title: Microarrays in cancer research.
abstract: Microarray technology has presented the scientific community with a compelling approach that allows for simultaneous evaluation of all cellular processes at once. Cancer, being one of the most challenging diseases due to its polygenic nature, presents itself as a perfect candidate for evaluation by this approach. Several recent articles have provided significant insight into the strengths and limitations of microarrays. Nevertheless, there are strong indications that this approach will provide new molecular markers that could be used in diagnosis and prognosis of cancers. To achieve these goals it is essential that there is a seamless integration of clinical and molecular biological data that allows us to elucidate genes and pathways involved in various cancers. To this effect we are currently evaluating gene expression profiles in human brain, ovarian, breast and hematopoetic, lung, colorectal, head and neck and biliary tract cancers. To address the issues we have a joint team of scientists, doctors and computer scientists from two Virginia Universities and a major healthcare provider. The study has been divided into several focus groups that include; Tissue Bank Clinical & Pathology Laboratory Data, Chip Fabrication, QA/QC, Tissue Devitalization, Database Design and Data Analysis, using multiple microarray platforms. Currently over 300 consenting patients have been enrolled in the study with the largest number being that of breast cancer patients. Clinical data on each patient is being compiled into a secure and interactive relational database and integration of these data elements will be accomplished by a common programming interface. This clinical database contains several key parameters on each patient including demographic (risk factors, nutrition, co-morbidity, familial history), histopathology (non genetic predictors), tumor, treatment and follow-up information. Gene expression data derived from the tissue samples will be linked to this database, which allows us to query the data at multiple levels. The challenge of tissue acquisition and processing is of paramount importance to the success of this venture. A tissue devitalization timeline protocol was devised to ensure sample and RNA integrity. Stringent protocols are being employed to ascertain accurate tumor homogeneity, by serial dissection of each tumor sample at 10 microM frozen sections followed by histopathological evaluation. The multiple platforms being utilized in this study include Affimetrix, Oligo-Chips and custom-designed cDNA arrays. Selected RNA samples will be evaluated on each platform between the groups. Analysis steps will involve normalization and standardization of gene expression data followed by hierarchical clustering to determine co-regulation profiles. The aim of this conjoint effort is to elucidate pathways and genes involved in various cancers, resistance mechanisms, molecular markers for diagnosis and prognosis.
authors.affiliation: Department of Molecular Biology and Microbiology, George Mason University, 10900 University Blvd, Manassas, VA 20110, USA. ggrant1@gmu.edu
authors.forename: Geraldine M
authors.initials: GM
authors.lastname: Grant
authors.forename: Amanda
authors.initials: A
authors.lastname: Fortney
authors.forename: Francesco
authors.initials: F
authors.lastname: Gorreta
authors.forename: Michael
authors.initials: M
authors.lastname: Estep
authors.forename: Luca
authors.initials: L
authors.lastname: Del Giacco
authors.forename: Amy
authors.initials: A
authors.lastname: Van Meter
authors.forename: Alan
authors.initials: A
authors.lastname: Christensen
authors.forename: Lakshmi
authors.initials: L
authors.lastname: Appalla
authors.forename: Chahla
authors.initials: C
authors.lastname: Naouar
authors.forename: Curtis
authors.initials: C
authors.lastname: Jamison
authors.forename: Ali
authors.initials: A
authors.lastname: Al-Timimi
authors.forename: Jean
authors.initials: J
authors.lastname: Donovan
authors.forename: James
authors.initials: J
authors.lastname: Cooper
authors.forename: Carleton
authors.initials: C
authors.lastname: Garrett
authors.forename: Vikas
authors.initials: V
authors.lastname: Chandhoke
mesh_terms: D003625:Data Collection; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012106:Research