'On the Spot' Digital Pathology of Breast Cancer Based on Single-Cell Mass Spectrometry Imaging.

ABSTRACT: The molecular pathology of breast cancer is challenging due to the complex heterogeneity of cellular subtypes. The ability to directly identify and visualize cell subtype distribution at the single-cell level within a tissue section enables precise and rapid diagnosis and prognosis. Here, we applied mass spectrometry imaging (MSI) to acquire and visualize the molecular profiles at the single-cell and subcellular levels of 14 different breast cancer cell lines. We built a molecular library of genetically well-characterized cell lines. Multistep processing, including deep learning, resulted in a breast cancer subtype, the cancer's hormone status, and a genotypic recognition model based on metabolic phenotypes with cross-validation rates of up to 97%. Moreover, we applied our single-cell-base

SUBMITTER: Cuypers E 

PROVIDER: S-EPMC9047448 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature