Leveraging advances in immunopathology and artificial intelligence to analyze in vitro tumor models in composition and space.

Journal: Advanced drug delivery reviews
Published Date:

Abstract

Cancer is the leading cause of death worldwide. Unfortunately, efforts to understand this disease are confounded by the complex, heterogenous tumor microenvironment (TME). Better understanding of the TME could lead to novel diagnostic, prognostic, and therapeutic discoveries. One way to achieve this involves in vitro tumor models that recapitulate the in vivo TME composition and spatial arrangement. Here, we review the potential of harnessing in vitro tumor models and artificial intelligence to delineate the TME. This includes (i) identification of novel features, (ii) investigation of higher-order relationships, and (iii) analysis and interpretation of multiomics data in a (iv) holistic, objective, reproducible, and efficient manner, which surpasses previous methods of TME analysis. We also discuss limitations of this approach, namely inadequate datasets, indeterminate biological correlations, ethical concerns, and logistical constraints; finally, we speculate on future avenues of research that could overcome these limitations, ultimately translating to improved clinical outcomes.

Authors

  • Tze Ker Matthew Leong
    Lee Kong Chian School of Medicine, Nanyang Technological University, Headquarters & Clinical Sciences Building, 11 Mandalay Road, Singapore 308232, Singapore.
  • Wen Shern Lo
    Lee Kong Chian School of Medicine, Nanyang Technological University, Headquarters & Clinical Sciences Building, 11 Mandalay Road, Singapore 308232, Singapore.
  • Wei En Zen Lee
    Lee Kong Chian School of Medicine, Nanyang Technological University, Headquarters & Clinical Sciences Building, 11 Mandalay Road, Singapore 308232, Singapore.
  • Benedict Tan
    Institute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR), 61 Biopolis Drive, Proteos, Singapore 138673, Singapore.
  • Xing Zhao Lee
    Arrive PTE LTD, 1 Maritime Square, Singapore 099253, Singapore.
  • Li Wen Justina Nadia Lee
    Institute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR), 61 Biopolis Drive, Proteos, Singapore 138673, Singapore.
  • Jia-Ying Joey Lee
    Bioinformatics Institute, Agency for Science, Technology, and Research, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore.
  • Nivedita Suresh
    Arrive PTE LTD, 1 Maritime Square, Singapore 099253, Singapore.
  • Lit-Hsin Loo
    Bioinformatics Institute, Agency for Science, Technology, and Research, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore. loolh@bii.a-star.edu.sg.
  • Evan Szu
    Arrive PTE LTD, 1 Maritime Square, Singapore 099253, Singapore.
  • Joe Yeong
    Institute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR), 61 Biopolis Drive, Proteos, Singapore 138673, Singapore; Department of Anatomical Pathology, Singapore General Hospital, 20 College Road, Academia, Level 10 Diagnostic Tower, Singapore 169856, Singapore. Electronic address: yeongps@imcb.a-star.edu.sg.