...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>BMC Medical Genomics >Toward the precision breast cancer survival prediction utilizing combined whole genome-wide expression and somatic mutation analysis
【24h】

Toward the precision breast cancer survival prediction utilizing combined whole genome-wide expression and somatic mutation analysis

机译：利用全基因组表达和体细胞突变分析相结合的精确乳腺癌生存预测

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Breast cancer is the most common type of invasive cancer in woman. It accounts for approximately 18% of all cancer deaths worldwide. It is well known that somatic mutation plays an essential role in cancer development. Hence, we propose that a prognostic prediction model that integrates somatic mutations with gene expression can improve survival prediction for cancer patients and also be able to reveal the genetic mutations associated with survival. Differential expression analysis was used to identify breast cancer related genes. Genetic algorithm (GA) and univariate Cox regression analysis were applied to filter out survival related genes. DAVID was used for enrichment analysis on somatic mutated gene set. The performance of survival predictors were assessed by Cox regression model and concordance index(C-index). We investigated the genome-wide gene expression profile and somatic mutations of 1091 breast invasive carcinoma cases from The Cancer Genome Atlas (TCGA). We identified 118 genes with high hazard ratios as breast cancer survival risk gene candidates (log rank p? 0.0001 and c-index?=?0.636). Multiple breast cancer survival related genes were found in this gene set, including FOXR2, FOXD1, MTNR1B and SDC1. Further genetic algorithm (GA) revealed an optimal gene set consisted of 88 genes with higher c-index (log rank p? 0.0001 and c-index?=?0.656). We validated this gene set on an independent breast cancer data set and achieved a similar performance (log rank p? 0.0001 and c-index?=?0.614). Moreover, we revealed 25 functional annotations, 15 gene ontology terms and 14 pathways that were significantly enriched in the genes that showed distinct mutation patterns in the different survival risk groups. These functional gene sets were used as new features for the survival prediction model. In particular, our results suggested that the Fanconi anemia pathway had an important role in breast cancer prognosis. Our study indicated that the expression levels of the gene signatures remain the effective indicators for breast cancer survival prediction. Combining the gene expression information with other types of features derived from somatic mutations can further improve the performance of survival prediction. The pathways that were associated with survival risk suggested by our study can be further investigated for improving cancer patient survival.
机译：乳腺癌是女性中最常见的浸润性癌症。它约占全球所有癌症死亡人数的18％。众所周知，体细胞突变在癌症发展中起着至关重要的作用。因此，我们建议将体细胞突变与基因表达整合在一起的预后预测模型可以改善癌症患者的生存预测，并且还能够揭示与生存相关的基因突变。差异表达分析用于鉴定乳腺癌相关基因。应用遗传算法（GA）和单变量Cox回归分析筛选出与生存相关的基因。 DAVID用于体细胞突变基因集的富集分析。通过Cox回归模型和一致性指数（C-index）评估生存预测指标的表现。我们研究了来自癌症基因组图谱（TCGA）的1091例乳腺浸润癌病例的全基因组基因表达谱和体细胞突变。我们确定了118个具有高危险比的基因作为乳腺癌存活风险基因候选基因（对数秩p≤0.0001，c-index≤0.636）。在该基因集中发现了多个与乳腺癌生存相关的基因，包括FOXR2，FOXD1，MTNR1B和SDC1。进一步的遗传算法（GA）揭示了由88个具有较高c指数（对数秩p？<0.0001，c-index？=？0.656）的基因组成的最佳基因集。我们在独立的乳腺癌数据集上验证了该基因集，并获得了相似的性能（对数秩p≤0.0001，c-index≤0.614）。此外，我们揭示了25个功能注释，15个基因本体术语和14条途径，这些途径显着丰富了在不同生存风险组中表现出不同突变模式的基因。这些功能基因集被用作生存预测模型的新功能。特别是，我们的结果表明，范可尼贫血途径在乳腺癌的预后中具有重要作用。我们的研究表明，基因签名的表达水平仍然是乳腺癌存活预测的有效指标。将基因表达信息与源自体细胞突变的其他类型特征结合在一起，可以进一步提高生存预测的性能。我们研究提出的与生存风险相关的途径可以进一步研究，以改善癌症患者的生存率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号