Evidence map›Paper›PMID 37056832›Full record

ArticleAmerican journal of translational research2023

Construction of a prognostic model of luteolin for endometrial carcinoma.

Junde Zhao, Wenjian Jiao, Xiaohui Sui, Jiani Zou, Jiuling Wang, Zhiheng Lin

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
9.1field-weighted citation impact, top 2% of its field
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

36 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Junde ZhaoShandong University of Traditional Chinese Medicine Jinan 250014, Shandong, China.
Wenjian JiaoShandong University of Traditional Chinese Medicine Jinan 250014, Shandong, China.
Xiaohui SuiShandong University of Traditional Chinese Medicine Jinan 250014, Shandong, China.
Jiani ZouShandong University of Traditional Chinese Medicine Jinan 250014, Shandong, China.
Jiuling WangOffice of Medical Insurance Management, Qilu Hospital of Shandong University Jinan 250012, Shandong, China.
Zhiheng LinShandong University of Traditional Chinese Medicine Jinan 250014, Shandong, China.
Shandong University of Traditional Chinese Medicine · CNQilu Hospital of Shandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveEndometrial cancer is one of the most common tumors of the female reproductive system, and the existing treatment options for advanced and metastatic endometrial cancer have certain limitations. The antitumor activity of luteolin has been gradually discovered. The purpose of this study was to predict the potential of luteolin in the treatment of endometrial cancer and to provide reference for future clinical drug use.

methodsThe target gene database of luteolin and differential gene dataset of uterine corpus endometrial carcinoma (UCEC) have been constructed to obtain the differential genes (DR-DEGs) for luteolin and UCEC. The Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis are performed at the same time. Genes associated with prognosis in DR-DEGs were screened and validated using univariate and multivariate COX risk regression analysis so as to construct a prognostic model. Genes are divided into high-risk and low-risk groups according to risk scores for survival analysis and the predictive effect of the model is evaluated. The role of immune function in UCEC is investigated by immune infiltration and immune checkpoint analysis Finally, Transwell experiment was conducted to investigate the effect of luteolin on the migration ability of endometrial cancer cells, and the expression changes of MMP1, IL-17 and VEGF were detected by q-PCR.

resultsThrough the GO, KEGG and GSEA enrichment analysis, we have found a significant enrichment in "IL 17 signaling (IL-17) pathway", "oxidative stress response" and "HOMOLOGOUS_RECOMBINATION". Through multivariate COX risk regression analysis, four genes associated with the prognosis are harvested, including "PRSS1, MMP1, ERBB2 and NUF2" which belong to high-risk genes. Kaplan-Meier analysis shows that the survival rate in the high risk group is lower than that in the low risk group, and the receiver operating characteristic (ROC) curve reveals that the predictive effect of the model is good and stable (area under 1-year curve (AUC) 0.569, two-year AUC 0.628 and three-year AUC 0.653). Immune infiltration and immune checkpoint analysis suggest that "CD40", "T cells regulatory (Tregs)", "dendritic cells resting" and "dendritic cells activated" are correlated with survival and prognosis in UCEC patients. In in vitro experiments, we found that the migration ability of endometrial cancer cells was significantly reduced after luteolin treatment, and the expressions of MMP1, IL-17 and VEGF were all decreased.

conclusionThrough bioinformatic analysis, we found that luteolin could slow down the progression of UCEC by inhibiting the production of inflammatory mediators such as IL-17 and oxidative stress, and constructed genetic prognostic models associated with them: PRSS1, MMP1, ERBB2 and NUF2, respectively. In addition, we found that luteolin has an inhibitory effect on the migration of endometrial cancer cells and can reduce the expressions of MMP1, IL-17 and VEGF, thus easing the progression of endometrial cancer.

Indexed as

bioinformatics analysisexperimental verificationLuteolintreatmentUCEC

Identifiers

PMID37056832
PMCPMC10086912
OpenAlexW4365478813

What OpenQuestion holds

Textmetadata
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.