Evidence map›Paper›PMID 38433235›Full record

ArticleJournal of translational medicine2024

CRISPR/Cas9-edited ROS1 + non-small cell lung cancer cell lines highlight differential drug sensitivity in 2D vs 3D cultures while reflecting established resistance profiles.

Marc Terrones, Christophe Deben, Felicia Rodrigues-Fortes, Anne Schepers, Ken Op de Beeck, Guy Van Camp, Geert Vandeweyer

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
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

7 authors at 1 institution in 1 country.

Marc TerronesCenter of Medical Genetics, University of Antwerp and Antwerp University Hospital, Edegem, Belgium.
Christophe DebenCenter for Oncological Research, University of Antwerp and Antwerp University Hospital, Wilrijk, Belgium.
Felicia Rodrigues-FortesCenter for Oncological Research, University of Antwerp and Antwerp University Hospital, Wilrijk, Belgium.
Anne SchepersCenter of Medical Genetics, University of Antwerp and Antwerp University Hospital, Edegem, Belgium.
Ken Op de BeeckCenter of Medical Genetics, University of Antwerp and Antwerp University Hospital, Edegem, Belgium.
Guy Van CampCenter of Medical Genetics, University of Antwerp and Antwerp University Hospital, Edegem, Belgium.
Geert VandeweyerCenter of Medical Genetics, University of Antwerp and Antwerp University Hospital, Edegem, Belgium. geert.vandeweyer@uantwerpen.be.ORCID 0000-0002-6262-6522
University of Antwerp · BE

Funding

Fonds Wetenschappelijk Onderzoek G094820N
6 · The paper itself

Abstract

introductionThe study of resistance-causing mutations in oncogene-driven tumors is fundamental to guide clinical decisions. Several point mutations affecting the ROS1 kinase domain have been identified in the clinical setting, but their impact requires further exploration, particularly in improved pre-clinical models. Given the scarcity of solid pre-clinical models to approach rare cancer subtypes like ROS1 + NSCLC, CRISPR/Cas9 technology allows the introduction of mutations in patient-derived cell lines for which resistant variants are difficult to obtain due to the low prevalence of cases within the clinical setting.

methodsIn the SLC34A2-ROS1 rearranged NSCLC cell line HCC78, we knocked-in through CRISPR/Cas9 technology three ROS1 drug resistance-causing mutations: G2032R, L2026M and S1986Y. Such variants are located in different functional regions of the ROS1 kinase domain, thus conferring TKI resistance through distinct mechanisms. We then performed pharmacological assays in 2D and 3D to assess the cellular response of the mutant lines to crizotinib, entrectinib, lorlatinib, repotrectinib and ceritinib. In addition, immunoblotting assays were performed in 2D-treated cell lines to determine ROS1 phosphorylation and MAP kinase pathway activity. The area over the curve (AOC) defined by the normalized growth rate (NGR_fit) dose-response curves was the variable used to quantify the cellular response towards TKIs.

resultsSpheroids derived from ROS1

conclusionIn this study we knock-in for the first time in a ROS1 + patient-derived cell line, three different known resistance-causing mutations using CRISPR/Cas9 in the endogenous translocated ROS1 alleles. Pharmacological assays performed in 2D and 3D cell culture revealed that spheroids are more sensitive to TKIs than cells cultured as a monolayer. This direct comparison between two culture systems could be done thanks to the implementation of normalized growth rates (NGR) to uniformly quantify drug response between 2D and 3D cell culture. Overall, this study presents the added value of using spheroids and positions lorlatinib and repotrectinib as the most effective TKIs against the studied ROS1 resistance point mutations.

Indexed as

AminopyridinesBenzamidesCarcinoma, Non-Small-Cell LungIndazolesLactamsLung NeoplasmsPyrazolesPyrimidinesSulfonesCRISPR-Cas SystemsCrizotinibDrug ResistanceHumansProtein-Tyrosine KinasesProto-Oncogene ProteinsAminopyridinesBenzamidesceritinibCrizotinibentrectinibIndazolesLactamslorlatinibProtein-Tyrosine KinasesProto-Oncogene ProteinsPyrazolesPyrimidinesROS1 protein, humanSulfones2D cell culture3D cell cultureCRISPR/Cas9Drug resistanceROS1 + Non-small cell lung cancerTyrosine kinase inhibitors

Identifiers

PMID38433235
PMCPMC10910754
OpenAlexW4392343382

What Socratic 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 Socratic graph.