title: The microarray-based approach for the analysis of the transcriptome.
abstract: Microarrays play an important role in the study of the transcriptome in a variety of conditions and species. This is documented by their widespread use over the last decade in areas such as cancer, immunology, neurological disorders, renal diseases, and many others, directed towards the new frontiers of personalized medicine and drug discovery. The following method covers a specific application of microarrays in the field of immunology, focusing on the study of antigen-induced T cell differentiation in response to viral or bacterial infection, and in the context of cancer. This protocol allows, through an "Omics" strategy, the study of the transcriptome of CTLs, concentrating only on the expression profiles of those genes more likely to be involved in CTL action. Since the biological question, in this case, is very specific, the advantage of this protocol with respect to a more traditional whole transcriptome microarray experiment is to remove the noise coming from all the genes not directly involved in the CTLs-specific pathways, highlighting weaker signals that otherwise would be hidden by the noise itself. To address this issue we have accurately selected all the CTLs-specific pathways, extracted all the genes belonging to them, and designed a CTL-specific microarray, based on all known validated transcripts deriving from these genes. This microarray has been built for the Agilent Technologies microarray platform, the only one that, to our knowledge, at present allows autonomously designing a completely customizable microarray. We used it in the context of renal cell carcinoma (RCC), but surely it will find several more applications in many other cancers and in the context of viral and bacterial infection.
authors.affiliation: Nephrology, Dialysis and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari "A. Moro", Policlinico, Piazza G. Cesare 11, Bari, 70124, Italy, matteo.accetturo@uniba.it.
authors.forename: Matteo
authors.initials: M
authors.lastname: Accetturo
authors.forename: Paola
authors.initials: P
authors.lastname: Pontrelli
authors.forename: Loreto
authors.initials: L
authors.lastname: Gesualdo
mesh_terms: D002292:Carcinoma, Renal Cell / Q000276:immunology; D002454:Cell Differentiation / Q000276:immunology; D002478:Cells, Cultured; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D007680:Kidney Neoplasms / Q000276:immunology; D008213:Lymphocyte Activation / Q000276:immunology; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D040081:Protein Array Analysis / Q000379:methods*; D012313:RNA / Q000032:analysis; D013602:T-Lymphocytes, Cytotoxic / Q000166:cytology / Q000276:immunology*; D059467:Transcriptome
chemical_list: D012313:RNA