Sparse feature selection for classification and prediction of metastasis in endometrial cancer
作者: Mehmet Eren AhsenTodd P. BorenNitin K. SinghBurook MisganawDavid G. MutchKathleen N. MooreFloor J. BackesCarolyn K. McCourtJayanthi S. LeaDavid S. MillerMichael A. WhiteMathukumalli Vidyasagar
作者单位: 1IBM Research
2The University of Tennessee, College of Medicine
3Apple R&D
4Harvard University
5The Washington University School of Medicine
6The University of Oklohoma
7The Ohio State University
8Brown University
9University of Texas Southwestern Medical Center
10The University of Texas at Dallas
刊名: BMC Genomics, 2017, Vol.18 (3)
来源数据库: Springer Journal
DOI: 10.1186/s12864-017-3604-y
关键词: Endometrial cancerLymph node metastasisSparse classificationMachine learning
英文摘要: Metastasis via pelvic and/or para-aortic lymph nodes is a major risk factor for endometrial cancer. Lymph-node resection ameliorates risk but is associated with significant co-morbidities. Incidence in patients with stage I disease is 4–22% but no mechanism exists to accurately predict it. Therefore, national guidelines for primary staging surgery include pelvic and para-aortic lymph node dissection for all patients whose tumor exceeds 2cm in diameter. We sought to identify a robust molecular signature that can accurately classify risk of lymph node metastasis in endometrial cancer patients. 86 tumors matched for age and race, and evenly distributed between lymph node-positive and lymph node-negative cases, were selected as a training cohort. Genomic micro-RNA expression was profiled for...
原始语种摘要: Metastasis via pelvic and/or para-aortic lymph nodes is a major risk factor for endometrial cancer. Lymph-node resection ameliorates risk but is associated with significant co-morbidities. Incidence in patients with stage I disease is 4–22% but no mechanism exists to accurately predict it. Therefore, national guidelines for primary staging surgery include pelvic and para-aortic lymph node dissection for all patients whose tumor exceeds 2cm in diameter. We sought to identify a robust molecular signature that can accurately classify risk of lymph node metastasis in endometrial cancer patients. 86 tumors matched for age and race, and evenly distributed between lymph node-positive and lymph node-negative cases, were selected as a training cohort. Genomic micro-RNA expression was profiled for...
全文获取路径: Springer  (合作)
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影响因子:4.397 (2012)

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关键词翻译
关键词翻译
  • endometrial 子宫内膜的
  • metastasis 同质蜕变
  • cancer 癌症
  • lymph 淋巴
  • classification 分类
  • feature 结构元件
  • resection 后方交会
  • matched 匹配的
  • aortic 织脉的
  • predictive 预言