Evidence map›Paper›PMID 33212997›Full record

ArticleInternational journal of molecular sciences2020

Digital Image Analysis Applied to Tumor Cell Proliferation, Aggressiveness, and Migration-Related Protein Synthesis in Neuroblastoma 3D Models.

Ezequiel Monferrer, Sabina Sanegre, Susana Martín-Vañó, Andrea García-Lizarribar, Rebeca Burgos-Panadero, Amparo López-Carrasco, Samuel Navarro, Josep Samitier, Rosa Noguera

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Vitronectin-based hydrogels recapitulate neuroblastoma growth conditions.Frontiers in cell and developmental biology · 2022
    Article
  7. Article
  8. 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

9 authors.

Ezequiel MonferrerDepartment of Pathology, Medical School, University of Valencia-INCLIVA Biomedical Health Research Institute, 46010 Valencia, Spain.
Sabina SanegreDepartment of Pathology, Medical School, University of Valencia-INCLIVA Biomedical Health Research Institute, 46010 Valencia, Spain.ORCID 0000-0003-0271-478X
Susana Martín-VañóDepartment of Pathology, Medical School, University of Valencia-INCLIVA Biomedical Health Research Institute, 46010 Valencia, Spain.
Andrea García-LizarribarInstitute for Bioengineering of Catalonia, Barcelona Institute of Science and Technology (IBEC-BIST), 08028 Barcelona, Spain.ORCID 0000-0001-5072-2093
Rebeca Burgos-PanaderoDepartment of Pathology, Medical School, University of Valencia-INCLIVA Biomedical Health Research Institute, 46010 Valencia, Spain.
Amparo López-CarrascoDepartment of Pathology, Medical School, University of Valencia-INCLIVA Biomedical Health Research Institute, 46010 Valencia, Spain.ORCID 0000-0001-9202-2597
Samuel NavarroDepartment of Pathology, Medical School, University of Valencia-INCLIVA Biomedical Health Research Institute, 46010 Valencia, Spain.
Josep SamitierInstitute for Bioengineering of Catalonia, Barcelona Institute of Science and Technology (IBEC-BIST), 08028 Barcelona, Spain.ORCID 0000-0002-1140-3679
Rosa NogueraDepartment of Pathology, Medical School, University of Valencia-INCLIVA Biomedical Health Research Institute, 46010 Valencia, Spain.ORCID 0000-0003-4546-7459

Funding

Asociación Fundación Española contra el Cáncer JAP-AECC (2018/150)CIBERONC CB16/12/00484CIBERONC-CIBERBBN ONC18PI03ISCIII (FIS) and FEDER (European Regional Development Fund) PI17/01558NEN Association (Nico contra el cáncer infantil) 2017- PVR00157
6 · The paper itself

Abstract

Patient-derived cancer 3D models are a promising tool that will revolutionize personalized cancer therapy but that require previous knowledge of optimal cell growth conditions and the most advantageous parameters to evaluate biomimetic relevance and monitor therapy efficacy. This study aims to establish general guidelines on 3D model characterization phenomena, focusing on neuroblastoma. We generated gelatin-based scaffolds with different stiffness and performed SK-N-BE(2) and SH-SY5Y aggressive neuroblastoma cell cultures, also performing co-cultures with mouse stromal Schwann cell line (SW10). Model characterization by digital image analysis at different time points revealed that cell proliferation, vitronectin production, and migration-related gene expression depend on growing conditions and are specific to the tumor cell line. Morphometric data show that 3D in vitro models can help generate optimal patient-derived cancer models, by creating, identifying, and choosing patterns of clinically relevant artificial microenvironments to predict patient tumor cell behavior and therapeutic responses.

Indexed as

Cell MovementCell ProliferationImage Processing, Computer-AssistedNeuroblastomaProtein BiosynthesisCell Line, TumorHumansNeoplasm ProteinsNeoplasm Proteins3D cancer modelingDOCK8KANK1Ki67preclinical therapeutic studiesvitronectin

Identifiers

PMID33212997
PMCPMC7698558

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.