ArticleOncology research2022
Identification of lncRNAs associated with the progression of acute lymphoblastic leukemia using a competing endogenous RNAs network.
Article in Oncology research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 8 citations in OpenAlex.
- Role of HOXA transcript antisense RNA myeloid-specific 1 in cancer (Review).Oncology letters · 2026Review
- Accurate prediction of candidate lncRNAs associated with DNA damage response based on gene expression patterns from graph neural networks.Bioinformatics advances · 2026Article
- Review
- Diagnostic and Predictive Value of LncRNA MCM3AP-AS1 in Sepsis and Its Regulatory Role in Sepsis-Induced Myocardial Dysfunction.Cardiovascular toxicology · 2024Article
- Improving prediction of blood cancer using leukemia microarray gene data and Chi2 features with weighted convolutional neural network.Scientific reports · 2024Article
- Roles of Interferon Regulatory Factor 1 in Tumor Progression and Regression: Two Sides of a Coin.International journal of molecular sciences · 2024Review
- Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute lymphoblastic leukemia (ALL) is a malignancy of bone marrow lymphoid precursors. Despite effective treatments, the causes of its progression or recurrence are still unknown. Finding prognostic biomarkers is needed for early diagnosis and more effective treatment. This study was performed to identify long non-coding RNAs (lncRNAs) involved in ALL progression by constructing a competitive endogenous RNA (ceRNA) network. These lncRNAs may serve as potential new biomarkers in the development of ALL. The GSE67684 dataset identified changes in lncRNAs and mRNAs involved in ALL progression. Data from this study were re-analyzed, and probes related to lncRNAs were retrieved. Targetscan, miRTarBase, and miRcode databases were used to identify microRNAs (miRNAs) related to the discovered genes and lncRNAs. The ceRNA network was constructed, and the candidate lncRNAs were selected. Finally, the results were validated with reverse transcription quantitative real-time PCR (RT-qPCR). The ceRNA network outcomes demonstrated that the top lncRNAs associated with altered mRNAs in ALL are IRF1-AS1, MCM3AP-AS1, TRAF3IP2-AS1, HOTAIRM1, CRNDE, and TUG1. Investigations of the subnets linked to MCM3AP-AS1, TRAF3IP2-AS1, and IRF1-AS1 indicated that these lncRNAs were considerably related to pathways associated with inflammation, metastasis, and proliferation. Higher expression levels of IRF1-AS1, MCM3AP-AS1, TRAF3IP2-AS1, CRNDE, and TUG1 were found in ALL samples compared to controls. The expression of MCM3AP-AS1, TRAF3IP2-AS1, and IRF1-AS1 is significantly elevated during the progression of ALL, playing an oncogenic role. Due to their role in the main cancer pathways, lncRNAs could be suitable therapeutic and diagnostic targets in ALL.
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