ArticleHeliyon2024
Construction and validation of a ubiquitination-related prognostic risk score signature in breast cancer.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Multi-cohort validation of a lipid metabolism and ferroptosis-associated index for prognosis and immunotherapy response prediction in hormone receptor-positive breast cancer.International journal of biological sciences · 2025Article
- F-box in breast cancer: mechanism of action and therapeutic potential.American journal of translational research · 2025Review
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Breast cancer (BC) is a highly common form of cancer that occurs in many parts of the world. However, early -stage BC is curable. Many patients with BC have poor prognostic outcomes owing to ineffective diagnostic and therapeutic tools. The ubiquitination system and associated proteins were found influencing the outcome of individuals with cancer. Therefore, developing a biomarker associated with ubiquitination genes to forecast BC patient outcomes is a feasible strategy. Objective: The primary goal of this work was to develop a novel risk score signature capable of accurately estimate the future outcome of patients with BC by targeting ubiquitinated genes. Methods: Univariate Cox regression analysis was conducted utilizing the E1, E2, and E3 ubiquitination-related genes in the GSE20685 dataset. Genes with p < 0.01 were screened again using the Non-negative Matrix Factorization (NMF) algorithm, and the resulting hub genes were composed of a risk score signature. Patients were categorized into two risk groups, and the predictive effect was tested using Kaplan-Meier (KM) and Receiver Operating Characteristic (ROC) curves. This risk score signature was later validated using multiple external datasets, namely TCGA-BRAC, GSE1456, GSE16446, GSE20711, GSE58812 and GSE96058. Immuno-microenvironmental, single-cell, and microbial analyses were also performed. Results: The selected gene signature comprising six ubiquitination-related genes ( Conclusion: This study established an risk score signature consisting of six ubiquitination genes, that can accurately forecast the outcome of patients with BC using multiple datasets. It can provide personalized and targeted assistance to provide the evaluation and therapy of individuals having BC.
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Registered trials
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