Evidence mapPaperPMID 41912937Full record

ReviewCurrent oncology reports2026

Liquid Biopsy in Uterine Leiomyosarcoma: Current Biomarkers, Emerging Technologies, and Future Perspectives.

Danru Zhang, Hongbo Wang

Abstract readReview
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In one paragraph

Review in Current oncology reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Danru ZhangDepartment of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, People's Republic of China.ORCID http://orcid.org/0009-0000-1512-2041
Hongbo WangDepartment of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, People's Republic of China. drwanghb69@hust.edu.cn.ORCID http://orcid.org/0000-0001-7090-1750

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewUterine leiomyosarcoma (uLMS) is a rare but aggressive malignant mesenchymal tumor, accounting for 2-5% of uterine malignancies. Because its symptoms and imaging features often resemble those of benign uterine leiomyoma (LM), accurate preoperative diagnosis remain difficult. This review summarizes recent advances in liquid biopsy for uLMS and explores its potential for early detection, molecular characterization, and treatment monitoring. RECENT

findingsLiquid biopsy enables minimally invasive detection of tumor-derived components such as circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), non-coding RNAs, and extracellular vesicles (EVs). Recurrent mutations in TP53, RB1, and ATRX have been identified through ctDNA analysis, while CTCs, ncRNAs, and EVs provide complementary information for monitoring tumor dynamics and therapeutic response. Emerging technologies including CRISPR-Cas systems, nanotechnology, electrochemical biosensors, and multi-omics integration enhance detection sensitivity and specificity. Liquid biopsy holds promise for improving uLMS diagnosis and management. However, standardization and biomarker validation remain essential to achieve reliable clinical translation and enable earlier, more precise treatment strategies.

Indexed as

Biomarkers, TumorLeiomyosarcomaUterine NeoplasmsCirculating Tumor DNAFemaleHumansLiquid BiopsyNeoplastic Cells, CirculatingBiomarkers, TumorCirculating Tumor DNABiomarkerCirculating tumor DNALiquid biopsyNon-coding RNAUterine leiomyosarcoma

Identifiers

What Socratic holds

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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.