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April 5, 2026Cancer Research0 citations

Abstract 5457: From tumor to model: Transcriptomic and therapeutic insights from patient-derived colorectal cancer organoids.

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MGMatthew GrazianoASAjeet P. SinghSFStephen Friend

Key Points

  • This research aims to understand the transcriptomic features and drug responses of patient-derived colorectal cancer organoids compared to conventional cell lines.
  • Expanded six colorectal cancer organoid models and ten cell lines for analysis.
  • Performed RNA sequencing to compare transcriptomic profiles among models and with tumor data from TCGA.
  • Screened organoids for drug sensitivity using six compounds targeting molecular pathways identified in RNA-seq.
  • Calculated IC50 values and assessed drug response through luminescent ATP viability assays.
  • Patient-derived organoids showed high genomic concordance with matched tumors, including shared mutations.
  • Key driver mutations such as APC, TP53, and KRAS were consistently detected across models.
  • Drug responses varied among organoids, confirming model-specific sensitivities.
  • Transcriptomic analysis revealed molecular heterogeneity and subtype-specific expression patterns.

Abstract

Abstract Background: Colorectal cancer (CRC) is the world’s second leading cause of cancer deaths, often diagnosed late due to its silent onset. To drive breakthroughs in drug discovery, scientists use both traditional cell lines and patient-derived models. The Human Cancer Models Initiative (HCMI)—a collaboration among the National Cancer Institute, Cancer Research UK, Wellcome Sanger Institute, Hubrecht Organoid Technology, and ATCC—has built a collection of clinically annotated CRC organoids that capture tumor biology and genetic diversity. Understanding differences in gene expression between organoids and conventional cell lines is key to improving disease models and developing better therapies. Methods: Six CRC organoid models from unique donors and ten CRC cell lines were expanded and analyzed via RNA sequencing. The models were derived from primary tissues across ten anatomical sites. Transcriptomic profiles were compared among models and against tumor data from The Cancer Genome Atlas (TCGA). A subset of models was screened for drug sensitivity using a panel of six compounds targeting molecular pathways identified by RNA-seq. Dose-response curves were generated, and IC50 values were calculated. Post-treatment cultures were evaluated using a luminescent ATP viability assay to assess drug response. Results: Patient-derived CRC organoids showed high genomic concordance with matched tumors, including shared single-nucleotide variants and ∼30-40% overlap in extrachromosomal DNA features. KRAS mutation discrepancies (e.g., G12D/G12V vs. G12R) indicated clonal evolution. Key driver mutations (APC, TP53, KRAS, PIK3CA, SMAD4) were consistently detected, corresponding with Oncomine targets. Histopathology confirmed retention of tumor-specific markers. Drug screening revealed variable responses across organoids, with fluorescence-based viability assays confirming model-specific sensitivities. Transcriptomic analysis highlighted molecular heterogeneity and distinct subtype-specific expression patterns. Several genes were consistently expressed across models, suggesting shared oncogenic pathways. Conclusion: CRC organoids from HCMI faithfully recapitulate key transcriptomic and mutational features of patient tumors while revealing diverse drug responses. These models offer valuable platforms for precision oncology, enabling the identification of variant-specific vulnerabilities and supporting personalized treatment strategies. Citation Format: Matthew Graziano, Ajeet Singh, Stephen Friend, Ruby E. Thamert, Utsav Sharma, Abhay Andar, Jonathan Jacobs, Carolina Lucchesi, . From tumor to model: Transcriptomic and therapeutic insights from patient-derived colorectal cancer organoids abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5457.

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Graziano et al. (2026) studied this question.

synapsesocial.com/papers/69d1fde4a79560c99a0a449ahttps://doi.org/10.1158/1538-7445.am2026-5457
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