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题名: Expression Changes in the Stroma of Prostate Cancer Predict Subsequent Relapse
作者: Jia, Zhenyu1; Rahmatpanah, Farah B.1; Chen, Xin1; Lernhardt, Waldemar2; Wang, Yipeng3; Xia, Xiao-Qin4; Sawyers, Anne1; Sutton, Manuel1; McClelland, Michael1, 5; Mercola, Dan1
通讯作者: Jia, ZY (reprint author), Univ Calif Irvine, Dept Pathol & Lab Med, Irvine, CA 92717 USA.
关键词: GENE-EXPRESSION ; TUMOR MICROENVIRONMENT ; RADICAL PROSTATECTOMY ; ACTIVE SURVEILLANCE ; TIME ; DIAGNOSIS ; MARKER ; COHORT ; CELLS ; MEN
刊名: PLOS ONE
发表日期: 2012-08-01
DOI: 10.1371/journal.pone.0041371
卷: 7, 期:8, 页:e41371
收录类别: SCI
文章类型: Article
部门归属: [Jia, Zhenyu; Rahmatpanah, Farah B.; Chen, Xin; Sawyers, Anne; Sutton, Manuel; McClelland, Michael; Mercola, Dan] Univ Calif Irvine, Dept Pathol & Lab Med, Irvine, CA 92717 USA; [Lernhardt, Waldemar] Proveri, San Diego, CA USA; [Wang, Yipeng] AltheaDx, San Diego, CA USA; [Xia, Xiao-Qin] Chinese Acad Sci, Dept Bioinformat, Inst Hydrobiol, Wuhan, Hubei, Peoples R China; [McClelland, Michael] Vaccine Res Inst San Diego, San Diego, CA USA
WOS标题词: Science & Technology
资助者: National Institutes of Health Strategic Partners for the Evaluation of Cancer Signatures (SPECS) Consortium [U01 CA1148102]; National Cancer Institute Early Detection Research Network (EDRN) Consortium [U01 CA152738]; University of California of Irvine Faculty Career Development Award; Chao Family Comprehensive Cancer Center at University of California of Irvine; Department of Defense Congressionally Directed Medical Research Programs [W81XWH-08-1-0720]; University of California of Irvine Institute for Cancer Research from the National Cancer Institute [T32CA009054]
类目[WOS]: Multidisciplinary Sciences
研究领域[WOS]: Science & Technology - Other Topics
摘要: Biomarkers are needed to address overtreatment that occurs for the majority of prostate cancer patients that would not die of the disease but receive radical treatment. A possible barrier to biomarker discovery may be the polyclonal/multifocal nature of prostate tumors as well as cell-type heterogeneity between patient samples. Tumor-adjacent stroma (tumor microenvironment) is less affected by genetic alteration and might therefore yield more consistent biomarkers in response to tumor aggressiveness. To this end we compared Affymetrix gene expression profiles in stroma near tumor and identified a set of 115 probe sets for which the expression levels were significantly correlated with time-to-relapse. We also compared patients that chemically relapsed shortly after prostatectomy (<1 year), and patients that did not relapse in the first four years after prostatectomy. We identified 131 differentially expressed microarray probe sets between these two categories. 19 probe sets (15 genes overlapped between the two gene lists with p<0.0001). We developed a PAM-based classifier by training on samples containing stroma near tumor: 9 rapid relapse patient samples and 9 indolent patient samples. We then tested the classifier on 47 different samples, containing 90% or more stroma. The classifier predicted the risk status of patients with an average accuracy of 87%. This is the first general tumor microenvironment-based prognostic classifier. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for predicting outcomes for patients.
英文摘要: Biomarkers are needed to address overtreatment that occurs for the majority of prostate cancer patients that would not die of the disease but receive radical treatment. A possible barrier to biomarker discovery may be the polyclonal/multifocal nature of prostate tumors as well as cell-type heterogeneity between patient samples. Tumor-adjacent stroma (tumor microenvironment) is less affected by genetic alteration and might therefore yield more consistent biomarkers in response to tumor aggressiveness. To this end we compared Affymetrix gene expression profiles in stroma near tumor and identified a set of 115 probe sets for which the expression levels were significantly correlated with time-to-relapse. We also compared patients that chemically relapsed shortly after prostatectomy (<1 year), and patients that did not relapse in the first four years after prostatectomy. We identified 131 differentially expressed microarray probe sets between these two categories. 19 probe sets (15 genes overlapped between the two gene lists with p<0.0001). We developed a PAM-based classifier by training on samples containing stroma near tumor: 9 rapid relapse patient samples and 9 indolent patient samples. We then tested the classifier on 47 different samples, containing 90% or more stroma. The classifier predicted the risk status of patients with an average accuracy of 87%. This is the first general tumor microenvironment-based prognostic classifier. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for predicting outcomes for patients.
关键词[WOS]: GENE-EXPRESSION ; TUMOR MICROENVIRONMENT ; RADICAL PROSTATECTOMY ; ACTIVE SURVEILLANCE ; TIME ; DIAGNOSIS ; MARKER ; COHORT ; CELLS ; MEN
语种: 英语
WOS记录号: WOS:000307212800017
ISSN号: 1932-6203
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.ihb.ac.cn/handle/342005/17270
Appears in Collections:水生生物分子与细胞生物学研究中心_期刊论文

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作者单位: 1.Univ Calif Irvine, Dept Pathol & Lab Med, Irvine, CA 92717 USA
2.Proveri, San Diego, CA USA
3.AltheaDx, San Diego, CA USA
4.Chinese Acad Sci, Dept Bioinformat, Inst Hydrobiol, Wuhan, Hubei, Peoples R China
5.Vaccine Res Inst San Diego, San Diego, CA USA

Recommended Citation:
Jia, Zhenyu; Rahmatpanah, Farah B.; Chen, Xin; Lernhardt, Waldemar; Wang, Yipeng; Xia, Xiao-Qin; Sawyers, Anne; Sutton, Manuel; McClelland, Michael; Mercola, Dan.Expression Changes in the Stroma of Prostate Cancer Predict Subsequent Relapse,PLOS ONE,2012,7(8):e41371
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