Cancer imaging articles from across Nature Portfolio

Spatial-omics tools, together with deep learning models, are revealing interactions between tumors and their environment, including immune cells, and are aiding human-like performance in histopathological analysis, with the potential to improve diagnostic accuracy and treatment choices.

Spatial proteomics has transformed cancer research by providing unparalleled insights into the microenvironmental landscape of tumors. Here we discuss how these technologies have significantly advanced our understanding of cell–cell interactions, tissue organization and spatially coordinated mechanisms underlying antitumor immune responses, and will pave the way for emerging breakthroughs in cancer research.

Ciwinska et al. asked whether natural tissue remodelling can drive mutant cell expansion and identified three protective mechanisms in the healthy mouse mammary gland that constrain the ability of mutant cells to transform and give rise to cancer.

Artificial intelligence can be leveraged to improve the detection of prostate cancer on magnetic resonance imaging; however, before this technology is implemented in clinical practice, further research is required.

Our non-randomized single-center clinical trial demonstrates the safety, cost-saving and time-saving potential of artificial intelligence (AI) assistance in the detection of breast cancer metastases in sentinel lymph nodes. AI assistance shows important benefits for pathologists and the laboratory workflow, which are needed as cancer incidence and diagnostics continue to rise.