Xu Xinsen, Huang Lei, Chan Chun Hei, Yu Tao, Miao Runchen, Liu Chang
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
118 Lancaster Terrace, Brookline, MA, USA.
Oncotarget. 2016 Jul 19;7(29):45926-45936. doi: 10.18632/oncotarget.10002.
Cancer molecular profiling provides better understanding of tumor mechanisms and helps to improve the existing cancer management. Here we present the gene expression signatures from ~9000 human tumors with clinical information across 32 malignancies from The Cancer Genome Atlas project (TCGA). Major predictors from the RNA sequencing data that were significantly correlated with cancer survival were identified. The expression level of these prognostic genes revealed significant genomic pathways that were clinically relevant to survival outcomes across human cancers. Furthermore, it is shown that in most cancer types, combinations of these genomic signatures with clinical information might yield improved predictions. Thus, with respect to clinical utility, our study reveals the promising values of genomic data from the pan-cancer perspective.
癌症分子剖析有助于更好地理解肿瘤机制,并有助于改善现有的癌症管理。在此,我们展示了来自癌症基因组图谱(TCGA)项目中约9000例具有临床信息的人类肿瘤的基因表达特征,这些肿瘤涵盖32种恶性肿瘤。我们从RNA测序数据中识别出了与癌症生存显著相关的主要预测因子。这些预后基因的表达水平揭示了与人类癌症生存结果临床相关的重要基因组通路。此外,研究表明,在大多数癌症类型中,将这些基因组特征与临床信息相结合可能会提高预测准确性。因此,就临床实用性而言,我们的研究从泛癌角度揭示了基因组数据的潜在价值。