Christopher L. Corless

This study analyzes gliosarcoma using digital spatial transcriptomics to compare glial and mesenchymal components with glioblastoma, identifying genetic and transcriptomic differences.

The paper identifies resistance mechanisms to KRAS-MEK pathway targeting in PDAC by analyzing clinical trial data and multi-omics profiles, showing that KRAS/MYC co-gain correlates with resistance and that co-targeting these genes is synergistic.

This paper introduces a deep learning method called SHIFT that translates histological images into virtual immunofluorescence images, improving efficiency and reducing costs in cancer diagnostics.