Evidence map›Paper›PMID 39707532›Full record

ArticleJournal of ovarian research2024

TIGIT

Fengzhen Chen, Yanying Xu, Xiangyu Liu, Na Dong, Lei Tian

Abstract read
In one paragraph

Article in Journal of ovarian research, 2024. 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. Article
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.

Fengzhen ChenDepartment of Gynecology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China. cfz_blue_7@163.com.
Yanying XuDepartment of Gynecology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
Xiangyu LiuTianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China.
Na DongDepartment of Gynecology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
Lei TianDepartment of Gynecology and Obstetrics, The Affiliated Hospital of Nankai University, Tianjin No. 4 Hospital, Tianjin, 300222, China.

Funding

the Science and Technology Fund of Tianjin Municipal Education Commission 2021KJ231
6 · The paper itself

Abstract

Immune checkpoint-based immunotherapy has shown limited efficacy in the treatment of ovarian cancer. In recent years, the emergence of immune checkpoint co-targeting therapies, led by the combination targeting of TIGIT and FAK, has shown promise in ovarian cancer treatment. Our preliminary research indicates that TIGIT is predominantly expressed in regulatory T cells during ovarian cancer. However, the therapeutic impact of TIGIT targeting based on regulatory T cells in ovarian cancer remains to be elucidated. We utilized ID8 cells to establish a mouse model of ovarian cancer. Through flow cytometry and co-culture methods, we validated the relationship between the functionality of regulatory T cells and tumor masses, and confirmed the crucial role of TIGIT in immune suppression in ovarian cancer. Furthermore, using Foxp3-diphtheria toxin receptor (DTR) mice, we substantiated that the combined TIGIT antibody treatment, based on targeting regulatory T cells, effectively slowed down the progression of ovarian cancer. Taken together, our results have demonstrated that dual targeting of regulatory T cells and TIGIT effectively retards tumor growth, laying the groundwork for the clinical application of immune checkpoint combination therapies. Future research in ovarian cancer immunotherapy is leaning towards a strategy that combines multiple targets, and specific cell-type immunotherapies.

Indexed as

CD8-Positive T-LymphocytesDisease Models, AnimalOvarian NeoplasmsProgrammed Cell Death 1 ReceptorReceptors, ImmunologicT-Lymphocytes, RegulatoryAnimalsCell Line, TumorFemaleHumansMiceProgrammed Cell Death 1 ReceptorReceptors, ImmunologicT cell Ig and ITIM domain protein, mouseOvarian cancerPD-1Regulatory T cellTIGIT

Identifiers

PMID39707532
PMCPMC11660701

What OpenQuestion 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 OpenQuestion graph.