ArticleJournal of cellular and molecular medicine2020
Systematic prediction of key genes for ovarian cancer by co-expression network analysis.
Article in Journal of cellular and molecular medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 24 citations in OpenAlex.
- Article
- Roles of MARCKSL1, MCM6, RFC4, and PLAU genes in esophageal cancer and their association with radiotherapy response.Scientific reports · 2025Article
- Quantitative and qualitative metrics of tumor stroma in predicting ovarian cancer outcomes and expansion of its study with AI-based tools.Molecular therapy. Oncology · 2025Review
- Collagen fiber density observed in metastatic ovarian cancer promotes tumor cell adhesion.Acta biomaterialia · 2025Article
- Multi-dimensional characterization of cellular states reveals clinically relevant immunological subtypes and therapeutic vulnerabilities in ovarian cancer.Journal of translational medicine · 2025Article
- Tumor-associated fibrosis: a unique mechanism promoting ovarian cancer metastasis and peritoneal dissemination.Cancer metastasis reviews · 2024Review
- Loss of mitochondrial pyruvate carrier 1 supports proline-dependent proliferation and collagen biosynthesis in ovarian cancer.Molecular metabolism · 2024Article
- HuR-dependent expression of Wisp1 is necessary for TGFβ-induced cardiac myofibroblast activity.Journal of molecular and cellular cardiology · 2023Article
- MLLT11-TRIL complex promotes the progression of endometrial cancer through PI3K/AKT/mTOR signaling pathway.Cancer biology & therapy · 2022Article
- TAF1A and ZBTB41 serve as novel key genes in cervical cancer identified by integrated approaches.Cancer gene therapy · 2021Article
- Adipocyte-specific deletion of HuR induces spontaneous cardiac hypertrophy and fibrosis.American journal of physiology. Heart and circulatory physiology · 2021Article
- Integrated study of miR-215 promoting breast cancer cell apoptosis by targeting RAD54B.Journal of cellular and molecular medicine · 2021Article
- Identification of Potential Biomarkers Associated with Prognosis in Gastric Cancer via Bioinformatics Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2021Article
- Integrated microRNA and mRNA signatures associated with overall survival in epithelial ovarian cancer.PloS one · 2021Article
- Integrated Protein-Protein Interaction and Weighted Gene Co-expression Network Analysis Uncover Three Key Genes in Hepatoblastoma.Frontiers in cell and developmental biology · 2021Article
- Systematic prediction of key genes for ovarian cancer by co-expression network analysis.Journal of cellular and molecular medicine · 2020Article
- Detailed Molecular Mechanism and Potential Drugs for COL1A1 in Carboplatin-Resistant Ovarian Cancer.Frontiers in oncology · 2020Article
- Bioinformatics Analysis of Key Genes and Pathways of Cervical Cancer.OncoTargets and therapy · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer (OC) is the most lethal gynaecological malignancy, characterized by high recurrence and mortality. However, the mechanisms of its pathogenesis remain largely unknown, hindering the investigation of the functional roles. This study sought to identify key hub genes that may serve as biomarkers correlated with prognosis. Here, we conduct an integrated analysis using the weighted gene co-expression network analysis (WGCNA) to explore the clinically significant gene sets and identify candidate hub genes associated with OC clinical phenotypes. The gene expression profiles were obtained from the MERAV database. Validations of candidate hub genes were performed with RNASeqV2 data and the corresponding clinical information available from The Cancer Genome Atlas (TCGA) database. In addition, we examined the candidate genes in ovarian cancer cells. Totally, 19 modules were identified and 26 hub genes were extracted from the most significant module (R
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.