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The interaction between tumor cells and the tumor microenvironment (TME) plays a crucial role in the occurrence, progression, and metastasis of cancer. Different types of cells within the TME are organized in a highly structured manner to facilitate efficient functioning, particularly within tumor tissues. However, traditional bulk RNA sequencing and the popular single-cell RNA sequencing (scRNA-seq) methods disrupt this cellular organization and do not provide spatial information. In contrast, the emergence of spatial omics databases offers a high-resolution perspective of the tumor landscape, revealing the complex interactions between cancer cells, immune cells, stromal cells, and the extracellular matrix.
Recently, various spatial omics technologies (such as spatial omics databases) have been developed, including sequencing-based and imaging-based technologies. Sequencing-based technologies capture and preserve spatial expression information by hybridizing RNA transcripts in situ to fixed spatial indexes, such as 10× Visium, spatial transcriptomics (ST), and Slide-seq. These technologies, including spatial omics databases, have propelled the field of spatial transcriptomics, particularly in the context of human diseases. However, the influx of spatial transcriptomics data also presents challenges. Diverse and complex data formats have increased the difficulty for most biologists, requiring more time and effort to process and utilize. Furthermore, each locus in tissue slices contains multiple cells, highlighting the importance of integrating scRNA-seq data in the analysis.
Spatial omics databases have profound implications for cancer research. Firstly, they provide high-resolution cellular spatial distribution information, helping researchers to gain deeper insights into the molecular biological characteristics of cells in different regions within tumors. Secondly, spatial omics databases can reveal intercellular interactions and communications, which are crucial for understanding the complexity of the tumor microenvironment. By integrating spatial transcriptomics and spatial proteomics data, researchers can comprehensively analyze the molecular mechanisms of tumor occurrence, development, and metastasis.
Moreover, spatial omics databases aid in the discovery of new tumor biomarkers and potential therapeutic targets, providing robust support for precision cancer treatment. In summary, spatial omics databases are essential tools in cancer research; they advance the in-depth study of cancer and offer new ideas and strategies for cancer diagnosis, treatment, and prevention.
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