ArticlePloS one2014
Molecular characterization of an intact p53 pathway subtype in high-grade serous ovarian cancer.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- DNA methylation-regulated AKAP12 expression modulates ECM remodeling and ADP/FAD ratio to influence prognosis in ovarian cancer.Journal of ovarian research · 2026Article
- P53 Gene as a Promising Biomarker and Potential Target for the Early Diagnosis of Reproductive Cancers.Cureus · 2024Review
- Multi-omics-based analysis of high grade serous ovarian cancer subtypes reveals distinct molecular processes linked to patient prognosis.FEBS open bio · 2023Article
- The Challenges and Prospects of p53-Based Therapies in Ovarian Cancer.Biomolecules · 2023Review
- Comprehensive Gene Mutation Profiling of Circulating Tumor DNA in Ovarian Cancer: Its Pathological and Prognostic Impact.Cancers · 2020Article
- Clinical relevance of TP53 hotspot mutations in high-grade serous ovarian cancers.British journal of cancer · 2020Article
- Gene microarray analysis of lncRNA and mRNA expression profiles in patients with high‑grade ovarian serous cancer.International journal of molecular medicine · 2018Article
- Exome and copy number variation analyses of Mayer-Rokitansky-Küster- Hauser syndrome.Human genome variation · 2018Article
- Mutant p53 stimulates cell invasion through an interaction with Rad21 in human ovarian cancer cells.Scientific reports · 2017Article
- TP53 mutations in epithelial ovarian cancer.Translational cancer research · 2016Article
- Identification of novel exonic mobile element insertions in epithelial ovarian cancers.Human genome variation · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-grade serous ovarian cancer (HGSOC) is the most aggressive histological type of epithelial ovarian cancer, which is characterized by a high frequency of somatic TP53 mutations. We performed exome analyses of tumors and matched normal tissues of 34 Japanese patients with HGSOC and observed a substantial number of patients without TP53 mutation (24%, 8/34). Combined with the results of copy number variation analyses, we subdivided the 34 patients with HGSOC into subtypes designated ST1 and ST2. ST1 showed intact p53 pathway and was characterized by fewer somatic mutations and copy number alterations. In contrast, the p53 pathway was impaired in ST2, which is characterized by abundant somatic mutations and copy number alterations. Gene expression profiles combined with analyses using the Gene Ontology resource indicate the involvement of specific biological processes (mitosis and DNA helicase) that are relevant to genomic stability and cancer etiology. In particular we demonstrate the presence of a novel subtype of patients with HGSOC that is characterized by an intact p53 pathway, with limited genomic alterations and specific gene expression profiles.
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.