Evidence map›Paper›PMID 35630206›Full record

ArticleMicromachines2022

The Effect of Dynamic, In Vivo-like Oxaliplatin on HCT116 Spheroids in a Cancer-on-Chip Model Is Representative of the Response in Xenografts.

Job Komen, Sanne M van Neerven, Elsbeth G B M Bossink, Nina E de Groot, Lisanne E Nijman, Albert van den Berg, Louis Vermeulen, Andries D van der Meer

Open access · goldAbstract read
In one paragraph

Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 47% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
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

8 authors at 2 institutions in 1 country.

Job KomenBIOS Lab on a Chip Group, MESA+ Institute for Nanotechnology, University of Twente, 7500 AE Enschede, The Netherlands.
Sanne M van NeervenLaboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology, Endocrinology and Metabolism, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands.
Elsbeth G B M BossinkLaboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology, Endocrinology and Metabolism, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands.
Nina E de GrootLaboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology, Endocrinology and Metabolism, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands.
Lisanne E NijmanLaboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology, Endocrinology and Metabolism, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands.
Albert van den BergBIOS Lab on a Chip Group, MESA+ Institute for Nanotechnology, University of Twente, 7500 AE Enschede, The Netherlands.
Louis VermeulenLaboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology, Endocrinology and Metabolism, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands.ORCID 0000-0002-6066-789X
Andries D van der MeerApplied Stem Cell Technologies, TechMed Centre, University of Twente, 7500 AE Enschede, The Netherlands.ORCID 0000-0002-8761-4077
Amsterdam University Medical Centers · NLUniversity of Twente · NL

Funding

Dutch Research Council 024.003.001
6 · The paper itself

Abstract

The cancer xenograft model in which human cancer cells are implanted in a mouse is one of the most used preclinical models to test the efficacy of novel cancer drugs. However, the model is imperfect; animal models are ethically burdened, and the imperfect efficacy predictions contribute to high clinical attrition of novel drugs. If microfluidic cancer-on-chip models could recapitulate key elements of the xenograft model, then these models could substitute the xenograft model and subsequently surpass the xenograft model by reducing variation, increasing sensitivity and scale, and adding human factors. Here, we exposed HCT116 colorectal cancer spheroids to dynamic, in vivo-like, concentrations of oxaliplatin, including a 5 day drug-free period, on-chip. Growth inhibition on-chip was comparable to existing xenograft studies. Furthermore, immunohistochemistry showed a similar response in proliferation and apoptosis markers. While small volume changes in xenografts are hard to detect, in the chip-system, we could observe a temporary growth delay. Lastly, histopathology and a pharmacodynamic model showed that the cancer spheroid-on-chip was representative of the proliferating outer part of a HCT116 xenograft, thereby capturing the major driver of the drug response of the xenograft. Hence, the cancer-on-chip model recapitulated the response of HCT116 xenografts to oxaliplatin and provided additional drug efficacy information.

Indexed as

cancer-on-chipcolorectal cancerdrug efficacymicrofluidicoxaliplatinpharmacodynamicspharmacokineticsxenograft

Identifiers

PMID35630206
PMCPMC9146796
OpenAlexW4229365242

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.