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<p>The tumor immune microenvironment (TiME) of human central nervous system (CNS) tumors remains to be comprehensively deciphered. Here, we employed flow cytometry and RNA sequencing analysis for a deep data-driven dissection of a diverse TiME and to uncover noncanonical immune cell types in human CNS tumors by using seven tumors from five patients. Myeloid subsets comprised classical microglia, monocyte-derived macrophages, neutrophils, and two noncanonical myeloid subsets: CD3<sup>+</sup> myeloids and CD19<sup>+</sup> myeloids. T lymphocyte subsets included double-negative (CD4<sup>−</sup> CD8<sup>−</sup>) T cells (DNTs). Noncanonical myeloids and DNTs were explored on independent datasets, suggesting that our DNT phenotype represents <i>γδ</i> T cells. Noncanonical myeloids were validated using orthogonal methods across 73 patients from three independent datasets. While the proportions of classical myeloids agreed with reported malignancy type-associated TiMEs, unexpectedly high lymphocyte frequencies were detected in gliosarcoma, which also showed a unique expression pattern of immune-related genes. Our findings highlight the potential of data-driven approaches in resolving CNS TiME to reveal the mosaic of immune cell types constituting TiME, warranting the need for future studies on the nonclassical immune cell subsets.</p>

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Unsupervised clustering reveals noncanonical myeloid cell subsets in the brain tumor microenvironment

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月3日

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  • Ismaïl Hermelo,
  • Tuomo Virtanen,
  • Iida Salonen,
  • Reetta Nätkin,
  • Sofia Keitaanniemi,
  • Aliisa M. Tiihonen,
  • Suvi Lehtipuro,
  • Laura Kummola,
  • Ella Raulamo,
  • Kristiina Nordfors,
  • Hannu Haapasalo,
  • Minna Rauhala,
  • Juha Kesseli,
  • Matti Nykter,
  • Joonas Haapasalo,
  • Kirsi Rautajoki

摘要

The tumor immune microenvironment (TiME) of human central nervous system (CNS) tumors remains to be comprehensively deciphered. Here, we employed flow cytometry and RNA sequencing analysis for a deep data-driven dissection of a diverse TiME and to uncover noncanonical immune cell types in human CNS tumors by using seven tumors from five patients. Myeloid subsets comprised classical microglia, monocyte-derived macrophages, neutrophils, and two noncanonical myeloid subsets: CD3+ myeloids and CD19+ myeloids. T lymphocyte subsets included double-negative (CD4− CD8−) T cells (DNTs). Noncanonical myeloids and DNTs were explored on independent datasets, suggesting that our DNT phenotype represents γδ T cells. Noncanonical myeloids were validated using orthogonal methods across 73 patients from three independent datasets. While the proportions of classical myeloids agreed with reported malignancy type-associated TiMEs, unexpectedly high lymphocyte frequencies were detected in gliosarcoma, which also showed a unique expression pattern of immune-related genes. Our findings highlight the potential of data-driven approaches in resolving CNS TiME to reveal the mosaic of immune cell types constituting TiME, warranting the need for future studies on the nonclassical immune cell subsets.