Discover oncology · 2026
Spatially resolved single cell analysis suggests an APOE NCF1 associated immunosuppressive niche and its prognostic signature in thyroid cancer.
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Su Han, Zhang Zheng, Li Nuo, Zhang Zimo, Zhang Renju, Li Ziyi, Chen Fen, Wang Xinyue, Zhang Shuyuan, Zhang Chao
Аннотация
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.
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.