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Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights

Author

Listed:
  • Sheeba J. Sujit

    (The University of Texas MD Anderson Cancer Center)

  • Muhammad Aminu

    (The University of Texas MD Anderson Cancer Center)

  • Tatiana V. Karpinets

    (The University of Texas MD Anderson Cancer Center)

  • Pingjun Chen

    (The University of Texas MD Anderson Cancer Center)

  • Maliazurina B. Saad

    (The University of Texas MD Anderson Cancer Center)

  • Morteza Salehjahromi

    (The University of Texas MD Anderson Cancer Center)

  • John D. Boom

    (The University of Texas MD Anderson Cancer Center
    Duke University)

  • Mohamed Qayati

    (The University of Texas MD Anderson Cancer Center)

  • James M. George

    (The University of Texas MD Anderson Cancer Center
    University of Michigan)

  • Haley Allen

    (Rice University)

  • Mara B. Antonoff

    (The University of Texas MD Anderson Cancer Center)

  • Lingzhi Hong

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center)

  • Xin Hu

    (The University of Texas MD Anderson Cancer Center)

  • Simon Heeke

    (The University of Texas MD Anderson Cancer Center)

  • Hai T. Tran

    (The University of Texas MD Anderson Cancer Center)

  • Xiuning Le

    (The University of Texas MD Anderson Cancer Center)

  • Yasir Y. Elamin

    (The University of Texas MD Anderson Cancer Center)

  • Mehmet Altan

    (The University of Texas MD Anderson Cancer Center)

  • Natalie I. Vokes

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center)

  • Ajay Sheshadri

    (The University of Texas MD Anderson Cancer Center)

  • Julie Lin

    (The University of Texas MD Anderson Cancer Center)

  • Jianhua Zhang

    (The University of Texas MD Anderson Cancer Center)

  • Yang Lu

    (The University of Texas MD Anderson Cancer Center)

  • Carmen Behrens

    (The University of Texas MD Anderson Cancer Center)

  • Myrna C. B. Godoy

    (The University of Texas MD Anderson Cancer Center)

  • Carol C. Wu

    (The University of Texas MD Anderson Cancer Center)

  • Joe Y. Chang

    (The University of Texas MD Anderson Cancer Center)

  • Caroline Chung

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center)

  • David A. Jaffray

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center)

  • Ignacio I. Wistuba

    (The University of Texas MD Anderson Cancer Center)

  • J. Jack Lee

    (The University of Texas MD Anderson Cancer Center)

  • Ara A. Vaporciyan

    (The University of Texas MD Anderson Cancer Center)

  • Don L. Gibbons

    (The University of Texas MD Anderson Cancer Center)

  • John Heymach

    (The University of Texas MD Anderson Cancer Center)

  • Jianjun Zhang

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center)

  • Tina Cascone

    (The University of Texas MD Anderson Cancer Center)

  • Jia Wu

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center)

Abstract

While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored. In our multi-institutional study of 394 NSCLC patients, we utilize pre-treatment computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to establish a habitat imaging framework for assessing regional heterogeneity within individual tumors. This framework identifies three PET/CT subtypes, which maintain prognostic value after adjusting for clinicopathologic risk factors including tumor volume. Additionally, these subtypes complement ctDNA in predicting disease recurrence. Radiogenomics analysis unveil the molecular underpinnings of these imaging subtypes, highlighting downregulation in interferon alpha and gamma pathways in the high-risk subtype. In summary, our study demonstrates that these habitat imaging subtypes effectively stratify NSCLC patients based on their risk levels for disease recurrence after initial curative surgery or radiotherapy, providing valuable insights for personalized treatment approaches.

Suggested Citation

  • Sheeba J. Sujit & Muhammad Aminu & Tatiana V. Karpinets & Pingjun Chen & Maliazurina B. Saad & Morteza Salehjahromi & John D. Boom & Mohamed Qayati & James M. George & Haley Allen & Mara B. Antonoff &, 2024. "Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47512-0
    DOI: 10.1038/s41467-024-47512-0
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    References listed on IDEAS

    as
    1. Bin Qiu & Wei Guo & Fan Zhang & Fang Lv & Ying Ji & Yue Peng & Xiaoxi Chen & Hua Bao & Yang Xu & Yang Shao & Fengwei Tan & Qi Xue & Shugeng Gao & Jie He, 2021. "Dynamic recurrence risk and adjuvant chemotherapy benefit prediction by ctDNA in resected NSCLC," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    2. Tina Cascone & Annikka Weissferdt & Myrna C. B. Godoy & William N. William & Cheuk H. Leung & Heather Y. Lin & Sreyashi Basu & Shalini S. Yadav & Apar Pataer & Kyle G. Mitchell & Md Abdul Wadud Khan &, 2021. "Nodal immune flare mimics nodal disease progression following neoadjuvant immune checkpoint inhibitors in non-small cell lung cancer," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    3. Wei Mu & Lei Jiang & JianYuan Zhang & Yu Shi & Jhanelle E. Gray & Ilke Tunali & Chao Gao & Yingying Sun & Jie Tian & Xinming Zhao & Xilin Sun & Robert J. Gillies & Matthew B. Schabath, 2020. "Non-invasive decision support for NSCLC treatment using PET/CT radiomics," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    4. Sergey P. Primakov & Abdalla Ibrahim & Janita E. Timmeren & Guangyao Wu & Simon A. Keek & Manon Beuque & Renée W. Y. Granzier & Elizaveta Lavrova & Madeleine Scrivener & Sebastian Sanduleanu & Esma Ka, 2022. "Automated detection and segmentation of non-small cell lung cancer computed tomography images," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
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