AI-based morphological typing of CRC-PDOs reveals potential targets for chemotherapy

Colorectal cancer (CRC) is a heterogenous disease, and patients have differences in therapeutic response. However, the mechanisms underlying inter-patient heterogeneity in the response to chemotherapeutic agents remain to be elucidated. Patient-derived organoids (PDOs) established from CRCs recapitulate various biological characteristics of tumor tissues, including cellular heterogeneity and the response to chemotherapy. PDOs established from CRCs exhibit various morphologies, but there are no criteria for defining these morphologies, which hampers the analysis of their biological significance. We developed an artificial intelligence (AI)-based classifier to categorize PDOs based on microscopic images according to their similarity in appearance and classified tubular adenocarcinoma-derived PDOs into six types. Transcriptome analysis identified differential expression of genes related to cell adhesion in some of the morphological types. Genes involved in ribosome biogenesis were also differentially expressed and were most highly expressed in morphological types exhibiting CRC stem cell properties. We identified an RNA polymerase I inhibitor, CX-5641, to be an upstream regulator of these type-specific gene sets. Notably, PDO types with increased expression of genes involved in ribosome biogenesis were resistant to CX-5461 treatment. These results uncover the biological significance of the morphology of PDOs and provide novel indicators by which to categorize CRCs.