Patient-based cross-platform comparison of oligonucleotide microarray expression profiles

Laboratory Investigation

Volumn 85, Issue 8, 2005, Pages 1024-1039

  Schlingemann, Joerg ^a   Habtemichael, Negusse ^b   Ittrich, Carina ^a   Toedt, Grischa ^a   Kramer, Heidi ^a   Hambek, Markus ^c   Knecht, Rainald ^c   Lichter, Peter ^a   Stauber, Roland ^b   Hahn, Meinhard ^a  

^a GERMAN CANCER RESEARCH CENTER DKFZ   (Germany)

^b INSTITUTE FOR TUMOR BIOLOGY AND EXPERIMENTAL THERAPY   (Germany)

^c GOETHE UNIVERSITY   (Germany)

Author keywords

Comparative study; Expression profiling; Head and neck cancer; Oligonucleotide microarray; Oligonucleotide probes; Reproducibility of results; Statistics and numerical data

Indexed keywords

COMPLEMENTARY DNA;

ARTICLE; CONTROLLED STUDY; CORRELATION ANALYSIS; DNA MICROARRAY; GENE EXPRESSION; GENETIC ANALYSIS; GENETIC TRANSCRIPTION; HEAD AND NECK CARCINOMA; HUMAN; HUMAN CELL; HUMAN TISSUE; MOLECULAR PROBE; PRIORITY JOURNAL; QUALITATIVE ANALYSIS; REAL TIME POLYMERASE CHAIN REACTION; SQUAMOUS CELL CARCINOMA;

BASE SEQUENCE; CARCINOMA, SQUAMOUS CELL; DNA PRIMERS; DNA PROBES; FEMALE; GENE EXPRESSION PROFILING; HEAD AND NECK NEOPLASMS; HUMANS; MALE; MIDDLE AGED; NUCLEIC ACID HYBRIDIZATION; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; POLYMERASE CHAIN REACTION; REPRODUCIBILITY OF RESULTS;

EID: 27144529544     PISSN: 00236837     EISSN: 15300307     Source Type: Journal    
DOI: 10.1038/labinvest.3700293     Document Type: Article

References (46)

1. Schena M, Shalon D, Davis RW, et al. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 1995;270:467-470.
2. Lockhart DJ, Dong H, Byrne MC, et al. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat Biotechnol 1996;14:1675-1680.
3. Hughes TR, Mao M, Jones AR, et al. Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nat Biotechnol 2001;19:342-347.
4. Wrobel G, Schlingemann J, Hummerich L, et al. Optimization of high-density cDNA-microarray protocols by 'design of experiments'. Nucleic Acids Res 2003;31:e67.
5. Kokocinski F, Wrobel G, Hahn M, et al. QuickLIMS: facilitating the data management for DNA-microarray fabrication. Bioinformatics 2003;19:283-284.
6. Knight J. When the chips are down. Nature 2001;410:860-861.
7. Yuen T, Wurmbach E, Pfeffer RL, et al. Accuracy and calibration of commercial oligonucleotide and custom cDNA microarrays. Nucleic Acids Res 2002;30:e48.
8. Mah N, Thelin A, Lu T, et al. A comparison of oligonucleotide and cDNA-based microarray systems. Physiol Genomics 2004;16:361-370.
9. Schlingemann J, Hess J, Wrobel G, et al. Profile of gene expression induced by the tumour promotor TPA in murine epithelial cells. Int J Cancer 2003;104:699-708.
10. Barczak A, Rodriguez MW, Hanspers K, et al. Spotted long oligonucleotide arrays for human gene expression analysis. Genome Res 2003;13:1775-1785.
11. Cox WG, Beaudet MP, Agnew JY, et al. Possible sources of dye-related signal correlation bias in two-color DNA microarray assays. Anal Biochem 2004;331:243-254.
12. Schlingemann J, Thuerigen O, Ittrich C, et al. Effective transcriptome amplification for expression profiling on sense-oriented oligonucleotide microarrays. Nucleic Acids Res 2005;33:e29.
13. UICC. TNM Classification of Malignant Tumours, 6th edn. John Wiley & Sons: New York, 2002.
14. Schena M, Shalon D, Heller R, et al. Parallel human genome analysis: microarray-based expression monitoring of 1000 genes. Proc Natl Acad Sci USA 1996;93:10614-10619.
15. R Development Core Team. R: A Language and Environment for Statistical Computing, 2nd edn. R Foundation for Statistical Computing: Vienna, 2004.
16. Gentleman RC, Carey VJ, Bates DM, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 2004;5:R80.
17. Huber W, Von Heydebreck A, Sultmann H, et al. Variance stabilization applied to microarray data calibration and to the quantification of differential expression. Bioinformatics 2002;18Suppl. 1:S96-S104.
18. Affymetrix. GeneChip Expression Analysis Technical Manual, 5th edn. Affymetrix: Santa Clara, 2004.
19. Affymetrix. Microarray Suite User Guide, 5th edn. Affymetrix: Santa Clara, 2001.
20. Wu Z, Irizarry R, Gentleman R, et al. A model-based background adjustment for oligonucleotide expression arrays. J Am Stat Assoc 2004;99:909-917.
21. Zhang J, Carey V, Gentleman R. An extensible application for assembling annotation for genomic data. Bioinformatics 2003;19:155-156.
22. Yang MC, Ruan QG, Yang JJ, et al. A statistical method for flagging weak spots improves normalization and ratio estimates in microarrays. Physiol Genomics 2001;7:45-53.
23. Smyth GK, Yang YH, Speed T. Statistical issues in cDNA microarray data analysis. Methods Mol Biol 2003;224:111-136.
24. Smyth GK. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 2004;3:Article 3.
25. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B 1995;57:289-300.
26. Wolfinger RD, Gibson G, Wolfinger ED, et al. Assessing gene significance from cDNA microarray expression data via mixed models. J Comput Biol 2001;8:625-637.
27. Benito M, Parker J, Du Q, et al. Adjustment of systematic microarray data biases. Bioinformatics 2004;20:105-114.
28. Ashburner M, Ball CA, Blake JA, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 2000;25:25-29.
29. Dennis Jr G, Sherman BT, Hosack DA, et al. DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol 2003;4:P3.
30. Hosack DA, Dennis Jr G, Sherman BT, et al. Identifying biological themes within lists of genes with EASE. Genome Biol 2003;4:R70.
31. Pfaffl MW. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res 2001;29:e45.
32. Edgar R, Domrachev M, Lash AE. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 2002;30:207-210.
33. Baugh LR, Hill AA, Brown EL, et al. Quantitative analysis of mRNA amplification by in vitro transcription. Nucleic Acids Res 2001;29:E29.
34. Tan PK, Downey TJ, Spitznagel Jr EL, et al. Evaluation of gene expression measurements from commercial microarray platforms. Nucleic Acids Res 2003;31:5676-5684.
35. Shippy R, Sendera TJ, Lockner R, et al. Performance evaluation of commercial short-oligonucleotide microarrays and the impact of noise in making cross-platform correlations. BMC Genomics 2004;5:61.
36. Jarvinen AK, Hautaniemi S, Edgren H, et al. Are data from different gene expression microarray platforms comparable? Genomics 2004;83:1164-1168.
37. Marshall E. Getting the noise out of gene arrays. Science 2004;306:630-631.
38. Rhodes DR, Barrette TR, Rubin MA, et al. Meta-analysis of microarrays: interstudy validation of gene expression profiles reveals pathway dysregulation in prostate cancer. Cancer Res 2002;62:4427-4433.
39. Sorlie T, Tibshirani R, Parker J, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 2003;100:8418-8423.
40. Mitchell SA, Brown KM, Henry MM, et al. Interplatform comparability of microarrays in acute lymphoblastic leukemia. BMC Genomics 2004;5:71.
41. Pruitt KD, Katz KS, Sicotte H, et al. Introducing RefSeq and LocusLink: curated human genome resources at the NCBI. Trends Genet 2000;16:44-47.
42. Pruitt KD, Maglott DR. RefSeq and LocusLink: NCBI gene-centered resources. Nucleic Acids Res 2001;29:137-140.
43. Mecham BH, Wetmore DZ, Szallasi Z, et al. Increased measurement accuracy for sequence-verified microarray probes. Physiol Genomics 2004;18:308-315.
44. Baum M, Bielau S, Rittner N, et al. Validation of a novel, fully integrated and flexible microarray bench-top facility for gene expression profiling. Nucleic Acids Res 2003;31:e151.
45. Boser BE, Guyon IM, Vapnik VN, Proceedings of the Fifth Annual Workshop on Computational Learning Theory. ACM Press: Pittsburgh, 1992, pp 144-152.
46. Brazma A, Hingamp P, Quackenbush J, et al. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 2001;29:365-371.