Evidence map›Paper›PMID 40046734›Full record

ArticleFrontiers in pharmacology2025

Uncovering potential targets for antibody-drug conjugates in the treatment of gynecologic malignancies.

Yuying Jiang, Yuance Xu, Junqi He, Lei Sui, Tian Li, Nannan Xia, Qin Yao

Abstract read
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Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 citing papers in PubMed.

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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

7 authors.

Yuying JiangDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Yuance XuDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Junqi HeDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Lei SuiDepartment of Obstetrics and Gynecology, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, China.
Tian LiDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Nannan XiaDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Qin YaoDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Antibody-drug conjugates (ADCs) play an important role in the targeted therapy of gynecological malignancies. The purpose of this study was to investigate the expression of targets in gynecologic malignancies in order to predict the selection of targets for the development of antibody-drug conjugates. Methods: In this article, we identified existing ADCs and their targets through clinical trial databases and public genomic datasets, performed differential analysis of tumor antigen targets (TATs) expression between tumor and normal tissues, and evaluated the necessity of the targets for tumor cell lines. Results: In gynecologic malignancies, we have identified several highly expressed TATs, some of which have been targeted by FDA-approved ADCs, such as TROP2 and Nectin-4, although these drugs have not been approved for the treatment of gynecologic cancers. At the same time, we also observed that some targets of ADCs that have not yet been approved by the FDA also show high expression levels in gynecologic malignancies tissues, such as MSLN, ERBB3, NaPi2b, etc. Furthermore, we identified TATs with high expression levels in various pathological subtypes of ovarian, endometrial, and cervical cancer. Notably, some TATs are crucial to the survival of tumor cells, such as CD71, TOP1, and TDGF1, which are essential for the survival of ovarian, endometrial, cervical, and other tumor cells. Conclusion: We have innovatively predicted the potential targets of ADCs in treating gynecological malignancies and provided a new perspective on applying some FDA-approved ADCs in indications for gynecological cancers.

Indexed as

antibody-drug conjugates (ADCs)gynecological malignanciesnew therapiestargeted therapytarget prediction

Identifiers

PMID40046734
PMCPMC11880013

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