A Sample Selection Strategy to Boost the Statistical Power of Signature Detection in Cancer Expression Profile Studies
文献类型：期刊论文
| 作者 | Jia, Zhenyu1,2; Wang, Yipeng3; Hu, Yuanjie4; McLaren, Christine5; Yu, Yingyan6,7; Ye, Kai8; Xia, Xiao-Qin9; Koziol, James A.10; Lernhardt, Waldemar11; McClelland, Michael1,12 |
| 刊名 | ANTI-CANCER AGENTS IN MEDICINAL CHEMISTRY
 |
| 出版日期 | 2013-02-01 |
| 卷号 | 13期号:2页码:203-211 |
| 关键词 | Expression profiles Cell-type heterogeneity Prostate cancer Statistical power Sample size Stepwise enrichment |
| ISSN号 | 1871-5206 |
| 通讯作者 | Jia, ZY (reprint author), Univ Calif Irvine, Dept Pathol & Lab Med, Irvine, CA 92697 USA. |
| 中文摘要 | In case-control profiling studies, increasing the sample size does not always improve statistical power because the variance may also be increased if samples are highly heterogeneous. For instance, tumor samples used for gene expression assay are often heterogeneous in terms of tissue composition or mechanism of progression, or both; however, such variation is rarely taken into account in expression profiles analysis. We use a prostate cancer prognosis study as an example to demonstrate that solely recruiting more patient samples may not increase power for biomarker detection at all. In response to the heterogeneity due to mixed tissue, we developed a sample selection strategy termed Stepwise Enrichment by which samples are systematically culled based on tumor content and analyzed with t-test to determine an optimal threshold for tissue percentage. The selected tissue-percentage threshold identified the most significant data by balancing the sample size and the sample homogeneity; therefore, the power is substantially increased for identifying the prognostic biomarkers in prostate tumor epithelium cells as well as in prostate stroma cells. This strategy can be generally applied to profiling studies where the level of sample heterogeneity can be measured or estimated. |
| 英文摘要 | In case-control profiling studies, increasing the sample size does not always improve statistical power because the variance may also be increased if samples are highly heterogeneous. For instance, tumor samples used for gene expression assay are often heterogeneous in terms of tissue composition or mechanism of progression, or both; however, such variation is rarely taken into account in expression profiles analysis. We use a prostate cancer prognosis study as an example to demonstrate that solely recruiting more patient samples may not increase power for biomarker detection at all. In response to the heterogeneity due to mixed tissue, we developed a sample selection strategy termed Stepwise Enrichment by which samples are systematically culled based on tumor content and analyzed with t-test to determine an optimal threshold for tissue percentage. The selected tissue-percentage threshold identified the most significant data by balancing the sample size and the sample homogeneity; therefore, the power is substantially increased for identifying the prognostic biomarkers in prostate tumor epithelium cells as well as in prostate stroma cells. This strategy can be generally applied to profiling studies where the level of sample heterogeneity can be measured or estimated. |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| 类目[WOS] | Oncology ; Chemistry, Medicinal |
| 研究领域[WOS] | Oncology ; Pharmacology & Pharmacy |
| 关键词[WOS] | GENE-EXPRESSION ; BREAST-CANCER ; PROSTATE-CANCER ; MICROARRAY DATA ; DNA MICROARRAY ; DECONVOLUTION ; PATTERNS ; BIOMARKERS ; PROGNOSIS ; SPECIMENS |
| 收录类别 | SCI |
| 资助信息 | National Institute of Health from NCI Strategic Partners for the Evaluation of Cancer Signatures (SPECS) program [U01 CA114810]; NCI Early Detection Research Network (EDRN) [U01 CA152738]; NCI SBIR [HHSN261200900055C]; University of California of Irvine Faculty Career Development Award; Chao Family Comprehensive Cancer Center at University of California of Irvine [P30CA62203]; [R01 CA068822] |
| 语种 | 英语 |
| WOS记录号 | WOS:000317848800004 |
| 公开日期 | 2013-10-31 |
| 源URL | [http://ir.ihb.ac.cn/handle/342005/19344]  |
| 专题 | 水生生物研究所_水生生物分子与细胞生物学研究中心_期刊论文 |
| 作者单位 | 1.Univ Calif Irvine, Dept Pathol & Lab Med, Irvine, CA 92697 USA 2.Guizhou Normal Coll, Guizhou Prov Key Lab Computat Nanomat Sci, Guiyang 550018, Peoples R China 3.AltheaDx Inc, San Diego, CA 92121 USA 4.Univ Calif Irvine, Dept Biol Chem, Irvine, CA 92697 USA 5.Univ Calif Irvine, Dept Epidemiol, Irvine, CA 92697 USA 6.Shanghai Jiao Tong Univ, Sch Med, Shanghai Ruijin Hosp, Shanghai 200025, Peoples R China 7.Shanghai Jiao Tong Univ, Sch Med, Shanghai Inst Digest Surg, Shanghai 200025, Peoples R China 8.Univ Med Ctr, Mol Epidemiol Sect, Leiden, Netherlands 9.Chinese Acad Sci, Inst Hydrobiol, Wuhan 430072, Peoples R China 10.Scripps Res Inst, La Jolla, CA 92037 USA |
| 推荐引用方式 GB/T 7714 | Jia, Zhenyu,Wang, Yipeng,Hu, Yuanjie,et al. A Sample Selection Strategy to Boost the Statistical Power of Signature Detection in Cancer Expression Profile Studies[J]. ANTI-CANCER AGENTS IN MEDICINAL CHEMISTRY,2013,13(2):203-211. |
| APA | Jia, Zhenyu.,Wang, Yipeng.,Hu, Yuanjie.,McLaren, Christine.,Yu, Yingyan.,...&Mercola, Dan.(2013).A Sample Selection Strategy to Boost the Statistical Power of Signature Detection in Cancer Expression Profile Studies.ANTI-CANCER AGENTS IN MEDICINAL CHEMISTRY,13(2),203-211. |
| MLA | Jia, Zhenyu,et al."A Sample Selection Strategy to Boost the Statistical Power of Signature Detection in Cancer Expression Profile Studies".ANTI-CANCER AGENTS IN MEDICINAL CHEMISTRY 13.2(2013):203-211. |
入库方式： OAI收割
来源：水生生物研究所
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