Trial reportCancer biomarkers : section A of Disease markers2023
Construction of a lncRNA-mediated ceRNA network and a genomic-clinicopathologic nomogram to predict survival for breast cancer patients.
Trial report in Cancer biomarkers : section A of Disease markers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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
6 citing papers in PubMed.
- The Roles of SHCBP1 in Cancer Hallmarks: Molecular Mechanisms and Therapeutic Implications.International journal of molecular sciences · 2025Review
- Oncogenic activation of SMYD3-SHCBP1 promotes breast cancer development and is coupled with resistance to immune therapy.Cell death & disease · 2025Article
- GCBRGCN: Integration of ceRNA and RGCN to Identify Gastric Cancer Biomarkers.Bioengineering (Basel, Switzerland) · 2025Article
- Glioblastoma stem cell long non-coding RNAs: therapeutic perspectives and opportunities.Frontiers in genetics · 2024Review
- Targeting ST8SIA6-AS1 counteracts KRASExperimental hematology & oncology · 2023Article
- Common Genetic Factors and Pathways in Alzheimer's Disease and Ischemic Stroke: Evidences from GWAS.Genes · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer (BC) is the most common cancer among women and a leading cause of cancer-related deaths worldwide. The diagnosis of early patients and the prognosis of advanced patients have not improved over the past several decades. The purpose of the present study was to identify the lncRNA-related genes based on ceRNA network and construct a credible model for prognosis in BC. Based on The Cancer Genome Atlas (TCGA) database, prognosis-related differently expressed genes (DEGs) and a lncRNA-associated ceRNA regulatory network were obtained in BC. The patients were randomly divided into a training group and a testing group. A ceRNA-related prognostic model as well as a nomogram was constructed for further study. A total of 844 DElncRNAs, 206 DEmiRNAs and 3295 DEmRNAs were extracted in BC, and 12 RNAs (HOTAIR, AC055854.1, ST8SIA6-AS1, AC105999.2, hsa-miR-1258, hsa-miR-7705, hsa-miR-3662, hsa-miR-4501, CCNB1, UHRF1, SPC24 and SHCBP1) among them were recognized for the construction of a prognostic risk model. Patients were then assigned to high-risk and low-risk groups according to the risk score. The Kaplan-Meier (K-M) analysis demonstrated that the high-risk group was closely associated with poor prognosis. The predictive nomogram combined with clinical features showed performance in clinical practice. In a nutshell, our ceRNA-related gene model and the nomogram graph are accurate and reliable tools for predicting prognostic outcomes of BC patients, and may make great contributions to modern precise medicine.
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