IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-30449-7.html
   My bibliography  Save this article

An integral genomic signature approach for tailored cancer therapy using genome-wide sequencing data

Author

Listed:
  • Xiao-Song Wang

    (University of Pittsburgh
    University of Pittsburgh)

  • Sanghoon Lee

    (University of Pittsburgh
    University of Pittsburgh)

  • Han Zhang

    (University of Pittsburgh
    University of Pittsburgh)

  • Gong Tang

    (University of Pittsburgh)

  • Yue Wang

    (University of Pittsburgh
    University of Pittsburgh)

Abstract

Low-cost multi-omics sequencing is expected to become clinical routine and transform precision oncology. Viable computational methods that can facilitate tailored intervention while tolerating sequencing biases are in high demand. Here we propose a class of transparent and interpretable computational methods called integral genomic signature (iGenSig) analyses, that address the challenges of cross-dataset modeling through leveraging information redundancies within high-dimensional genomic features, averaging feature weights to prevent overweighing, and extracting unbiased genomic information from large tumor cohorts. Using genomic dataset of chemical perturbations, we develop a battery of iGenSig models for predicting cancer drug responses, and validate the models using independent cell-line and clinical datasets. The iGenSig models for five drugs demonstrate predictive values in six clinical studies, among which the Erlotinib and 5-FU models significantly predict therapeutic responses in three studies, offering clinically relevant insights into their inverse predictive signature pathways. Together, iGenSig provides a computational framework to facilitate tailored cancer therapy based on multi-omics data.

Suggested Citation

  • Xiao-Song Wang & Sanghoon Lee & Han Zhang & Gong Tang & Yue Wang, 2022. "An integral genomic signature approach for tailored cancer therapy using genome-wide sequencing data," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-30449-7
    DOI: 10.1038/s41467-022-30449-7
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-30449-7
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-30449-7?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. Jordi Barretina & Giordano Caponigro & Nicolas Stransky & Kavitha Venkatesan & Adam A. Margolin & Sungjoon Kim & Christopher J.Wilson & Joseph Lehár & Gregory V. Kryukov & Dmitriy Sonkin & Anupama Red, 2012. "Addendum: The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity," Nature, Nature, vol. 492(7428), pages 290-290, December.
    2. 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).
    3. Jordi Barretina & Giordano Caponigro & Nicolas Stransky & Kavitha Venkatesan & Adam A. Margolin & Sungjoon Kim & Christopher J. Wilson & Joseph Lehár & Gregory V. Kryukov & Dmitriy Sonkin & Anupama Re, 2012. "The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity," Nature, Nature, vol. 483(7391), pages 603-607, March.
    4. Hothorn, Torsten & Lausen, Berthold, 2003. "On the exact distribution of maximally selected rank statistics," Computational Statistics & Data Analysis, Elsevier, vol. 43(2), pages 121-137, June.
    5. Benjamin Haibe-Kains & Nehme El-Hachem & Nicolai Juul Birkbak & Andrew C. Jin & Andrew H. Beck & Hugo J. W. L. Aerts & John Quackenbush, 2013. "Inconsistency in large pharmacogenomic studies," Nature, Nature, vol. 504(7480), pages 389-393, December.
    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. Smriti Chawla & Anja Rockstroh & Melanie Lehman & Ellca Ratther & Atishay Jain & Anuneet Anand & Apoorva Gupta & Namrata Bhattacharya & Sarita Poonia & Priyadarshini Rai & Nirjhar Das & Angshul Majumd, 2022. "Gene expression based inference of cancer drug sensitivity," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    2. Adrià Fernández-Torras & Miquel Duran-Frigola & Martino Bertoni & Martina Locatelli & Patrick Aloy, 2022. "Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    3. Jurica Levatić & Marina Salvadores & Francisco Fuster-Tormo & Fran Supek, 2022. "Mutational signatures are markers of drug sensitivity of cancer cells," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    4. Caitlin E. Mills & Kartik Subramanian & Marc Hafner & Mario Niepel & Luca Gerosa & Mirra Chung & Chiara Victor & Benjamin Gaudio & Clarence Yapp & Ajit J. Nirmal & Nicholas Clark & Peter K. Sorger, 2022. "Multiplexed and reproducible high content screening of live and fixed cells using Dye Drop," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    5. Junyi Chen & Xiaoying Wang & Anjun Ma & Qi-En Wang & Bingqiang Liu & Lang Li & Dong Xu & Qin Ma, 2022. "Deep transfer learning of cancer drug responses by integrating bulk and single-cell RNA-seq data," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    6. Omar Alhalabi & Jianfeng Chen & Yuxue Zhang & Yang Lu & Qi Wang & Sumankalai Ramachandran & Rebecca Slack Tidwell & Guangchun Han & Xinmiao Yan & Jieru Meng & Ruiping Wang & Anh G. Hoang & Wei-Lien Wa, 2022. "MTAP deficiency creates an exploitable target for antifolate therapy in 9p21-loss cancers," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    7. Yan Li & Chen Xu & Bing Wang & Fujiang Xu & Fahan Ma & Yuanyuan Qu & Dongxian Jiang & Kai Li & Jinwen Feng & Sha Tian & Xiaohui Wu & Yunzhi Wang & Yang Liu & Zhaoyu Qin & Yalan Liu & Jing Qin & Qi Son, 2022. "Proteomic characterization of gastric cancer response to chemotherapy and targeted therapy reveals potential therapeutic strategies," Nature Communications, Nature, vol. 13(1), pages 1-26, December.
    8. Aina Maria Mas & Enrique Goñi & Igor Ruiz de los Mozos & Aida Arcas & Luisa Statello & Jovanna González & Lorea Blázquez & Wei Ting Chelsea Lee & Dipika Gupta & Álvaro Sejas & Shoko Hoshina & Alexandr, 2023. "ORC1 binds to cis-transcribed RNAs for efficient activation of replication origins," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    9. Nicolae Sapoval & Amirali Aghazadeh & Michael G. Nute & Dinler A. Antunes & Advait Balaji & Richard Baraniuk & C. J. Barberan & Ruth Dannenfelser & Chen Dun & Mohammadamin Edrisi & R. A. Leo Elworth &, 2022. "Current progress and open challenges for applying deep learning across the biosciences," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    10. G. Gambardella & G. Viscido & B. Tumaini & A. Isacchi & R. Bosotti & D. di Bernardo, 2022. "A single-cell analysis of breast cancer cell lines to study tumour heterogeneity and drug response," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    11. Seungyeul Yoo & Abhilasha Sinha & Dawei Yang & Nasser K. Altorki & Radhika Tandon & Wenhui Wang & Deebly Chavez & Eunjee Lee & Ayushi S. Patel & Takashi Sato & Ranran Kong & Bisen Ding & Eric E. Schad, 2022. "Integrative network analysis of early-stage lung adenocarcinoma identifies aurora kinase inhibition as interceptor of invasion and progression," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    12. Shi, Chengchun & Xu, Tianlin & Bergsma, Wicher & Li, Lexin, 2021. "Double generative adversarial networks for conditional independence testing," LSE Research Online Documents on Economics 112550, London School of Economics and Political Science, LSE Library.
    13. Alon Stern & Mariam Fokra & Boris Sarvin & Ahmad Abed Alrahem & Won Dong Lee & Elina Aizenshtein & Nikita Sarvin & Tomer Shlomi, 2023. "Inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    14. Sandor Spisak & David Chen & Pornlada Likasitwatanakul & Paul Doan & Zhixin Li & Pratyusha Bala & Laura Vizkeleti & Viktoria Tisza & Pushpamali Silva & Marios Giannakis & Brian Wolpin & Jun Qi & Nilay, 2024. "Identifying regulators of aberrant stem cell and differentiation activity in colorectal cancer using a dual endogenous reporter system," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    15. Mariela Cortés-López & Laura Schulz & Mihaela Enculescu & Claudia Paret & Bea Spiekermann & Mathieu Quesnel-Vallières & Manuel Torres-Diz & Sebastian Unic & Anke Busch & Anna Orekhova & Monika Kuban &, 2022. "High-throughput mutagenesis identifies mutations and RNA-binding proteins controlling CD19 splicing and CART-19 therapy resistance," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    16. Qiwei Jiang & Xiaomei Zhang & Xiaoming Dai & Shiyao Han & Xueji Wu & Lei Wang & Wenyi Wei & Ning Zhang & Wei Xie & Jianping Guo, 2022. "S6K1-mediated phosphorylation of PDK1 impairs AKT kinase activity and oncogenic functions," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    17. Yanli Liu & Zhong Wu & Jin Zhou & Dinesh K. A. Ramadurai & Katelyn L. Mortenson & Estrella Aguilera-Jimenez & Yifei Yan & Xiaojun Yang & Alison M. Taylor & Katherine E. Varley & Jason Gertz & Peter S., 2021. "A predominant enhancer co-amplified with the SOX2 oncogene is necessary and sufficient for its expression in squamous cancer," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    18. Sayantani Ghosh Dastidar & Bony Kumar & Bo Lauckner & Damien Parrello & Danielle Perley & Maria Vlasenok & Antariksh Tyagi & Nii Koney-Kwaku Koney & Ata Abbas & Sergei Nechaev, 2023. "Transcriptional responses of cancer cells to heat shock-inducing stimuli involve amplification of robust HSF1 binding," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    19. Sumana Srivatsa & Hesam Montazeri & Gaia Bianco & Mairene Coto-Llerena & Mattia Marinucci & Charlotte K. Y. Ng & Salvatore Piscuoglio & Niko Beerenwinkel, 2022. "Discovery of synthetic lethal interactions from large-scale pan-cancer perturbation screens," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    20. Cemal Erdem & Sean M. Gross & Laura M. Heiser & Marc R. Birtwistle, 2023. "MOBILE pipeline enables identification of context-specific networks and regulatory mechanisms," Nature Communications, Nature, vol. 14(1), pages 1-16, December.

    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_s41467-022-30449-7. 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.