ArticleAging2020
Identification of a 15-pseudogene based prognostic signature for predicting survival and antitumor immune response in breast cancer.
Article in Aging, 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
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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
5 citing papers in PubMed, 8 citations in OpenAlex.
- KCNN4 as a genomic determinant of cytosolic delivery by the attenuated cationic lytic peptide L17E.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Article
- Somatic Copy Number Alterations in Colorectal Cancer Lead to a Differentially Expressed ceRNA Network (ceRNet).Current issues in molecular biology · 2023Article
- N6-methyladenosine-associated prognostic pseudogenes contribute to predicting immunotherapy benefits and therapeutic agents in head and neck squamous cell carcinoma.Theranostics · 2022Article
- MLSP: A bioinformatics tool for predicting molecular subtypes and prognosis in patients with breast cancer.Computational and structural biotechnology journal · 2022Article
- Immune-Related Genes to Construct a Novel Prognostic Model of Breast Cancer: A Chemosensitivity-Based Study.Frontiers in immunology · 2021Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pseudogenes are noncoding RNAs that have been revealed to play critical roles in oncogenesis and tumor progression. However, their functional roles have not been comprehensively clarified in breast cancer. Here, we systematically analyzed the RNA sequencing data of 13931 pseudogenes in 775 breast cancer patients from The Cancer Genome Atlas dataset, and ultimately identified 15 prognostic pseudogenes by univariate Cox proportional hazard regression. A risk score model was constructed based on the prognostic pseudogenes via LASSO analysis and dichotomized patients into low- and high-risk subgroups. Patients in the high-risk group had a significantly shorter overall survival than those in the low-risk group. The prognostic value of these 15 pseudogenes and the risk score model were further validated in the European Genome-Phenome Archive dataset. Furthermore, we performed consensus clustering of the 15 prognostic pseudogenes and found that their expression pattern was significantly associated with tumor malignancy and host antitumor immune response, in terms of infiltrating immune cell compositions, antigen presenting genes expression, cytolytic activity and T-cell exhausted markers. This study indicated that these 15 prognostic pseudogenes were significantly correlated with tumor malignancy and host antitumor immune response in breast cancer, and might serve as potential targets for immunotherapy.
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