Reference-free transcriptome exploration reveals novel RNAs for prostate cancer diagnosis
Reference-free transcriptome exploration reveals novel RNAs for prostate cancer diagnosis
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DOI：
10.26508/lsa.201900449
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发表时间：
2019-12-01
影响因子：
4.4
通讯作者：
Morillon, Antonin
中科院分区：
文献类型：
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作者：
Pinskaya, Marina;Saci, Zohra;Morillon, Antonin
RNA测序技术的使用有望改进基于全面转录本集的诊断工具。然而，在临床标本中挖掘人类转录组数据的疾病生物标志物受到依赖于独特和注释的转录物的常规基于参考的方案的有限能力的限制。在这里，我们实施了一个盲的无参考计算协议，DE-kupl，从组织来源的总链RNA测序数据集推断尚未参考的RNA变异。作为实验室测试，该方案用于检测嵌入前列腺癌中表达的推定长非编码（lnc）RNA中的RNA序列。通过筛选1,179个候选者，我们确定了21个lncRNA，这些lncRNA在144个组织标本中通过NanoString进一步验证了稳健的肿瘤特异性表达。预测建模产生了一个限制性探针面板，使超过90%的癌症真阳性检测在一个独立的癌症基因组图谱队列。值得注意的是，这种仅由9种未注释的lncRNA组成的临床特征在检测高风险肿瘤方面大大优于PCA 3，PCA 3是唯一使用的前列腺癌lncRNA生物标志物。该模块化工作流程高度敏感，可应用于任何病理学或临床应用。
The use of RNA-sequencing technologies held a promise of improved diagnostic tools based on comprehensive transcript sets. However, mining human transcriptome data for disease biomarkers in clinical specimens are restricted by the limited power of conventional reference-based protocols relying on unique and annotated transcripts. Here, we implemented a blind reference-free computational protocol, DE-kupl, to infer yet unreferenced RNA variations from total stranded RNA-sequencing datasets of tissue origin. As a bench test, this protocol was powered for detection of RNA subsequences embedded into putative long noncoding (lnc)RNAs expressed in prostate cancer. Through filtering of 1,179 candidates, we defined 21 lncRNAs that were further validated by NanoString for robust tumor-specific expression in 144 tissue specimens. Predictive modeling yielded a restricted probe panel enabling more than 90% of true-positive detections of cancer in an independent The Cancer Genome Atlas cohort. Remarkably, this clinical signature made of only nine unannotated lncRNAs largely outperformed PCA3, the only used prostate cancer lncRNA biomarker, in detection of high-risk tumors. This modular workflow is highly sensitive and can be applied to any pathology or clinical application.