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A 6-lncRNA Signature to Improve Prognostic Prediction of Colon Cancer

Authors :
Wang Yuhang
Chen Lu
Pei Lixia
Chen Yufeng
Hu Yue
Hou Wenzhen
Song Yafang
Sun Mengzhu
Sun Jianhua
Source :
BioMedica, Vol 37, Iss 1, Pp 29-38 (2021)
Publication Year :
2021
Publisher :
Discover STM Publishing Ltd, 2021.

Abstract

Background and Objective: Background and Objective: Colorectal cancer is one of the most common malignant tumors in the world. The prognosis of colorectal cancer is still considered as worse despite the rapid development of treatment methods in the recent years. Therefore, it is important to understand the pathogenesis and development for more accurate prognostic methods. The present study aimed to identify a long non‑coding (lnc) RNAs‑based signature for prognostic determination of colon cancer patients. Methods: Datasets from the GEO and TCGA databases were used, differential expression of lncRNA was analyzed, and a 6‑lncRNA signature was identified. KEGG and GO was used to enrich the signal pathway to determine the biological effects of these 6-lncRNA. Results: This study has designed a prognosis model containing “LINC01494”, “TRPM2-AS”, “ATP1A1-AS1”, “FRY-AS1”, “LINC01360”, and “RBFADN” based on data set of colorectal cancer patients available in the TCGA and GEO databases. The prognostic model of lncRNAs may predict the prognosis of patients with colorectal cancer. Conclusion: The present study identified a 6‑lncRNA signature that could predict the survival rate for colon cancer patients. Further studies may be carried out to strengthen the findings of the present study.

Details

Language :
English
ISSN :
27103471
Volume :
37
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BioMedica
Publication Type :
Academic Journal
Accession number :
edsdoj.071743e8bc164b02a06efd7e8a67b154
Document Type :
article
Full Text :
https://doi.org/10.51441/BioMedica/5-167