4.7 Article

Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome

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NPJ PRECISION ONCOLOGY
卷 6, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41698-022-00277-5

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  1. National Cancer Institute [1U24CA199374-01, R01CA202752-01A1, R01CA208236-01A1, R01 CA216579-01A1, R01 CA220581-01A1, 1U01 CA239055-01, 1U01CA248226-01, 1U54CA254566-01, R03CA219603, R37CA245154, P50CA196530]
  2. National Heart, Lung and Blood Institute [1R01HL15127701A1]
  3. National Institute for Biomedical Imaging and Bioengineering [1R43EB028736-01]
  4. National Center for Research Resources [1 C06 RR12463-01]
  5. VA Merit Review Award from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service [IBX004121A]
  6. Office of the Assistant Secretary of Defense for Health Affairs, through the Breast Cancer Research Program [W81XWH-19-1-0668]
  7. Office of the Assistant Secretary of Defense for Health Affairs, through Prostate Cancer Research Program [W81XWH-15-1-0558, W81XWH-20-1-0851]
  8. Office of the Assistant Secretary of Defense for Health Affairs, through Lung Cancer Research Program [W81XWH-18-1-0440, W81XWH-20-1-0595, W81XWH16-1-0160]
  9. Office of the Assistant Secretary of Defense for Health Affairs, through Peer Reviewed Cancer Research Program [W81XWH-18-1-0404]
  10. Kidney Precision Medicine Project (KPMP) Glue Grant
  11. Ohio Third Frontier Technology Validation Fund
  12. National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health [UL1TR0002548]
  13. Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering at Case Western Reserve University
  14. Stand Up To Cancer -American Cancer Society Lung Cancer Dream Team Translational Research Grants [SU2C-AACR-DT1715, SU2C-AACR-DT22-17]
  15. National Science Foundation [CON501692]
  16. Cancer Research Switzerland [MD-PhD-508806-2020]
  17. NIH roadmap for Medical Research

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This study reveals the spatial differences in tumor-infiltrating lymphocytes (TILs) between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). TIL density is prognostic of overall survival in LUAD, while spatial arrangement is more prognostically relevant in LUSC. The TIL signature specific to LUAD is associated with overall survival and response to therapy. In both subtypes, TIL features are associated with immune scores and biological pathways related to immune recognition, response, and evasion.
Despite known histological, biological, and clinical differences between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), relatively little is known about the spatial differences in their corresponding immune contextures. Our study of over 1000 LUAD and LUSC tumors revealed that computationally derived patterns of tumor-infiltrating lymphocytes (TILs) on H&E images were different between LUAD (N = 421) and LUSC (N = 438), with TIL density being prognostic of overall survival in LUAD and spatial arrangement being more prognostically relevant in LUSC. In addition, the LUAD-specific TIL signature was associated with OS in an external validation set of 100 NSCLC treated with more than six different neoadjuvant chemotherapy regimens, and predictive of response to therapy in the clinical trial CA209-057 (n = 303). In LUAD, the prognostic TIL signature was primarily comprised of CD4(+) T and CD8(+) T cells, whereas in LUSC, the immune patterns were comprised of CD4(+) T, CD8(+) T, and CD20(+) B cells. In both subtypes, prognostic TIL features were associated with transcriptomics-derived immune scores and biological pathways implicated in immune recognition, response, and evasion. Our results suggest the need for histologic subtype-specific TIL-based models for stratifying survival risk and predicting response to therapy. Our findings suggest that predictive models for response to therapy will need to account for the unique morphologic and molecular immune patterns as a function of histologic subtype of NSCLC.

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