Evidence map›Paper›PMID 41233888›Full record

ReviewJournal of ovarian research2025

T-cell receptor therapy in ovarian cancer: concepts and challenges.

Xiaohan Wang, Zhuoyao Li, Mengwen Zhang, Yunhe Yu, Weihua Tong

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of ovarian research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Xiaohan WangDepartment of Gynecologic Oncology, Gynecology and Obstetrics Centre, The First Hospital of Jilin University, Changchun, China.
Zhuoyao LiDepartment of Gynecologic Oncology, Gynecology and Obstetrics Centre, The First Hospital of Jilin University, Changchun, China.
Mengwen ZhangDepartment of Gynecologic Oncology, Gynecology and Obstetrics Centre, The First Hospital of Jilin University, Changchun, China.
Yunhe Yu *Department of Gynecologic Oncology, Gynecology and Obstetrics Centre, The First Hospital of Jilin University, Changchun, China. yuyunhe@jlu.edu.cn.
Weihua Tong *Department of Gynecologic Oncology, Gynecology and Obstetrics Centre, The First Hospital of Jilin University, Changchun, China. tongwh@jlu.edu.cn.

Funding

National Outstanding Youth Science Fund Project of National Natural Science Foundation of China (No.82403254
6 · The paper itself

Abstract

With high rates of occurrence, recurrence, and mortality, ovarian cancer(OC) is among the most prevalent malignant neoplasms of the female reproductive system, which frequently result in a poor prognosis. The limited efficacy of early diagnosis and screening measures results in 75% of patients being diagnosed at an advanced stage. Despite the achievements of conventional therapeutic modalities, these therapies continue to experience challenges, including the occurrence of relapses and the development of drugs resistance.Recent advancements in precision medicine have identified the T-cell receptor (TCR) as a pivotal biomarker for both early ovarian cancer diagnosis and immunotherapy, given its central role in antigen recognition. This paper elaborates on the structure and function of the T-cell receptor, TCR immunohistochemistry repertoire and detection technology, TCR repertoire application in disease prediction, and the TCR-based immunotherapy strategy (known as TCR-T-cell therapy), along with its application and challenge in ovarian cancer.

Indexed as

ImmunotherapyImmunotherapy, AdoptiveOvarian NeoplasmsReceptors, Antigen, T-CellFemaleHumansReceptors, Antigen, T-CellCancer Early DetectionCancer immunotherapyOvarian cancerT-cell receptorsTCR repertoireTCR therapy

Identifiers

PMID41233888
PMCPMC12616972

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.