Single-cell profiling defines cellular ecosystems and malignant cell state coupling across pan-cancer tumor microenvironments
Year: 2026
Type: article
Abstract: Tumors are embedded within complex microenvironments composed of malignant, immune and stromal cells, yet how coordinated cellular organization shapes tumor biology across cancers remains incompletely understood. Here we integrate single-cell transcriptomic profiles from over two million cells spanning 19 human epithelial cancers to construct a comprehensive pan-cancer atlas of tumor microenvironment (TME) organization. We identify cell subsets selectively enriched in tumors compared with normal tissues and show that their relative abundance is associated with clinical outcomes. By clustering tumors according to their cellular composition, we define eight recurrent cellular ecosystem subtypes that capture coordinated variation in immune and stromal architectures across cancer types. Comparative analyses reveal that these ecosystem states are associated with distinct tumor-intrinsic molecular programs, including differences in signaling pathway activity, transcriptional regulation and copy number alterations. We further uncover subtype-specific patterns of ligand–receptor interactions linking malignant cells with immune and stromal compartments and provide independent spatial support for these interactions using spatial transcriptomic data. Together, this work provides a unified framework for tumor ecosystem stratification and highlights cellular organization as a key dimension of tumor heterogeneity with potential implications for precision cancer therapy.
Source: Molecular Cancer
Institutions: Second Hospital of Tianjin Medical University, State Key Laboratory of Experimental Hematology, Tianjin Medical University, Chinese Academy of Medical Sciences & Peking Union Medical College, Institute of Hematology & Blood Diseases Hospital, State Key Laboratory of Digital Medical Engineering, Southeast University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $5,090
Awards: G2805102501, G6245397410
OpenAlex ID: W7170929993
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