Spatially resolved single cell analysis suggests an APOE NCF1 associated immunosuppressive niche and its prognostic signature in thyroid cancer
BACKGROUND: Thyroid carcinoma (TC) presents a rising global incidence, with a subset of cases progressing aggressively despite standard therapies. The tumor microenvironment (TME), particularly the functional state of CD8⁺ T cells, is crucial in disease progression, yet a systematic, high-resolution understanding of the cellular interactions associated with immune exhaustion and tumor evolution in TC remains limited. METHODS: To address this, we performed an integrated single-cell and spatial transcriptomic analysis of human TC samples. Our approach combined scRNA-seq data processing, cell communication inference, spatial co-localization validation, and machine learning-based prognostic modeling. RESULT: We identified a distinct tumor cell subcluster (Trem/T01) characterized by APOE expression and a CD8⁺ exhausted T cell (Tex) subset. Computational and spatial analyses revealed a potential APOE (from Trem)-NCF1 (from CD8⁺ Tex) interaction axis, with these cell types demonstrating significant spatial proximity in tumor tissues. Furthermore, we derived a prognostic gene signature from this network, constructing a robust risk stratification model validated across independent cohorts. CONCLUSION: This study uniquely delineates a specific tumor-immune interactive niche in TC, providing insights into potential mechanisms into immune evasion via the APOE-NCF1 axis and delivering a translatable framework for patient prognostication.
Authors
- Zimo Zhang
- Ziyi Li
- Renju Zhang
- Shuyuan Zhang
- Chao Zhang
- Han Su
- Fen Chen
- LI Nuo
- Zheng Zhang
- Xinyue Wang
Institutions
- Anhui Medical University (CN)
- First Affiliated Hospital of Anhui Medical University (CN)
- Second Affiliated Hospital of Anhui Medical University (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2026-05-30
- DOI
- https://doi.org/10.1007/s12672-026-05061-6
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00