Evidence map›Paper›PMID 36114548›Full record

ReviewJournal of experimental & clinical cancer research : CR2022

Harnessing preclinical models for the interrogation of ovarian cancer.

Tianyu Qin, Junpeng Fan, Funian Lu, Li Zhang, Chen Liu, Qiyue Xiong, Yang Zhao, Gang Chen, Chaoyang Sun

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of experimental & clinical cancer research : CR, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. PD-1Journal of experimental & clinical cancer research : CR · 2025
    Article
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  6. Article
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  8. Review
  9. Article
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  13. Review
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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

9 authors.

Tianyu Qin *Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Research building of Tongji Hospital, No.2 Jiankang Avenue, Caidian Street, Caidian District, Wuhan, 430030, China.
Junpeng Fan *Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Research building of Tongji Hospital, No.2 Jiankang Avenue, Caidian Street, Caidian District, Wuhan, 430030, China.
Funian LuDepartment of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Research building of Tongji Hospital, No.2 Jiankang Avenue, Caidian Street, Caidian District, Wuhan, 430030, China.
Li ZhangDepartment of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Research building of Tongji Hospital, No.2 Jiankang Avenue, Caidian Street, Caidian District, Wuhan, 430030, China.
Chen LiuDepartment of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Research building of Tongji Hospital, No.2 Jiankang Avenue, Caidian Street, Caidian District, Wuhan, 430030, China.
Qiyue XiongDepartment of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Research building of Tongji Hospital, No.2 Jiankang Avenue, Caidian Street, Caidian District, Wuhan, 430030, China.
Yang ZhaoDepartment of Plastic Cosmetic and Burn Surgery, Taihe Hospital, Hubei University of Medicine, Shiyan, 442008, China.
Gang ChenDepartment of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Research building of Tongji Hospital, No.2 Jiankang Avenue, Caidian Street, Caidian District, Wuhan, 430030, China. gumpc@126.com.
Chaoyang SunDepartment of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Research building of Tongji Hospital, No.2 Jiankang Avenue, Caidian Street, Caidian District, Wuhan, 430030, China. suncydoctor@gmail.com.ORCID http://orcid.org/0000-0003-2469-1638

Funding

Beijing Kanghua Foundation for Development of Traditional Chinese and Western Medicine KH-2021-LQJJ-006Science Fund for Distinguished Young Scholars of Hubei Province 2020CFA066The Key R&D Program of Hubei Province 2020BCA067The Nature and Science Foundation of China 81874106The Nature and Science Foundation of China 81974408The Nature and Science Foundation of China 82073259
6 · The paper itself

Abstract

Ovarian cancer (OC) is a heterogeneous malignancy with various etiology, histopathology, and biological feature. Despite accumulating understanding of OC in the post-genomic era, the preclinical knowledge still undergoes limited translation from bench to beside, and the prognosis of ovarian cancer has remained dismal over the past 30 years. Henceforth, reliable preclinical model systems are warranted to bridge the gap between laboratory experiments and clinical practice. In this review, we discuss the status quo of ovarian cancer preclinical models which includes conventional cell line models, patient-derived xenografts (PDXs), patient-derived organoids (PDOs), patient-derived explants (PDEs), and genetically engineered mouse models (GEMMs). Each model has its own strengths and drawbacks. We focus on the potentials and challenges of using these valuable tools, either alone or in combination, to interrogate critical issues with OC.

Indexed as

Ovarian NeoplasmsAnimalsCarcinoma, Ovarian EpithelialDisease Models, AnimalFemaleHumansMiceOrganoidsGenetically engineered mouse modelsOvarian cancerPatient-derived organoidsPatient-derived xenograftPersonalised medicinePreclinical models

Identifiers

PMID36114548
PMCPMC9479310

What Socratic holds

Textmetadata
LicenceCC BY
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.