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The Innovation Life > 2025 Vol. 3 > No. 2 > 100123
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Intratumoral heterogeneity: Targeting origin vs. variations and AI-driven non-invasive assessment

  • 1.

    Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China

  • 2.

    Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education; Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology; National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering); School of Engineering Medicine, Beihang University, Beijing, 100191, China

  • 3.

    Department of Respiratory and Clinical Care Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China

  • 4.

    These authors contributed equally

More Information
  • Corresponding author: liuyuanrentao@sjtu.edu.cn
  • Received Date:  January 20, 2025
    Accepted Date:  February 21, 2025
    Published Online:  March 03, 2025
The Innovation Life  3(2),  https://doi.org/10.59717/j.xinn-life.2025.100123  |  Cite this article
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    • REFERENCES
  • [1] Karasaki T., Moore D. A., Veeriah S., et al. (2023). Evolutionary characterization of lung adenocarcinoma morphology in TRACERx. Nat. Med. 29:833−845. DOI:10.1038/s41591-023-02230-w

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    [2] Hobor S., Al Bakir M., Hiley C. T., et al. (2024). Mixed responses to targeted therapy driven by chromosomal instability through p53 dysfunction and genome doubling. Nat. Commun. 15:4871. DOI:10.1038/s41467-024-47606-9

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    [3] Lu W.-T., Zalmas L.-P., Bailey C., et al. (2024). TRACERx analysis identifies a role for FAT1 in regulating chromosomal instability and whole-genome doubling via Hippo signalling. Nat. Cell Biol. DOI:10.1038/s41556-024-01558-w

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    [4] Al-Rawi D. H., Lettera E., Li J., et al. (2024). Targeting chromosomal instability in patients with cancer. Nat. Rev. Clin. Oncol. 21:645−659. DOI:10.1038/s41571-024-00923-w

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    [5] Luo M., Yang W., Bai L., et al. (2024). Artificial intelligence for life sciences: A comprehensive guide and future trends. The Innovation Life 2:100105. DOI:10.59717/j.xinn-life.2024.100105

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  • Cite this article:

    Wu F., Zhang D. and Ren T. (2025). Intratumoral heterogeneity: Targeting origin vs. variations and AI-driven non-invasive assessment. The Innovation Life 3:100123. https://doi.org/10.59717/j.xinn-life.2025.100123
    Wu F., Zhang D. and Ren T. (2025). Intratumoral heterogeneity: Targeting origin vs. variations and AI-driven non-invasive assessment. The Innovation Life 3:100123. https://doi.org/10.59717/j.xinn-life.2025.100123

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