ArticleJournal of ovarian research2020
Systematic analysis of ovarian cancer platinum-resistance mechanisms via text mining.
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 9 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
9 citing papers in PubMed, 23 citations in OpenAlex.
- Cost effectiveness of bevacizumab plus carboplatin paclitaxel versus carboplatin paclitaxel as front line for advanced ovarian cancer in Thailand.Scientific reports · 2025Article
- Enhancing precision medicine: a nomogram for predicting platinum resistance in epithelial ovarian cancer.World journal of surgical oncology · 2024Article
- Identification of EMP1 as a critical gene for cisplatin resistance in ovarian cancer by using integrated bioinformatics analysis.Cancer medicine · 2023Article
- Potential prognostic role of somatic mutations in a set of cancer susceptibility genes in ovarian carcinoma: A follow-up multicentric study from Pakistan.Cancer biomarkers : section A of Disease markers · 2023Article
- Maggot Extract Inhibits Cell Migration and Tumor Growth by Targeting HSP90AB1 in Ovarian Cancer.Journal of clinical medicine · 2022Article
- CD44Journal of the Egyptian National Cancer Institute · 2022Article
- Impact of neoadjuvant chemotherapy on somatic mutation status in high-grade serous ovarian carcinoma.Journal of ovarian research · 2022Article
- Review
- Pathogenic Heteroplasmic Somatic Mitochondrial DNA Mutation Confers Platinum-Resistance and Recurrence of High-Grade Serous Ovarian Cancer.Cancer management and research · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPlatinum resistance is an important cause of clinical recurrence and death for ovarian cancer. This study tries to systematically explore the molecular mechanisms for platinum resistance in ovarian cancer and identify regulatory genes and pathways via text mining and other methods.
methodsGenes in abstracts of associated literatures were identified. Gene ontology and protein-protein interaction (PPI) network analysis were performed. Then co-occurrence between genes and ovarian cancer subtypes were carried out followed by cluster analysis.
resultsGenes with highest frequencies are mostly involved in DNA repair, apoptosis, metal transport and drug detoxification, which are closely related to platinum resistance. Gene ontology analysis confirms this result. Some proteins such as TP53, HSP90, ESR1, AKT1, BRCA1, EGFR and CTNNB1 work as hub nodes in PPI network. According to cluster analysis, specific genes were highlighted in each subtype of ovarian cancer, indicating that various subtypes may have different resistance mechanisms respectively.
conclusionsPlatinum resistance in ovarian cancer involves complicated signaling pathways and different subtypes may have specific mechanisms. Text mining, combined with other bio-information methods, is an effective way for systematic analysis.
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.