ArticleCancer biomarkers : section A of Disease markers2019
Bioinformatics analysis of potential prognostic biomarkers among Krüppel-like transcription Factors (KLFs) in breast cancer.
Article in Cancer biomarkers : section A of Disease markers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- The induction of ferroptosis by KLF11/NCOA4 axis: the inhibitory role in clear cell renal cell carcinoma.Human cell · 2023Article
- The functions and prognostic value of Krüppel-like factors in breast cancer.Cancer cell international · 2022Article
- The Krüppel-like factor Cabut has cell cycle regulatory properties similar to E2F1.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- KLF11 Expression Predicts Poor Prognosis in Glioma Patients.International journal of general medicine · 2021Article
- Effect of Photodynamic Therapy on Gemcitabine-Resistant CholangiocarcinomaFrontiers in cell and developmental biology · 2021Article
- Bioinformatics analysis of the expression of HOXC13 and its role in the prognosis of breast cancer.Oncology letters · 2020Article
- Up-regulation of KLF17 expression increases the sensitivity of gastric cancer to 5-fluorouracil.International journal of immunopathology and pharmacologyArticle
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3 authors.
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Abstract
backgroundBreast cancer is a worldwide leading cause of cancer mortality and it is associated with numerous tumor suppressor genes and oncogenes. Growing evidence exists that different KLFs play pivotal roles of in human malignancies. However, the function of KLFs in breast cancer development has remained uncovered.
objectiveTo explore the potential prognostic biomarkers among KLFs in breast cancer.
methodsIn the present study, by using multiple large open databases, such as Oncomine database, Kaplan-Meier Plotter, and bc-GenExMiner online software, we deeply analyzed the expressions and clinical values about KLFs in patients with breast cancer.
resultsKLF4/5/8/9/10/15 were significantly down-regulated in breast cancer samples. KLF11 exerts significantly negative effect on the prognosis of patients, whereas expressions of KLF4/15 were associated with better prognosis. Moreover, the vital genes KLF4/11/15 showed significant association with clinical parameters including age, estrogen receptor, progesterone receptor, epidermal growth factor receptor-2, Scarff-Bloom-Richardson grade, and Nottingham prognostic index.
conclusionsBioinformatics analysis suggested that KLF4/11/15, compared to other KLFs, might be potential prognostic indicators and treatment targets for breast cancer patients.
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