ArticleJournal of translational medicine2025
Panmim: a resource of pan-cancer metastasis immune microenvironment.
Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundCancer metastasis, the process by which tumor cells spread from the primary site to other organs, is one of the leading causes of death in cancer patients. However, due to its complexity and unpredictability, the study of cancer metastasis remains a significant challenge in medicine. In recent years, with the advancement of high-throughput sequencing technologies and single-cell transcriptomics, we could gain a deeper understanding of the molecular mechanisms and cellular heterogeneity underlying cancer metastasis. There is an accumulating volume of publicly available cancer metastasis research data. Nevertheless, these resources lack proper organization, hindering systematic analysis.
methodsIn this study, we developed an integrated resource named Panmim ( http://www.gdwk-bioinfo.com/pan_metastasis/home ) to investigate the immune microenvironment of metastatic tumors. The database currently encompasses 90 single-cell RNA-seq datasets from metastatic cancers of diverse origins, encapsulating 14 distinct metastatic sites and 36 primary cancer types. Panmim facilitates a cellular-level comparison of similarities and differences between primary and metastatic cancers, encompassing pathway analysis, alterations in cellular metabolic pathways, cellular distribution preferences, and various aspects of intercellular communication.
resultsPanmim presents the analysis results through an intuitive interactive graphical interface, enabling users to explore and understand the complex biological phenomena during cancer metastasis more conveniently. This resource will become a valuable tool for biologists and bioinformaticians to study the mechanisms of cancer metastasis, providing important data support and scientific basis for the optimization of cancer treatment strategies.
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