Evidence map›Paper›PMID 40507285›Full record

ArticleCancers2025

Clinical Application of Next-Generation Sequencing for Molecular Classification in the Management of Endometrial Cancer: An Observational Cohort Study.

Sabrina Paratore, Angela Russo, Giusi Blanco, Katia Lanzafame, Eliana Giurato, Giovanni Bartoloni, Marco D'Asta, Mirella Sapienza, Valeria Solarino, Valentina Vinci and 3 more

Abstract read
In one paragraph

Article in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. 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

13 authors.

Sabrina ParatoreDepartment of Pathological Anatomy, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Angela RussoDepartment of Pathological Anatomy, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Giusi BlancoDepartment of Medical Oncology, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Katia LanzafameDepartment of Medical Oncology, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Eliana GiuratoDepartment of Pathological Anatomy, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Giovanni BartoloniDepartment of Pathological Anatomy, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Marco D'AstaDepartment of Obstetrics and Gynecology, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Mirella SapienzaDepartment of Obstetrics and Gynecology, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Valeria SolarinoRadiotherapy Unit, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Valentina VinciRadiology Unit, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Giulia Maria BonannoDepartment of Obstetrics and Gynecology, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Giuseppe EttoreDepartment of Obstetrics and Gynecology, ARNAS Garibaldi Hospital, 95122 Catania, Italy.
Roberto BordonaroDepartment of Medical Oncology, ARNAS Garibaldi Hospital, 95122 Catania, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesEndometrial cancer (EC) is the most common malignancy of the female genital tract. In 2013, The Cancer Genome Atlas analyzed the molecular profile of endometrial tumors identifying four risk classes (POLE ultramutated, mismatch repair-deficient, copy-number low-microsatellite stable, and copy-number high-serous-like. This classification is reshaping the current understanding of EC, enabling more refined risk stratification and uncovering potential therapeutic targets tailored to specific molecular subgroups. In the context of these four categories, it is possible to identify different molecular alterations that correlate with different prognoses. METHODS AND

resultsWe retrospectively analyzed tissue samples from eighty-five EC patients, performing multigene profiling using a 50-gene next-generation sequencing (NGS) panel to categorize them into distinct molecular subtypes; we observed the following distribution: 5.9% POLE, 25.8% mismatch repair-deficient/microsatellite instability (MMRd/MSI), 11.8% p53abn/TP53mut, and 56.5% NSMP. A favorable concordance (97.6%) was shown in MSI NGS-based analysis and MMR IHC results, and the agreement rate of p53 IHC and

conclusionsOur study highlights the potential of a medium-complexity NGS panel for supporting the molecular classification of endometrial cancer, complementing the existing diagnostic algorithms. By identifying additional biomarkers, we provided valuable insights into the genomic landscape of EC. However, further exploration of the molecular profiles is needed to validate these findings and improve the identification of patients at a higher risk of unfavorable outcomes.

Indexed as

clinicopathological featuresendometrial cancermismatch repair-deficientmolecular profileno specific molecular profilePOLE mutatedTP53mutated

Identifiers

PMID40507285
PMCPMC12153688

What Socratic holds

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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 Socratic graph.