Comparison of the Prognostic Utility of the Diverse Molecular Data among lncRNA, DNA Methylation, microRNA, and mRNA across Five Human Cancers
文献类型：期刊论文
| 作者 | Liu Changning
|
| 刊名 | PLOS ONE
 |
| 出版日期 | 2015 |
| 卷号 | 10期号:11页码:e0142433 |
| 关键词 | OVARIAN-CARCINOMA CLINICAL UTILITY GENOMIC ANALYSES GENE SELECTION BREAST-CANCER TUMOR TYPES SURVIVAL BIOMARKERS NETWORK MODELS |
| 中文摘要 | Introduction Advances in high-throughput technologies have generated diverse informative molecular markers for cancer outcome prediction. Long non-coding RNA (lncRNA) and DNA methylation as new classes of promising markers are emerging as key molecules in human cancers; however, the prognostic utility of such diverse molecular data remains to be explored. Materials and Methods We proposed a computational pipeline (IDFO) to predict patient survival by identifying prognosis-related biomarkers using multi-type molecular data (mRNA, microRNA, DNA methylation, and lncRNA) from 3198 samples of five cancer types. We assessed the predictive performance of both single molecular data and integrated multi-type molecular data in patient survival stratification, and compared their relative importance in each type of cancer, respectively. Survival analysis using multivariate Cox regression was performed to investigate the impact of the IDFO-identified markers and traditional variables on clinical outcome. Results Using the IDFO approach, we obtained good predictive performance of the molecular datasets (bootstrap accuracy: 0.71-0.97) in five cancer types. Impressively, lncRNA was identified as the best prognostic predictor in the validated cohorts of four cancer types, followed by DNA methylation, mRNA, and then microRNA. We found the incorporating of multi-type molecular data showed similar predictive power to single-type molecular data, but with the exception of the lncRNA + DNA methylation combinations in two cancers. Survival analysis of proportional hazard models confirmed a high robustness for lncRNA and DNA methylation as prognosis factors independent of traditional clinical variables. Conclusion Our study provides insight into systematically understanding the prognostic performance of diverse molecular data in both single and aggregate patterns, which may have specific reference to subsequent related studies. |
| 公开日期 | 2016-01-25 |
| 源URL | [http://ir.xtbg.org.cn/handle/353005/9651]  |
| 专题 | 西双版纳热带植物园_2012年后新成立研究组 |
| 通讯作者 | Liu Changning |
| 推荐引用方式 GB/T 7714 | Liu Changning. Comparison of the Prognostic Utility of the Diverse Molecular Data among lncRNA, DNA Methylation, microRNA, and mRNA across Five Human Cancers[J]. PLOS ONE,2015,10(11):e0142433. |
| APA | Liu Changning.(2015).Comparison of the Prognostic Utility of the Diverse Molecular Data among lncRNA, DNA Methylation, microRNA, and mRNA across Five Human Cancers.PLOS ONE,10(11),e0142433. |
| MLA | Liu Changning."Comparison of the Prognostic Utility of the Diverse Molecular Data among lncRNA, DNA Methylation, microRNA, and mRNA across Five Human Cancers".PLOS ONE 10.11(2015):e0142433. |
入库方式： OAI收割
来源：西双版纳热带植物园
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