Evidence map›Paper›PMID 39971443›Full record

ArticleInternational journal of gynecological cancer : official journal of the International Gynecological Cancer Society2025

A fully next-generation sequencing-based method of classifying molecular sub-types of endometrial cancer retains prognostic value and expands biomarker targets.

Mark C Valentine, Amanda Wong, Ling Chen, Feiyu Du, Andrew E O Hughes, David H Spencer, Eric J Duncavage, Lulu Sun

Abstract read
In one paragraph

Article in International journal of gynecological cancer : official journal of the International Gynecological Cancer Society, 2025. 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. Frontiers in oncology · 2025
    Review
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

8 authors.

Mark C ValentineWashington University School of Medicine in St. Louis, Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Siteman Cancer Center, St. Louis, MO, USA.
Amanda WongWashington University School of Medicine in St. Louis, Department of Pathology and Immunology, Division of Anatomic and Molecular Pathology, St. Louis, MO, USA.
Ling ChenWashington University School of Medicine in St. Louis, Institute for Informatics, Data Science and Biostatistics, St. Louis, MO, USA.
Feiyu DuWashington University School of Medicine in St. Louis, Department of Medicine, Division of Oncology, St. Louis, MO, USA.
Andrew E O HughesWashington University School of Medicine in St. Louis, Department of Pathology and Immunology, Division of Anatomic and Molecular Pathology, St. Louis, MO, USA.
David H SpencerWashington University School of Medicine in St. Louis, Department of Medicine, Division of Oncology, St. Louis, MO, USA.
Eric J DuncavageWashington University School of Medicine in St. Louis, Department of Pathology and Immunology, Division of Anatomic and Molecular Pathology, St. Louis, MO, USA.
Lulu SunWashington University School of Medicine in St. Louis, Department of Pathology and Immunology, Division of Anatomic and Molecular Pathology, St. Louis, MO, USA. Electronic address: sunl@wustl.edu.

Funding

Washington University Center for Cellular ImagingP30CA091842 · NCI · WASHINGTON UNIVERSITY · PI TIMOTHY J. EBERLEIN · 2001 to 2026
$128.0M
NCI NIH HHS P30 CA091842
6 · The paper itself

Abstract

objectiveThe molecular classification of endometrial cancer into POLE-ultra-mutated, mismatch repair-deficient, p53-mutated, and no specific molecular profile sub-types has significant prognostic value and is recommended in the evaluation of all patients with endometrial cancer. Nonetheless, there has been inconsistent clinical implementation. One possible barrier is the current practice of using several different assays, each with its own result, that subsequently need to be integrated. We developed a single, fully next-generation sequencing (NGS)-based assay that sub-types endometrial samples and evaluated it against an existing algorithm.

methodsMolecular sub-typing was retrospectively performed on 142 formalin-fixed, paraffin-embedded endometrial cancer samples using a clinically validated NGS panel targeting 133 genes and additional loci for micro-satellite instability and tumor mutational burden. In parallel, these same samples were classified by the World Health Organization algorithm using mismatch repair and p53 immunohistochemistry, and POLE sequencing. Concordance between algorithms was assessed, and the prognostic value of each was evaluated. We further explored racial disparities in outcomes and assessed other prognostic and potentially therapeutic biomarkers.

resultsThe sequencing-based method was highly concordant with the World Health Organization algorithm (136/142 patients, Cohen's κ = 0.94) and retained prognostic value, with a significant difference in overall survival and progression-free survival by sub-type, and similar stratification to that initially identified in The Cancer Genome Atlas analysis. In addition, 11 cases had sequence variants in the previously established prognostic biomarker CTNNB1, and 3 cases had potentially targetable sequence variants in ERBB2. Endometrial cancer outcomes in Black individuals were worse, in part owing to the increased incidence of sub-types with a poor prognosis.

conclusionsA fully sequencing-based assay streamlines molecular classification of endometrial cancer and retains the prognostic value of other validated methods, which may aid clinical implementation. The additional genomic information obtained with an NGS panel, beyond the classification markers, can broaden potentially applicable therapies.

Indexed as

Biomarkers, TumorEndometrial NeoplasmsHigh-Throughput Nucleotide SequencingAdultAgedAged, 80 and overAlgorithmsDNA Mismatch RepairDNA Polymerase IIFemaleHumansMiddle AgedMutationPoly-ADP-Ribose Binding ProteinsPrognosisRetrospective StudiesBiomarkers, TumorDNA Polymerase IIPOLE protein, humanPoly-ADP-Ribose Binding ProteinsEndometrial CancerMolecular ProfilingNext-Generation Sequencing

Identifiers

PMID39971443
PMCPMC13051393

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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.