IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-34568-z.html
   My bibliography  Save this article

Systematic characterization of cancer transcriptome at transcript resolution

Author

Listed:
  • Wei Hu

    (Shanghai Jiao Tong University School of Medicine)

  • Yangjun Wu

    (Fudan University Shanghai Cancer Center)

  • Qili Shi

    (Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University)

  • Jingni Wu

    (Shanghai Jiao Tong University School of Medicine)

  • Deping Kong

    (Shanghai Jiao Tong University School of Medicine)

  • Xiaohua Wu

    (Fudan University Shanghai Cancer Center)

  • Xianghuo He

    (Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University)

  • Teng Liu

    (Shanghai Jiao Tong University School of Medicine
    Taizhou University)

  • Shengli Li

    (Shanghai Jiao Tong University School of Medicine)

Abstract

Transcribed RNAs undergo various regulation and modification to become functional transcripts. Notably, cancer transcriptome has not been fully characterized at transcript resolution. Herein, we carry out a reference-based transcript assembly across >1000 cancer cell lines. We identify 498,255 transcripts, approximately half of which are unannotated. Unannotated transcripts are closely associated with cancer-related hallmarks and show clinical significance. We build a high-confidence RNA binding protein (RBP)-transcript regulatory network, wherein most RBPs tend to regulate transcripts involved in cell proliferation. We identify numerous transcripts that are highly associated with anti-cancer drug sensitivity. Furthermore, we establish RBP-transcript-drug axes, wherein PTBP1 is experimentally validated to affect the sensitivity to decitabine by regulating KIAA1522-a6 transcript. Finally, we establish a user-friendly data portal to serve as a valuable resource for understanding cancer transcriptome diversity and its potential clinical utility at transcript level. Our study substantially extends cancer RNA repository and will facilitate anti-cancer drug discovery.

Suggested Citation

  • Wei Hu & Yangjun Wu & Qili Shi & Jingni Wu & Deping Kong & Xiaohua Wu & Xianghuo He & Teng Liu & Shengli Li, 2022. "Systematic characterization of cancer transcriptome at transcript resolution," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-34568-z
    DOI: 10.1038/s41467-022-34568-z
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-34568-z
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-022-34568-z?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. Eric T. Wang & Rickard Sandberg & Shujun Luo & Irina Khrebtukova & Lu Zhang & Christine Mayr & Stephen F. Kingsmore & Gary P. Schroth & Christopher B. Burge, 2008. "Alternative isoform regulation in human tissue transcriptomes," Nature, Nature, vol. 456(7221), pages 470-476, November.
    2. Eric L. Nostrand & Peter Freese & Gabriel A. Pratt & Xiaofeng Wang & Xintao Wei & Rui Xiao & Steven M. Blue & Jia-Yu Chen & Neal A. L. Cody & Daniel Dominguez & Sara Olson & Balaji Sundararaman & Liju, 2020. "A large-scale binding and functional map of human RNA-binding proteins," Nature, Nature, vol. 583(7818), pages 711-719, July.
    3. Donny D. Licatalosi & Aldo Mele & John J. Fak & Jernej Ule & Melis Kayikci & Sung Wook Chi & Tyson A. Clark & Anthony C. Schweitzer & John E. Blume & Xuning Wang & Jennifer C. Darnell & Robert B. Darn, 2008. "HITS-CLIP yields genome-wide insights into brain alternative RNA processing," Nature, Nature, vol. 456(7221), pages 464-469, November.
    4. Clare Pacini & Joshua M. Dempster & Isabella Boyle & Emanuel Gonçalves & Hanna Najgebauer & Emre Karakoc & Dieudonne Meer & Andrew Barthorpe & Howard Lightfoot & Patricia Jaaks & James M. McFarland & , 2021. "Integrated cross-study datasets of genetic dependencies in cancer," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    5. Sarah Djebali & Carrie A. Davis & Angelika Merkel & Alex Dobin & Timo Lassmann & Ali Mortazavi & Andrea Tanzer & Julien Lagarde & Wei Lin & Felix Schlesinger & Chenghai Xue & Georgi K. Marinov & Jaina, 2012. "Landscape of transcription in human cells," Nature, Nature, vol. 489(7414), pages 101-108, September.
    6. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    7. Mahmoud Ghandi & Franklin W. Huang & Judit Jané-Valbuena & Gregory V. Kryukov & Christopher C. Lo & E. Robert McDonald & Jordi Barretina & Ellen T. Gelfand & Craig M. Bielski & Haoxin Li & Kevin Hu & , 2019. "Next-generation characterization of the Cancer Cell Line Encyclopedia," Nature, Nature, vol. 569(7757), pages 503-508, May.
    8. Alison D. Tang & Cameron M. Soulette & Marijke J. van Baren & Kevyn Hart & Eva Hrabeta-Robinson & Catherine J. Wu & Angela N. Brooks, 2020. "Full-length transcript characterization of SF3B1 mutation in chronic lymphocytic leukemia reveals downregulation of retained introns," Nature Communications, Nature, vol. 11(1), pages 1-12, 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. Humberto J. Ferreira & Brian J. Stevenson & HuiSong Pak & Fengchao Yu & Jessica Almeida Oliveira & Florian Huber & Marie Taillandier-Coindard & Justine Michaux & Emma Ricart-Altimiras & Anne I. Kraeme, 2024. "Immunopeptidomics-based identification of naturally presented non-canonical circRNA-derived peptides," Nature Communications, Nature, vol. 15(1), pages 1-18, 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. Feng Wang & Yang Xu & Robert Wang & Beatrice Zhang & Noah Smith & Amber Notaro & Samantha Gaerlan & Eric Kutschera & Kathryn E. Kadash-Edmondson & Yi Xing & Lan Lin, 2023. "TEQUILA-seq: a versatile and low-cost method for targeted long-read RNA sequencing," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Elizabeth A. Werren & Geneva R. LaForce & Anshika Srivastava & Delia R. Perillo & Shaokun Li & Katherine Johnson & Safa Baris & Brandon Berger & Samantha L. Regan & Christian D. Pfennig & Sonja Munnik, 2024. "TREX tetramer disruption alters RNA processing necessary for corticogenesis in THOC6 Intellectual Disability Syndrome," Nature Communications, Nature, vol. 15(1), pages 1-21, December.
    3. Areum Han & Peter Stoilov & Anthony J Linares & Yu Zhou & Xiang-Dong Fu & Douglas L Black, 2014. "De Novo Prediction of PTBP1 Binding and Splicing Targets Reveals Unexpected Features of Its RNA Recognition and Function," PLOS Computational Biology, Public Library of Science, vol. 10(1), pages 1-18, January.
    4. Xiangbin Ruan & Kaining Hu & Xiaochang Zhang, 2023. "PIE-seq: identifying RNA-binding protein targets by dual RNA-deaminase editing and sequencing," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    5. Haoran Zhu & Yuning Yang & Yunhe Wang & Fuzhou Wang & Yujian Huang & Yi Chang & Ka-chun Wong & Xiangtao Li, 2023. "Dynamic characterization and interpretation for protein-RNA interactions across diverse cellular conditions using HDRNet," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    6. Xiao Chen & Yinglu Li & Fang Zhu & Xinjing Xu & Brian Estrella & Manuel A. Pazos & John T. McGuire & Dimitris Karagiannis & Varun Sahu & Mustafo Mustafokulov & Claudio Scuoppo & Francisco J. Sánchez-R, 2023. "Context-defined cancer co-dependency mapping identifies a functional interplay between PRC2 and MLL-MEN1 complex in lymphoma," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    7. Arashdeep Singh & Arati Rajeevan & Vishaka Gopalan & Piyush Agrawal & Chi-Ping Day & Sridhar Hannenhalli, 2022. "Broad misappropriation of developmental splicing profile by cancer in multiple organs," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    8. Ruitong Li & Olaf Klingbeil & Davide Monducci & Michael J. Young & Diego J. Rodriguez & Zaid Bayyat & Joshua M. Dempster & Devishi Kesar & Xiaoping Yang & Mahdi Zamanighomi & Christopher R. Vakoc & Ta, 2022. "Comparative optimization of combinatorial CRISPR screens," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    9. Michelle M. Kameda-Smith & Helen Zhu & En-Ching Luo & Yujin Suk & Agata Xella & Brian Yee & Chirayu Chokshi & Sansi Xing & Frederick Tan & Raymond G. Fox & Ashley A. Adile & David Bakhshinyan & Kevin , 2022. "Characterization of an RNA binding protein interactome reveals a context-specific post-transcriptional landscape of MYC-amplified medulloblastoma," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    10. Zhiping Zhang & Bongmin Bae & Winston H. Cuddleston & Pedro Miura, 2023. "Coordination of alternative splicing and alternative polyadenylation revealed by targeted long read sequencing," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    11. Tutz, Gerhard & Pößnecker, Wolfgang & Uhlmann, Lorenz, 2015. "Variable selection in general multinomial logit models," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 207-222.
    12. Ernesto Carrella & Richard M. Bailey & Jens Koed Madsen, 2018. "Indirect inference through prediction," Papers 1807.01579, arXiv.org.
    13. Rui Wang & Naihua Xiu & Kim-Chuan Toh, 2021. "Subspace quadratic regularization method for group sparse multinomial logistic regression," Computational Optimization and Applications, Springer, vol. 79(3), pages 531-559, July.
    14. Mkhadri, Abdallah & Ouhourane, Mohamed, 2013. "An extended variable inclusion and shrinkage algorithm for correlated variables," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 631-644.
    15. Masakazu Higuchi & Mitsuteru Nakamura & Shuji Shinohara & Yasuhiro Omiya & Takeshi Takano & Daisuke Mizuguchi & Noriaki Sonota & Hiroyuki Toda & Taku Saito & Mirai So & Eiji Takayama & Hiroo Terashi &, 2022. "Detection of Major Depressive Disorder Based on a Combination of Voice Features: An Exploratory Approach," IJERPH, MDPI, vol. 19(18), pages 1-13, September.
    16. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
    17. Gustavo Glusman & Juan Caballero & Max Robinson & Burak Kutlu & Leroy Hood, 2013. "Optimal Scaling of Digital Transcriptomes," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-12, November.
    18. Vincent, Martin & Hansen, Niels Richard, 2014. "Sparse group lasso and high dimensional multinomial classification," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 771-786.
    19. Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
    20. Perrot-Dockès Marie & Lévy-Leduc Céline & Chiquet Julien & Sansonnet Laure & Brégère Margaux & Étienne Marie-Pierre & Robin Stéphane & Genta-Jouve Grégory, 2018. "A variable selection approach in the multivariate linear model: an application to LC-MS metabolomics data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 17(5), pages 1-14, October.

    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_s41467-022-34568-z. 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.