From Tumor to Model: Transcriptomic and Therapeutic Insights from Patient-derived Colorectal Cancer Organoids
American Association for Cancer Research® (AACR) Annual Meeting 2026
San Diego, California, United States
April 21, 2026Abstract
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.
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Ajeet Singh, PhD
Senior Scientist, ATCC
Dr. Ajeet Singh is Senior Scientist at ATCC where he is focused on providing reference-grade whole transcriptome data that is authenticated, standard, and traceable to physical source materials available in ATCC’s biorepository. Prior to joining ATCC, Dr. Singh received his PhD in Agricultural Plant Pathology where he performed research focused on epidemiology and integrated management of plants pests and diseases. He then performed postdoctoral research at the National Institute of Environmental Health Sciences and subsequently worked as a Senior Staff Scientist at the National Cancer Institute. Dr. Singh has extensive experience in biomedical research with his research career expanding an array of interrelated disciplines exploring epigenetics, chromatin and gene expression in reproductive developmental toxicology, stem cell biology, and cancer.
Human Cancer Models Initiative
ATCC is collaborating with the Human Cancer Models Initiative (HCMI) to offer scientists a wide variety of next-generation 2-D and 3-D patient-derived in vitro cancer models, including organoids.
ATCC is committed to making available a growing collection of models generated by the HCMI, which will include both common as well as rare and understudied examples of cancer from numerous tissues. These HCMI models are valuable tools to study cancer, identify and target novel therapies, and facilitate translational cancer research.
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