'N-of-1-pathways' unveils personal deregulated mechanisms from a single pair of RNA-Seq samples: towards precision medicine.
'N-of-1-pathways' unveils personal deregulated mechanisms from a single pair of RNA-Seq samples: towards precision medicine.
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DOI：
10.1136/amiajnl-2013-002519
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发表时间：
2014-11
期刊：
影响因子：
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通讯作者：
Lussier YA
中科院分区：
文献类型：
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作者：
Gardeux V;Achour I;Li J;Maienschein-Cline M;Li H;Pesce L;Parinandi G;Bahroos N;Winn R;Foster I;Garcia JG;Lussier YA
精准医学的出现使得个体分子数据能够纳入患者护理中。事实上，DNA 测序可以预测个体患者的体细胞突变。然而，这些遗传特征忽视了对治疗的动态表观遗传和表型反应。与此同时，准确的个人转录组解释仍然是一个尚未解决的挑战。此外，N-of-1（单受试者）功效试验越来越多地进行，但对于分子标记发现来说动力不足。 “N-of-1-pathways”是一个基于三个原则的全球框架：(i) 统计宇宙是单个患者； (ii) 显着性源自由来自同一患者的配对样本提供动力的基因组/生物模块； (iii) 基因组/生物模块之间的相似性评估研究内和交叉研究的共性和差异。因此，患者基因水平的概况被转化为解除管制的途径。根据 55 名肺腺癌患者的 RNA-Seq，N-of-1-pathways 预测每位患者的失调通路。跨患者 N-of-1 路径获得了与传统基因集富集分析 (GSEA) 和差异表达基因 (DEG) 富集相当的结果，并在三项外部评估中得到验证。此外，热图和星图突出显示了从分子到器官系统水平的个体和共享机制（例如，DNA 修复、信号传导、免疫反应）。根据患者解除管制机制与独立金标准的相似性对患者进行排名，产生无监督的极端生存表型簇（p = 0.03）。 N-of-1 路径框架为个体无病生存提供了稳健的统计和相关生物学解释，而这一点在传统的跨患者研究中经常被忽视。它支持具有较小队列的机制级分类器以及 N-of-1 研究。 http://lussierlab.org/publications/N-of-1-pathways
The emergence of precision medicine allowed the incorporation of individual molecular data into patient care. Indeed, DNA sequencing predicts somatic mutations in individual patients. However, these genetic features overlook dynamic epigenetic and phenotypic response to therapy. Meanwhile, accurate personal transcriptome interpretation remains an unmet challenge. Further, N-of-1 (single-subject) efficacy trials are increasingly pursued, but are underpowered for molecular marker discovery. ‘N-of-1-pathways’ is a global framework relying on three principles: (i) the statistical universe is a single patient; (ii) significance is derived from geneset/biomodules powered by paired samples from the same patient; and (iii) similarity between genesets/biomodules assesses commonality and differences, within-study and cross-studies. Thus, patient gene-level profiles are transformed into deregulated pathways. From RNA-Seq of 55 lung adenocarcinoma patients, N-of-1-pathways predicts the deregulated pathways of each patient. Cross-patient N-of-1-pathways obtains comparable results with conventional genesets enrichment analysis (GSEA) and differentially expressed gene (DEG) enrichment, validated in three external evaluations. Moreover, heatmap and star plots highlight both individual and shared mechanisms ranging from molecular to organ-systems levels (eg, DNA repair, signaling, immune response). Patients were ranked based on the similarity of their deregulated mechanisms to those of an independent gold standard, generating unsupervised clusters of diametric extreme survival phenotypes (p=0.03). The N-of-1-pathways framework provides a robust statistical and relevant biological interpretation of individual disease-free survival that is often overlooked in conventional cross-patient studies. It enables mechanism-level classifiers with smaller cohorts as well as N-of-1 studies. http://lussierlab.org/publications/N-of-1-pathways