Spatial single-cell proteomics landscape decodes the tumor microenvironmental ecosystem of intrahepatic cholangiocarcinoma.

Background And Aims: The prognoses and therapeutic responses of patients with intrahepatic cholangiocarcinoma (iCCA) depend on spatial interactions among tumor microenvironment (TME) components. However, the spatial TME characteristics of iCCA remain poorly understood. The aim of this study was to generate a comprehensive spatial atlas of iCCA using artificial intelligence-assisted spatial multiomics patterns and to identify spatial features associated with prognosis and immunotherapy.

Base-resolution mC profiling across the mammalian transcriptome by bisulfite-free enzyme-assisted chemical labeling approach.

5-methylcytosine (mC) is a prevalent RNA modification crucial for gene expression regulation. However, accurate and sensitive mC sites identification remains challenging due to severe RNA degradation and reduced sequence complexity during bisulfite sequencing (BS-seq). Here, we report mC-TAC-seq, a bisulfite-free approach combining TET-assisted mC-to-fC oxidation with selective chemical labeling, therefore enabling direct base-resolution mC detection through pre-enrichment and C-to-T transitions at mC sites.