Medical applications of microarray technologies: a regulatory science perspective

The potential medical applications of microarrays have generated much excitement, and some skepticism, within the biomedical community. Some researchers have suggested that within the decade microarrays will be routinely used in the selection, assessment, and quality control of the best drugs for pharmaceutical development, as well as for disease diagnosis and for monitoring desired and adverse outcomes of therapeutic interventions. Realizing this potential will be a challenge for the whole scientific community, as breakthroughs that show great promise at the bench often fail to meet the requirements of clinicians and regulatory scientists. The development of a cooperative framework among regulators, product sponsors, and technology experts will be essential for realizing the revolutionary promise that microarrays hold for drug development, regulatory science, medical practice and public health.

[1]  E. Petricoin,et al.  Use of proteomic patterns in serum to identify ovarian cancer , 2002, The Lancet.

[2]  H. Moch,et al.  Tissue microarrays for rapid linking of molecular changes to clinical endpoints. , 2001, The American journal of pathology.

[3]  Ash A. Alizadeh,et al.  Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling , 2000, Nature.

[4]  Yudong D. He,et al.  Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.

[5]  D. Botstein,et al.  Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[6]  T. Tsunoda,et al.  Genome-wide analysis of gene expression in human hepatocellular carcinomas using cDNA microarray: identification of genes involved in viral carcinogenesis and tumor progression. , 2001, Cancer research.

[7]  G. A. Whitmore,et al.  Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[8]  G. MacBeath Proteomics comes to the surface , 2001, Nature Biotechnology.

[9]  C. Ball,et al.  Microarray databases: standards and ontologies , 2002, Nature Genetics.

[10]  S. M. Kim,et al.  Cystic fibrosis mutation detection by hybridization to light‐generated DNA probe arrays , 1996, Human mutation.

[11]  Allen D. Roses,et al.  Genome-based pharmacogenetics and the pharmaceutical industry , 2002, Nature Reviews Drug Discovery.

[12]  J. Mesirov,et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.

[13]  S. P. Fodor,et al.  Strategies for mutational analysis of the large multiexon ATM gene using high-density oligonucleotide arrays. , 1998, Genome research.

[14]  R. Todd,et al.  Oral cancer in vivo gene expression profiling assisted by laser capture microdissection and microarray analysis , 2001, Oncogene.

[15]  E. Dougherty,et al.  Multivariate measurement of gene expression relationships. , 2000, Genomics.

[16]  N. Sampas,et al.  Molecular classification of cutaneous malignant melanoma by gene expression profiling , 2000, Nature.

[17]  A Chakravarti,et al.  High-throughput variation detection and genotyping using microarrays. , 2001, Genome research.

[18]  P. Brown,et al.  A DNA microarray system for analyzing complex DNA samples using two-color fluorescent probe hybridization. , 1996, Genome research.

[19]  Russ B Altman,et al.  Challenges for biomedical informatics and pharmacogenomics. , 2002, Annual review of pharmacology and toxicology.

[20]  E. Petricoin,et al.  Reverse phase protein microarrays which capture disease progression show activation of pro-survival pathways at the cancer invasion front , 2001, Oncogene.

[21]  D J Lockhart,et al.  Genome-wide detection of allelic imbalance using human SNPs and high-density DNA arrays. , 2000, Genome research.

[22]  Stuart L. Schreiber,et al.  Dissecting glucose signalling with diversity-oriented synthesis and small-molecule microarrays , 2002, Nature.

[23]  L. Kruglyak,et al.  Genetic Dissection of Transcriptional Regulation in Budding Yeast , 2002, Science.

[24]  P. Brown,et al.  Genomics and human disease—variations on variation , 1998, Nature Genetics.

[25]  B. Meade,et al.  Analysis of gene expression induced by irritant and sensitizing chemicals using oligonucleotide arrays. , 2001, International immunopharmacology.

[26]  R G Ulrich,et al.  Clustering of hepatotoxins based on mechanism of toxicity using gene expression profiles. , 2001, Toxicology and applied pharmacology.

[27]  R. Shippy,et al.  An assessment of Motorola CodeLink microarray performance for gene expression profiling applications. , 2002, Nucleic acids research.

[28]  Eric D Wieben,et al.  Primer on medical genomics. Part III: Microarray experiments and data analysis. , 2002, Mayo Clinic proceedings.

[29]  T. Poggio,et al.  Prediction of central nervous system embryonal tumour outcome based on gene expression , 2002, Nature.

[30]  J. Mills,et al.  A new approach for filtering noise from high-density oligonucleotide microarray datasets. , 2001, Nucleic acids research.

[31]  M. King,et al.  BRCA1 transcriptionally regulates genes involved in breast tumorigenesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[32]  E. Lander,et al.  MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia , 2002, Nature Genetics.

[33]  T. Barrette,et al.  Profiling of cancer cells using protein microarrays: discovery of novel radiation-regulated proteins. , 2001, Cancer research.

[34]  K. Büssow,et al.  High-throughput protein arrays: prospects for molecular diagnostics. , 2002, Trends in molecular medicine.

[35]  E Mahlamäki,et al.  Hormone therapy failure in human prostate cancer: analysis by complementary DNA and tissue microarrays. , 1999, Journal of the National Cancer Institute.

[36]  M. Ringnér,et al.  Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks , 2001, Nature Medicine.

[37]  M. Honda,et al.  Identification of differentially expressed genes in hepatocellular carcinoma with cDNA microarrays , 2001, Hepatology.

[38]  James L. Winkler,et al.  Accessing Genetic Information with High-Density DNA Arrays , 1996, Science.

[39]  Ronald W. Davis,et al.  Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray , 1995, Science.

[40]  J. Sudbø,et al.  Gene-expression profiles in hereditary breast cancer. , 2001, The New England journal of medicine.

[41]  M. Oh,et al.  Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects. , 2001, Nucleic acids research.

[42]  P. Bushel,et al.  Detection of diluted gene expression alterations using cDNA microarrays. , 2002, BioTechniques.

[43]  E. Petricoin,et al.  Clinical proteomics: translating benchside promise into bedside reality , 2002, Nature Reviews Drug Discovery.

[44]  Christopher J. Lee,et al.  A genomic view of alternative splicing , 2002, Nature Genetics.

[45]  C R Cantor Pharmacogenetics becomes pharmacogenomics: wake up and get ready. , 1999, Molecular diagnosis : a journal devoted to the understanding of human disease through the clinical application of molecular biology.

[46]  D. Figeys,et al.  Proteomics on a chip: Promising developments , 2001, Electrophoresis.

[47]  L. Penland,et al.  Use of a cDNA microarray to analyse gene expression patterns in human cancer , 1996, Nature Genetics.

[48]  L. Staudt,et al.  The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. , 2002, The New England journal of medicine.

[49]  R E Stoll,et al.  Assessment of cisplatin-induced nephrotoxicity by microarray technology. , 2001, Toxicological sciences : an official journal of the Society of Toxicology.

[50]  F. Barany,et al.  Mutation Detection in K‐ras, BRCA1, BRCA2, and p53 Using PCR/LDR and a Universal DNA Microarray , 2000, Annals of the New York Academy of Sciences.

[51]  M. Bittner,et al.  Human prostate cancer and benign prostatic hyperplasia: molecular dissection by gene expression profiling. , 2001, Cancer research.

[52]  J. Trent,et al.  Microarrays and toxicology: The advent of toxicogenomics , 1999, Molecular carcinogenesis.

[53]  Jason E. Stewart,et al.  Minimum information about a microarray experiment (MIAME)—toward standards for microarray data , 2001, Nature Genetics.

[54]  T. Stamey,et al.  Molecular genetic profiling of Gleason grade 4/5 prostate cancers compared to benign prostatic hyperplasia. , 2001, The Journal of urology.

[55]  Mark W. Craven,et al.  Identification of toxicologically predictive gene sets using cDNA microarrays. , 2001, Molecular pharmacology.

[56]  K. Morgan Gene expression analysis reveals chemical-specific profiles. , 2002, Toxicological sciences : an official journal of the Society of Toxicology.

[57]  A. Sinha,et al.  Gene expression profile analysis by DNA microarrays: promise and pitfalls. , 2001, JAMA.

[58]  S. P. Fodor,et al.  Detection of heterozygous mutations in BRCA1 using high density oligonucleotide arrays and two–colour fluorescence analysis , 1996, Nature Genetics.

[59]  R. Spang,et al.  Predicting the clinical status of human breast cancer by using gene expression profiles , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[60]  D. Lockhart,et al.  Expression monitoring by hybridization to high-density oligonucleotide arrays , 1996, Nature Biotechnology.

[61]  Todd,et al.  Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning , 2002, Nature Medicine.

[62]  A. Sajantila,et al.  Y-chromosomal SNPs in Finno-Ugric-speaking populations analyzed by minisequencing on microarrays. , 2001, Genome research.