ArticleMedicine2022
Identification of prognosis-related hub genes of ovarian cancer through bioinformatics analyses and experimental verification.
Article in Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 19 citations in OpenAlex.
- Exploring Molecular Signature and Prognostic Biomarkers in Ovarian Cancer: Insights From Late-Stage, Recurrent, and Metastatic Tumors.Biotechnology and applied biochemistry · 2026Article
- Identification of key candidate genes for ovarian cancer using integrated statistical and machine learning approaches.Briefings in bioinformatics · 2025Article
- Identification of a novel chemotherapy benefit index for patients with advanced ovarian cancer based on Bayesian network analysis.PloS one · 2025Article
- The oncogenic role and regulatory mechanism of PGK1 in human non-small cell lung cancer.Biology direct · 2024Article
- The Tumor Stemness Indice mRNAsi can Act as Molecular Typing Tool for Lung Adenocarcinoma.Biochemical genetics · 2023Article
- Orphan G Protein-Coupled Receptor GPR37 as an Emerging Therapeutic Target.ACS chemical neuroscience · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer (OC) is a lethal and highly prevalent disease in women worldwide. The disease is often diagnosed in late stages, which leads to its rapid progression and low survival rate. This study aims to identify new prognostic genes for OC. Based on 2 datasets from the National Center for Biotechnology Information Gene Expression Omnibus public database, we constructed 2 Weighted Gene Co-expression Network Analysis networks. Then, we selected and intersected 2 key modules to screen key genes. Enrichment analyses were performed, and a protein-protein interaction network was constructed. The cytoHubba plugin of Cytoscape and survival analysis were used to screen hub genes related to prognosis. The expression of hub genes was analyzed by GEPIA and verified by quantitative Real-Time PCR. Gene alteration frequency analysis, gene set variation analysis, immune infiltration analysis, drug sensitivity analysis, tumor mutation burden, and neoantigen analyses were conducted to determine the prognostic value and molecular mechanisms of the hub genes. In total, 214 key genes were selected from 2 Weighted Gene Co-expression Network Analysis networks, and 3 hub genes, namely ALDH1A2, CLDN4, and GPR37, were identified as prognostic candidates through cytoHubba and survival analysis. Three hub genes were significantly associated with overall survival of OC patients. GEPIA and quantitative Real-Time PCR indicated that ALDH1A2 expression was significantly downregulated, while expression of CLDN4 and GPR37 was upregulated in OC samples compared with normal samples. CIBERSORT showed that 3 hub genes were closely associated with the infiltrating immune cells. GDSC showed that hub genes expression influenced IC50 values of chemotherapeutic drugs. OC patients with high expression of ALDH1A2 and CLDN4 had lower TMB and low ALDH1A2 expression could produce a larger number of neoantigens. In conclusion, the 3 hub genes (ALDH1A2, CLDN4 and GPR37) identified through bioinformatics analyses in the present study may serve as OC prognosis biomarkers. The study findings offer valuable insights into OC progression and mechanisms.
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.