ArticleJournal of oncology2020
Cancer Stem Cell Characteristics by Network Analysis of Transcriptome Data Stemness Indices in Breast Carcinoma.
Article in Journal of oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 5 citations in OpenAlex.
- Application of artificial intelligence-based stemness index in cancer.Frontiers in oncology · 2025Review
- Human CKAP2L shows a cell cycle-dependent expression pattern and exhibits microtubule-stabilizing properties.FEBS open bio · 2024Article
- Identification of Potential Breast Cancer Stem Cell Biomarkers in the Secretome Using a Network Interaction Approach Analysis.Asian Pacific journal of cancer prevention : APJCP · 2024Article
- Article
- BCSCdb: a database of biomarkers of cancer stem cells.Database : the journal of biological databases and curation · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveBreast cancer (BC) affects women all over the world. This study aimed at screening out potential biomarkers through performing an in-depth analysis of data from the previous research and database.
designThis study made full use of RNA sequencing (RNA-seq) data from cancer genomic maps (TCGA) and screened key genes related to stemness by merging WGCNA with BC mRNAsi.
resultsThe related mRNAsi data were downloaded, and the transcriptional levels of mRNAsi in cancers contrasted with normal samples. The results showed that there was a significantly higher mRNAsi expression in BC tissues (
conclusionThis study is the first to show the important role of stemness-related genes in the prognosis of BC. However, future clinical trials are needed to confirm these results and promote the application of these key genes in prognosis evaluation.
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.