The Nicolas Rajsky laboratory team at the Max Delbrueck Center in Germany has developed a spatial transcription platform called Open-ST, which can reconstruct gene expression within patient tissue cells in a three-dimensional (3D) manner and draw molecular maps of tissue samples with subcellular accuracy. The relevant paper was published in the new issue of the journal Cell. Transcriptomics is the discipline that studies gene expression in cells or cell populations, usually excluding spatial information, while spatial transcriptomics can measure the spatial expression of RNA in tissue samples. The Open-ST platform provides an economical, high-resolution, and easy-to-use method that can capture both tissue morphology of samples and spatial transcriptomic information of tissue slices. This platform can utilize a series of 2D images to reconstruct them into a 3D "virtual three-dimensional organization". In the experiment, researchers successfully identified the diversity characteristics of immune, stromal, and tumor cell populations using samples from healthy and metastatic lymph nodes of head and neck cancer patients. These cell clusters are organized around communication hotspots within the primary tumor, but this tissue is disrupted in metastatic tumors. The Open-ST platform highlights potential biomarkers at the boundaries of 3D tumors or lymph nodes based on images drawn from cancer tissue samples, which may become new drug targets. And these potential biomarkers are not visible in 2D analysis. The Open-ST platform provides unprecedented precision for research. For example, people can locate any position in a 3D image, analyze the molecular mechanisms inside individual cells, or the boundaries between healthy cells and cancer cells. This helps to understand how cancer cells interact with the surrounding environment, providing a new perspective for exploring the interaction between cancer cells and the immune system. In addition, the platform is not limited to cancer research and can also be used to explore various types of tissues and organisms. At present, researchers have made the entire experimental and computational workflow free of charge for widespread use. (Lai Xin She)