已发表论文

预测肺腺癌特异性生存率的表达特征模型

 

Authors Shi X, Tan H, Le X, Xian H, Li X, Huang K, Luo VY, Liu Y, Wu Z, Mo HY, Chen AM, Liang Y, Zhang J

Received 11 December 2017

Accepted for publication 9 April 2018

Published 24 September 2018 Volume 2018:10 Pages 3717—3732

DOI https://doi.org/10.2147/CMAR.S159563

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Cristina Weinberg

Peer reviewer comments 2

Editor who approved publication: Dr Luzhe Sun

Background: The current TNM staging system plays a central role in lung adenocarcinoma (LUAD) prognosis. However, it may not adequately stratify the risk of tumor recurrence. With the aid of gene expression profiling, we identified 31 lncRNAs whose expressions in tumor tissues could be used as a risk indicator for the guidance of lung cancer therapy. This exploratory analysis may shed new light on identification of potential prognostic factors.
Materials and methods: A survival prediction scoring model was developed from the data that are publicly available in The Cancer Genome Atlas (TCGA) LUAD RNA Sequencing dataset. Multivariate Cox regression analysis and Kaplan–Meier analysis were performed on a cohort of 254 stage I lung carcinoma patients with survival records.
Results: Our model indicates that the panels comprising 31 lncRNAs are highly associated with overall survival (OS): 18.9% (95% CI: 10.4%–34.5%) and 89.5% (95% CI: 80.7%–99.2%) for the high- and low-risk group, respectively. The specificity and sensitivity of the model are verified, which show that the area under receiver operating characteristic curve yields 0.881, meaning our model has good accuracy and it is feasible for further applications.
Conclusion: The 31-lncRNA model might be able to predict OS in patients with LUAD with high accuracy. Its further applications in biomolecular experiments using clinical samples with independent cohorts of patients are needed to verify the results.
Keywords: lung adenocarcinoma, lncRNA, signature, survival analysis, prognosis, RNA-seq




Figure 2 Survival curves for LUAD patients in all stages using...