EvoNiche: a comprehensive database for dissecting tumor niche dynamics and spatiotemporal evolution within the cancer ecosystem

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ID: 332871
2026
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Abstract
The tumor ecosystem is organized into diverse ecological niches that undergo continuous regional remodeling and spatiotemporal evolution during tumor progression. Systematically characterizing the regional dynamics of these niches and reconstructing their spatiotemporal trajectories are essential for understanding tumor development, metastasis, and therapeutic response. Here, we present EvoNiche (https://bio-bigdata.hrbmu.edu.cn/EvoNiche or http://evoniche.bio-database.com/), a comprehensive database designed to systematically dissect the regional dynamics and spatiotemporal patterns of the tumor ecosystem by integrating 91 matched spatial and single-cell transcriptomic datasets spanning 35 cancer types. EvoNiche incorporates 712 tissue sections comprising 1 953 708 spatial spots and 58 single-cell datasets containing 2 945 536 cells, identifies 5609 spatial niches, and reconstructs tissue-level and cell-level spatiotemporal trajectories across tumor ecosystems. Through integrated analytical frameworks, EvoNiche enables comprehensive characterization of tumor ecosystem remodeling by resolving spatially organized cellular compositions, region-specific and trajectory-associated molecular programs and biological functions, spatially proximal cell-cell interactions, and spatial pseudotime-associated changes. Furthermore, EvoNiche prioritizes region-specific and transition genes as spatially derived candidate genes through systematic evaluation across pan-cancer and immunotherapy cohorts. Collectively, EvoNiche serves as a valuable resource for investigating regional ecosystem organization and spatiotemporal patterns across human cancers, and elucidating the regulatory mechanisms underlying tumor progression and therapeutic response.
Reference Key
openalex_W7222925697 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Hongying Zhao, Xiangzhe Yin, Siya Wang, Wentong Yu, Zhichao Geng, Yanwu Sun, Wanting Jiao, Hongzheng Yu, Yunpeng Zhang, Peng Wang, Shangwei Ning, Li Wang
Journal Nucleic Acids Research
Year 2026
DOI
10.1093/nar/gkag1027
URL
https://doi.org/10.1093/nar/gkag1027
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