...
首页> 外文期刊>Computers in Biology and Medicine >Multi-scale representation of proteomic data exhibits distinct microRNA regulatory modules in non-smoking female patients with lung adenocarcinoma
【24h】

Multi-scale representation of proteomic data exhibits distinct microRNA regulatory modules in non-smoking female patients with lung adenocarcinoma

机译:蛋白质组学数据的多尺度表示表现出在非吸烟女性肺腺癌患者中的明显微瘤监管模块

获取原文
获取原文并翻译 | 示例
           

摘要

Adenocarcinoma in female non-smokers is an under-explored subgroup of non-small cell lung cancer (NSCLC), in which the molecular mechanism and genetic risk factors remain unclear. We analyzed the protein profiles of plasma samples of 45 patients in this subgroup and 60 non-cancer subjects using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Among 85 peaks of mass spectra, the differential expression analysis identified 15 markers based on False Discovery Rate control and the Discrete Wavelet Transforms further selected a cluster of 6 markers that were consistently observed at multiple scales of mass-charge ratios. This marker cluster, corresponding to 7 unique proteins, was able to distinguish the female non-smokers with adenocarcinoma from non cancer subjects with a value of accuracy of 87.6%. We also predicted the role of competing endogenous RNAs (ceRNAs) in 3 out of these 7 proteins. Other studies reported that these ceRNAs and their targeting microRNAs, miR-206 and miR-613, were significantly associated with NSCLC. This study paves a crucial path for further investigating the genetic markers and molecular mechanism of this special NSCLC subgroup.
机译:女性非吸烟者的腺癌是非小细胞肺癌(NSCLC)的缺陷亚组,其中分子机制和遗传危险因素仍不清楚。我们使用表面增强的激光解吸/电离飞行时间质谱法分析了该亚组中45名患者的45名患者的蛋白质样品的蛋白质谱。在85个质谱峰之间,鉴别表达分析鉴定了基于假发现速率控制的15个标记,并且离散小波变换进一步选择了在质量电荷比的多个尺度上一致地观察到的6个标记的簇。该标记簇对应于7种独特的蛋白质,能够将女性非吸烟者与非癌症受试者的腺癌区分开,值为87.6%。我们还预测了这些7个蛋白中的3个中的内源性RNA(Cernas)的作用。其他研究报告说,这些Cernas及其靶向MicroRNA,miR-206和miR-613与NSCLC显着相关。本研究铺平了重要的路径,用于进一步研究这种特殊NSCLC亚组的遗传标记和分子机制。

著录项

相似文献

  • 外文文献
  • 中文文献
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