An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients

被引：2276

作者：

Gyoerffy, Balazs ^{[1
,2
]}

Lanczky, Andras ^{[1
,2
,3
]}

Eklund, Aron C. ^{[4
]}

Denkert, Carsten ^{[5
]}

Budczies, Jan ^{[5
]}

Li, Qiyuan ^{[4
]}

Szallasi, Zoltan ^{[4
,6
]}

机构：

[1] Hungarian Acad Sci, Joint Res Lab, H-1083 Budapest, Hungary

[2] Semmelweis Univ, Dept Pediat 1, H-1083 Budapest, Hungary

[3] Pazmany Peter Univ, Budapest, Hungary

[4] Tech Univ Denmark, Ctr Biol Sequence Anal, DK-2800 Lyngby, Denmark

[5] Charite, D-13353 Berlin, Germany

[6] Harvard Univ, Sch Med, Harvard MIT Div Hlth Sci & Technol CHIP HST, Childrens Hosp,Informat Program, Boston, MA USA

来源：

BREAST CANCER RESEARCH AND TREATMENT | 2010年 / 123卷 / 03期

关键词：

Survival analysis; Breast cancer; Prognosis; EXPRESSION MEASUREMENTS; HISTOLOGIC GRADE; ADJUVANT THERAPY; RECEPTOR STATUS; METASTASIS; SIGNATURE; TAMOXIFEN; MARKERS; REPRODUCIBILITY; CHEMOTHERAPY;

D O I：

10.1007/s10549-009-0674-9

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Validating prognostic or predictive candidate genes in appropriately powered breast cancer cohorts are of utmost interest. Our aim was to develop an online tool to draw survival plots, which can be used to assess the relevance of the expression levels of various genes on the clinical outcome both in untreated and treated breast cancer patients. A background database was established using gene expression data and survival information of 1,809 patients downloaded from GEO (Affymetrix HGU133A and HGU133+2 microarrays). The median relapse free survival is 6.43 years, 968/1,231 patients are estrogen-receptor (ER) positive, and 190/1,369 are lymph-node positive. After quality control and normalization only probes present on both Affymetrix platforms were retained (n = 22,277). In order to analyze the prognostic value of a particular gene, the cohorts are divided into two groups according to the median (or upper/lower quartile) expression of the gene. The two groups can be compared in terms of relapse free survival, overall survival, and distant metastasis free survival. A survival curve is displayed, and the hazard ratio with 95% confidence intervals and logrank P value are calculated and displayed. Additionally, three subgroups of patients can be assessed: systematically untreated patients, endocrine-treated ER positive patients, and patients with a distribution of clinical characteristics representative of those seen in general clinical practice in the US. Web address: www.kmplot.com. We used this integrative data analysis tool to confirm the prognostic power of the proliferation-related genes TOP2A and TOP2B, MKI67, CCND2, CCND3, CCNDE2, as well as CDKN1A, and TK2. We also validated the capability of microarrays to determine estrogen receptor status in 1,231 patients. The tool is highly valuable for the preliminary assessment of biomarkers, especially for research groups with limited bioinformatic resources.

引用

页码：725 / 731

页数：7

共 33 条

[21] Population-based validation of the prognostic model ADJUVANT! for early breast cancer [J].

Olivotto, IA ;

Bajdik, CD ;

Ravdin, PM ;

Speers, CH ;

Coldman, AJ ;

Norris, BD ;

Davis, GJ ;

Chia, SK ;

Gelmon, KA .

JOURNAL OF CLINICAL ONCOLOGY, 2005, 23 (12) :2716-2725

[22] A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer [J].

Paik, S ;

Shak, S ;

Tang, G ;

Kim, C ;

Baker, J ;

Cronin, M ;

Baehner, FL ;

Walker, MG ;

Watson, D ;

Park, T ;

Hiller, W ;

Fisher, ER ;

Wickerham, DL ;

Bryant, J ;

Wolmark, N .

NEW ENGLAND JOURNAL OF MEDICINE, 2004, 351 (27) :2817-2826

[23] Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer [J].

Paik, Soonmyung ;

Tang, Gong ;

Shak, Steven ;

Kim, Chungyeul ;

Baker, Joffre ;

Kim, Wanseop ;

Cronin, Maureen ;

Baehner, Frederick L. ;

Watson, Drew ;

Bryant, John ;

Costantino, Joseph P. ;

Geyer, Charles E., Jr. ;

Wickerham, D. Lawrence ;

Wolmark, Norman .

JOURNAL OF CLINICAL ONCOLOGY, 2006, 24 (23) :3726-3734

[24] Gene expression profiling spares early breast cancer patients from adjuvant therapy:: derived and validated in two population-based cohorts [J].

Pawitan, Y ;

Bjöhle, J ;

Amler, L ;

Borg, AL ;

Egyhazi, S ;

Hall, P ;

Han, X ;

Holmberg, L ;

Huang, F ;

Klaar, S ;

Liu, ET ;

Miller, L ;

Nordgren, H ;

Ploner, A ;

Sandelin, K ;

Shaw, PM ;

Smeds, J ;

Skoog, L ;

Wedrén, S ;

Bergh, J .

BREAST CANCER RESEARCH, 2005, 7 (06) :R953-R964

[25]

Pusztai L, 2003, CLIN CANCER RES, V9, P2406

[26] Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer [J].

Ravdin, PM ;

Siminoff, LA ;

Davis, GJ ;

Mercer, MB ;

Hewlett, J ;

Gerson, N ;

Parker, HL .

JOURNAL OF CLINICAL ONCOLOGY, 2001, 19 (04) :980-991

[27] The humoral immune system has a key prognostic impact in node-negative breast cancer [J].

Schmidt, Marcus ;

Boehm, Daniel ;

von Toerne, Christian ;

Steiner, Eric ;

Puhl, Alexander ;

Pilch, Henryk ;

Lehr, Hans-Anton ;

Hengstler, Jan G. ;

Koelbl, Heinz ;

Gehrmann, Mathias .

CANCER RESEARCH, 2008, 68 (13) :5405-5413

[28] The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements [J].

Shi, Leming ;

Reid, Laura H. ;

Jones, Wendell D. ;

Shippy, Richard ;

Warrington, Janet A. ;

Baker, Shawn C. ;

Collins, Patrick J. ;

de Longueville, Francoise ;

Kawasaki, Ernest S. ;

Lee, Kathleen Y. ;

Luo, Yuling ;

Sun, Yongming Andrew ;

Willey, James C. ;

Setterquist, Robert A. ;

Fischer, Gavin M. ;

Tong, Weida ;

Dragan, Yvonne P. ;

Dix, David J. ;

Frueh, Felix W. ;

Goodsaid, Federico M. ;

Herman, Damir ;

Jensen, Roderick V. ;

Johnson, Charles D. ;

Lobenhofer, Edward K. ;

Puri, Raj K. ;

Scherf, Uwe ;

Thierry-Mieg, Jean ;

Wang, Charles ;

Wilson, Mike ;

Wolber, Paul K. ;

Zhang, Lu ;

Amur, Shashi ;

Bao, Wenjun ;

Barbacioru, Catalin C. ;

Lucas, Anne Bergstrom ;

Bertholet, Vincent ;

Boysen, Cecilie ;

Bromley, Bud ;

Brown, Donna ;

Brunner, Alan ;

Canales, Roger ;

Cao, Xiaoxi Megan ;

Cebula, Thomas A. ;

Chen, James J. ;

Cheng, Jing ;

Chu, Tzu-Ming ;

Chudin, Eugene ;

Corson, John ;

Corton, J. Christopher ;

Croner, Lisa J. .

NATURE BIOTECHNOLOGY, 2006, 24 (09) :1151-1161

[29] The removal of multiplicative, systematic bias allows integration of breast cancer gene expression datasets - improving meta-analysis and prediction of prognosis [J].

Sims, Andrew H. ;

Smethurst, Graeme J. ;

Hey, Yvonne ;

Okoniewski, Michal J. ;

Pepper, Stuart D. ;

Howell, Anthony ;

Miller, Crispin J. ;

Clarke, Robert B. .

BMC MEDICAL GENOMICS, 2008, 1 (1)

[30] Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis [J].

Sotiriou, C ;

Wirapati, P ;

Loi, S ;

Harris, A ;

Fox, S ;

Smeds, J ;

Nordgren, H ;

Farmer, P ;

Praz, V ;

Haibe-Kains, B ;

Desmedt, C ;

Larsimont, D ;

Cardoso, F ;

Peterse, H ;

Nuyten, D ;

Buyse, M ;

Van de Vijver, MJ ;

Bergh, J ;

Piccart, MT ;

Delorenzi, M .

JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2006, 98 (04) :262-272

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