Evidence map›Paper›PMID 41946858›Full record

ArticleScientific reports2026

Potential biomarkers of Ewing sarcoma identified through a Europe-wide analysis of prospectively collected samples.

Andreas Ranft, Günther H S Richter, Juan Diaz-Martin, Susanne Jabar, Marvin Jens, Maximilian Kerkhoff, Maite Blanquer-Maceiras, Rosa Noguera, Inken Piro, Katja Steiger and 8 more

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

18 authors.

Andreas Ranft *Pediatrics III, University Hospital Essen, West German Cancer Center, Essen, Germany. Andreas.Ranft@uk-essen.de.
Günther H S Richter *Department of Pediatrics, Division of Oncology and Hematology, Charite- Universitätsmedizin Berlin, Berlin, Germany.
Juan Diaz-MartinUniversity of Valencia / INCLIVA / CIBERONC, Valencia, Spain.
Susanne JabarPediatrics III, University Hospital Essen, West German Cancer Center, Essen, Germany.
Marvin JensDepartment of Pediatrics, Division of Oncology and Hematology, Charite- Universitätsmedizin Berlin, Berlin, Germany.
Maximilian KerkhoffPediatrics III, University Hospital Essen, West German Cancer Center, Essen, Germany.
Maite Blanquer-MaceirasUniversity of Valencia / INCLIVA / CIBERONC, Valencia, Spain.
Rosa NogueraUniversity of Valencia / INCLIVA / CIBERONC, Valencia, Spain.
Inken PiroInstitute of Pathology, TUM School of Medicine and Health, Technische Universität München, Munich, Germany.
Katja SteigerInstitute of Pathology, TUM School of Medicine and Health, Technische Universität München, Munich, Germany.
Stefan BurdachInstitute of Pathology, TUM School of Medicine and Health, Technische Universität München, Munich, Germany.
Alessandro ParraExperimental Oncology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
Piero PicciExperimental Oncology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
Marco GambarottiDepartment of Pathology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
Wolfgang HartmannDepartment of Pathology, University Hospital Muenster, Muenster, Germany.
Katia ScotlandiExperimental Oncology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
Enrique de AlavaInstitute of Biomedicine of Sevilla, IBiS/Virgen del Rocio University Hospital, CSIC/University of Sevilla/CIBERONC, Seville, Spain.
Uta DirksenPediatrics III, University Hospital Essen, West German Cancer Center, Essen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical features, aside from disease stage, have proven insufficient to identify patients at extremely high or low risk. There are few established biological markers for EwS. The discovery of new prognostic and/or predictive biomarkers could improve our understanding of tumor heterogeneity, facilitate individual risk stratification, and aid targeted therapies. We initiated a pan-European study using formalin-fixed, prospectively collected, primary tumors prior to chemotherapy from 335 patients in two clinical trial registries, EURO-Ewing 99 and Ewing 2008, to analyze correlation and survival of ten potential prognostic biomarkers. Immunohistochemical (IHC) analyses were conducted for STEAP1, DKK2, and EZH2, while MIR34A and LGALS3BP expression was investigated by quantitative PCR. Genomic alterations, including gain of chromosome 1q, loss of ADAM3A, loss of chromosome 16q, as well as loss of heterozygosity (LOH) and percentage of the genome altered (PGA), were analyzed by FISH and/or SNP-based arrays of genomic DNA. To consider the observed variation in the number of analyzed samples per biomarker (N = 102–300), effect size measures were computed. Correlations between dichotomized biomarker expressions were generally low, except for those reflecting genomic alterations (ϕ >= 0.20 <= 0.38; P < .05). Several relevant correlations were found with clinical features of the underlying EwS patients (ϕ >= 0.20 <= 0.31; P < .05). Most promising prognostic values with clinically relevant effect sizes (OS), adjusted for known prognostic variables, were high MIR34A expression (HR = 0.29; P < .01), LOH (HR = 2.44; P < .05), and PGA (HR = 2.20; P = .05). This pan-European study identified MIR34A, LOH, and PGA as the most promising biomarkers for the prognosis of survival in a well-characterized EWS patient cohort.

Indexed as

Biomarkers, TumorBone NeoplasmsSarcoma, EwingAdolescentAdultChildChild, PreschoolEuropeFemaleHumansMaleMicroRNAsPrognosisProspective StudiesYoung AdultBiomarkers, TumorMicroRNAsBiomarkersEwing sarcomaPrognosis

Identifiers

PMID41946858
PMCPMC13057395

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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.