Prognostic microRNA signatures derived from The Cancer Genome Atlas for head and neck squamous cell carcinomas.
Prognostic microRNA signatures derived from The Cancer Genome Atlas for head and neck squamous cell carcinomas.
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DOI：
10.1002/cam4.718
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发表时间：
2016-07
期刊：
影响因子：
4
通讯作者：
Wang X
中科院分区：
文献类型：
--
作者：
Wong N;Khwaja SS;Baker CM;Gay HA;Thorstad WL;Daly MD;Lewis JS Jr;Wang X
识别新的预后生物标记物通常需要一个大型数据集，为发现研究提供足够的统计能力。为此，我们利用来自癌症基因组图谱(TCGA)的高通量数据，在头颈部鳞状细胞癌(HNSCC)中识别了一组预后生物标志物，包括口咽鳞状细胞癌(OPSCC)和其他亚型。在这项研究中，我们分析了从TCGA患者获得的miRNA-seq数据，以确定OPSCC的预后生物标志物。对识别出的miRNAs进行了独立队列的进一步测试。我们还分析了来自TCGA的miRNA-seq数据，以确定口腔鳞状细胞癌(OSCC)和喉鳞状细胞癌(LSCC)中的miRNA的预后。我们的研究发现miR-193B-3p和miR-455-5p与OPSCC的生存呈正相关，miR-92a-3p和miR-497-5p与OPSCC的生存呈负相关。这四种miRNAs的联合表达特征是预测OPSCC患者总体生存的指标，更重要的是，这一特征在独立的OPSCC队列中得到了验证。此外，我们在口腔鳞状细胞癌和喉鳞状细胞癌中分别发现了四个预示生存的miRNAs，并且联合签名对HNSCC的亚型具有特异性。使用来自TCGA的测序数据作为主要来源，在OPSCC中开发了一个强大的4-miRNA预后信号，以及在其他HNSCC亚型中的预后信号。这表明了使用TCGA作为一种潜在资源来开发预后工具以改善个性化患者护理的力量。
Identification of novel prognostic biomarkers typically requires a large dataset which provides sufficient statistical power for discovery research. To this end, we took advantage of the high‐throughput data from The Cancer Genome Atlas (TCGA) to identify a set of prognostic biomarkers in head and neck squamous cell carcinomas (HNSCC) including oropharyngeal squamous cell carcinoma (OPSCC) and other subtypes. In this study, we analyzed miRNA‐seq data obtained from TCGA patients to identify prognostic biomarkers for OPSCC. The identified miRNAs were further tested with an independent cohort. miRNA‐seq data from TCGA was also analyzed to identify prognostic miRNAs in oral cavity squamous cell carcinoma (OSCC) and laryngeal squamous cell carcinoma (LSCC). Our study identified that miR‐193b‐3p and miR‐455‐5p were positively associated with survival, and miR‐92a‐3p and miR‐497‐5p were negatively associated with survival in OPSCC. A combined expression signature of these four miRNAs was prognostic of overall survival in OPSCC, and more importantly, this signature was validated in an independent OPSCC cohort. Furthermore, we identified four miRNAs each in OSCC and LSCC that were prognostic of survival, and combined signatures were specific for subtypes of HNSCC. A robust 4‐miRNA prognostic signature in OPSCC, as well as prognostic signatures in other subtypes of HNSCC, was developed using sequencing data from TCGA as the primary source. This demonstrates the power of using TCGA as a potential resource to develop prognostic tools for improving individualized patient care.