ArticleCancer cell international2020
Identification of four hub genes as promising biomarkers to evaluate the prognosis of ovarian cancer in silico.
Article in Cancer cell international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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.
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
23 citing papers in PubMed, 55 citations in OpenAlex.
- Biomaterials for biomarker imaging and detection.Journal of advanced research · 2026Review
- A comprehensive review of the emerging role of NRF3 in ovarian cancer tumorigenesis and progression.Journal of ovarian research · 2026Review
- Identification of key candidate genes for ovarian cancer using integrated statistical and machine learning approaches.Briefings in bioinformatics · 2025Article
- Effects of lncRNA RP11-499E18.1 on the malignant biological behavior of ovarian cancer cells.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025Article
- CAP superfamily proteins in human: a new target for cancer therapy.Medical oncology (Northwood, London, England) · 2024Review
- Identification and validation of IRF6 related to ovarian cancer and biological function and prognostic value.Journal of ovarian research · 2024Article
- Advances in Genomic Data and Biomarkers: Revolutionizing NSCLC Diagnosis and Treatment.Cancers · 2023Review
- Role of fibrilins in human cancer: A narrative review.Health science reports · 2023Article
- Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer.Oncology research · 2023Article
- The extracellular matrix glycoprotein fibrillin-1 in health and disease.Frontiers in cell and developmental biology · 2023Review
- Identification of key genes associated with polycystic ovary syndrome (PCOS) and ovarian cancer using an integrated bioinformatics analysis.Journal of ovarian research · 2022Article
- Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer.Computational and mathematical methods in medicine · 2022Article
- Identification of a Gene Signature of Cancer-Associated Fibroblasts to Predict Prognosis in Ovarian Cancer.Frontiers in genetics · 2022Article
- Deciphering the immune landscape dominated by cancer-associated fibroblasts to investigate their potential in indicating prognosis and guiding therapeutic regimens in high grade serous ovarian carcinoma.Frontiers in immunology · 2022Article
- A pancancer overview of FBN1, asprosin and its cognate receptor OR4M1 with detailed expression profiling in ovarian cancer.Oncology letters · 2021Article
- Predictive value of RAD51 on the survival and drug responsiveness of ovarian cancer.Cancer cell international · 2021Article
- The expression and prognostic value of the epidermal growth factor receptor family in glioma.BMC cancer · 2021Article
- Identification of a three-gene-based prognostic model in multiple myeloma using bioinformatics analysis.PeerJ · 2021Article
- Low Expression of RILPL2 Predicts Poor Prognosis and Correlates With Immune Infiltration in Endometrial Carcinoma.Frontiers in molecular biosciences · 2021Article
- LncRNA RP11-499E18.1 Inhibits Proliferation, Migration, and Epithelial-Mesenchymal Transition Process of Ovarian Cancer Cells by Dissociating PAK2-SOX2 Interaction.Frontiers in cell and developmental biology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOvarian cancer (OvCa) is one of the most fatal cancers among females in the world. With growing numbers of individuals diagnosed with OvCa ending in deaths, it is urgent to further explore the potential mechanisms of OvCa oncogenesis and development and related biomarkers.
methodsThe gene expression profiles of GSE49997 were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was applied to explore the most potent gene modules associated with the overall survival (OS) and progression-free survival (PFS) events of OvCa patients, and the prognostic values of these genes were exhibited and validated based on data from training and validation sets. Next, protein-protein interaction (PPI) networks were built by GeneMANIA. Besides, enrichment analysis was conducted using DAVID website.
resultsAccording to the WGCNA analysis, a total of eight modules were identified and four hub genes (MM > 0.90) in the blue module were reserved for next analysis. Kaplan-Meier analysis exhibited that these four hub genes were significantly associated with worse OS and PFS in the patient cohort from GSE49997. Moreover, we validated the short-term (4-years) and long-term prognostic values based on the GSE9891 data, respectively. Last, PPI networks analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed several potential mechanisms of four hub genes and their co-operators participating in OvCa progression.
conclusionFour hub genes (
Indexed as
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.