A four-long non-coding RNA signature in predicting breast cancer survival
| Autor: | Ping Li, Zhangru Yang, Shen Fu, Qing Zhang, Jin Meng |
|---|---|
| Jazyk: | angličtina |
| Předmět: |
Oncology
Cancer Research medicine.medical_specialty Time Factors Survival Breast Neoplasms Expression Kaplan-Meier Estimate Prognostic Bioinformatics Disease-Free Survival lncRNA Breast cancer Predictive Value of Tests Risk Factors Internal medicine Databases Genetic Biomarkers Tumor Gene signature medicine Adjuvant therapy Humans Gene Proportional Hazards Models Long non coding RNA business.industry Proportional hazards model Gene Expression Profiling Research Reproducibility of Results Biomarker medicine.disease Long non-coding RNA Gene expression profiling Treatment Outcome ROC Curve Area Under Curve Multivariate Analysis Biomarker (medicine) Female RNA Long Noncoding business |
| Zdroj: | Journal of Experimental & Clinical Cancer Research : CR |
| ISSN: | 1756-9966 |
| DOI: | 10.1186/s13046-014-0084-7 |
| Popis: | Background Many long non-coding RNAs(lncRNAs) have been found to be a good marker for several tumors. Using lncRNA-mining approach, we aimed to identify lncRNA expression signature that can predict breast cancer patient survival. Methods We performed LncRNA expression profiling in 887 breast cancer patients from Gene Expression Omnibus (GEO) datasets. The association between lncRNA signature and clinical survival was analyzed using the training set(n = 327, from GSE 20685). The validation for the association was performed in another three independent testing sets(252 from GSE21653, 204 from GSE12276, and 104 from GSE42568). Results A set of four lncRNA genes (U79277, AK024118, BC040204, AK000974) have been identified by the random survival forest algorithm. Using a risk score based on the expression signature of these lncRNAs, we separated the patients into low-risk and high-risk groups with significantly different survival times in the training set. This signature was validated in the other three cohorts. Further study revealed that the four-lncRNA expression signature was independent of age and subtype. Gene Set Enrichment Analysis (GSEA) suggested that gene sets were involved in several cancer metastasis related pathways. Conclusions These findings indicate that lncRNAs may be implicated in breast cancer pathogenesis. The four-lncRNA signature may have clinical implications in the selection of high-risk patients for adjuvant therapy. Electronic supplementary material The online version of this article (doi:10.1186/s13046-014-0084-7) contains supplementary material, which is available to authorized users. |
| Databáze: | OpenAIRE |
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