ArticleCancers2020
Identification of Novel microRNA Prognostic Markers Using Cascaded Wx, a Neural Network-Based Framework, in Lung Adenocarcinoma Patients.
Article in Cancers, 2020. 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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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
7 citing papers in PubMed.
- miRNAs in anti-cancer drug resistance of non-small cell lung cancer: Recent advances and future potential.Frontiers in pharmacology · 2022Review
- circ_0000567/miR-421/Journal of Cancer · 2022Article
- Identification of an eleven-miRNA signature to predict the prognosis of endometrial cancer.Bioengineered · 2021Article
- Diagnostic and prognostic value of microRNA-2355-3p and contribution to the progression in lung adenocarcinoma.Bioengineered · 2021Article
- Prognosis Value of microRNA-3677-3p in Lung Adenocarcinoma and Its Regulatory Effect on Tumor Progression.Cancer management and research · 2021Article
- Diagnostic and Therapeutic Implications of microRNAs in Non-Small Cell Lung Cancer.International journal of molecular sciences · 2020Review
- Classify multicategory outcome in patients with lung adenocarcinoma using clinical, transcriptomic and clinico-transcriptomic data: machine learning versus multinomial models.American journal of cancer research · 2020Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The evolution of next-generation sequencing technology has resulted in a generation of large amounts of cancer genomic data. Therefore, increasingly complex techniques are required to appropriately analyze this data in order to determine its clinical relevance. In this study, we applied a neural network-based technique to analyze data from The Cancer Genome Atlas and extract useful microRNA (miRNA) features for predicting the prognosis of patients with lung adenocarcinomas (LUAD). Using the Cascaded Wx platform, we identified and ranked miRNAs that affected LUAD patient survival and selected the two top-ranked miRNAs (miR-374a and miR-374b) for measurement of their expression levels in patient tumor tissues and in lung cancer cells exhibiting an altered epithelial-to-mesenchymal transition (EMT) status. Analysis of miRNA expression from tumor samples revealed that high miR-374a/b expression was associated with poor patient survival rates. In lung cancer cells, the EMT signal induced miR-374a/b expression, which, in turn, promoted EMT and invasiveness. These findings demonstrated that this approach enabled effective identification and validation of prognostic miRNA markers in LUAD, suggesting its potential efficacy for clinical use.
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Registered trials
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