ArticleJournal of ovarian research2020
Bioinformatics analysis of gene expression profile of serous ovarian carcinomas to screen key genes and pathways.
Article in Journal of ovarian research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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.
Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- Article
- Multi-omics analysis reveals the panoramic picture of TOP2A in pan-cancer.Scientific reports · 2025Article
- Mitotic Functions and Characters of KIF11 in Cancers.Biomolecules · 2024Review
- Novel immune-related gene signature for risk stratification and prognosis prediction in ovarian cancer.Journal of ovarian research · 2023Article
- CDC20 is a novel biomarker for improved clinical predictions in epithelial ovarian cancer.American journal of cancer research · 2022Article
- Leveraging Genomics, Transcriptomics, and Epigenomics to Understand the Biology and Chemoresistance of Ovarian Cancer.Cancers · 2021Review
- Review
- The Progression and Prospects of the Gene Expression Profiling in Ovarian Epithelial Cancer.Gynecology and minimally invasive therapyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundSerous ovarian carcinomas (SCA) are the most common and most aggressive ovarian carcinoma subtype which etiology remains unclear. To investigate the prospective role of mRNAs in the tumorigenesis and progression of SCA, the aberrantly expressed mRNAs were calculated based on the NCBI-GEO RNA-seq data.
resultsOf 21,755 genes with 89 SCA and SBOT cases from 3 independent laboratories, 59 mRNAs were identified as differentially expressed genes (DEGs) (|log
conclusionsFrom all the above results, we speculate that KIF11, CDC20 and TOP2A played an important role in SCA.
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Identifiers
What OpenQuestion holds
Registered trials
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.