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Abstract：
Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, identification of genome instability-associated lncRNAs and their clinical significance in cancers remain largely unexplored. Here, we developed a mutator hypothesis-derived computational frame combining lncRNA expression profiles and somatic mutation profiles in a tumor genome and identified 128 novel genomic instability-associated lncRNAs in breast cancer as a case study. We then identified a genome instability-derived two lncRNA-based gene signature (GILncSig) that stratified patients into high- and low-risk groups with significantly different outcome and was further validated in multiple independent patient cohorts. Furthermore, the GILncSig correlated with genomic mutation rate in both ovarian cancer and breast cancer, indicating its potential as a measurement of the degree of genome instability. The GILncSig was able to divide TP53 wide-type patients into two risk groups, with the low-risk group showing significantly improved outcome and the high-risk group showing no significant difference compared with those with TP53 mutation. In summary, this study provided a critical approach and resource for further studies examining the role of lncRNAs in genome instability and introduced a potential new avenue for identifying genomic instability-associated cancer biomarkers.
摘要：
新出现的证据揭示了长链非编码RNA（lncRNA）在维持基因组不稳定性中的关键作用。然而,基因组不稳定性相关lncRNAs的鉴定及其在癌症中的临床意义仍未被探索。这里,我们开发了一个基于突变假说的计算框架,将肿瘤基因组中的lncRNA表达谱和体细胞突变谱相结合,并在乳腺癌中鉴定了128个新的基因组不稳定性相关lncRNA作为案例研究.然后，我们确定了基因组不稳定性衍生的两个基于lncRNA的基因签名（GILncSig），将患者分为具有显着不同结果的高风险和低风险组，并在多个独立患者队列中进一步验证。此外，GILncSig与卵巢癌和乳腺癌的基因组突变率相关，表明其作为基因组不稳定程度的度量的潜力。GILncSig能够将TP53宽型患者分为两个风险组，与TP53突变组相比，低危组的结局显着改善，而高危组则没有显着差异。总之,这项研究为进一步研究lncRNAs在基因组不稳定性中的作用提供了一个关键的方法和资源,并为鉴定基因组不稳定性相关的癌症生物标志物提供了一个潜在的新途径.
