Evidence map›Paper›PMID 41514564›Full record

ReviewCancers2025

Molecular Classification of Endometrial Carcinomas: Review and Recent Updates.

Anita Kumari, Himani Kumar, Samuel E Harvey, Deyin Xing, Zaibo Li

Abstract readReview
In one paragraph

Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. 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

5 authors.

Anita KumariDepartment of Pathology, The Ohio State University, Columbus, OH 43210, USA.
Himani KumarDepartment of Pathology, The Ohio State University, Columbus, OH 43210, USA.ORCID 0009-0007-6035-1135
Samuel E HarveyDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.ORCID 0000-0002-2574-9005
Deyin XingDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Zaibo LiDepartment of Pathology, The Ohio State University, Columbus, OH 43210, USA.ORCID 0000-0003-1325-1696

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endometrial carcinoma (EC) continues to represent a major cause of gynecologic cancer-related mortality among women worldwide. Its multifactorial etiopathogenesis and underlying molecular heterogeneity have been the focus of extensive investigation. While traditional histological classification provides essential diagnostic insight, it is limited in predicting prognosis and therapeutic response due to significant interobserver variability. Recent advances in molecular biology and cancer genomics have profoundly enhanced understanding of EC pathogenesis. The Cancer Genome Atlas (TCGA) project delineated four distinct molecular subtypes of EC, POLE ultra-mutated, microsatellite instability hypermutated (MSI-H), copy number low (CNL) and copy number high (CNH), each defined by unique genomic alterations, histopathologic features, and clinical behaviors. These molecular groups demonstrate significant prognostic and therapeutic implications, correlating with differential outcomes and treatment responses. This review summarizes current evidence on the genomic landscape of endometrial carcinoma and underscores the pivotal role of molecular classification in improving diagnostic accuracy, prognostic stratification, and personalized therapy. Ongoing research into molecular biomarkers holds promise for refining patient management and optimizing clinical outcomes.

Indexed as

endometrial carcinomamicrosatellite instabilityp53POLE-ultramutated

Identifiers

PMID41514564
PMCPMC12785015

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.