MOSBY enables multi-omic inference and spatial biomarker discovery from whole slide images.

ABSTRACT: The utility of deep neural nets has been demonstrated for mapping hematoxylin-and-eosin (H&E) stained image features to expression of individual genes. However, these models have not been employed to discover clinically relevant spatial biomarkers. Here we develop MOSBY (Multi-Omic translation of whole slide images for Spatial Biomarker discoverY) that leverages contrastive self-supervised pretraining to extract improved H&E whole slide images features, learns a mapping between image and bulk omic profiles (RNA, DNA, and protein), and utilizes tile-level information to discover spatial biomarkers. We validate MOSBY gene and gene set predictions with spatial transcriptomic and serially-sectioned CD8 IHC image data. We demonstrate that MOSBY-inferred colocalization features have survival-pre

SUBMITTER: Senbabaoglu Y 

PROVIDER: S-EPMC11303705 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature