Evidence map›Paper›PMID 31708970›Full record

ArticleFrontiers in genetics2019

Identification of Potential Biomarkers in Association With Progression and Prognosis in Epithelial Ovarian Cancer by Integrated Bioinformatics Analysis.

Jinhui Liu, Huangyang Meng, Siyue Li, Yujie Shen, Hui Wang, Wu Shan, Jiangnan Qiu, Jie Zhang, Wenjun Cheng

Abstract read
In one paragraph

Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

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  14. Knockdown of DLGAP5 suppresses cell proliferation, induces GExperimental and therapeutic medicine · 2021
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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.

Jinhui LiuDepartment of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Huangyang MengDepartment of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Siyue LiDepartment of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Yujie ShenDepartment of Otorhinolaryngology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Hui WangDepartment of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Wu ShanDepartment of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Jiangnan QiuDepartment of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Jie ZhangDepartment of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Wenjun ChengDepartment of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial ovarian cancer (EOC) is one of the malignancies in women, which has the highest mortality. However, the microlevel mechanism has not been discussed in detail. The expression profiles GSE27651, GSE38666, GSE40595, and GSE66957 including 188 tumor and 52 nontumor samples were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were filtered using R software, and we performed functional analysis using the clusterProfiler. Cytoscape software, the molecular complex detection plugin and database STRING analyzed DEGs to construct protein-protein interaction network. We identified 116 DEGs including 81 upregulated and 35 downregulated DEGs. Functional analysis revealed that they were significantly enriched in the extracellular region and biosynthesis of amino acids. We next identified four bioactive compounds (vorinostat, LY-294002,trichostatin A, and tanespimycin) based on ConnectivityMap. Then 114 nodes were obtained in protein-protein interaction. The three most relevant modules were detected. In addition, according to degree ≥ 10, 14 core genes including FOXM1, CXCR4, KPNA2, NANOG, UBE2C, KIF11, ZWINT, CDCA5, DLGAP5, KIF15, MCM2, MELK, SPP1, and TRIP13 were identified. Kaplan-Meier analysis, Oncomine, and Gene Expression Profiling Interactive Analysis showed that overexpression of FOXM1, SPP1, UBE2C, KIF11, ZWINT, CDCA5, UBE2C, and KIF15 was related to bad prognosis of EOC patients. CDCA5, FOXM1, KIF15, MCM2, and ZWINT were associated with stage. Receiver operating characteristic (ROC) curve showed that messenger RNA levels of these five genes exhibited better diagnostic efficiency for normal and tumor tissues. The Human Protein Atlas database was performed. The protein levels of these five genes were significantly higher in tumor tissues compared with normal tissues. Functional enrichment analysis suggested that all the hub genes played crucial roles in citrate cycle tricarboxylic acid cycle. Furthermore, the univariate and multivariate Cox proportional hazards regression showed that ZWINT was independent prognostic indictor among EOC patients. The genes and pathways discovered in the above studies may open a new direction for EOC treatment.

Indexed as

bioinformatical analysisbiomarkerCmapdifferentially expressed genesepithelial ovarian cancerprognosisprotein–protein interaction

Identifiers

PMID31708970
PMCPMC6822059

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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.