基因表达谱预测III期结肠癌预后。

A. Barrier, P. Böelle, D. Brault, A. Flahault, S. Dudoit, A. Lemoine
{"title":"基因表达谱预测III期结肠癌预后。","authors":"A. Barrier, P. Böelle, D. Brault, A. Flahault, S. Dudoit, A. Lemoine","doi":"10.1200/jco.2007.25.18_suppl.10590","DOIUrl":null,"url":null,"abstract":"B20 Purpose. This study aimed to assess the possibility to build a microarray-based prognosis predictor (PP) for stage III colon cancer that could be used to guide postoperative chemotherapy. Material and methods. Thirty-six patients, operated on for a stage III colon cancer, were included in this study. Eighteen patients have subsequently developed a liver metastasis, while the other 18 have remained disease-free for at least 5 years. Tumor mRNA samples were profiled using the Affymetrix HGU133A GeneChip. Patients were repeatedly and randomly divided into 10,000 training (TS) and validation sets (VS) of 10 different sizes. For each TS/VS split, a 30-gene prognosis predictor (PP), identified on the TS by selecting the 30 most differentially expressed genes and applying diagonal linear discriminant analysis, was used to predict the prognoses of VS patients. Results. The 10,000 30-gene PP yielded the following average prognosis prediction performance measures: 72.9% accuracy, 72.2% sensitivity, 73.6% specificity. Improvements in prognosis prediction were observed with increasing TS size (76.1% accuracy, 75.2% sensitivity, and 77.1% specificity for TS of size 32). The 30-gene PP were found to be highly-variable in composition across TS/VS splits. A total of 7,096 genes were included in the 10,000 PP; the higher number of selections for a gene was 5,896. Conclusions. Microarray gene expression profiling is able to predict the prognosis of stage III colon cancer patients and, thus, might be used to guide adjuvant chemotherapy.","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stage III colon cancer prognosis prediction by gene expression profiling.\",\"authors\":\"A. Barrier, P. Böelle, D. Brault, A. Flahault, S. Dudoit, A. Lemoine\",\"doi\":\"10.1200/jco.2007.25.18_suppl.10590\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"B20 Purpose. This study aimed to assess the possibility to build a microarray-based prognosis predictor (PP) for stage III colon cancer that could be used to guide postoperative chemotherapy. Material and methods. Thirty-six patients, operated on for a stage III colon cancer, were included in this study. Eighteen patients have subsequently developed a liver metastasis, while the other 18 have remained disease-free for at least 5 years. Tumor mRNA samples were profiled using the Affymetrix HGU133A GeneChip. Patients were repeatedly and randomly divided into 10,000 training (TS) and validation sets (VS) of 10 different sizes. For each TS/VS split, a 30-gene prognosis predictor (PP), identified on the TS by selecting the 30 most differentially expressed genes and applying diagonal linear discriminant analysis, was used to predict the prognoses of VS patients. Results. The 10,000 30-gene PP yielded the following average prognosis prediction performance measures: 72.9% accuracy, 72.2% sensitivity, 73.6% specificity. Improvements in prognosis prediction were observed with increasing TS size (76.1% accuracy, 75.2% sensitivity, and 77.1% specificity for TS of size 32). The 30-gene PP were found to be highly-variable in composition across TS/VS splits. A total of 7,096 genes were included in the 10,000 PP; the higher number of selections for a gene was 5,896. Conclusions. Microarray gene expression profiling is able to predict the prognosis of stage III colon cancer patients and, thus, might be used to guide adjuvant chemotherapy.\",\"PeriodicalId\":9487,\"journal\":{\"name\":\"Cancer Epidemiology and Prevention Biomarkers\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Epidemiology and Prevention Biomarkers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1200/jco.2007.25.18_suppl.10590\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Epidemiology and Prevention Biomarkers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1200/jco.2007.25.18_suppl.10590","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

B20的目的。本研究旨在评估构建基于微阵列的III期结肠癌预后预测器(PP)的可能性,该预测器可用于指导术后化疗。材料和方法。36名III期结肠癌手术患者参与了这项研究。18名患者随后发生肝转移,而其他18名患者至少5年没有发病。使用Affymetrix HGU133A基因芯片分析肿瘤mRNA样本。将患者反复随机分为10个不同大小的10000个训练集(TS)和验证集(VS)。对于每次TS/VS分裂,通过选择30个差异表达最多的基因并应用对角线性判别分析,在TS上确定一个30基因预后预测因子(PP),用于预测VS患者的预后。结果。1万个30个基因的PP产生了以下平均预后预测指标:准确率72.9%,敏感性72.2%,特异性73.6%。随着TS大小的增加,预后预测有所改善(对于32大小的TS,准确率为76.1%,灵敏度为75.2%,特异性为77.1%)。发现30个基因的PP在TS/VS分裂中组成高度可变。10000个PP中共包含7096个基因;一个基因的较高选择数为5896。结论。微阵列基因表达谱能够预测III期结肠癌患者的预后,因此可能用于指导辅助化疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stage III colon cancer prognosis prediction by gene expression profiling.
B20 Purpose. This study aimed to assess the possibility to build a microarray-based prognosis predictor (PP) for stage III colon cancer that could be used to guide postoperative chemotherapy. Material and methods. Thirty-six patients, operated on for a stage III colon cancer, were included in this study. Eighteen patients have subsequently developed a liver metastasis, while the other 18 have remained disease-free for at least 5 years. Tumor mRNA samples were profiled using the Affymetrix HGU133A GeneChip. Patients were repeatedly and randomly divided into 10,000 training (TS) and validation sets (VS) of 10 different sizes. For each TS/VS split, a 30-gene prognosis predictor (PP), identified on the TS by selecting the 30 most differentially expressed genes and applying diagonal linear discriminant analysis, was used to predict the prognoses of VS patients. Results. The 10,000 30-gene PP yielded the following average prognosis prediction performance measures: 72.9% accuracy, 72.2% sensitivity, 73.6% specificity. Improvements in prognosis prediction were observed with increasing TS size (76.1% accuracy, 75.2% sensitivity, and 77.1% specificity for TS of size 32). The 30-gene PP were found to be highly-variable in composition across TS/VS splits. A total of 7,096 genes were included in the 10,000 PP; the higher number of selections for a gene was 5,896. Conclusions. Microarray gene expression profiling is able to predict the prognosis of stage III colon cancer patients and, thus, might be used to guide adjuvant chemotherapy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信