Abstract 667: Mapping and targeting spatial heterogeneity in CRC through patient-derived organoids.

Abstract Inter- and intra-patient heterogeneity, as well as spatial heterogeneity of cancer cells and the tumor microenvironment (TME), is a formidable barrier for cancer therapies. Ex vivo, patient-derived organoids (PDOs) hold promise as better platforms for drug development and can be applied in personalized medicine. Previous work has shown that genomic and clonal heterogeneity of tumors, as well as expression heterogeneity, can be maintained in PDOs. However, it remains unclear whether PDOs preserve the same degree of spatial expression heterogeneity observed in the original tumors. We propose an analytical pipeline combining spatial transcriptomic and phenotypic analysis of PDOs that can capture and track spatial heterogeneity across multiple assays, including during drug treatment.We have developed an organoid multi-embedding platform that allows parallel analysis of multiplex organoid cultures using imaging-based spatial transcriptomics. We validate the platform by comparison to non-spatial single-cell transcriptomic and donor tumor spatial transcriptomic analyses. With that, we have analyzed 40 CRC (colorectal cancer) PDOs and 16 CRC PDO-tumor pairs by spatial transcriptomics (Xenium 10x), including drug treatments, organoid developmental trajectories, and co-culture experiments. We have discovered intra- and inter-patient heterogeneity in tumors and PDOs and linked gene expression to organoid shapes. We further distinguished different expression programs in CRC and linked them to the spatial positioning of malignant cells in tumors. Finally, we have identified and analyzed dormant organoids in heterogeneous PDO cultures and compared them to the original tumors.The combination of ex vivo PDOs and spatial transcriptomics could open novel avenues for drug development selectively targeting spatial subsets of cancer cells and the TME. Citation Format: Maxim Norkin, Jonathan Bac, Louis McConnel, Sylvie Andre, Marina Alexandra Gaveta, Joerg Huelsken, Marianna Rapsomaniki, Raphael Gottardo, Krisztian Homicsko. Mapping and targeting spatial heterogeneity in CRC through patient-derived 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 667.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-667
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 667: Mapping and targeting spatial heterogeneity in CRC through patient-derived organoids.

Maxim Norkin, Jonathan Bac, Joerg Huelsken, Krisztián Homicskó et al.
Cancer Research
Single-cell and spatial transcriptomics
article

Abstract 667: Mapping and targeting spatial heterogeneity in CRC through patient-derived organoids.

Maxim Norkin, Jonathan Bac, Joerg Huelsken, Krisztián Homicskó, Marianna Rapsomaniki, Sylvie André, Marina Alexandre Gaveta, Louis McConnel, Raphael Gottardo
article en

Abstract

Abstract Inter- and intra-patient heterogeneity, as well as spatial heterogeneity of cancer cells and the tumor microenvironment (TME), is a formidable barrier for cancer therapies. Ex vivo, patient-derived organoids (PDOs) hold promise as better platforms for drug development and can be applied in personalized medicine. Previous work has shown that genomic and clonal heterogeneity of tumors, as well as expression heterogeneity, can be maintained in PDOs. However, it remains unclear whether PDOs preserve the same degree of spatial expression heterogeneity observed in the original tumors. We propose an analytical pipeline combining spatial transcriptomic and phenotypic analysis of PDOs that can capture and track spatial heterogeneity across multiple assays, including during drug treatment.We have developed an organoid multi-embedding platform that allows parallel analysis of multiplex organoid cultures using imaging-based spatial transcriptomics. We validate the platform by comparison to non-spatial single-cell transcriptomic and donor tumor spatial transcriptomic analyses. With that, we have analyzed 40 CRC (colorectal cancer) PDOs and 16 CRC PDO-tumor pairs by spatial transcriptomics (Xenium 10x), including drug treatments, organoid developmental trajectories, and co-culture experiments. We have discovered intra- and inter-patient heterogeneity in tumors and PDOs and linked gene expression to organoid shapes. We further distinguished different expression programs in CRC and linked them to the spatial positioning of malignant cells in tumors. Finally, we have identified and analyzed dormant organoids in heterogeneous PDO cultures and compared them to the original tumors.The combination of ex vivo PDOs and spatial transcriptomics could open novel avenues for drug development selectively targeting spatial subsets of cancer cells and the TME. Citation Format: Maxim Norkin, Jonathan Bac, Louis McConnel, Sylvie Andre, Marina Alexandra Gaveta, Joerg Huelsken, Marianna Rapsomaniki, Raphael Gottardo, Krisztian Homicsko. Mapping and targeting spatial heterogeneity in CRC through patient-derived 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 667.

Cancer ResearchVol. 86(7_Supplement)
Centre Hospitalier Universitaire Vaudois (CH), École Polytechnique Fédérale de Lausanne (CH), University of Lausanne (CH)
Good health and well-being
Openalex Percentile: Top 28%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.