Evidence map›Paper›PMID 40442848›Full record

ArticleJournal of ovarian research2025

Single-cell RNA sequencing reveals the role of GTF2F2 in ovarian cancer oncogenesis and progression.

Haiyang Du, Gao Si, Jiqing Si, Xuejie Song, Fuchun Si

Abstract read
In one paragraph

Article 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

Haiyang DuTraditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, 450046, China.
Gao SiDepartment of Orthopedic, The Third Hospital of Peking University, Beijing, 100029, China.
Jiqing SiHenan Hospital of TCM, The Second Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou, 450046, China.
Xuejie SongTraditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, 450046, China.
Fuchun SiTraditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, 450046, China. sifc2000@hotmail.com.

Funding

2022 Provincial Science and Technology R&D PlanJoint Fund (cultivation of superior disciplines) No: 222301420024Key scientific research projects of universities of Henan Provincial Department of Education No:21A360018The research was funded by the Henan science and technology research project NO.222102310187
6 · The paper itself

Abstract

backgroundOvarian cancer is one of the most common malignancies of the female reproductive system and is associated with poor prognosis. This study aimed to utilize single-cell RNA sequencing to investigate the heterogeneity of malignant epithelial cells in ovarian cancer, focusing on their potential functions and the implications for treatment and prognosis.

methodsSingle-cell RNA sequencing data were clustered using a single-cell transcriptome clustering method, and malignant epithelial cells were identified through copy number variation analysis. The interaction patterns between different malignant subpopulations and immune/stromal cells were analyzed using cell-to-cell communication analysis. A risk score (URS) model based on the UBE2C + epithelial subpopulation was then constructed through LASSO and multivariable Cox regression. High and low URS groups were compared in terms of tumor mutational burden (TMB), survival outcomes, and drug sensitivity. Finally, the role of GTF2F2 in ovarian cancer progression was validated through gene knockdown experiments in an ovarian cancer cell line (ES-2).

resultsThree major malignant epithelial cell subpopulations were identified (TMSB4X + Epi, TSC22D1 + Epi, and UBE2C + Epi). The UBE2C + Epi subpopulation exhibited higher stemness and greater invasive potential. The constructed URS model effectively stratified patients into high- and low-risk groups, with the high-risk group displaying a higher TMB level (p = 0.00011). Drug sensitivity predictions indicated that osimertinib, rapamycin, and dihydrorotenone might have stronger inhibitory effects in the high-risk group, whereas ERK inhibitors were more effective in the low-risk group. Functional assays demonstrated that GTF2F2 knockdown significantly suppressed ovarian cancer cell migration and invasion. Western blot analyses further showed elevated E-cadherin and reduced N-cadherin expression, suggesting that GTF2F2 may promote epithelial-mesenchymal transition (EMT).

conclusionThe risk score model established in this study offers a novel framework for patient stratification and personalized therapy. Notably, the identification of the UBE2C + Epi subpopulation and key genes such as GTF2F2 highlights potential diagnostic and therapeutic targets, shedding light on the pathogenesis of ovarian cancer and paving the way for precision medicine approaches.

Indexed as

CarcinogenesisOvarian NeoplasmsTranscription Factors, TFIICell Line, TumorDisease ProgressionFemaleGene Expression Regulation, NeoplasticHumansPrognosisSequence Analysis, RNASingle-Cell AnalysisTranscription Factors, TFIIEMTGTF2 F2Ovarian cancerSingle-cell RNA sequencingUBE2 C + Epi

Identifiers

PMID40442848
PMCPMC12121145

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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.