Evidence map›Paper›PMID 33326106›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2021

Ewing Sarcoma PDX Models.

Didier Surdez, Lorena Landuzzi, Katia Scotlandi, Maria Cristina Manara

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Biological Sample Collection to Advance Research and Treatment: A Fight Osteosarcoma Through European Research and Euro Ewing Consortium Statement.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
    Guideline
  2. Review
  3. Choosing the right animal model for sarcoma research.Cellular and molecular life sciences : CMLS · 2026
    Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. 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

4 authors.

Didier SurdezINSERM U830, Équipe Labellisée LNCC, Genetics and Biology of Pediatric Cancers, PSL Research University, SIREDO Oncology Centre, Institut Curie Research Centre, Paris, France.
Lorena LanduzziIRCCS-Istituto Ortopedico Rizzoli, Experimental Oncology Laboratory, Bologna, Italy.
Katia ScotlandiIRCCS-Istituto Ortopedico Rizzoli, Experimental Oncology Laboratory, Bologna, Italy.
Maria Cristina ManaraIRCCS-Istituto Ortopedico Rizzoli, Experimental Oncology Laboratory, Bologna, Italy. mariacristina.manara@ior.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ewing sarcoma (EWS) is a rare malignant pediatric tumor and patient derived xenografts (PDXs) could represent a possibility to increase the number of available models to study this disease. Compared to cell derived xenografts (CDX), PDXs are reported to better recapitulate tumor microenvironment, heterogeneity, genetic and epigenetic features and are considered reliable models for their better predictive value when comparing preclinical efficacy and treatment response in patients. In this chapter, we extensively describe a method for generating Ewing sarcoma PDX models, for their validation and molecular characterization.

Indexed as

Disease Models, AnimalHeterograftsAnimalsBiopsyBone NeoplasmsCell Line, TumorHumansImmunohistochemistryMiceMice, Inbred NODMice, SCIDSarcoma, EwingTumor MicroenvironmentEwing sarcomaImmunodeficient micePatient-derived xenograftsPediatric tumorsPreclinical models

Identifiers

What OpenQuestion holds

Textmetadata
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.