Transcriptional Profiles in Peripheral Blood Mononuclear Cells Prognostic of Clinical Outcomes in Patients with Advanced Renal Cell Carcinoma

Author:

Burczynski Michael E.1,Twine Natalie C.1,Dukart Gary2,Marshall Bonnie2,Hidalgo Manuel3,Stadler Walter M.4,Logan Theodore5,Dutcher Janice6,Hudes Gary7,Trepicchio William L.8,Strahs Andrew9,Immermann Fred10,Slonim Donna K.11,Dorner Andrew J.1

Affiliation:

1. 1Molecular Profiling and Biomarker Discovery,

2. 4Clinical Research and Development, Wyeth Research, Collegeville, Pennsylvania;

3. 5University of Texas Health Science Center, San Antonio, Texas;

4. 6University of Chicago, Chicago, Illinois;

5. 7Indiana University, Indianapolis, Indiana;

6. 8Our Lady of Mercy Medical Center, New York Medical College, Bronx, New York;

7. 9Fox Chase Cancer Center, Philadelphia, Pennsylvania;

8. 10Millenium Pharmaceuticals, Cambridge, Massachusetts; and

9. 2Clinical Biostatistics, and

10. 11Biometrics Research, Wyeth Research, Pearl River, New York

11. 3Bioinformatics, Wyeth Research, Cambridge, Massachusetts;

Abstract

Abstract Purpose: Given their accessibility, surrogate tissues, such as peripheral blood mononuclear cells (PBMC), may provide potential predictive biomarkers in clinical pharmacogenomic studies. In leukemias and lymphomas, the prognostic value of peripheral blast expression profiles is clear; however, it is unclear whether circulating mononuclear cells of patients with solid tumors might yield profiles with similar prognostic associations. Experimental Design: In this study, we evaluated the association of expression profiles in PBMCs with clinical outcomes in patients with advanced renal cell cancer. Transcriptional patterns in PBMCs of 45 renal cell cancer patients were compared with clinical outcome data at the conclusion of a phase II study of the mTOR kinase inhibitor CCI-779 to determine whether pretreatment transcriptional patterns in PBMCs were correlated with eventual patient outcomes. Results: Unsupervised hierarchical clustering of the PBMC profiles using all expressed genes identified clusters of patients with significant differences in survival. Cox proportional hazards modeling showed that the expression levels of many PBMC transcripts were predictors for the patient outcomes of time to progression and overall survival (time to death). Supervised class prediction approaches identified multivariate expression patterns in PBMCs capable of assigning favorable outcomes of time to death and time to progression in a test set of renal cancer patients, with overall performance accuracies of 72% and 85%, respectively. Conclusions: The present study provides the first example of gene expression profiling in peripheral blood, a clinically accessible surrogate tissue, for identifying patterns of gene expression associated with higher likelihoods of positive outcome in patients with a solid tumor.

Publisher

American Association for Cancer Research (AACR)

Subject

Cancer Research,Oncology

Reference20 articles.

1. Su AI, Welsh JB, Sapinoso LM, et al. Molecular classification of human carcinomas by use of gene expression signatures. Cancer Res 2001;61:7388–93.

2. Ramaswamy S, Tamayo P, Rifkin R, et al. Multiclass cancer diagnosis using tumor gene expression signatures. Proc Natl Acad Sci U S A 2001;98:15149–54.

3. van't Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415:530–6.

4. Beer DG, Kardia SL, Huang CC, et al. Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nat Med 2002;8:816–24.

5. Rosenwald A, Wright G, Chan WC, et al. The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. N Engl J Med 2002;346:1937–47.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3