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学科主题: 临床医学
题名:
Diagnosis of gastric cancer using decision tree classification of mass spectral data
作者: Su, Yahui; Shen, Jing; Qian, Honggang; Ma, Huachong; Ji, Jiafu; Ma, Hong; Ma, Longhua; Zhang, Weihua; Meng, Ling; Li, Zhenfu; Wu, Jian; Jin, Genglin; Zhang, Jianzhi; Shou, Chengchao
刊名: CANCER SCIENCE
发表日期: 2007
DOI: 10.1111/j.1349-7006.2006.00339.x
卷: 98, 期:1, 页:37-43
收录类别: SCI
文章类型: Article
WOS标题词: Science & Technology
类目[WOS]: Oncology
研究领域[WOS]: Oncology
关键词[WOS]: LASER DESORPTION/IONIZATION-TIME ; SERUM PROTEOMIC PATTERNS ; PROSTATE-CANCER ; OVARIAN-CANCER ; CARCINOEMBRYONIC ANTIGEN ; GASTROINTESTINAL-CANCER ; FOLLOW-UP ; IDENTIFICATION ; SPECTROMETRY ; COAGULATION
英文摘要:

Although gastric cancer is the second leading cause of cancer death worldwide, specific and sensitive biomarkers that can be used for its diagnosis are still unavailable. Attempting to improve on current approaches to the serological diagnosis of gastric cancer, we subjected serum samples from 245 individuals (including 127 gastric cancer patients, 100 age- and sex-matched healthy individuals, nine benign gastric lesion patients and nine colorectal cancer patients) for analysis by surface-enhanced laser desorption/ionization (SELDI) mass spectrometry. Peaks were detected with Ciphergen SELDI software version 3.1.1 and analyzed with Biomarker Patterns′ software 5.0. We developed a classifier for separating the gastric cancer groups from the healthy groups. Three protein masses with 1468, 3935 and 7560 m/z were selected as a potential ′fingerprint′ for the detection of gastric cancer. It was able to distinguish the gastric cancer patients from the health volunteers with a sensitivity of 95.6% and a specificity of 92.0% in the training set. In the blinding set, it was capable of differentiating the gastric cancer samples from the others with a specificity of 88.0%, a sensitivity of 85.3%, and an accuracy of 86.4%. These values were all higher than those achieved in a parallel analysis by measuring serum carcinoembryonic antigen (CEA) and carbohydrate antigen (CA)19-9 together. Therefore, the decision tree analysis of serum proteomic patterns has the potential to be used in gastric cancer diagnosis.

语种: 英语
WOS记录号: WOS:000242221500008
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.bjmu.edu.cn/handle/400002259/64815
Appears in Collections:北京大学临床肿瘤学院_期刊论文

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作者单位: 1.Peking Univ, Sch Oncol, Beijing 100036, Peoples R China
2.Beijing Canc Hosp & Inst, Beijing 100036, Peoples R China
3.Beijing Chaoyang Hosp, Beijing 100020, Peoples R China
4.Ciphergen Biosyst, Fremont, CA 94555 USA

Recommended Citation:
Su, Yahui,Shen, Jing,Qian, Honggang,et al. Diagnosis of gastric cancer using decision tree classification of mass spectral data[J]. CANCER SCIENCE,2007,98(1):37-43.
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