Identification of Novel microRNA Prognostic Markers Using Cascaded Wx, a Neural Network-Based Framework, in Lung Adenocarcinoma Patients
- 주제(키워드) microRNA , lung adenocarcinoma , prognosis , Cascaded Wx , machine learning
- 주제(기타) Oncology
- 설명문(일반) [Kim, Jeong Seon; Lee, Sieun; Kim, Sae Eun; Ahn, Young-Ho] Ewha Womans Univ, Coll Med, Dept Mol Med, Seoul 07804, South Korea; [Kim, Jeong Seon; Lee, Sieun; Ahn, Young-Ho] Ewha Womans Univ, Coll Med, Inflammat Canc Microenvironm Res Ctr, Seoul 07804, South Korea; [Chun, Sang Hoon; Hong, Ji Hyung; Ko, Yoon Ho] Catholic Univ Korea, Coll Med, Dept Internal Med, Div Oncol, Seoul 06591, South Korea; [Park, Sungsoo] Deargen Inc, Daejeon 34051, South Korea; [Kang, Keunsoo] Dankook Univ, Coll Nat Sci, Dept Microbiol, Cheonan 31116, South Korea; [Ko, Yoon Ho] Catholic Univ Korea, Coll Med, Canc Res Inst, Seoul 06591, South Korea
- 등재 SCIE, SCOPUS
- OA유형 Green Published, gold
- 발행기관 MDPI
- 발행년도 2020
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000172421
- 본문언어 영어
- Published As https://dx.doi.org/10.3390/cancers12071890
- PubMed https://pubmed.ncbi.nlm.nih.gov/32674274
초록/요약
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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