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

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, Lingzhi Hong, Xin Hu, Simon Heeke, Hai T. Tran, Xiuning Le, Yasir Y. Elamin, Mehmet Altan, Natalie I. Vokes, Ajay Sheshadri, Julie Lin, Jianhua Zhang, Yang Lu, Carmen Behrens, Myrna C. B. Godoy, Carol C. Wu, Joe Y. Chang, Caroline Chung, David A. Jaffray, Ignacio I. Wistuba, J. Jack Lee, Ara A. Vaporciyan, Don L. Gibbons, John Heymach, Jianjun Zhang, Tina Cascone and Jia Wu ()
Additional contact information
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
Mohamed Qayati: The University of Texas MD Anderson Cancer Center
James M. George: The University of Texas MD Anderson Cancer Center
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
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
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
David A. Jaffray: 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
Tina Cascone: The University of Texas MD Anderson Cancer Center
Jia Wu: The University of Texas MD Anderson Cancer Center

Nature Communications, 2024, vol. 15, issue 1, 1-14

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41467-024-47512-0

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