Evidence map›Paper›PMID 40093980›Full record

ArticleTherapeutic advances in medical oncology2025

Enhancing precision in sarcoma diagnosis: nCounter fusion panel implementation in a middle-income country.

Flávia Escremim de Paula, Murilo Bonatelli, Monise Tadin Dos Reis, Karla Emília de Sá Rodrigues, Léon C van Kempen, Gustavo Ramos Teixeira, Rui Manuel Reis

Abstract read
In one paragraph

Article in Therapeutic advances in medical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Flávia Escremim de PaulaMolecular Diagnostic Laboratory, Barretos Cancer Hospital, Barretos, Brazil.ORCID https://orcid.org/0009-0001-9236-990X
Murilo BonatelliMolecular Diagnostic Laboratory, Barretos Cancer Hospital, Barretos, Brazil.
Monise Tadin Dos ReisPathology Department, Barretos Cancer Hospital, Barretos, Brazil.
Karla Emília de Sá RodriguesPediatric Department, Barretos Cancer Hospital, Barretos, Brazil.
Léon C van KempenDepartment of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Gustavo Ramos TeixeiraMolecular Diagnostic Laboratory, Barretos Cancer Hospital, Barretos, Brazil.
Rui Manuel ReisMolecular Diagnostic Laboratory, Barretos Cancer Hospital, Barretos, Brazil.ORCID https://orcid.org/0000-0002-9639-7940

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sarcoma diagnosis is challenging due to numerous subtypes with similar histopathological features and the high cost of fusion detection methods, particularly in middle-income countries. Objectives: To implement a cost-effective custom-based nCounter approach previously validated for fusion analysis of suspected sarcoma in Brazil. Design and methods: RNA isolated from 56 routine sarcomas, which were formalin-fixed and paraffin-embedded, was analyzed using a custom nCounter assay that detects 174 common sarcoma gene fusions. The results were compared to fluorescence in situ hybridization (FISH)/next-generation sequencing (NGS) and clinicopathological data. Results: The nCounter assay was conclusive in 98.2% of cases, identifying 25 gene fusions with 82.5% accuracy, 76.6% sensitivity, and 100% specificity compared to FISH/NGS. Conclusion: Although it does not identify all sarcoma fusions, especially for rare subtypes, the present nCounter assay is a rapid, affordable, and accurate tool for sarcoma diagnosis in resource-limited settings.

Indexed as

biomarkerslow- and middle-income countriesmolecular diagnosticsnCountersarcoma

Identifiers

PMID40093980
PMCPMC11907538

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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.