & Simo V. Zhang & Eric Levy & Gabor Bartha & John West & Michael P. Snyder & Richard O. , 2022. "A machine learning algorithm with subclonal sensitivity reveals widespread pan-cancer human leukocyte antigen loss of heterozygosity," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    15. Khoa A. Tran & Venkateswar Addala & Rebecca L. Johnston & David Lovell & Andrew Bradley & Lambros T. Koufariotis & Scott Wood & Sunny Z. Wu & Daniel Roden & Ghamdan Al-Eryani & Alexander Swarbrick & E, 2023. "Performance of tumour microenvironment deconvolution methods in breast cancer using single-cell simulated bulk mixtures," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    16. Thomas J Crisman & Ivette Zelaya & Dan R Laks & Yining Zhao & Riki Kawaguchi & Fuying Gao & Harley I Kornblum & Giovanni Coppola, 2016. "Identification of an Efficient Gene Expression Panel for Glioblastoma Classification," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-19, November.

    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:13:y:2022:i:1:d:10.1038_s41467-022-33248-2. 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.