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Predicting survival times for neuroblastoma patients using RNA-seq expression profiles.
Biology Direct ( IF 5.7 ) Pub Date : 2018-05-30 , DOI: 10.1186/s13062-018-0213-x
Tyler Grimes 1 , Alejandro R Walker 1 , Susmita Datta 1 , Somnath Datta 1
Affiliation  

BACKGROUND Neuroblastoma is the most common tumor of early childhood and is notorious for its high variability in clinical presentation. Accurate prognosis has remained a challenge for many patients. In this study, expression profiles from RNA-sequencing are used to predict survival times directly. Several models are investigated using various annotation levels of expression profiles (genes, transcripts, and introns), and an ensemble predictor is proposed as a heuristic for combining these different profiles. RESULTS The use of RNA-seq data is shown to improve accuracy in comparison to using clinical data alone for predicting overall survival times. Furthermore, clinically high-risk patients can be subclassified based on their predicted overall survival times. In this effort, the best performing model was the elastic net using both transcripts and introns together. This model separated patients into two groups with 2-year overall survival rates of 0.40±0.11 (n=22) versus 0.80±0.05 (n=68). The ensemble approach gave similar results, with groups 0.42±0.10 (n=25) versus 0.82±0.05 (n=65). This suggests that the ensemble is able to effectively combine the individual RNA-seq datasets. CONCLUSIONS Using predicted survival times based on RNA-seq data can provide improved prognosis by subclassifying clinically high-risk neuroblastoma patients. REVIEWERS This article was reviewed by Subharup Guha and Isabel Nepomuceno.

中文翻译:

使用RNA-seq表达谱预测神经母细胞瘤患者的生存时间。

背景技术神经母细胞瘤是儿童期最常见的肿瘤,并且因其临床表现的高度可变性而臭名昭著。对于许多患者而言,准确的预后仍然是一个挑战。在这项研究中,来自RNA测序的表达谱可直接预测存活时间。使用表达谱(基因,转录本和内含子)的各种注释级别研究了几种模型,并提出了整体预测器作为组合这些不同谱的启发式方法。结果与仅使用临床数据预测整体生存时间相比,使用RNA-seq数据可提高准确性。此外,可根据临床高危患者的预测总体生存时间对其进行分类。为此,表现最好的模型是同时使用转录本和内含子的弹性网。该模型将患者分为两组,其两年总生存率分别为0.40±0.11(n = 22)和0.80±0.05(n = 68)。集成方法给出了相似的结果,组为0.42±0.10(n = 25)对0.82±0.05(n = 65)。这表明该集成体能够有效地组合各个RNA-seq数据集。结论使用基于RNA-seq数据的预测生存时间,可以通过对临床高危神经母细胞瘤患者进行亚分类来改善预后。审阅者本文由Subharup Guha和Isabel Nepomuceno审阅。10(n = 25)对0.82±0.05(n = 65)。这表明该集成体能够有效地组合各个RNA-seq数据集。结论使用基于RNA-seq数据的预测生存时间,可以通过对临床高危神经母细胞瘤患者进行亚分类来改善预后。审阅者本文由Subharup Guha和Isabel Nepomuceno审阅。10(n = 25)对0.82±0.05(n = 65)。这表明该集成体能够有效地组合各个RNA-seq数据集。结论使用基于RNA-seq数据的预测生存时间,可以通过对临床高危神经母细胞瘤患者进行亚分类来改善预后。审阅者本文由Subharup Guha和Isabel Nepomuceno审阅。
更新日期:2020-04-22
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