IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-47957-3.html
   My bibliography  Save this article

Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis

Author

Listed:
  • George Rosenberger

    (Columbia University Irving Medical Center)

  • Wenxue Li

    (Yale University)

  • Mikko Turunen

    (Columbia University Irving Medical Center)

  • Jing He

    (Columbia University Irving Medical Center
    Regeneron Genetics Center)

  • Prem S. Subramaniam

    (Columbia University Irving Medical Center)

  • Sergey Pampou

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

  • Aaron T. Griffin

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

  • Charles Karan

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

  • Patrick Kerwin

    (Columbia University Irving Medical Center)

  • Diana Murray

    (Columbia University Irving Medical Center)

  • Barry Honig

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

  • Yansheng Liu

    (Yale University
    Yale University School of Medicine)

  • Andrea Califano

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

Abstract

Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. Leveraging progress in proteomic technologies and network-based methodologies, we introduce Virtual Enrichment-based Signaling Protein-activity Analysis (VESPA)—an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations—and use it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogating tumor-specific enzyme/substrate interactions accurately infers kinase and phosphatase activity, based on their substrate phosphorylation state, effectively accounting for signal crosstalk and sparse phosphoproteome coverage. The analysis elucidates time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring, experimentally confirmed by CRISPR knock-out assays, suggesting broad applicability to cancer and other diseases.

Suggested Citation

  • George Rosenberger & Wenxue Li & Mikko Turunen & Jing He & Prem S. Subramaniam & Sergey Pampou & Aaron T. Griffin & Charles Karan & Patrick Kerwin & Diana Murray & Barry Honig & Yansheng Liu & Andrea , 2024. "Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis," Nature Communications, Nature, vol. 15(1), pages 1-27, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47957-3
    DOI: 10.1038/s41467-024-47957-3
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-47957-3
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-024-47957-3?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. Hongxu Ding & Eugene F. Douglass & Adam M. Sonabend & Angeliki Mela & Sayantan Bose & Christian Gonzalez & Peter D. Canoll & Peter A. Sims & Mariano J. Alvarez & Andrea Califano, 2018. "Quantitative assessment of protein activity in orphan tissues and single cells using the metaVIPER algorithm," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    3. Alejo Efeyan & William C. Comb & David M. Sabatini, 2015. "Nutrient-sensing mechanisms and pathways," Nature, Nature, vol. 517(7534), pages 302-310, January.
    4. 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.
    5. 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.
    6. 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.
    7. Sam Crowl & Ben T. Jordan & Hamza Ahmed & Cynthia X. Ma & Kristen M. Naegle, 2022. "KSTAR: An algorithm to predict patient-specific kinase activities from phosphoproteomic data," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    8. Kendall R. Sanson & Ruth E. Hanna & Mudra Hegde & Katherine F. Donovan & Christine Strand & Meagan E. Sullender & Emma W. Vaimberg & Amy Goodale & David E. Root & Federica Piccioni & John G. Doench, 2018. "Optimized libraries for CRISPR-Cas9 genetic screens with multiple modalities," Nature Communications, Nature, vol. 9(1), pages 1-15, 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. 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.
    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. Hyeong-Min Lee & William C. Wright & Min Pan & Jonathan Low & Duane Currier & Jie Fang & Shivendra Singh & Stephanie Nance & Ian Delahunty & Yuna Kim & Richard H. Chapple & Yinwen Zhang & Xueying Liu , 2023. "A CRISPR-drug perturbational map for identifying compounds to combine with commonly used chemotherapeutics," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    4. 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.
    5. Katelyn L. Mortenson & Courtney Dawes & Emily R. Wilson & Nathan E. Patchen & Hailey E. Johnson & Jason Gertz & Swneke D. Bailey & Yang Liu & Katherine E. Varley & Xiaoyang Zhang, 2024. "3D genomic analysis reveals novel enhancer-hijacking caused by complex structural alterations that drive oncogene overexpression," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    6. Min Wu & Tingting Wang & Nan Ji & Ting Lu & Ran Yuan & Lingxiang Wu & Junxia Zhang & Mengyuan Li & Penghui Cao & Jiarui Zhao & Guanzhang Li & Jianyu Li & Yu Li & Yujie Tang & Zhengliang Gao & Xiuxing , 2024. "Multi-omics and pharmacological characterization of patient-derived glioma cell lines," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    7. 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.
    8. Kelsy C. Cotto & Yang-Yang Feng & Avinash Ramu & Megan Richters & Sharon L. Freshour & Zachary L. Skidmore & Huiming Xia & Joshua F. McMichael & Jason Kunisaki & Katie M. Campbell & Timothy Hung-Po Ch, 2023. "Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    9. Noha A. M. Shendy & Melissa Bikowitz & Logan H. Sigua & Yang Zhang & Audrey Mercier & Yousef Khashana & Stephanie Nance & Qi Liu & Ian M. Delahunty & Sarah Robinson & Vanshita Goel & Matthew G. Rees &, 2024. "Group 3 medulloblastoma transcriptional networks collapse under domain specific EP300/CBP inhibition," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    10. Han Jin & Cheng Zhang & Martin Zwahlen & Kalle Feilitzen & Max Karlsson & Mengnan Shi & Meng Yuan & Xiya Song & Xiangyu Li & Hong Yang & Hasan Turkez & Linn Fagerberg & Mathias Uhlén & Adil Mardinoglu, 2023. "Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    11. Sean A. Misek & Aaron Fultineer & Jeremie Kalfon & Javad Noorbakhsh & Isabella Boyle & Priyanka Roy & Joshua Dempster & Lia Petronio & Katherine Huang & Alham Saadat & Thomas Green & Adam Brown & John, 2024. "Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.

    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_s41467-024-47957-3. 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.