Spatial integration of multi-omics data from serial sections using the novel Multi-Omics Imaging Integration Toolset.

ABSTRACT:

Background

Truly understanding the cancer biology of heterogeneous tumors in precision medicine requires capturing the complexities of multiple omics levels and the spatial heterogeneity of cancer tissue. Techniques like mass spectrometry imaging (MSI) and spatial transcriptomics (ST) achieve this by spatially detecting metabolites and RNA but are often applied to serial sections. To fully leverage the advantage of such multi-omics data, the individual measurements need to be integrated into 1 dataset.

Results

We present the Multi-Omics Imaging Integration Toolset (MIIT), a Python framework for integrating spatially resolved multi-omics data. A key component of MIIT's integration is the registration of serial sections for which we developed a nonrigid registration algorithm,

SUBMITTER: Wess M 

PROVIDER: S-EPMC12077394 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature