Deciphering spatial heterogeneity of patient-derived organoids of colorectal tumors for drug discovery

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Abstract

The spatial organization of tumors is critical for drug development, as spatial heterogeneity in cancer cells and the tumor microenvironment can present a significant barrier to effective therapies. Patient-derived tumor organoids (PDOs) offer promising platforms to study tumor biology and for drug development. Previous studies have demonstrated that PDOs can maintain the genomic/clonal heterogeneity of tumors, as well as expression heterogeneity. However, the spatial heterogeneity of PDOs and its correlation with the original tumors remains unclear. We propose an integrated pipeline combining spatial transcriptomics and phenotypic analyses of PDOs to capture and track spatial heterogeneity. This platform integrates multiplexed organoid cultures with imaging-based spatial transcriptomics and analysis at single organoid resolution. We validate the platform by comparing results with non-spatial single-cell transcriptomic data and spatial transcriptomic analysis of donor tumors. The combination of ex vivo PDOs and spatial transcriptomics could open novel avenues for developing drugs.
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Abstract The spatial organization of tumors is critical for drug development, as spatial heterogeneity in cancer cells and the tumor microenvironment can present a significant barrier to effective therapies. Patient-derived tumor organoids (PDOs) offer promising platforms to study tumor biology and for drug development. Previous studies have demonstrated that PDOs can maintain the genomic/clonal heterogeneity of tumors, as well as expression heterogeneity. However, the spatial heterogeneity of PDOs and its correlation with the original tumors remains unclear. We propose an integrated pipeline combining spatial transcriptomics and phenotypic analyses of PDOs to capture and track spatial heterogeneity. This platform integrates multiplexed organoid cultures with imaging-based spatial transcriptomics and analysis at single organoid resolution. We validate the platform by comparing results with non-spatial single-cell transcriptomic data and spatial transcriptomic analysis of donor tumors. The combination of ex vivo PDOs and spatial transcriptomics could open novel avenues for developing drugs. Competing Interest Statement The authors have declared no competing interest. Footnotes 1. Exchange signs for Maxim Norkin in the author list. (should be co-correspondence) 2. Figure 5 (current) should be Figure 2. 3. Add figure names on top/before each figure. 4. Add Figure annotations/captions. 5. Supp figures link doesn't work

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europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
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last seen: 2026-05-26T02:00:01.498150+00:00
License: CC-BY-NC-ND-4.0