Evidence map›Paper›PMID 38486335›Full record

ArticleJournal of ovarian research2024

Unraveling the molecular mechanisms of lymph node metastasis in ovarian cancer: focus on MEOX1.

Jiajia Li, Yihua Sun, Xiuling Zhi, Yating Sun, Zulimire Abudousalamu, Qianhan Lin, Bin Li, Liangqing Yao, Mo Chen

Open access · goldAbstract 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.8field-weighted citation impact, top 8% 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

6 citing papers in PubMed, 7 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

9 authors at 2 institutions in 1 country.

Jiajia Li *Department of Gynecology Oncology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, 200011, China.
Yihua Sun *Department of Pathology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, 200011, China.
Xiuling ZhiDepartment of Physiology and Pathophysiology, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China.
Yating SunDepartment of Gynecology Oncology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, 200011, China.
Zulimire AbudousalamuDepartment of Gynecology Oncology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, 200011, China.
Qianhan LinDepartment of Gynecology Oncology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, 200011, China.
Bin LiDepartment of Physiology and Pathophysiology, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China.
Liangqing YaoDepartment of Gynecology Oncology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, 200011, China. yaoliangqing@163.com.
Mo ChenDepartment of Gynecology Oncology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, 200011, China. chenmo_nicy@163.com.
Obstetrics and Gynecology Hospital of Fudan University · CNFudan University · CN

Funding

National Natural Science Foundation of China 82002750Shanghai Municipal Health and Family Planning Commission 20184Y0254Shanghai Pujiang Programme 23PJD009
6 · The paper itself

Abstract

backgroundLymph node metastasis (LNM) is a major factor contributing to the high mortality rate of ovarian cancer, making the treatment of this disease challenging. However, the molecular mechanism underlying LNM in ovarian cancer is still not well understood, posing a significant obstacle to overcome.

resultsThrough data mining from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we have identified MEOX1 as a specific gene associated with LNM in ovarian cancer. The expression of MEOX1 was found to be relatively high in serous ovarian adenocarcinoma, and its higher expression were associated with increased tumor grade and poorer clinical prognosis for ovarian cancer patients. Bioinformatics analysis revealed that MEOX1 exhibited the highest mRNA levels among all cancer types in ovarian cancer tissues and cell lines. Furthermore, gene set enrichment analysis (GSEA) and pathway analysis demonstrated that MEOX1 was involved in various LNM-related biological activities, such as lymphangiogenesis, lymphatic vessel formation during metastasis, epithelial-mesenchymal transition (EMT), G2/M checkpoint, degradation of extracellular matrix, and collagen formation. Additionally, the expression of MEOX1 was positively correlated with the expression of numerous prolymphangiogenic factors in ovarian cancer. To validate our findings, we conducted experiments using clinical tissue specimens and cell lines, which confirmed that MEOX1 was highly expressed in high-grade serous ovarian cancer (HGSOC) tissues and various ovarian cancer cell lines (A2780, SKOV3, HO8910, and OVCAR5) compared to normal ovarian tissues and normal ovarian epithelial cell line IOSE-80, respectively. Notably, we observed a higher protein level of MEOX1 in tumor tissues of LNM-positive HGSOC compared to LNM-negative HGSOC. Moreover, our fundamental experiments demonstrated that suppression of MEOX1 led to inhibitory effects on ovarian cancer cell proliferation and EMT, while overexpression of MEOX1 enhanced the proliferation and EMT capacities of ovarian cancer cells.

conclusionsThe results of our study indicate that MEOX1 plays a role in the lymph node metastasis of ovarian cancer by regulating multiple biological activities, including the proliferation and EMT of ovarian cancer, lymphangiogenesis, and ECM remodeling. Our findings suggest that MEOX1 could serve as a potential biomarker for the diagnosis and treatment of ovarian cancer with LNM.

Indexed as

Ovarian NeoplasmsCarcinoma, Ovarian EpithelialCell Line, TumorCell ProliferationFemaleHomeodomain ProteinsHumansLymphatic MetastasisTranscription FactorsHomeodomain ProteinsMEOX1 protein, humanTranscription FactorsBioinformaticsLymphangiogenesisLymph node metastasisMEOX1Ovarian cancer

Identifiers

PMID38486335
PMCPMC10938838
OpenAlexW4392817613

What OpenQuestion 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 OpenQuestion graph.