Evidence map›Paper›PMID 42432867›Full record

ArticleCancer biomarkers : section A of Disease markers

A novel diagnostic model for early-stage high-grade serous ovarian cancer based on serum tRNA-derived fragments.

Xueyuan Zhao, Weijia Wen, Yan Jia, Li Yuan, Linna Chen, Songlin Liu, Haolin Fan, Hongye Jiang, Chaoyun Pan, Chunyu Zhang and 1 more

Abstract read
In one paragraph

Article in Cancer biomarkers : section A of Disease markers. 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

11 authors.

Xueyuan ZhaoDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.ORCID 0009-0005-0820-0765
Weijia WenDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Yan JiaDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Li YuanDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Linna ChenDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Songlin LiuDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Haolin FanDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Hongye JiangDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Chaoyun PanZhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Chunyu ZhangDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Shuzhong YaoDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early detection of ovarian cancer, particularly high-grade serous ovarian cancer (HGSOC), remains challenging due to the lack of reliable biomarkers. This study investigated the potential of tRNA-derived small RNAs (tsRNAs) as non-invasive diagnostic biomarkers using liquid biopsy. Using qRT-PCR, we analyzed the relative Ct values of selected tsRNAs in plasma samples from healthy controls and patients with early- and late-stage HGSOC. A logistic regression model constructed using the relative Ct value of the selected tsRNA demonstrated high sensitivity and specificity for distinguishing ovarian cancer patients from healthy controls, including those with early-stage disease. The model was validated in a multi-center cohort, and analysis confirmed the dysregulation of this tsRNA in tumor tissue compared to normal tissue. These findings suggest that this single plasma tsRNA may serve as a promising biomarker for early HGSOC detection, supporting its potential clinical utility pending further mechanistic studies.

Indexed as

Biomarkers, TumorCystadenocarcinoma, SerousOvarian NeoplasmsRNA, TransferAgedEarly Detection of CancerFemaleHumansMiddle AgedNeoplasm GradingNeoplasm StagingBiomarkers, TumorRNA, Transferdiagnosticmolecular biomarkersovarian cancer

Identifiers

PMID42432867
PMCPMC13354906

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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 OpenQuestion graph.