Heliyon (Sep 2024)

Prognostic significance of immune-cell distribution and tumoral spread through air spaces – Multiplex spatial immunophenotyping analysis–

  • Shunichiro Matsuoka,
  • Takashi Eguchi,
  • Mai Iwaya,
  • Maho Seshimoto,
  • Shuji Mishima,
  • Daisuke Hara,
  • Hirotaka Kumeda,
  • Kentaro Miura,
  • Kazutoshi Hamanaka,
  • Takeshi Uehara,
  • Kimihiro Shimizu

Journal volume & issue
Vol. 10, no. 17
p. e37412

Abstract

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Objectives: Spread through air spaces (STAS) is a form of lung cancer invasion that extends beyond the tumor edge and is associated with a worse prognosis. Recent advances in immunotherapy highlight the importance of understanding the tumor microenvironment. This study aimed to investigate the prognostic significance of immune-cell distribution in lung cancer, focusing on the association with STAS. Materials and methods: We retrospectively analyzed 283 patients who underwent curative-intent lung resection for primary lung cancer. Multiplex immunofluorescence staining/phenotyping was performed on tissue microarrays to assess the distribution of CD4, CD8, CD20, CD68, and FoxP3 immune cells within the center and tumor edge. We defined the delta-Edge value (Δ) as the difference in the number of immune cells between the tumor edge and center. Recurrence-free probability (RFP) was analyzed using Kaplan–Meier and Cox proportional hazard models. Results: High ΔCD4 and ΔCD8 values were significantly associated with worse RFP. In stage I adenocarcinoma patients, STAS, and high ΔCD8 were independent risk factors for recurrence. Effect modification analysis revealed that high ΔFoxP3 was significantly associated with worse RFP in patients with STAS, but not in those without STAS. Patients with STAS and high Δimmune cell values had the lowest RFP among all groups. Conclusion: Immune-cell distribution, particularly CD4, CD8, and FoxP3, is a crucial prognostic factor in lung cancer. STAS and specific immune cell distribution patterns can be used to further stratify patient prognosis. Understanding these interactions may provide insights into potential therapeutic targets for personalized lung cancer treatment.

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