Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees

BMC Bioinformatics

Volumn 14, Issue , 2013, Pages

  Chou, Hsiu Ling ^a   Yao, Chung Tay ^b   Su, Sui Lun ^c   Lee, Chia Yi ^c   Hu, Kuang Yu ^d   Terng, Harn Jing ^e   Shih, Yun Wen ^c   Chang, Yu Tien ^c   Lu, Yu Fen ^c   Chang, Chi Wen ^f   Wahlqvist, Mark L ^g   Wetter, Thomas ^h   Chu, Chi Ming ^c  

^a ORIENTAL INSTITUTE OF TECHNOLOGY   (Taiwan)

^b CATHAY GENERAL HOSPITAL   (Taiwan)

^c NATIONAL DEFENSE MEDICAL CENTER   (Taiwan)

^d CHUNG HUA UNIVERSITY   (Taiwan)

^e Advpharma Inc   (Taiwan)

^f CHANG GUNG UNIVERSITY COLLEGE OF MEDICINE   (Taiwan)

^g NATIONAL HEALTH RESEARCH INSTITUTES   (Taiwan)

^h UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

Artificial neural network; Breast cancer; Decision tree; Logistic regression; Microarray

Indexed keywords

AREA UNDER ROC CURVE (AUC); BREAST CANCER; CDNA MICROARRAY ANALYSIS; DATA MINING ALGORITHM; GENE EXPRESSION PROFILES; GENE EXPRESSION PROFILING; LOGISTIC REGRESSIONS; MICROARRAY TECHNOLOGIES;

ALGORITHMS; DATA MINING; DECISION TREES; EXTRAPOLATION; FORECASTING; GENE EXPRESSION; LOGISTICS; MICROARRAYS; NEURAL NETWORKS; REGRESSION ANALYSIS; STATISTICAL TESTS;

DISEASES;

COMPLEMENTARY DNA;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BREAST TUMOR; DECISION TREE; DNA MICROARRAY; FEMALE; GENE EXPRESSION PROFILING; GENETIC DATABASE; GENETICS; HUMAN; RECURRENT DISEASE; SAMPLE SIZE; STATISTICAL MODEL; SURVIVAL;

BREAST NEOPLASMS; DATABASES, GENETIC; DECISION TREES; DNA, COMPLEMENTARY; FEMALE; GENE EXPRESSION PROFILING; HUMANS; LOGISTIC MODELS; NEURAL NETWORKS (COMPUTER); OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; RECURRENCE; SAMPLE SIZE; SURVIVAL ANALYSIS;

EID: 84875056983     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-14-100     Document Type: Article

References (28)

1. American Cancer Society 2011, http://www.cancer.org/docroot/home/index.asp.
2. Eifel P, Axelson JA, Costa J, Crowley J, Curran WJ, Deshler A, Fulton S, Hendricks CB, Kemeny M, Kornblith AB. National Institutes of Health Consensus Development Conference Statement: adjuvant therapy for breast cancer: 1-3 November 2000. J Natl Cancer Inst 2001, 93:979-989.
3. McGuire WL. Breast cancer prognostic factors: evaluation guidelines. J Natl Cancer Inst 1991, 83:154-155. 10.1093/jnci/83.3.154, 1988696.
4. Davis CA, Gerick F, Hintermair V, Friedel CC, Fundel K, Kuffner R, Zimmer R. Reliable gene signatures for microarray classification: assessment of stability and performance. Bioinformatics 2006, 22:2356-2363. 10.1093/bioinformatics/btl400, 16882647.
5. Gemignani F, Perra C, Landi S, Canzian F, Kurg A, Tonisson N, Galanello R, Cao A, Metspalu A, Romeo G. Reliable detection of beta-thalassemia and G6PD mutations by a DNA microarray. Clin Chem 2002, 48:2051-2054.
6. Gutmann O, Kuehlewein R, Reinbold S, Niekrawietz R, Steinert CP, de Heij B, Zengerle R, Daub M. Fast and reliable protein microarray production by a new drop-in-drop technique. Lab Chip 2005, 5:675-681. 10.1039/b418765b, 15915261.
7. Lassmann S, Kreutz C, Schoepflin A, Hopt U, Timmer J, Werner M. A novel approach for reliable microarray analysis of microdissected tumor cells from formalin-fixed and paraffin-embedded colorectal cancer resection specimens. J Mol Med 2009, 87:211-224. 10.1007/s00109-008-0419-y, 19066834.
8. Shi L, Perkins RG, Fang H, Tong W. Reproducible and reliable microarray results through quality control: good laboratory proficiency and appropriate data analysis practices are essential. Curr Opin Biotechnol 2008, 19:10-18. 10.1016/j.copbio.2007.11.003, 18155896.
9. Stirewalt DL, Pogosova-Agadjanyan EL, Khalid N, Hare DR, Ladne PA, Sala-Torra O, Zhao LP, Radich JP. Single-stranded linear amplification protocol results in reproducible and reliable microarray data from nanogram amounts of starting RNA. Genomics 2004, 83:321-331. 10.1016/j.ygeno.2003.08.008, 14706461.
10. van der Spek PJ, Kremer A, Murry L, Walker MG. Are gene expression microarray analyses reliable? A review of studies of retinoic acid responsive genes. Genomics Proteomics Bioinformatics 2003, 1:9-14.
11. Xu X, Li Y, Zhao H, Wen SY, Wang SQ, Huang J, Huang KL, Luo YB. Rapid and reliable detection and identification of GM events using multiplex PCR coupled with oligonucleotide microarray. J Agric Food Chem 2005, 53:3789-3794. 10.1021/jf048368t, 15884798.
12. Desmedt C, Piette F, Loi S, Wang Y, Lallemand F, Haibe-Kains B, Viale G, Delorenzi M, Zhang Y, d'Assignies MS. Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series. Clin Cancer Res 2007, 13:3207-3214. 10.1158/1078-0432.CCR-06-2765, 17545524.
13. Ivshina AV, George J, Senko O, Mow B, Putti TC, Smeds J, Lindahl T, Pawitan Y, Hall P, Nordgren H. Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer. Cancer Res 2006, 66:10292-10301. 10.1158/0008-5472.CAN-05-4414, 17079448.
14. Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J, Nordgren H, Farmer P, Praz V, Haibe-Kains B. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 2006, 98:262-272. 10.1093/jnci/djj052, 16478745.
15. Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F, Talantov D, Timmermans M, Meijer-van Gelder ME, Yu J. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 2005, 365:671-679.
16. Wang Y, Sun G, Ji Z, Xing C, Liang Y. Weighted change-point method for detecting differential gene expression in breast cancer microarray data. PLoS One 2012, 7:e29860. 10.1371/journal.pone.0029860, 3262809, 22276133.
17. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 2005, 102:15545-15550. 10.1073/pnas.0506580102, 1239896, 16199517.
18. Padoan A. Net Reclassification Improvement (NRI) has been proposed as an alternative to the area under the curve of the the ROC 2010, The MathWorks, Inc, http://www.mathworks.com/matlabcentral/fileexchange/28579-net-reclassification-improvement&watching=28579. Accessed 22. November 2012.
19. Pencina MJ, D'Agostino RB, D'Agostino RB, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 2008, 27:157-172. discussion 207-212, 10.1002/sim.2929, 17569110.
20. Pencina MJ, D'Agostino RB, Demler OV. Novel metrics for evaluating improvement in discrimination: net reclassification and integrated discrimination improvement for normal variables and nested models. Stat Med 2012, 31:101-113. 10.1002/sim.4348, 3341978, 22147389.
21. Pencina MJ, D'Agostino RB, Steyerberg EW. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 2011, 30:11-21. 10.1002/sim.4085, 3341973, 21204120.
22. Beyer SJ, Zhang X, Jimenez RE, Lee ML, Richardson AL, Huang K, Jhiang SM. Microarray analysis of genes associated with cell surface NIS protein levels in breast cancer. BMC Res Notes 2011, 4:397. 10.1186/1756-0500-4-397, 3205061, 21989294.
23. Delen D, Walker G, Kadam A. Predicting breast cancer survivability: a comparison of three data mining methods. Artif Intell Med 2005, 34:113-127. 10.1016/j.artmed.2004.07.002, 15894176.
24. Kumar R, Sharma A, Tiwari RK. Application of microarray in breast cancer: An overview. J Pharm Bioallied Sci 2012, 4:21-26. 3283953, 22368395.
25. Snow PB, Kerr DJ, Brandt JM, Rodvold DM. Neural network and regression predictions of 5-year survival after colon carcinoma treatment. Cancer 2001, 91:1673-1678. 10.1002/1097-0142(20010415)91:8+<1673::AID-CNCR1182>3.0.CO;2-T, 11309767.
26. Hsu YH. Investigating the Models of Logistic Regression, Decision Tree, Artificial Neural Network and Hybrid Analysis for Predicting Coronary Artery Disease 2007, Taipei, Taiwan: Master Thesis of National Defense Medical Center.
27. Xu L, Tan AC, Winslow RL, Geman D. Merging microarray data from separate breast cancer studies provides a robust prognostic test. BMC Bioinformatics 2008, 9:125. 10.1186/1471-2105-9-125, 2409450, 18304324.
28. Pawitan Y, Bjohle J, Amler L, Borg AL, Egyhazi S, Hall P, Han X, Holmberg L, Huang F, Klaar S. Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts. Breast Cancer Res 2005, 7:R953-R964. 10.1186/bcr1325, 1410752, 16280042.