Microarrays for cancer diagnosis and classification

Advances in Experimental Medicine and Biology

Volumn 593, Issue , 2007, Pages 74-85

  Perez Diez, Ainhoa ^a   Morgun, Andrey ^a   Shulzhenko, Natalia ^a  

^a NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

TUMOR MARKER;

CANCER CLASSIFICATION; CANCER DIAGNOSIS; DATA ANALYSIS; DIAGNOSTIC ACCURACY; DIAGNOSTIC VALUE; GENE EXPRESSION PROFILING; HEMATOLOGIC MALIGNANCY; HUMAN; MICROARRAY ANALYSIS; NEOPLASM; PREDICTION; PRIORITY JOURNAL; PROGNOSIS; REVIEW; SOLID TUMOR;

EID: 84934441807     PISSN: 00652598     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-0-387-39978-2_8     Document Type: Review

References (42)

1. Simon R, Radmacher MD, Dobbin K et al. Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. J Natl Cancer Inst 2003; 95:14-18.
2. Ntzani EE, Ioannidis JP. Predictive ability of DNA microarrays for cancer outcomes and correlates: An empirical assessment. Lancet 2003; 362:1439-1444
3. Golub TR, Slonim DK, Tamayo P et al. Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science 1999; 286:531-537.
4. Ramaswamy S, Ross KN, Lander ES et al. A molecular signature of metastasis in primary solid tumors. Nat Genetics 2003; 33:49-54
5. Bullinger L, Dohner K, Bair E et al. Use of gene-expression profiling to identify prognostic sub-classes in adult acute myeloid leukemia. N Engl J Med 2004; 350:1605-1616
6. Bittner M, Meltzer P, Chen Y et al. Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature 2000; 406:536-540.
7. Alizadeh AA, Eisen MB, Davis RE et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000; 403:503-511.
8. Perou CM, Sorlie T, Eisen MB et al. Molecular portraits of human breast tumours. Nature 2000; 406:747-752
9. Roepman P, Wessels LF, Kettelarij N et al. An expression profile for diagnosis of lymph node metastases from primary head and neck squamous cell carcinomas. Nat Genet 2005; 37:182-186.
10. Ebert BL, Golub TR. Genomic approaches to hematologic malignancies. Blood 2004; 104:923-932.
11. Harris NL, Jaffe ES, Diebold J et al. World Health Organization classification of neoplastic diseases of the hematopoietic and lymphoid tissues: Report of the Clinical Advisory Committee meeting. J Clin Oncol 1999; 12:3835-3849.
12. Grimwade D, Walker H, Oliver F et al. The importance of diagnostic cytogenetics on outcome in AML: Analysis of 1,612 patients entered into the MRC AML 10 trial. The Medical Research Council Adult and Children's Leukaemia Working Parties. Blood 1998; 92:2322-2333.
13. Bloomfield CD, Lawrence D, Byrd JC et al. Frequency of prolonged remission duration after high-dose cytarabine intensification in acute myeloid leukemia varies by cytogenetic subtype. Cancer Res 1998; 58:4173-4179.
14. Player A, Barrett JC, Kawasaki ES. Laser capture microdissection, microarrays and the precise definition of a cancer cell. Expert Rev Mol Diagn 2004; 4:831-840.
15. Ohyama H, Zhang X, Kohno Y et al. Laser capture microdissection-generated target sample for high-density oligonucleotide array hybridization. Biotechniques 2000; 29:530-536.
16. Ernst T, Hergenhahn M, Kenzelmann M et al. Decrease and gain of gene expression are equally discriminatory markers for prostate carcinoma: A gene expression analysis on total and microdissected prostate tissue. Am J Pathol 2002; 160:2169-2180.
17. Sanchez-Carbayo M, Saint F, Lozano JJ et al. Comparison of gene expression profiles in laser-microdissected, nonembedded, and OCT-embedded tumor samples by oligonucleotide microarray analysis. Clin Chem 2003; 49:2096-2100.
18. Dorudi S, Hart IR. Mechanisms underlying invasion and metastasis. Curr Opin Oncol 1993; 5:130-135.
19. Basset P, Okada A, Chenard MP et al. Matrix metalloproteinases as stromal effectors of human carcinoma progression: Therapeutic implications. Matrix Biol 1997; 15:535-541.
20. Chung LW, Baseman A, Assikis V et al. Molecular insights into prostate cancer progression: The missing link of tumor microenvironment. J Urol 2005; 173:10-20.
21. 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.
22. Dobbin KK, Beer DG, Meyerson M et al. Interlaboratory comparability study of cancer gene expression analysis using oligonucleotide microarrays. Clin Cancer Res 2005; 11:565-572.
23. Michiels S, Koscielny S, Hill C. Prediction of cancer outcome with microarrays: A multiple random validation strategy. Lancet 2005; 365:488-492.
24. van 't Veer LJ, Dai H, van de Vijver MJ et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002; 415:530-536.
25. Sotiriou C, Neo SY, McShane LM et al. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA 2003; 100:10393-10398.
26. Kallioniemi O. Medicine: Profile of a tumour. Nature 2004; 428:379-382.
27. Xiong M, Li W, Zhao J et al. Feature (gene) selection in gene expression-based tumor classification. Mol Genet Metab 2001; 73:239-247.
28. Fu LM, Fu-Liu CS. Multi-class cancer subtype classification based on gene expression signatures with reliability analysis. FEBS Lett 2004; 561:186-190.
29. Gordon GJ, Jensen RV, Hsiao LL et al. Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesothelioma. Cancer Res 2002; 62:4963-4967.
30. Bueno R, Loughlin KR, Powell MH et al. A diagnostic test for prostate cancer from gene expression profiling data. J Urol 2004; 171:903-906.
31. Dhanasekaran SM, Barrette TR, Ghosh D et al. Delineation of prognostic biomarkers in prostate cancer. Nature 2001; 412:822-826.
32. Welsh JB, Sapinoso LM, Su Al et al. Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer. Cancer Res 2001; 61:5974-5978.
33. Lossos IS, Czerwinski DK, Alizadeh AA et al. Prediction of survival in diffuse large-B-cell lymphoma based on the expression of six genes. N Engl J Med 2004; 350:1828-1837.
34. Brabender J, Marjoram P, Salonga D et al. A multigene expression panel for the molecular diagnosis of Barrett's esophagus and Barrett's adenocarcinoma of the esophagus. Oncogene 2004; 23:4780-4788.
35. Mori K, Aoyagi K, Ueda T et al. Highly specific marker genes for detecting minimal gastric cancer cells in cytology negative peritoneal washings. Biochem Biophys Res Commun 2004; 313:931-937.
36. Rubin MA, Zhou M, Dhanasekaran SM et al. alpha-Methylacyl coenzyme A racemase as a tissue biomarker for prostate cancer. JAMA 2002; 287:1662-70.
37. Nishizuka S, Chen ST, Gwadry FG et al. Diagnostic markers that distinguish colon and ovarian adenocarcinomas: Identification by genomic, proteomic, and tissue array profiling. Cancer Res 2003; 63:5243-50.
38. Huddleston HG, Wong KK, Welch WR et al. Clinical applications of microarray technology: Creatine kinase B is an up-regulated gene in epithelial ovarian cancer and shows promise as a serum marker. Gynecol Oncol 2005; 96:77-83.
39. Mok SC, Chao J, Skates S et al. Prostasin, a potential serum marker for ovarian cancer: Identification through microarray technology. J Natl Cancer Inst 2001; 93:1458-1464.
40. Kim JH, Skates SJ, Uede T et al. Osteopontin as a potential diagnostic biomarker for ovarian cancer. JAMA 2002; 287:1671-9.
41. Rhodes DR, Yu J, Shanker K et al. Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression Proc Natl Acad Sci USA 2004; 101:9309-9314.
42. Choi JK, Choi JY, Kim DG et al. Integrative analysis of multiple gene expression profiles applied to liver cancer study. FEBS Lett 2004; 565:93-100.