Integrative single-cell and spatial transcriptomics uncover ELK4-mediated mechanisms in

Background: Globally, gastric cancer (GC) stands as the fifth most prevalent form of malignant neoplasm and represents a significant contributor to mortality associated with oncological conditions. Despite advancements in therapeutic strategies for GC, the outcomes for patients with advanced stages of the disease continue to be unfavorable, largely due to tumor heterogeneity and the challenges posed by resistance to therapeutic agents. Metabolic reprogramming is pivotal in driving the advancement of GC, contributing to the development of resistance to pharmacological treatments and facilitating the cancer's ability to evade immune surveillance. Developing multi-target comprehensive treatment strategies by integrating tumor microenvironment (TME) modulation holds promise for significantly improving therapeutic efficacy. Methods: The study analyzed GC and identified key cell subtypes by integrating data derived from single-cell RNA-sequencing (scRNA-seq) alongside spatial transcriptomics information. Cell type identification was accomplished using the tool of Seurat, and the spatial distribution of cell types was revealed through the Robust Cell Type Decomposition technique. CellChat was used to analyze the interactions between key cell subtypes and other cells, and the "StLearn" package was employed to investigate spatial cell communication in depth. Additionally, the functional role of the key molecule ELK4 was validated through Results: This research utilized scRNA-seq combined with spatial transcriptomics to comprehensively analyze GC, identifying the C1 Conclusion: This study revealed the main significance of the C1