Evidence map›Paper›PMID 39635022›Full record

ArticleThe EPMA journal2024

Pharmacoproteomics reveals energy metabolism pathways as therapeutic targets of ivermectin in ovarian cancer toward 3P medical approaches.

Zhijun Li, Na Li, Marie Louise Ndzie Noah, Qianwen Shao, Xianquan Zhan

Abstract read
In one paragraph

Article in The EPMA journal, 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.

Zhijun LiShandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, Shandong 250117 People's Republic of China.
Na LiShandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, Shandong 250117 People's Republic of China.
Marie Louise Ndzie NoahShandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, Shandong 250117 People's Republic of China.
Qianwen ShaoShandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, Shandong 250117 People's Republic of China.
Xianquan ZhanShandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, Shandong 250117 People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Ovarian cancer is the malignant tumor with the highest mortality rate in the female reproductive system, enormous socio-economic burden, and limited effective drug therapy. There is an urgent need to find novel effective drugs for ovarian cancer therapy. Our previous in vitro studies demonstrate that ivermectin effectively inhibits ovarian cancer cells and affects energy metabolism pathways. This study aims to clarify in vivo mechanisms and therapeutic targets of ivermectin in the treatment of ovarian cancer to establish predictive biomarkers, guide personalized treatments, and improve preventive strategies in the framework of 3P medicine. Methods: A TOV-21G tumor-bearing mouse model was constructed based on histopathological data and biochemical parameters. TMT-based proteomic analysis was performed on tumor tissues from the different treatment groups. All significantly differentially abundant proteins were characterized by hierarchical clustering, Gene Ontology (GO) enrichment analyses, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In addition, the data were integrated and analyzed with the proteomic data of clinical ovarian cancer tissues from our previous study and the proteomic data of ivermectin intervention in ovarian cancer cells to identify key regulators of ivermectin. Results: Ivermectin (10 mg/kg) had a significant anti-ovarian cancer effect in mice, with a tumor inhibitory rate of 61.5%. Molecular changes in tumor tissue of ivermectin-treated mice were established, and protein-protein interaction (PPI) analysis showed that the main differential pathway networks included the TCA cycle, propanoate metabolism, 2-0xocarboxyacid metabolism, and other pathways. Integrating our previous clinical ovarian cancer tissue and cell experimental data, this study found that ivermectin significantly interfered with the energy metabolic pathways of ovarian cancer, including glycolysis, TCA cycle, oxidative phosphorylation, and other related pathways. Conclusions: This study evaluated the anti-ovarian cancer effect in vitro and in vivo, and its specific regulatory effect on energy metabolism. The expressions of drug target molecules in the energy metabolism pathway of ovarian cancer will be used to guide the diagnosis and prevention of ovarian cancer. The significant efficacy of ivermectin will be applied to the treatment of ovarian cancer and personalized medication. This has guiding significance for the clinical diagnosis, treatment, personalized medication, and prognosis evaluation of ovarian cancer. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00385-1.

Indexed as

AutophagyBiomarker guided treatmentsEnergy metabolismIvermectinMitochondriaOvarian cancerPersonalized drug therapyPharmacoproteomicsPredictive preventive personalized medicine (PPPM / 3PM)Prognosis evaluation

Identifiers

PMID39635022
PMCPMC11612093

What Socratic holds

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Registered trials

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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 Socratic graph.