ArticleJournal of personalized medicine2021
Identification of Novel Biomarkers and Candidate Drug in Ovarian Cancer.
Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 22 citations in OpenAlex.
- Identification of ribosomal stress related signature genes and immune microenvironment analysis in ovarian cancer based on multi-machine learning.Discover oncology · 2026Article
- ATP synthasome contributes to efficient energy flux in malignant breast cancer.Molecular cancer · 2026Article
- CREB1 regulates RECQL4 to inhibit mitophagy and promote esophageal cancer metastasis.Journal of clinical biochemistry and nutrition · 2024Article
- Spatial and single-cell explorations uncover prognostic significance and immunological functions of mitochondrial calcium uniporter in breast cancer.Cancer cell international · 2024Article
- Spatial and single-cell analyses uncover links between ALKBH1 and tumor-associated macrophages in gastric cancer.Cancer cell international · 2024Article
- Review
- Identification of Driver Genes and miRNAs in Ovarian Cancer through an Integrated In-Silico Approach.Biology · 2023Article
- cAMP-Dependent Signaling and Ovarian Cancer.Cells · 2022Review
- Expression status and prognostic significance of mitochondrial dynamics OPA3 in human ovarian cancer.Aging · 2022Article
- Special Issue "Cancer Biomarker Research and Personalized Medicine".Journal of personalized medicine · 2022Article
- Article
- Integrative Multiomics Evaluation of IIDH1 Metabolic Enzyme as a Candidate Oncogene That is Correlated with Poor Prognosis and Immune Infiltration in Prostate Adenocarcinoma.Journal of oncology · 2022Article
- Article
- Ovarian Cancer: Biomarkers and Targeted Therapy.Biomedicines · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper investigates the expression of the CREB1 gene in ovarian cancer (OV) by deeply excavating the gene information in the multiple databases and the mechanism thereof. In short, we found that the expression of the CREB1 gene in ovarian cancer tissue was significantly higher than that of normal ovarian tissue. Kaplan-Meier survival analysis showed that the overall survival was significantly shorter in patients with high expression of the CREB1 gene than those in patients with low expression of the CREB1 gene, and the prognosis of patients with low expression of the CREB1 gene was better. The CREB1 gene may play a role in the occurrence and development of ovarian cancer by regulating the process of protein. Based on differentially expressed genes, 20 small-molecule drugs that potentially target CREB1 with abnormal expression in OV were obtained from the CMap database. Among these compounds, we found that naloxone has the greatest therapeutic value for OV. The high expression of the CREB1 gene may be an indicator of poor prognosis in ovarian cancer patients. Targeting CREB1 may be a potential tool for the diagnosis and treatment of OV.
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.