Researchers unveiled DREAMS, a tissue-aware method published in Nature Cell Biology designed to map DNA and RNA modification landscapes with spatial resolution. Unlike uniform-tissue averaging approaches, DREAMS aims to reveal how chemical epigenetic information is distributed across anatomical contexts, enabling more precise links between modifications and cellular states. In spatial biology instrumentation and processing, new work highlighted PASTA for tyramide-oligonucleotide amplification, positioning the method as a way to push sensitivity for multimodal spatial assays without losing molecular localization. These tools are increasingly important for decoding disease biology where microenvironment context matters. For data analysis, a machine-learning approach called HisToSpatialCNV predicts spatial copy-number variations directly from pathology images, targeting the problem of reading genomic heterogeneity from conventional slides while improving interpretability for pathology workflows.