Establishment, biobanking, and multi-omics characterization of 41 patient-derived colorectal cancer organoids: MYC/PRC classification

PURPOSE: Colorectal cancer (CRC) exhibits marked genetic, transcriptomic, and phenotypic heterogeneity, limiting the robustness of existing molecular classification systems. We aimed to apply and validate an SMI-based MYC/PRC classification framework in CRC patient-derived organoids and to characterize its molecular, pharmacologic, and clinical relevance across independent cohorts. METHODS: We established 41 CRC PDOs from 28 patients and performed whole-exome sequencing, RNA sequencing, and high-throughput drug screening. SMI scores (-1 to 1) were used to classify PDOs as MYC-type (stem-like) or PRC-type (differentiated). A concordantly classified subset of 25 PDOs underwent integrative multi-omics analyses. Findings were validated in an expanded cohort of 181 CRC PDOs and in TCGA-COAD. We compared pathway activities, mutational profiles, and drug responses, and performed archetypal modeling (K = 2) to position samples along a MYC-PRC transcriptional continuum. RESULTS: MYC-type PDOs exhibited enrichment of cell-cycle and proliferation-related programs, whereas PRC-type PDOs showed differentiation-associated transcriptional programs, including coagulation and NF-κB signaling. Drug screening showed greater sensitivity of MYC-type PDOs to MEK/EGFR-targeted agents, whereas PRC-type PDOs displayed more heterogeneous responses. Archetypal modeling preserved the α(PRC)-α(MYC) trade-off and sample ordering across feature sets and larger cohorts. Validation in the expanded PDO dataset and TCGA-COAD reproduced subtype-specific transcriptional patterns and supported their clinical relevance. CONCLUSIONS: SMI-based MYC/PRC classification captures biologically coherent tumor states with distinct molecular features and therapeutic sensitivities. This transcriptome-based framework complements existing classification systems and may support subtype-informed therapeutic prioritization in CRC.