Combining genome-wide and targeted gene expression profiling in drug discovery: Microarrays and real-time PCR

Drug Discovery Today

Volumn 9, Issue 19, 2004, Pages 838-845

  Brazeau, Daniel A ^a  

^a UNIVERSITY AT BUFFALO   (United States)

Author keywords

Bioinformatics; Chemical Biology; Cluster analysis; Drug Discovery; False discovery rate; Family wise error rate; Oligonucleotides; Permutation analysis; Pharmaceutical Science

Indexed keywords

FLUORESCENT DYE;

ALGORITHM; DNA MICROARRAY; DRUG MECHANISM; GENE EXPRESSION; GENE TARGETING; GENETIC IDENTIFICATION; GENETIC TRANSCRIPTION; GENOME; MOLECULAR CLONING; MOLECULE; REAL TIME POLYMERASE CHAIN REACTION; REVIEW; STANDARDIZATION; STATISTICAL ANALYSIS; STUDENT T TEST; VALIDATION PROCESS;

ANIMALS; DRUG DESIGN; GENE EXPRESSION PROFILING; GENOME; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PHARMACOGENETICS; POLYMERASE CHAIN REACTION;

EID: 4644362593     PISSN: 13596446     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1359-6446(04)03231-3     Document Type: Review

References (94)

1. Schena M., et al. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science. 270:1995;467-470
2. Lockhart D.J., et al. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat. Biotechnol. 14:1996;1675-1680
3. Brown P.O., Botstein D. Exploring the new world of the genome with DNA microarrays. Nat. Genet. 21:1999;33-37
4. Eickhoff B., et al. Normalization of array hybridization experiments in differential gene expression analysis. Nucleic Acids Res. 27:1999;e33
5. Tseng G.C., et al. Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects. Nucleic Acids Res. 29:2001;2549-2557
6. Bolstad B.M., et al. A comparison of normalization methods for high-density oligonucleotide array data based on variance and bias. Bioinformatics. 19:2003;185-193
7. Hoffmann R.T., et al. Profound effect of normalization on detection of differentially expressed genes in oligonucleotide microarray data analysis. Genome Biol. 14:2002;. research0033
8. Wilson D.L., et al. New normalization methods for cDNA microarray data. Bioinformatics. 19:2003;1325-1332
9. Yang Y.H., et al. Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 30:2002;e15
10. Vandesompele J.K., et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 3:2002;. research0034
11. Kerr M., Churchill G.A. Analysis of variance for gene expression microarray data. J. Comput. Biol. 7:2000;819-837
12. Parmigiani G.,, et al. The Analysis of Gene Expression. Methods and Software (Statistics for Biology and Health). 2003;Springer
13. Brazma A., Vilo J. Gene expression data analysis. FEBS Lett. 480:2000;17-24
14. King H.C., Sinha A.A. Gene expression profile analysis by DNA microarrays: promises and pitfalls. J. Am. Med. Assoc. 286:2001;2280-2288
15. Lee M-L.T., et al. Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations. Proc. Natl. Acad. Sci. U. S. A. 97:2000;9834-9839
16. Quackenbush J. Computational analysis of microarray data. Nat. Rev. Genet. 2:2001;418-427
17. Smyth G.K., et al. Statistical Issues in cDNA Microarray Data Analysis. Brownstein M.J., Khodursky A.B. Functional Genomics: Methods and Protocols. 2003;111-136 Humana Press
18. Kerr M.K., Churchill G.A. Statistical design and the analysis of gene expression. Genet. Res. 77:2001;123-128
19. Miller R.A., et al. Interpretation, design, and analysis of gene array expression experiments. J. Gerontol. A Biol. Sci. Med. Sci. 56:2001;B52-B57
20. Draghici S. Data Analysis Tools for DNA Microarrays. 2003;Chapman and Hall
21. Speed T. Statistical Analysis of Gene Expression Data. 2003;Chapman and Hall
22. Dudoit S., et al. Statistical models for identifying differentially expressed genes in replicated cDNA microarray experiments. Technical Report. 578:2000;111-139 University of California, Berkeley
23. Eisen M.B., et al. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. U. S. A. 95:1998;14863-14868
24. Tavazoie S., et al. Systematic determination of genetic network architecture. Nat. Genet. 22:1999;281-285
25. Toronen P., et al. Analysis of gene expression data using self-organizing maps. FEBS Lett. 451:1999;142-146
26. Ringner M., et al. Analyzing array data using supervised methods. Pharmacogenomics. 3:2002;403-415
27. Cui X., Churchill G.A. Statistical tests for differential expression in cDNA microarray experiments. Genome Biol. 4:2003;210
28. Troyanskaya O.G., et al. Nonparametric methods for identifying differentially expressed genes in microarray data. Bioinformatics. 18:2002;1454-1461
29. Efron B., Tibshirani R. Empirical Bayes methods and false discovery rates for microarrays. Genet. Epidemiol. 23:2002;70-86
30. Pan W. On the use of permutation in and the performance of a class of nonparametric methods to detect differential gene expression. Bioinformatics. 19:2003;1333-1340
31. Broberg P. Statistical methods for ranking differentially expressed genes. Genome Biol. 4:2003;R41
32. Zhao Y., et al. Modified nonparametric approaches to detecting differentially expressed gene in replicated microarray experiments. Bioinformatics. 19:2003;1046-1054
33. Brody J.P., et al. Significance and statistical errors in the analysis of DNA microarray data. Proc. Natl. Acad. Sci. U. S. A. 99:2002;12975-12978
34. Xu R., Li X. A comparison of parametric versus permutation methods with applications to general and temporal microarray gene expression data. Bioinformatics. 19:2003;1284-1289
35. Shaffer J.P. Modified sequentially rejective multiple test procedures. J. Am. Stat. Assoc. 81:1986;826-831
36. Hochberg Y., Tamhane A.C. Multiple Comparison Procedures. 1987;Wiley
37. Felsenstein J. Confidence limits on phylogenies: an approach using bootstrap. Evolution. 39:1985;783-791
38. Benjamini Y., Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Roy. Statist. Soc. B. 57:1995;289-300
39. Storey, J.D. and Tibshirani, R. (2001) Estimating false discovery rate under dependence with application to DNA microarrays. Technical Report 28, pp. 1-24, Department of Statistics, Stanford University
40. Storey J.D. A direct approach to false discovery rates. J. Roy. Statist. Soc. B. 64:2002;479-498
41. Storey J.D., Tibshirani R. Statistical significance for genome-wide studies. Proc. Natl. Acad. Sci. U. S. A. 100:2003;9440-9445
42. Reiner A., et al. Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics. 19:2003;368-375
43. Benjamini Y., Yekutieli D. The control of the false discovery rate in multiple tests under dependency. Ann. Stat. 29:2001;1165-1188
44. Storey J.D., Tibshirani R. SAM Thresholding and False Discovery Rates for Detecting Differential Gene Expression in DNA Micorarrays. Parmigiani G.,, et al. The Analysis of Gene Expression. Methods and Software. 2003;272-290 Springer
45. Wang E.Q., et al. cDNA microarray analysis of vascular gene expression after nitric oxide donor infusions in rats: implications for nitrate tolerance mechanisms. AAPS PharmSci. 4:2002;E10
46. Tran D.C., et al. Inhalant nitrite exposure alters mouse hepatic angiogenic gene expression. Biochem. Biophys. Res. Commun. 310:2003;439-445
47. Westfall P.H., Young S.S. Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment. 1993;Wiley
48. Tusher V.G., et al. Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. U. S. A. 98:2001;5116-5121
49. Pan W. A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments. Bioinformatics. 18:2002;546-554
50. Pan W., et al. A mixture model approach to detecting differentially expressed genes with microarray data. Funct. Integr. Genomics. 3:2003;117-124
51. Taniguchi M., et al. Quantitative assessment of DNA microarrays: comparison with northern blots. Genomics. 71:2001;34-39
52. Yuen T., et al. Accuracy and calibration of commercial oligonucleotide and custom cDNA microarrays. Nucleic Acids Res. 30:2002;e48
53. Chen G., et al. Discordant protein and mRNA expression in lung adenocarcinomas. Mol. Cell. Proteomics. 1:2002;304-313
54. Gygi S.P., et al. Correlation between protein and mRNA abundance in yeast. Mol. Cell. Biol. 19:1999;1720-1730
55. Li J., et al. Differential gene expression patterns revealed by oligonucleotide versus long cDNA arrays. Toxicol. Sci. 69:2002;383-390
56. Kothapalli R., et al. Microarray results: how accurate are they? BMC Bioinformatics. 3:2002;22-32
57. Kuo W.P., et al. Analysis of matched mRNA measurements from two different microarray technologies. Bioinformatics. 18:2002;405-412
58. Tan P.K., et al. Evaluation of gene expression measurements from commercial microarray platforms. Nucleic Acids Res. 31:2003;5676-5684
59. Liss B. Improved quantitative real-time RT-PCR for expression profiling of individual cells. Nucleic Acids Res. 30:2002;e89
60. Zimmermann K., Mannhalter W. Technical aspects of quantitative competitive PCR. Biotechniques. 21:1996;268-279
61. Freeman W.M., et al. Quantitative RT-PCR: pitfalls and potential. Biotechniques. 26:1999;112-125
62. Bustin S.A. Quantification of mRNA using real-time reverse transcription (PCR) (RT-PCR): trends and problems. J. Mol. Endocrinol. 29:2002;23-39
63. Heid C., et al. Real time quantitative PCR. Genome Res. 6:1996;986-994
64. Didenko V.V. DNA probes using fluorescence resonance energy transfer (FRET): designs and applications. Biotechniques. 31:2001;1106-1121
65. Wall S.J., Edwards D.R. Quantitative reverse transcription-polymerase chain reaction (RT-PCR): a comparison of primer-dropping, competitive, and real-time RT-PCRs. Anal. Biochem. 300:2002;269-273
66. Lekanne Deprez R.H., et al. Sensitivity and accuracy of quantitative real-time polymerase chain reaction using SYBR green I depends on cDNA synthesis conditions. Anal. Biochem. 307:2002;63-69
67. Livak K., et al. Oligonucleotides with fluorescent dyes at opposite ends provide a quenched probe system useful for detecting PCR products and nucleic acid hybridization. PCR Methods Appl. 4:1995;357-362
68. Holland P.M., et al. Detection of specific polymerase chain reaction product by utilizing the 5′ to 3′ exonuclease activity of Thermus aquaticus. Proc. Natl. Acad. Sci. U. S. A. 88:1991;7276-7280
69. Bonnet G., et al. Thermodynamic basis of the enhanced specificity of structured DNA probes. Proc. Natl. Acad. Sci. U. S. A. 96:1999;6171-6176
70. Tyagi S., Kramer F.R. Molecular beacons: probes that fluoresce upon hybridization. Nat. Biotechnol. 14:1996;303-308
71. Tyagi S., et al. Multicolor molecular beacons for allele discrimination. Nat. Biotechnol. 16:1998;49-53
72. Whitcombe D., et al. Detection of PCR products using self-probing amplicons and fluorescence. Nat. Biotechnol. 17:1999;804-807
73. Nazarenko I., et al. Multiplex quantitative PCR using self-quenched primers labeled with a single fluorophore. Nucleic Acids Res. 30:2002;e37
74. Pattyn F., et al. RTPrimerDB: the real-time PCR primer and probe database. Nucleic Acids Res. 31:2003;122-123
75. Wang X., Seed B. A PCR primer bank for quantitative gene expression analysis. Nucleic Acids Res. 31:2003;e154
76. Ke L.D., et al. A reliability test of standard-based quantitative PCR: exogenous vs endogenous standards. Mol. Cell. Probes. 14:2000;127-135
77. Vandesompele J., et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 3:2002;. research0034
78. Pfaffl M.W. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res. 29:2001;e45
79. Pfaffl M., et al. Relative expression software tool (REST) for group-wise comparison and statistical analysis of relative expression results in real-time PCR. Nucleic Acids Res. 30:2002;e36
80. Rioja I., et al. Joint cytokine quantification in two rodent arthritis models: kinetics of expression, correlation of mRNA and protein levels and response to prednisolone treatment. Clin. Exp. Immunol. 137:2004;65-73
81. Vermeer H., et al. Glucocorticoid-induced increase in lymphocytic FKBP51 messenger ribonucleic acid expression: a potential marker for glucocorticoid sensitivity, potency, and bioavailability. J. Clin. Endocrinol. Metab. 88:2003;277-284
82. Xie H.J., et al. Alteration of pharmacokinetics of cyclophosphamide and suppression of the cytochrome p450 genes by ciprofloxacin. Bone Marrow Transplant. 31:2003;197-203
83. Cisternino S.C., et al. Expression, upregulation, and transport activity of the multidrug-resistance protein Abcg2 at the mouse blood-brain barrier. Cancer Res. 64:2004;3296-3301
84. Denk G.U., et al. Downregulation of the organic cation transporter 1 of rat liver in obstructive cholestasis. Hepatology. 39:2004;1382-1389
85. Schaarschmidt T.J., et al. Expression of multidrug resistance proteins in rat and human chronic pancreatitis. Pancreas. 28:2004;45-52
86. Cummings J.G., et al. Factors influencing the cellular accumulation of SN-38 and camptothecin. Cancer Chemother. Pharmacol. 49:2002;194-200
87. Steinbach D., et al. The multidrug resistance-associated protein 3 (MRP3) is associated with a poor outcome in childhood ALL and may account for the worse prognosis in male patients and T-cell immunophenotype. Blood. 102:2003;4493-4498
88. DeLozier, T.C. et al. (2004) CYP2C44, a new murine CYP2C that metabolizes arachidonic acid to unique stereospecific products. J. Pharmacol. Exp. Ther. DOI; 10.1124/jpet.104.067819 (E-pub ahead of print; http://jpet.aspetjournals. org)
89. Kogure T.Y., et al. The efficacy of the combination therapy of 5-fluorouracil, cisplatin and leucovorin for hepatocellular carcinoma and its predictable factors. Cancer Chemother. Pharmacol. 53:2004;296-304
90. Wilkening S., Bader A. Influence of culture time on the expression of drug-metabolizing enzymes in primary human hepatocytes and hepatoma cell line HepG2. J. Biochem. Mol. Toxicol. 17:2003;207-213
91. Smith G.R.S., et al. Quantitative real-time reverse transcription- polymerase chain reaction analysis of drug metabolizing and cytoprotective genes in psoriasis and regulation by ultraviolet radiation. J. Invest. Dermatol. 121:2003;390-398
92. Weise A.S., et al. Development and evaluation of a rapid and reliable method for cytochrome P450 2C8 genotyping. Clin. Lab. 50:2004;141-148
93. Saito K.S., et al. Detection of the four sequence variations of MDR1 gene using TaqMan MGB probe-based real-time PCR and haplotype analysis in healthy Japanese subjects. Clin. Biochem. 36:2003;511-518
94. Hiratsuka M.Y., et al. Allele and genotype frequencies of CYP2B6 and CYP3A5 in the Japanese population. Eur. J. Clin. Pharmacol. 58:2002;417-421