ArticleOncotarget2017
Protein-coding genes, long non-coding RNAs combined with microRNAs as a novel clinical multi-dimension transcriptome signature to predict prognosis in ovarian cancer.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 14 citations in OpenAlex.
- Review
- AKT-mediated regulation of chromatin ubiquitylation and tumorigenesis through Mel18 phosphorylation.Oncogene · 2021Article
- Article
- Identification of a novel CpG methylation signature to predict prognosis in lung squamous cell carcinoma.Cancer biomarkers : section A of Disease markers · 2021Article
- A novel signature of two long non-coding RNAs in BRCA mutant ovarian cancer to predict prognosis and efficiency of chemotherapy.Journal of ovarian research · 2020Article
- Article
- 7-lncRNA Assessment Model for Monitoring and Prognosis of Breast Cancer Patients: Based on Cox Regression and Co-expression Analysis.Frontiers in oncology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer is prevalent in women which is usually diagnosed at an advanced stage with a high mortality rate. The aim of this study is to investigate protein-coding gene, long non-coding RNA, and microRNA associated with the prognosis of patients with ovarian serous carcinoma by mining data from TCGA (The Cancer Genome Atlas) public database. The clinical data of ovarian serous carcinoma patients was downloaded from TCGA database in September, 2016. The mean age and survival time of 407 patients with ovarian serous carcinoma were 59.71 ± 11.54 years and 32.98 ± 26.66 months. Cox's proportional hazards regression analysis was conducted to analyze genes that were significantly associated with the survival of ovarian serous carcinoma patients in the training group. Using the random survival forest algorithm, Kaplan-Meier and ROC analysis, we kept prognostic genes to construct the multi-dimensional transcriptome signature with max area under ROC curve (AUC) (0.69 in the training group and 0.62 in the test group). The selected signature composed by
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.