Evidence map›Paper›PMID 38414064›Full record

ArticleJournal of experimental & clinical cancer research : CR2024

Organoids as a biomarker for personalized treatment in metastatic colorectal cancer: drug screen optimization and correlation with patient response.

Lidwien P Smabers, Emerens Wensink, Carla S Verissimo, Esmee Koedoot, Katerina-Chara Pitsa, Maarten A Huismans, Celia Higuera Barón, Mayke Doorn, Liselot B Valkenburg-van Iersel, Geert A Cirkel and 10 more

Open access · goldAbstract read
In one paragraph

Article in Journal of experimental & clinical cancer research : CR, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
12.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

47 citing papers in PubMed, 45 citations in OpenAlex.

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  6. A Colon Cancer Organoid-on-a-Chip Model for In Vitro Therapy Assessment.International journal of molecular sciences · 2026
    Article
  7. New developments and applications of human organoids.Nature reviews. Molecular cell biology · 2026
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  17. The role of NADFrontiers in oncology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors at 5 institutions in 1 country.

Lidwien P Smabers *Department of Medical Oncology, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands.
Emerens Wensink *Department of Medical Oncology, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands.
Carla S VerissimoHUB Organoids B.V, Utrecht, The Netherlands.
Esmee KoedootHUB Organoids B.V, Utrecht, The Netherlands.
Katerina-Chara PitsaHUB Organoids B.V, Utrecht, The Netherlands.
Maarten A HuismansMolecular Cancer Research, Center for Molecular Medicine, UMCU, Utrecht, The Netherlands.
Celia Higuera BarónHUB Organoids B.V, Utrecht, The Netherlands.
Mayke DoornHUB Organoids B.V, Utrecht, The Netherlands.
Liselot B Valkenburg-van IerselDepartment of Medical Oncology, Maastricht University Medical Center, Maastricht, The Netherlands.
Geert A CirkelDepartment of Medical Oncology, Meander Medical Center, Amersfoort, The Netherlands.
Anneta BrousaliUtrecht Platform for Organoid Technology (UPORT), UMCU, Utrecht, The Netherlands.
René OvermeerHUB Organoids B.V, Utrecht, The Netherlands.
Miriam KoopmanDepartment of Medical Oncology, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands.
Manon N BraatDepartment of Radiology, UMCU, Utrecht, The Netherlands.
Bas Penning de VriesDepartment of Epidemiology, Julius Center for Health Sciences and Primary Care, UMCU, Utrecht, The Netherlands.
Sjoerd G EliasDepartment of Epidemiology, Julius Center for Health Sciences and Primary Care, UMCU, Utrecht, The Netherlands.
Robert G VriesHUB Organoids B.V, Utrecht, The Netherlands.
Onno KranenburgUtrecht Platform for Organoid Technology (UPORT), UMCU, Utrecht, The Netherlands.
Sylvia F Boj *HUB Organoids B.V, Utrecht, The Netherlands. s.boj@huborganoids.nl.
Jeanine M Roodhart *Department of Medical Oncology, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands. j.roodhart@umcutrecht.nl.
University Medical Center Utrecht · NLUtrecht University · NLHubrecht Institute for Developmental Biology and Stem Cell Research · NLMaastricht University · NLMeander Medisch Centrum · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe inability to predict treatment response of colorectal cancer patients results in unnecessary toxicity, decreased efficacy and survival. Response testing on patient-derived organoids (PDOs) is a promising biomarker for treatment efficacy. The aim of this study is to optimize PDO drug screening methods for correlation with patient response and explore the potential to predict responses to standard chemotherapies.

methodsWe optimized drug screen methods on 5-11 PDOs per condition of the complete set of 23 PDOs from patients treated for metastatic colorectal cancer (mCRC). PDOs were exposed to 5-fluorouracil (5-FU), irinotecan- and oxaliplatin-based chemotherapy. We compared medium with and without N-acetylcysteine (NAC), different readouts and different combination treatment set-ups to capture the strongest association with patient response. We expanded the screens using the optimized methods for all PDOs. Organoid sensitivity was correlated to the patient's response, determined by % change in the size of target lesions. We assessed organoid sensitivity in relation to prior exposure to chemotherapy, mutational status and sidedness.

resultsDrug screen optimization involved excluding N-acetylcysteine from the medium and biphasic curve fitting for 5-FU & oxaliplatin combination screens. CellTiter-Glo measurements were comparable with CyQUANT and did not affect the correlation with patient response. Furthermore, the correlation improved with application of growth rate metrics, when 5-FU & oxaliplatin was screened in a ratio, and 5-FU & SN-38 using a fixed dose of SN-38. Area under the curve was the most robust drug response curve metric. After optimization, organoid and patient response showed a correlation coefficient of 0.58 for 5-FU (n = 6, 95% CI -0.44,0.95), 0.61 for irinotecan- (n = 10, 95% CI -0.03,0.90) and 0.60 for oxaliplatin-based chemotherapy (n = 11, 95% CI -0.01,0.88). Median progression-free survival of patients with resistant PDOs to oxaliplatin-based chemotherapy was significantly shorter than sensitive PDOs (3.3 vs 10.9 months, p = 0.007). Increased resistance to 5-FU in patients with prior exposure to 5-FU/capecitabine was adequately reflected in PDOs (p = 0.003).

conclusionsOur study emphasizes the critical impact of the screening methods for determining correlation between PDO drug screens and mCRC patient outcomes. Our 5-step optimization strategy provides a basis for future research on the clinical utility of PDO screens.

Indexed as

Colonic NeoplasmsColorectal NeoplasmsAcetylcysteineAntineoplastic Combined Chemotherapy ProtocolsFluorouracilHumansIrinotecanOrganoidsOxaliplatinPrecision MedicineAcetylcysteineFluorouracilIrinotecanOxaliplatinCancerChemotherapyColorectal cancerDrug screeningOncologyOrganoidsPrecision medicine

Identifiers

PMID38414064
PMCPMC10898042
OpenAlexW4392200290

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.